{"cells": [{"cell_type": "markdown", "id": "100c2262", "metadata": {"papermill": {"duration": 0.018049, "end_time": "2023-03-14T16:08:42.495700", "exception": false, "start_time": "2023-03-14T16:08:42.477651", "status": "completed"}, "tags": []}, "source": ["\n", "# Tutorial 9: Normalizing Flows for Image Modeling\n", "\n", "* **Author:** Phillip Lippe\n", "* **License:** CC BY-SA\n", "* **Generated:** 2023-03-14T16:07:05.259127\n", "\n", "In this tutorial, we will take a closer look at complex, deep normalizing flows.\n", "The most popular, current application of deep normalizing flows is to model datasets of images.\n", "As for other generative models, images are a good domain to start working on because\n", "(1) CNNs are widely studied and strong models exist,\n", "(2) images are high-dimensional and complex,\n", "and (3) images are discrete integers.\n", "In this tutorial, we will review current advances in normalizing flows for image modeling,\n", "and get hands-on experience on coding normalizing flows.\n", "Note that normalizing flows are commonly parameter heavy and therefore computationally expensive.\n", "We will use relatively simple and shallow flows to save computational cost and allow you to run the notebook on CPU,\n", "but keep in mind that a simple way to improve the scores of the flows we study here is to make them deeper.\n", "This notebook is part of a lecture series on Deep Learning at the University of Amsterdam.\n", "The full list of tutorials can be found at https://uvadlc-notebooks.rtfd.io.\n", "\n", "\n", "---\n", "Open in [{height=\"20px\" width=\"117px\"}](https://colab.research.google.com/github/PytorchLightning/lightning-tutorials/blob/publication/.notebooks/course_UvA-DL/09-normalizing-flows.ipynb)\n", "\n", "Give us a \u2b50 [on Github](https://www.github.com/Lightning-AI/lightning/)\n", "| Check out [the documentation](https://pytorch-lightning.readthedocs.io/en/stable/)\n", "| Join us [on Slack](https://www.pytorchlightning.ai/community)"]}, {"cell_type": "markdown", "id": "87ad8b6e", "metadata": {"papermill": {"duration": 0.008889, "end_time": "2023-03-14T16:08:42.513816", "exception": false, "start_time": "2023-03-14T16:08:42.504927", "status": "completed"}, "tags": []}, "source": ["## Setup\n", "This notebook requires some packages besides pytorch-lightning."]}, {"cell_type": "code", "execution_count": 1, "id": "d2626593", "metadata": {"colab": {}, "colab_type": "code", "execution": {"iopub.execute_input": "2023-03-14T16:08:42.564704Z", "iopub.status.busy": "2023-03-14T16:08:42.564240Z", "iopub.status.idle": "2023-03-14T16:08:45.876740Z", "shell.execute_reply": "2023-03-14T16:08:45.875371Z"}, "id": "LfrJLKPFyhsK", "lines_to_next_cell": 0, "papermill": {"duration": 3.355994, "end_time": "2023-03-14T16:08:45.879658", "exception": false, "start_time": "2023-03-14T16:08:42.523664", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n", "\u001b[0m"]}], "source": ["! pip install --quiet \"ipython[notebook]>=8.0.0, <8.12.0\" \"seaborn\" \"pytorch-lightning>=1.4, <2.0.0\" \"torch>=1.8.1, <1.14.0\" \"tabulate\" \"lightning>=2.0.0rc0\" \"torchmetrics>=0.7, <0.12\" \"torchvision\" \"matplotlib\" \"setuptools==67.4.0\""]}, {"cell_type": "markdown", "id": "c4fcf3d8", "metadata": {"papermill": {"duration": 0.009032, "end_time": "2023-03-14T16:08:45.902797", "exception": false, "start_time": "2023-03-14T16:08:45.893765", "status": "completed"}, "tags": []}, "source": ["<div class=\"center-wrapper\"><div class=\"video-wrapper\"><iframe src=\"https://www.youtube.com/embed/U1fwesIusbg\" title=\"YouTube video player\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe></div></div>\n", "Throughout this notebook, we make use of [PyTorch Lightning](https://lightning.ai/docs/pytorch/stable/).\n", "The first cell imports our usual libraries."]}, {"cell_type": "code", "execution_count": 2, "id": "91b34352", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:45.922980Z", "iopub.status.busy": "2023-03-14T16:08:45.922606Z", "iopub.status.idle": "2023-03-14T16:08:49.148569Z", "shell.execute_reply": "2023-03-14T16:08:49.147852Z"}, "papermill": {"duration": 3.238278, "end_time": "2023-03-14T16:08:49.150284", "exception": false, "start_time": "2023-03-14T16:08:45.912006", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Global seed set to 42\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Using device cuda:0\n"]}], "source": ["import math\n", "import os\n", "import time\n", "import urllib.request\n", "from urllib.error import HTTPError\n", "\n", "import lightning as L\n", "import matplotlib\n", "import matplotlib.pyplot as plt\n", "import matplotlib_inline.backend_inline\n", "import numpy as np\n", "import seaborn as sns\n", "import tabulate\n", "import torch\n", "import torch.nn as nn\n", "import torch.nn.functional as F\n", "import torch.optim as optim\n", "import torch.utils.data as data\n", "import torchvision\n", "from IPython.display import HTML, display\n", "from lightning.pytorch.callbacks import LearningRateMonitor, ModelCheckpoint\n", "from matplotlib.colors import to_rgb\n", "from torch import Tensor\n", "from torchvision import transforms\n", "from torchvision.datasets import MNIST\n", "from tqdm.notebook import tqdm\n", "\n", "%matplotlib inline\n", "matplotlib_inline.backend_inline.set_matplotlib_formats(\"svg\", \"pdf\") # For export\n", "matplotlib.rcParams[\"lines.linewidth\"] = 2.0\n", "sns.reset_orig()\n", "\n", "# Path to the folder where the datasets are/should be downloaded (e.g. MNIST)\n", "DATASET_PATH = os.environ.get(\"PATH_DATASETS\", \"data\")\n", "# Path to the folder where the pretrained models are saved\n", "CHECKPOINT_PATH = os.environ.get(\"PATH_CHECKPOINT\", \"saved_models/tutorial11\")\n", "\n", "# Setting the seed\n", "L.seed_everything(42)\n", "\n", "# Ensure that all operations are deterministic on GPU (if used) for reproducibility\n", "torch.backends.cudnn.deterministic = True\n", "torch.backends.cudnn.benchmark = False\n", "\n", "# Fetching the device that will be used throughout this notebook\n", "device = torch.device(\"cpu\") if not torch.cuda.is_available() else torch.device(\"cuda:0\")\n", "print(\"Using device\", device)"]}, {"cell_type": "markdown", "id": "4bcabe69", "metadata": {"papermill": {"duration": 0.009295, "end_time": "2023-03-14T16:08:49.170996", "exception": false, "start_time": "2023-03-14T16:08:49.161701", "status": "completed"}, "tags": []}, "source": ["Again, we have a few pretrained models. We download them below to the specified path above."]}, {"cell_type": "code", "execution_count": 3, "id": "0a65243d", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:49.191095Z", "iopub.status.busy": "2023-03-14T16:08:49.190541Z", "iopub.status.idle": "2023-03-14T16:08:50.538855Z", "shell.execute_reply": "2023-03-14T16:08:50.537598Z"}, "papermill": {"duration": 1.361205, "end_time": "2023-03-14T16:08:50.541518", "exception": false, "start_time": "2023-03-14T16:08:49.180313", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Downloading https://raw.githubusercontent.com/phlippe/saved_models/main/tutorial11/MNISTFlow_simple.ckpt...\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Downloading https://raw.githubusercontent.com/phlippe/saved_models/main/tutorial11/MNISTFlow_vardeq.ckpt...\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Downloading https://raw.githubusercontent.com/phlippe/saved_models/main/tutorial11/MNISTFlow_multiscale.ckpt...\n"]}], "source": ["# Github URL where saved models are stored for this tutorial\n", "base_url = \"https://raw.githubusercontent.com/phlippe/saved_models/main/tutorial11/\"\n", "# Files to download\n", "pretrained_files = [\"MNISTFlow_simple.ckpt\", \"MNISTFlow_vardeq.ckpt\", \"MNISTFlow_multiscale.ckpt\"]\n", "# Create checkpoint path if it doesn't exist yet\n", "os.makedirs(CHECKPOINT_PATH, exist_ok=True)\n", "\n", "# For each file, check whether it already exists. If not, try downloading it.\n", "for file_name in pretrained_files:\n", " file_path = os.path.join(CHECKPOINT_PATH, file_name)\n", " if not os.path.isfile(file_path):\n", " file_url = base_url + file_name\n", " print(\"Downloading %s...\" % file_url)\n", " try:\n", " urllib.request.urlretrieve(file_url, file_path)\n", " except HTTPError as e:\n", " print(\n", " \"Something went wrong. Please try to download the file from the GDrive folder, or contact the author with the full output including the following error:\\n\",\n", " e,\n", " )"]}, {"cell_type": "markdown", "id": "23698177", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.009424, "end_time": "2023-03-14T16:08:50.566184", "exception": false, "start_time": "2023-03-14T16:08:50.556760", "status": "completed"}, "tags": []}, "source": ["We will use the MNIST dataset in this notebook.\n", "MNIST constitutes, despite its simplicity, a challenge for small generative models as it requires the global understanding of an image.\n", "At the same time, we can easily judge whether generated images come from the same distribution as the dataset\n", "(i.e. represent real digits), or not.\n", "\n", "To deal better with the discrete nature of the images, we transform them\n", "from a range of 0-1 to a range of 0-255 as integers."]}, {"cell_type": "code", "execution_count": 4, "id": "9965c930", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:50.586882Z", "iopub.status.busy": "2023-03-14T16:08:50.586498Z", "iopub.status.idle": "2023-03-14T16:08:51.988192Z", "shell.execute_reply": "2023-03-14T16:08:51.987570Z"}, "papermill": {"duration": 1.413875, "end_time": "2023-03-14T16:08:51.989455", "exception": false, "start_time": "2023-03-14T16:08:50.575580", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\n", "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to /__w/6/s/.datasets/MNIST/raw/train-images-idx3-ubyte.gz\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "8e868462f756444d9b1a566c8f77d457", "version_major": 2, "version_minor": 0}, "text/plain": [" 0%| | 0/9912422 [00:00<?, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"name": "stdout", "output_type": "stream", "text": ["Extracting /__w/6/s/.datasets/MNIST/raw/train-images-idx3-ubyte.gz to /__w/6/s/.datasets/MNIST/raw\n"]}, {"name": "stdout", "output_type": "stream", "text": ["\n", "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\n", "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz to /__w/6/s/.datasets/MNIST/raw/train-labels-idx1-ubyte.gz\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "6e93eead70d64710b21580c9dfdcab47", "version_major": 2, "version_minor": 0}, "text/plain": [" 0%| | 0/28881 [00:00<?, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"name": "stdout", "output_type": "stream", "text": ["Extracting /__w/6/s/.datasets/MNIST/raw/train-labels-idx1-ubyte.gz to /__w/6/s/.datasets/MNIST/raw\n", "\n", "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\n", "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz to /__w/6/s/.datasets/MNIST/raw/t10k-images-idx3-ubyte.gz\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "60985b1c703d4f8aa3aba175811d2a69", "version_major": 2, "version_minor": 0}, "text/plain": [" 0%| | 0/1648877 [00:00<?, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"name": "stdout", "output_type": "stream", "text": ["Extracting /__w/6/s/.datasets/MNIST/raw/t10k-images-idx3-ubyte.gz to /__w/6/s/.datasets/MNIST/raw\n", "\n", "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\n", "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to /__w/6/s/.datasets/MNIST/raw/t10k-labels-idx1-ubyte.gz\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "85c1da41f2e24252b1bfd646e70cdce8", "version_major": 2, "version_minor": 0}, "text/plain": [" 0%| | 0/4542 [00:00<?, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"name": "stdout", "output_type": "stream", "text": ["Extracting /__w/6/s/.datasets/MNIST/raw/t10k-labels-idx1-ubyte.gz to /__w/6/s/.datasets/MNIST/raw\n", "\n"]}, {"name": "stderr", "output_type": "stream", "text": ["Global seed set to 42\n"]}], "source": ["# Convert images from 0-1 to 0-255 (integers)\n", "def discretize(sample):\n", " return (sample * 255).to(torch.int32)\n", "\n", "\n", "# Transformations applied on each image => make them a tensor and discretize\n", "transform = transforms.Compose([transforms.ToTensor(), discretize])\n", "\n", "# Loading the training dataset. We need to split it into a training and validation part\n", "train_dataset = MNIST(root=DATASET_PATH, train=True, transform=transform, download=True)\n", "L.seed_everything(42)\n", "train_set, val_set = torch.utils.data.random_split(train_dataset, [50000, 10000])\n", "\n", "# Loading the test set\n", "test_set = MNIST(root=DATASET_PATH, train=False, transform=transform, download=True)\n", "\n", "# We define a set of data loaders that we can use for various purposes later.\n", "# Note that for actually training a model, we will use different data loaders\n", "# with a lower batch size.\n", "train_loader = data.DataLoader(train_set, batch_size=256, shuffle=False, drop_last=False)\n", "val_loader = data.DataLoader(val_set, batch_size=64, shuffle=False, drop_last=False, num_workers=4)\n", "test_loader = data.DataLoader(test_set, batch_size=64, shuffle=False, drop_last=False, num_workers=4)"]}, {"cell_type": "markdown", "id": "f2a87c6f", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.010169, "end_time": "2023-03-14T16:08:52.011203", "exception": false, "start_time": "2023-03-14T16:08:52.001034", "status": "completed"}, "tags": []}, "source": ["In addition, we will define below a function to simplify the visualization of images/samples.\n", "Some training examples of the MNIST dataset is shown below."]}, {"cell_type": "code", "execution_count": 5, "id": "d170c817", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:52.035150Z", "iopub.status.busy": "2023-03-14T16:08:52.034845Z", "iopub.status.idle": "2023-03-14T16:08:52.192780Z", "shell.execute_reply": "2023-03-14T16:08:52.192170Z"}, "papermill": {"duration": 0.172541, "end_time": "2023-03-14T16:08:52.193954", "exception": false, "start_time": "2023-03-14T16:08:52.021413", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"341.674839pt\" height=\"180.72pt\" viewBox=\"0 0 341.674839 180.72\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:08:52.069465</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 180.72 \n", "L 341.674839 180.72 \n", "L 341.674839 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#pf280b881e8)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image05743962ba\" transform=\"scale(1 -1) translate(0 -166.32)\" x=\"7.2\" y=\"-7.2\" width=\"327.6\" height=\"166.32\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"pf280b881e8\">\n", " <rect x=\"7.2\" y=\"7.2\" width=\"327.274839\" height=\"166.32\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 600x300 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["def show_imgs(imgs, title=None, row_size=4):\n", " # Form a grid of pictures (we use max. 8 columns)\n", " num_imgs = imgs.shape[0] if isinstance(imgs, Tensor) else len(imgs)\n", " is_int = imgs.dtype == torch.int32 if isinstance(imgs, Tensor) else imgs[0].dtype == torch.int32\n", " nrow = min(num_imgs, row_size)\n", " ncol = int(math.ceil(num_imgs / nrow))\n", " imgs = torchvision.utils.make_grid(imgs, nrow=nrow, pad_value=128 if is_int else 0.5)\n", " np_imgs = imgs.cpu().numpy()\n", " # Plot the grid\n", " plt.figure(figsize=(1.5 * nrow, 1.5 * ncol))\n", " plt.imshow(np.transpose(np_imgs, (1, 2, 0)), interpolation=\"nearest\")\n", " plt.axis(\"off\")\n", " if title is not None:\n", " plt.title(title)\n", " plt.show()\n", " plt.close()\n", "\n", "\n", "show_imgs([train_set[i][0] for i in range(8)])"]}, {"cell_type": "markdown", "id": "bd028bb1", "metadata": {"papermill": {"duration": 0.010648, "end_time": "2023-03-14T16:08:52.215564", "exception": false, "start_time": "2023-03-14T16:08:52.204916", "status": "completed"}, "tags": []}, "source": ["## Normalizing Flows as generative model\n", "\n", "In the previous lectures, we have seen Energy-based models, Variational Autoencoders (VAEs)\n", "and Generative Adversarial Networks (GANs) as example of generative models.\n", "However, none of them explicitly learn the probability density function $p(x)$ of the real input data.\n", "While VAEs model a lower bound, energy-based models only implicitly learn the probability density.\n", "GANs on the other hand provide us a sampling mechanism for generating new data, without offering a likelihood estimate.\n", "The generative model we will look at here, called Normalizing Flows, actually models the true data distribution\n", "$p(x)$ and provides us with an exact likelihood estimate.\n", "Below, we can visually compare VAEs, GANs and Flows\n", "(figure credit - [Lilian Weng](https://lilianweng.github.io/lil-log/2018/10/13/flow-based-deep-generative-models.html)):\n", "\n", "<center width=\"100%\"><img src=\"https://github.com/Lightning-AI/lightning-tutorials/raw/main/course_UvA-DL/09-normalizing-flows/comparison_GAN_VAE_NF.png\" width=\"600px\"></center>\n", "\n", "The major difference compared to VAEs is that flows use *invertible* functions $f$\n", "to map the input data $x$ to a latent representation $z$.\n", "To realize this, $z$ must be of the same shape as $x$.\n", "This is in contrast to VAEs where $z$ is usually much lower dimensional than the original input data.\n", "However, an invertible mapping also means that for every data point $x$, we have a corresponding latent representation\n", "$z$ which allows us to perform lossless reconstruction ($z$ to $x$).\n", "In the visualization above, this means that $x=x'$ for flows, no matter what invertible function $f$ and input $x$ we choose.\n", "\n", "Nonetheless, how are normalizing flows modeling a probability density with an invertible function?\n", "The answer to this question is the rule for change of variables.\n", "Specifically, given a prior density $p_z(z)$ (e.g. Gaussian) and an invertible function $f$,\n", "we can determine $p_x(x)$ as follows:\n", "\n", "$$\n", "\\begin{split}\n", " \\int p_x(x) dx & = \\int p_z(z) dz = 1 \\hspace{1cm}\\text{(by definition of a probability distribution)}\\\\\n", " \\Leftrightarrow p_x(x) & = p_z(z) \\left|\\frac{dz}{dx}\\right| = p_z(f(x)) \\left|\\frac{df(x)}{dx}\\right|\n", "\\end{split}\n", "$$\n", "\n", "Hence, in order to determine the probability of $x$, we only need to determine its probability in latent space,\n", "and get the derivate of $f$.\n", "Note that this is for a univariate distribution, and $f$ is required to be invertible and smooth.\n", "For a multivariate case, the derivative becomes a Jacobian of which we need to take the determinant.\n", "As we usually use the log-likelihood as objective, we write the multivariate term with logarithms below:\n", "\n", "$$\n", "\\log p_x(\\mathbf{x}) = \\log p_z(f(\\mathbf{x})) + \\log{} \\left|\\det \\frac{df(\\mathbf{x})}{d\\mathbf{x}}\\right|\n", "$$\n", "\n", "Although we now know how a normalizing flow obtains its likelihood, it might not be clear what a normalizing flow does intuitively.\n", "For this, we should look from the inverse perspective of the flow starting with the prior probability density $p_z(z)$.\n", "If we apply an invertible function on it, we effectively \"transform\" its probability density.\n", "For instance, if $f^{-1}(z)=z+1$, we shift the density by one while still remaining a valid probability distribution,\n", "and being invertible.\n", "We can also apply more complex transformations, like scaling: $f^{-1}(z)=2z+1$, but there you might see a difference.\n", "When you scale, you also change the volume of the probability density, as for example on uniform distributions\n", "(figure credit - [Eric Jang](https://blog.evjang.com/2018/01/nf1.html)):\n", "\n", "<center width=\"100%\"><img src=\"https://github.com/Lightning-AI/lightning-tutorials/raw/main/course_UvA-DL/09-normalizing-flows/uniform_flow.png\" width=\"300px\"></center>\n", "\n", "You can see that the height of $p(y)$ should be lower than $p(x)$ after scaling.\n", "This change in volume represents $\\left|\\frac{df(x)}{dx}\\right|$ in our equation above,\n", "and ensures that even after scaling, we still have a valid probability distribution.\n", "We can go on with making our function $f$ more complex.\n", "However, the more complex $f$ becomes, the harder it will be to find the inverse $f^{-1}$ of it,\n", "and to calculate the log-determinant of the Jacobian $\\log{} \\left|\\det \\frac{df(\\mathbf{x})}{d\\mathbf{x}}\\right|$.\n", "An easier trick to stack multiple invertible functions $f_{1,...,K}$ after each other, as all together,\n", "they still represent a single, invertible function.\n", "Using multiple, learnable invertible functions, a normalizing flow attempts to transform\n", "$p_z(z)$ slowly into a more complex distribution which should finally be $p_x(x)$.\n", "We visualize the idea below\n", "(figure credit - [Lilian Weng](https://lilianweng.github.io/lil-log/2018/10/13/flow-based-deep-generative-models.html)):\n", "\n", "<center width=\"100%\"><img src=\"https://github.com/Lightning-AI/lightning-tutorials/raw/main/course_UvA-DL/09-normalizing-flows/normalizing_flow_layout.png\" width=\"700px\"></center>\n", "\n", "Starting from $z_0$, which follows the prior Gaussian distribution, we sequentially apply the invertible\n", "functions $f_1,f_2,...,f_K$, until $z_K$ represents $x$.\n", "Note that in the figure above, the functions $f$ represent the inverted function from $f$ we had above\n", "(here: $f:Z\\to X$, above: $f:X\\to Z$).\n", "This is just a different notation and has no impact on the actual flow design because all $f$ need to be invertible anyways.\n", "When we estimate the log likelihood of a data point $x$ as in the equations above,\n", "we run the flows in the opposite direction than visualized above.\n", "Multiple flow layers have been proposed that use a neural network as learnable parameters,\n", "such as the planar and radial flow.\n", "However, we will focus here on flows that are commonly used in image\n", "modeling, and will discuss them in the rest of the notebook along with\n", "the details of how to train a normalizing flow."]}, {"cell_type": "markdown", "id": "be852389", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.010512, "end_time": "2023-03-14T16:08:52.236613", "exception": false, "start_time": "2023-03-14T16:08:52.226101", "status": "completed"}, "tags": []}, "source": ["## Normalizing Flows on images\n", "\n", "<div class=\"center-wrapper\"><div class=\"video-wrapper\"><iframe src=\"https://www.youtube.com/embed/qMoGcRhVrF8\" title=\"YouTube video player\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe></div></div>\n", "\n", "To become familiar with normalizing flows, especially for the application of image modeling,\n", "it is best to discuss the different elements in a flow along with the implementation.\n", "As a general concept, we want to build a normalizing flow that maps an input image (here MNIST) to an equally sized latent space:\n", "\n", "<center width=\"100%\" style=\"padding: 10px\"><img src=\"https://github.com/Lightning-AI/lightning-tutorials/raw/main/course_UvA-DL/09-normalizing-flows/image_to_gaussian.svg\" width=\"450px\"></center>\n", "\n", "As a first step, we will implement a template of a normalizing flow in PyTorch Lightning.\n", "During training and validation, a normalizing flow performs density estimation in the forward direction.\n", "For this, we apply a series of flow transformations on the input $x$ and estimate the probability\n", "of the input by determining the probability of the transformed point $z$ given a prior,\n", "and the change of volume caused by the transformations.\n", "During inference, we can do both density estimation and sampling new points by inverting the flow transformations.\n", "Therefore, we define a function `_get_likelihood` which performs density estimation,\n", "and `sample` to generate new examples.\n", "The functions `training_step`, `validation_step` and `test_step` all make use of `_get_likelihood`.\n", "\n", "The standard metric used in generative models, and in particular normalizing flows, is bits per dimensions (bpd).\n", "Bpd is motivated from an information theory perspective and describes how many bits we would need to encode a particular example in our modeled distribution.\n", "The less bits we need, the more likely the example in our distribution.\n", "When we test for the bits per dimension of our test dataset, we can judge whether our model generalizes to new samples of the dataset and didn't memorize the training dataset.\n", "In order to calculate the bits per dimension score, we can rely on the negative log-likelihood and change the log base (as bits are binary while NLL is usually exponential):\n", "\n", "$$\\text{bpd} = \\text{nll} \\cdot \\log_2\\left(\\exp(1)\\right) \\cdot \\left(\\prod d_i\\right)^{-1}$$\n", "\n", "where $d_1,...,d_K$ are the dimensions of the input.\n", "For images, this would be the height, width and channel number.\n", "We divide the log likelihood by these extra dimensions to have a metric which we can compare for different image resolutions.\n", "In the original image space, MNIST examples have a bits per dimension\n", "score of 8 (we need 8 bits to encode each pixel as there are 256\n", "possible values)."]}, {"cell_type": "code", "execution_count": 6, "id": "e75ff1f5", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:52.260104Z", "iopub.status.busy": "2023-03-14T16:08:52.259443Z", "iopub.status.idle": "2023-03-14T16:08:52.276630Z", "shell.execute_reply": "2023-03-14T16:08:52.276152Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.031425, "end_time": "2023-03-14T16:08:52.278733", "exception": false, "start_time": "2023-03-14T16:08:52.247308", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class ImageFlow(L.LightningModule):\n", " def __init__(self, flows, import_samples=8):\n", " \"\"\"\n", " Args:\n", " flows: A list of flows (each a nn.Module) that should be applied on the images.\n", " import_samples: Number of importance samples to use during testing (see explanation below). Can be changed at any time\n", " \"\"\"\n", " super().__init__()\n", " self.flows = nn.ModuleList(flows)\n", " self.import_samples = import_samples\n", " # Create prior distribution for final latent space\n", " self.prior = torch.distributions.normal.Normal(loc=0.0, scale=1.0)\n", " # Example input for visualizing the graph\n", " self.example_input_array = train_set[0][0].unsqueeze(dim=0)\n", "\n", " def forward(self, imgs):\n", " # The forward function is only used for visualizing the graph\n", " return self._get_likelihood(imgs)\n", "\n", " def encode(self, imgs):\n", " # Given a batch of images, return the latent representation z and ldj of the transformations\n", " z, ldj = imgs, torch.zeros(imgs.shape[0], device=self.device)\n", " for flow in self.flows:\n", " z, ldj = flow(z, ldj, reverse=False)\n", " return z, ldj\n", "\n", " def _get_likelihood(self, imgs, return_ll=False):\n", " \"\"\"Given a batch of images, return the likelihood of those.\n", "\n", " If return_ll is True, this function returns the log likelihood of the input. Otherwise, the ouptut metric is\n", " bits per dimension (scaled negative log likelihood)\n", " \"\"\"\n", " z, ldj = self.encode(imgs)\n", " log_pz = self.prior.log_prob(z).sum(dim=[1, 2, 3])\n", " log_px = ldj + log_pz\n", " nll = -log_px\n", " # Calculating bits per dimension\n", " bpd = nll * np.log2(np.exp(1)) / np.prod(imgs.shape[1:])\n", " return bpd.mean() if not return_ll else log_px\n", "\n", " @torch.no_grad()\n", " def sample(self, img_shape, z_init=None):\n", " \"\"\"Sample a batch of images from the flow.\"\"\"\n", " # Sample latent representation from prior\n", " if z_init is None:\n", " z = self.prior.sample(sample_shape=img_shape).to(device)\n", " else:\n", " z = z_init.to(device)\n", "\n", " # Transform z to x by inverting the flows\n", " ldj = torch.zeros(img_shape[0], device=device)\n", " for flow in reversed(self.flows):\n", " z, ldj = flow(z, ldj, reverse=True)\n", " return z\n", "\n", " def configure_optimizers(self):\n", " optimizer = optim.Adam(self.parameters(), lr=1e-3)\n", " # An scheduler is optional, but can help in flows to get the last bpd improvement\n", " scheduler = optim.lr_scheduler.StepLR(optimizer, 1, gamma=0.99)\n", " return [optimizer], [scheduler]\n", "\n", " def training_step(self, batch, batch_idx):\n", " # Normalizing flows are trained by maximum likelihood => return bpd\n", " loss = self._get_likelihood(batch[0])\n", " self.log(\"train_bpd\", loss)\n", " return loss\n", "\n", " def validation_step(self, batch, batch_idx):\n", " loss = self._get_likelihood(batch[0])\n", " self.log(\"val_bpd\", loss)\n", "\n", " def test_step(self, batch, batch_idx):\n", " # Perform importance sampling during testing => estimate likelihood M times for each image\n", " samples = []\n", " for _ in range(self.import_samples):\n", " img_ll = self._get_likelihood(batch[0], return_ll=True)\n", " samples.append(img_ll)\n", " img_ll = torch.stack(samples, dim=-1)\n", "\n", " # To average the probabilities, we need to go from log-space to exp, and back to log.\n", " # Logsumexp provides us a stable implementation for this\n", " img_ll = torch.logsumexp(img_ll, dim=-1) - np.log(self.import_samples)\n", "\n", " # Calculate final bpd\n", " bpd = -img_ll * np.log2(np.exp(1)) / np.prod(batch[0].shape[1:])\n", " bpd = bpd.mean()\n", "\n", " self.log(\"test_bpd\", bpd)"]}, {"cell_type": "markdown", "id": "939bf7af", "metadata": {"papermill": {"duration": 0.01055, "end_time": "2023-03-14T16:08:52.304898", "exception": false, "start_time": "2023-03-14T16:08:52.294348", "status": "completed"}, "tags": []}, "source": ["The `test_step` function differs from the training and validation step in that it makes use of importance sampling.\n", "We will discuss the motiviation and details behind this after\n", "understanding how flows model discrete images in continuous space."]}, {"cell_type": "markdown", "id": "248c83f9", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.010749, "end_time": "2023-03-14T16:08:52.326437", "exception": false, "start_time": "2023-03-14T16:08:52.315688", "status": "completed"}, "tags": []}, "source": ["### Dequantization\n", "\n", "Normalizing flows rely on the rule of change of variables, which is naturally defined in continuous space.\n", "Applying flows directly on discrete data leads to undesired density models where arbitrarly high likelihood are placed on a few, particular values.\n", "See the illustration below:\n", "\n", "<center><img src=\"https://github.com/Lightning-AI/lightning-tutorials/raw/main/course_UvA-DL/09-normalizing-flows/dequantization_issue.svg\" width=\"40%\"/></center>\n", "\n", "The black points represent the discrete points, and the green volume the density modeled by a normalizing flow in continuous space.\n", "The flow would continue to increase the likelihood for $x=0,1,2,3$ while having no volume on any other point.\n", "Remember that in continuous space, we have the constraint that the overall volume of the probability density must be 1 ($\\int p(x)dx=1$).\n", "Otherwise, we don't model a probability distribution anymore.\n", "However, the discrete points $x=0,1,2,3$ represent delta peaks with no width in continuous space.\n", "This is why the flow can place an infinite high likelihood on these few points while still representing a distribution in continuous space.\n", "Nonetheless, the learned density does not tell us anything about the distribution among the discrete points,\n", "as in discrete space, the likelihoods of those four points would have to sum to 1, not to infinity.\n", "\n", "To prevent such degenerated solutions, a common solution is to add a small amount of noise to each discrete value, which is also referred to as dequantization.\n", "Considering $x$ as an integer (as it is the case for images), the dequantized representation $v$ can be formulated as $v=x+u$ where $u\\in[0,1)^D$.\n", "Thus, the discrete value $1$ is modeled by a distribution over the interval $[1.0, 2.0)$, the value $2$ by an volume over $[2.0, 3.0)$, etc.\n", "Our objective of modeling $p(x)$ becomes:\n", "\n", "$$ p(x) = \\int p(x+u)du = \\int \\frac{q(u|x)}{q(u|x)}p(x+u)du = \\mathbb{E}_{u\\sim q(u|x)}\\left[\\frac{p(x+u)}{q(u|x)} \\right]$$\n", "\n", "with $q(u|x)$ being the noise distribution.\n", "For now, we assume it to be uniform, which can also be written as $p(x)=\\mathbb{E}_{u\\sim U(0,1)^D}\\left[p(x+u) \\right]$.\n", "\n", "In the following, we will implement Dequantization as a flow transformation itself.\n", "After adding noise to the discrete values, we additionally transform the volume into a Gaussian-like shape.\n", "This is done by scaling $x+u$ between $0$ and $1$, and applying the invert of the sigmoid function $\\sigma(z)^{-1} = \\log z - \\log 1-z$.\n", "If we would not do this, we would face two problems:\n", "\n", "1.\n", "The input is scaled between 0 and 256 while the prior distribution is a Gaussian with mean $0$ and standard deviation $1$.\n", "In the first iterations after initializing the parameters of the flow, we would have extremely low likelihoods for large values like $256$.\n", "This would cause the training to diverge instantaneously.\n", "2.\n", "As the output distribution is a Gaussian, it is beneficial for the flow to have a similarly shaped input distribution.\n", "This will reduce the modeling complexity that is required by the flow.\n", "\n", "Overall, we can implement dequantization as follows:"]}, {"cell_type": "code", "execution_count": 7, "id": "9e1c0242", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:52.349387Z", "iopub.status.busy": "2023-03-14T16:08:52.348820Z", "iopub.status.idle": "2023-03-14T16:08:52.362864Z", "shell.execute_reply": "2023-03-14T16:08:52.362396Z"}, "papermill": {"duration": 0.028177, "end_time": "2023-03-14T16:08:52.365251", "exception": false, "start_time": "2023-03-14T16:08:52.337074", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class Dequantization(nn.Module):\n", " def __init__(self, alpha=1e-5, quants=256):\n", " \"\"\"\n", " Args:\n", " alpha: small constant that is used to scale the original input.\n", " Prevents dealing with values very close to 0 and 1 when inverting the sigmoid\n", " quants: Number of possible discrete values (usually 256 for 8-bit image)\n", " \"\"\"\n", " super().__init__()\n", " self.alpha = alpha\n", " self.quants = quants\n", "\n", " def forward(self, z, ldj, reverse=False):\n", " if not reverse:\n", " z, ldj = self.dequant(z, ldj)\n", " z, ldj = self.sigmoid(z, ldj, reverse=True)\n", " else:\n", " z, ldj = self.sigmoid(z, ldj, reverse=False)\n", " z = z * self.quants\n", " ldj += np.log(self.quants) * np.prod(z.shape[1:])\n", " z = torch.floor(z).clamp(min=0, max=self.quants - 1).to(torch.int32)\n", " return z, ldj\n", "\n", " def sigmoid(self, z, ldj, reverse=False):\n", " # Applies an invertible sigmoid transformation\n", " if not reverse:\n", " ldj += (-z - 2 * F.softplus(-z)).sum(dim=[1, 2, 3])\n", " z = torch.sigmoid(z)\n", " else:\n", " z = z * (1 - self.alpha) + 0.5 * self.alpha # Scale to prevent boundaries 0 and 1\n", " ldj += np.log(1 - self.alpha) * np.prod(z.shape[1:])\n", " ldj += (-torch.log(z) - torch.log(1 - z)).sum(dim=[1, 2, 3])\n", " z = torch.log(z) - torch.log(1 - z)\n", " return z, ldj\n", "\n", " def dequant(self, z, ldj):\n", " # Transform discrete values to continuous volumes\n", " z = z.to(torch.float32)\n", " z = z + torch.rand_like(z).detach()\n", " z = z / self.quants\n", " ldj -= np.log(self.quants) * np.prod(z.shape[1:])\n", " return z, ldj"]}, {"cell_type": "markdown", "id": "8f1d2ba6", "metadata": {"papermill": {"duration": 0.010565, "end_time": "2023-03-14T16:08:52.390006", "exception": false, "start_time": "2023-03-14T16:08:52.379441", "status": "completed"}, "tags": []}, "source": ["A good check whether a flow is correctly implemented or not, is to verify that it is invertible.\n", "Hence, we will dequantize a randomly chosen training image, and then quantize it again.\n", "We would expect that we would get the exact same image out:"]}, {"cell_type": "code", "execution_count": 8, "id": "05d6e03d", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:52.412837Z", "iopub.status.busy": "2023-03-14T16:08:52.412458Z", "iopub.status.idle": "2023-03-14T16:08:52.426314Z", "shell.execute_reply": "2023-03-14T16:08:52.425832Z"}, "papermill": {"duration": 0.027687, "end_time": "2023-03-14T16:08:52.428343", "exception": false, "start_time": "2023-03-14T16:08:52.400656", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Global seed set to 42\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Dequantization was not invertible.\n", "Original value: 0\n", "Reconstructed value: 1\n"]}], "source": ["# Testing invertibility of dequantization layer\n", "L.seed_everything(42)\n", "orig_img = train_set[0][0].unsqueeze(dim=0)\n", "ldj = torch.zeros(\n", " 1,\n", ")\n", "dequant_module = Dequantization()\n", "deq_img, ldj = dequant_module(orig_img, ldj, reverse=False)\n", "reconst_img, ldj = dequant_module(deq_img, ldj, reverse=True)\n", "\n", "d1, d2 = torch.where(orig_img.squeeze() != reconst_img.squeeze())\n", "if len(d1) != 0:\n", " print(\"Dequantization was not invertible.\")\n", " for i in range(d1.shape[0]):\n", " print(\"Original value:\", orig_img[0, 0, d1[i], d2[i]].item())\n", " print(\"Reconstructed value:\", reconst_img[0, 0, d1[i], d2[i]].item())\n", "else:\n", " print(\"Successfully inverted dequantization\")\n", "\n", "# Layer is not strictly invertible due to float precision constraints\n", "# assert (orig_img == reconst_img).all().item()"]}, {"cell_type": "markdown", "id": "64743184", "metadata": {"papermill": {"duration": 0.010719, "end_time": "2023-03-14T16:08:52.453044", "exception": false, "start_time": "2023-03-14T16:08:52.442325", "status": "completed"}, "tags": []}, "source": ["In contrast to our expectation, the test fails.\n", "However, this is no reason to doubt our implementation here as only one single value is not equal to the original.\n", "This is caused due to numerical inaccuracies in the sigmoid invert.\n", "While the input space to the inverted sigmoid is scaled between 0 and 1, the output space is between $-\\infty$ and $\\infty$.\n", "And as we use 32 bits to represent the numbers (in addition to applying logs over and over again),\n", "such inaccuries can occur and should not be worrisome.\n", "Nevertheless, it is good to be aware of them, and can be improved by using a double tensor (float64).\n", "\n", "Finally, we can take our dequantization and actually visualize the\n", "distribution it transforms the discrete values into:"]}, {"cell_type": "code", "execution_count": 9, "id": "d4d49a0a", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:52.476344Z", "iopub.status.busy": "2023-03-14T16:08:52.475761Z", "iopub.status.idle": "2023-03-14T16:08:52.922166Z", "shell.execute_reply": "2023-03-14T16:08:52.921514Z"}, "papermill": {"duration": 0.462246, "end_time": "2023-03-14T16:08:52.926115", "exception": false, "start_time": "2023-03-14T16:08:52.463869", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"400.095313pt\" height=\"226.194375pt\" viewBox=\"0 0 400.095313 226.194375\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:08:52.653925</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 226.194375 \n", "L 400.095313 226.194375 \n", "L 400.095313 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g id=\"patch_2\">\n", " <path d=\"M 50.14375 188.638125 \n", "L 384.94375 188.638125 \n", "L 384.94375 22.318125 \n", "L 50.14375 22.318125 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"matplotlib.axis_1\">\n", " <g id=\"xtick_1\">\n", " <g id=\"text_1\">\n", " <!-- -4.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(40.388281 203.236563) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-2d\" d=\"M 313 2009 \n", "L 1997 2009 \n", "L 1997 1497 \n", "L 313 1497 \n", "L 313 2009 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-34\" d=\"M 2419 4116 \n", "L 825 1625 \n", "L 2419 1625 \n", "L 2419 4116 \n", "z\n", "M 2253 4666 \n", "L 3047 4666 \n", "L 3047 1625 \n", "L 3713 1625 \n", "L 3713 1100 \n", "L 3047 1100 \n", "L 3047 0 \n", "L 2419 0 \n", "L 2419 1100 \n", "L 313 1100 \n", "L 313 1709 \n", "L 2253 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-2e\" d=\"M 684 794 \n", "L 1344 794 \n", "L 1344 0 \n", "L 684 0 \n", "L 684 794 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-30\" d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2d\"/>\n", " <use xlink:href=\"#DejaVuSans-34\" x=\"36.083984\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"99.707031\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"131.494141\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_2\">\n", " <g id=\"text_2\">\n", " <!-- -1.9 -->\n", " <g style=\"fill: #262626\" transform=\"translate(126.707177 203.236563) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-31\" d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-39\" d=\"M 703 97 \n", "L 703 672 \n", "Q 941 559 1184 500 \n", "Q 1428 441 1663 441 \n", "Q 2288 441 2617 861 \n", "Q 2947 1281 2994 2138 \n", "Q 2813 1869 2534 1725 \n", "Q 2256 1581 1919 1581 \n", "Q 1219 1581 811 2004 \n", "Q 403 2428 403 3163 \n", "Q 403 3881 828 4315 \n", "Q 1253 4750 1959 4750 \n", "Q 2769 4750 3195 4129 \n", "Q 3622 3509 3622 2328 \n", "Q 3622 1225 3098 567 \n", "Q 2575 -91 1691 -91 \n", "Q 1453 -91 1209 -44 \n", "Q 966 3 703 97 \n", "z\n", "M 1959 2075 \n", "Q 2384 2075 2632 2365 \n", "Q 2881 2656 2881 3163 \n", "Q 2881 3666 2632 3958 \n", "Q 2384 4250 1959 4250 \n", "Q 1534 4250 1286 3958 \n", "Q 1038 3666 1038 3163 \n", "Q 1038 2656 1286 2365 \n", "Q 1534 2075 1959 2075 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2d\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"36.083984\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"99.707031\"/>\n", " <use xlink:href=\"#DejaVuSans-39\" x=\"131.494141\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_3\">\n", " <g id=\"text_3\">\n", " <!-- -1.1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(162.3242 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-2d\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"36.083984\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"99.707031\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"131.494141\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_4\">\n", " <g id=\"text_4\">\n", " <!-- -0.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(186.627581 203.236563) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-35\" d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2d\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"36.083984\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"99.707031\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"131.494141\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_5\">\n", " <g id=\"text_5\">\n", " <!-- 0.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(209.801699 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_6\">\n", " <g id=\"text_6\">\n", " <!-- 0.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(231.590935 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_7\">\n", " <g id=\"text_7\">\n", " <!-- 1.1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(255.894311 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_8\">\n", " <g id=\"text_8\">\n", " <!-- 1.9 -->\n", " <g style=\"fill: #262626\" transform=\"translate(291.511333 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-39\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_9\">\n", " <g id=\"text_9\">\n", " <!-- 4.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(376.992188 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-34\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"text_10\">\n", " <!-- z -->\n", " <g style=\"fill: #262626\" transform=\"translate(214.919531 216.914688) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-7a\" d=\"M 353 3500 \n", "L 3084 3500 \n", "L 3084 2975 \n", "L 922 459 \n", "L 3084 459 \n", "L 3084 0 \n", "L 275 0 \n", "L 275 525 \n", "L 2438 3041 \n", "L 353 3041 \n", "L 353 3500 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-7a\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"matplotlib.axis_2\">\n", " <g id=\"ytick_1\">\n", " <g id=\"text_11\">\n", " <!-- 0.00 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 192.437344) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"159.033203\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_2\">\n", " <g id=\"text_12\">\n", " <!-- 0.05 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 162.197344) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"159.033203\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_3\">\n", " <g id=\"text_13\">\n", " <!-- 0.10 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 131.957344) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"95.410156\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"159.033203\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_4\">\n", " <g id=\"text_14\">\n", " <!-- 0.15 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 101.717344) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"95.410156\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"159.033203\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_5\">\n", " <g id=\"text_15\">\n", " <!-- 0.20 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 71.477344) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-32\" d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"95.410156\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"159.033203\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_6\">\n", " <g id=\"text_16\">\n", " <!-- 0.25 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 41.237344) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"95.410156\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"159.033203\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"text_17\">\n", " <!-- Probability -->\n", " <g style=\"fill: #262626\" transform=\"translate(14.798438 131.907031) rotate(-90) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-50\" d=\"M 1259 4147 \n", "L 1259 2394 \n", "L 2053 2394 \n", "Q 2494 2394 2734 2622 \n", "Q 2975 2850 2975 3272 \n", "Q 2975 3691 2734 3919 \n", "Q 2494 4147 2053 4147 \n", "L 1259 4147 \n", "z\n", "M 628 4666 \n", "L 2053 4666 \n", "Q 2838 4666 3239 4311 \n", "Q 3641 3956 3641 3272 \n", "Q 3641 2581 3239 2228 \n", "Q 2838 1875 2053 1875 \n", "L 1259 1875 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-72\" d=\"M 2631 2963 \n", "Q 2534 3019 2420 3045 \n", "Q 2306 3072 2169 3072 \n", "Q 1681 3072 1420 2755 \n", "Q 1159 2438 1159 1844 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1341 3275 1631 3429 \n", "Q 1922 3584 2338 3584 \n", "Q 2397 3584 2469 3576 \n", "Q 2541 3569 2628 3553 \n", "L 2631 2963 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6f\" d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-62\" d=\"M 3116 1747 \n", "Q 3116 2381 2855 2742 \n", "Q 2594 3103 2138 3103 \n", "Q 1681 3103 1420 2742 \n", "Q 1159 2381 1159 1747 \n", "Q 1159 1113 1420 752 \n", "Q 1681 391 2138 391 \n", "Q 2594 391 2855 752 \n", "Q 3116 1113 3116 1747 \n", "z\n", "M 1159 2969 \n", "Q 1341 3281 1617 3432 \n", "Q 1894 3584 2278 3584 \n", "Q 2916 3584 3314 3078 \n", "Q 3713 2572 3713 1747 \n", "Q 3713 922 3314 415 \n", "Q 2916 -91 2278 -91 \n", "Q 1894 -91 1617 61 \n", "Q 1341 213 1159 525 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "L 1159 4863 \n", "L 1159 2969 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-61\" d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-69\" d=\"M 603 3500 \n", "L 1178 3500 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 3500 \n", "z\n", "M 603 4863 \n", "L 1178 4863 \n", "L 1178 4134 \n", "L 603 4134 \n", "L 603 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6c\" d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-74\" d=\"M 1172 4494 \n", "L 1172 3500 \n", "L 2356 3500 \n", "L 2356 3053 \n", "L 1172 3053 \n", "L 1172 1153 \n", "Q 1172 725 1289 603 \n", "Q 1406 481 1766 481 \n", "L 2356 481 \n", "L 2356 0 \n", "L 1766 0 \n", "Q 1100 0 847 248 \n", "Q 594 497 594 1153 \n", "L 594 3053 \n", "L 172 3053 \n", "L 172 3500 \n", "L 594 3500 \n", "L 594 4494 \n", "L 1172 4494 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-79\" d=\"M 2059 -325 \n", "Q 1816 -950 1584 -1140 \n", "Q 1353 -1331 966 -1331 \n", "L 506 -1331 \n", "L 506 -850 \n", "L 844 -850 \n", "Q 1081 -850 1212 -737 \n", "Q 1344 -625 1503 -206 \n", "L 1606 56 \n", "L 191 3500 \n", "L 800 3500 \n", "L 1894 763 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2059 -325 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-50\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"58.552734\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"97.416016\"/>\n", " <use xlink:href=\"#DejaVuSans-62\" x=\"158.597656\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"222.074219\"/>\n", " <use xlink:href=\"#DejaVuSans-62\" x=\"283.353516\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"346.830078\"/>\n", " <use xlink:href=\"#DejaVuSans-6c\" x=\"374.613281\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"402.396484\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"430.179688\"/>\n", " <use xlink:href=\"#DejaVuSans-79\" x=\"469.388672\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_1\">\n", " <defs>\n", " <path id=\"m64202ac6c4\" d=\"M 50.14375 -37.55625 \n", "L 50.14375 -48.238657 \n", "L 50.562773 -48.342109 \n", "L 50.981797 -48.446538 \n", "L 51.40082 -48.551936 \n", "L 51.819844 -48.658306 \n", "L 52.238867 -48.765666 \n", "L 52.65789 -48.874031 \n", "L 53.076914 -48.98339 \n", "L 53.495937 -49.093766 \n", "L 53.91496 -49.205165 \n", "L 54.333984 -49.317593 \n", "L 54.753007 -49.431062 \n", "L 55.172031 -49.545573 \n", "L 55.591054 -49.661149 \n", "L 56.010077 -49.777787 \n", "L 56.429101 -49.895495 \n", "L 56.848134 -50.014286 \n", "L 57.267157 -50.134177 \n", "L 57.686181 -50.255161 \n", "L 58.105204 -50.377258 \n", "L 58.524228 -50.500469 \n", "L 58.943251 -50.624814 \n", "L 59.362274 -50.750297 \n", "L 59.781298 -50.876921 \n", "L 60.200321 -51.004708 \n", "L 60.619344 -51.133657 \n", "L 61.038368 -51.263777 \n", "L 61.457391 -51.395085 \n", "L 61.876415 -51.527584 \n", "L 62.295438 -51.66129 \n", "L 62.714461 -51.796209 \n", "L 63.133485 -51.93235 \n", "L 63.552508 -52.069722 \n", "L 63.971532 -52.208345 \n", "L 64.390555 -52.348208 \n", "L 64.809578 -52.48934 \n", "L 65.228602 -52.631741 \n", "L 65.647625 -52.775426 \n", "L 66.066648 -52.920401 \n", "L 66.485672 -53.066683 \n", "L 66.904705 -53.21428 \n", "L 67.323729 -53.363193 \n", "L 67.742752 -53.513441 \n", "L 68.161775 -53.665031 \n", "L 68.580799 -53.817968 \n", "L 68.999822 -53.972279 \n", "L 69.418845 -54.127959 \n", "L 69.837869 -54.285028 \n", "L 70.256892 -54.44349 \n", "L 70.675916 -54.603354 \n", "L 71.094939 -54.764641 \n", "L 71.513962 -54.927348 \n", "L 71.932986 -55.0915 \n", "L 72.352009 -55.257094 \n", "L 72.771032 -55.424149 \n", "L 73.190056 -55.592677 \n", "L 73.609079 -55.762684 \n", "L 74.028103 -55.934187 \n", "L 74.447126 -56.107181 \n", "L 74.866149 -56.281697 \n", "L 75.285173 -56.457737 \n", "L 75.704196 -56.635314 \n", "L 76.12322 -56.814441 \n", "L 76.542243 -56.995118 \n", "L 76.961276 -57.177374 \n", "L 77.3803 -57.361201 \n", "L 77.799323 -57.546628 \n", "L 78.218346 -57.733647 \n", "L 78.63737 -57.922288 \n", "L 79.056393 -58.112546 \n", "L 79.475417 -58.304443 \n", "L 79.89444 -58.497991 \n", "L 80.313463 -58.693205 \n", "L 80.732487 -58.890075 \n", "L 81.15151 -59.088635 \n", "L 81.570533 -59.288886 \n", "L 81.989557 -59.490845 \n", "L 82.40858 -59.69451 \n", "L 82.827604 -59.899908 \n", "L 83.246627 -60.107049 \n", "L 83.66565 -60.315948 \n", "L 84.084674 -60.526595 \n", "L 84.503697 -60.739016 \n", "L 84.92272 -60.953234 \n", "L 85.341744 -61.169239 \n", "L 85.760767 -61.387058 \n", "L 86.179791 -61.60669 \n", "L 86.598814 -61.82815 \n", "L 87.017847 -62.051468 \n", "L 87.436871 -62.276634 \n", "L 87.855894 -62.503656 \n", "L 88.274918 -62.732571 \n", "L 88.693941 -62.963367 \n", "L 89.112964 -63.196061 \n", "L 89.531988 -63.430662 \n", "L 89.951011 -63.667199 \n", "L 90.370034 -63.905661 \n", "L 90.789058 -64.146071 \n", "L 91.208081 -64.388443 \n", "L 91.627105 -64.63278 \n", "L 92.046128 -64.879095 \n", "L 92.465151 -65.1274 \n", "L 92.884175 -65.37771 \n", "L 93.303198 -65.630039 \n", "L 93.722221 -65.884386 \n", "L 94.141245 -66.140777 \n", "L 94.560268 -66.399216 \n", "L 94.979292 -66.659712 \n", "L 95.398315 -66.922281 \n", "L 95.817338 -67.186936 \n", "L 96.236362 -67.453678 \n", "L 96.655385 -67.722519 \n", "L 97.074408 -67.993472 \n", "L 97.493432 -68.266551 \n", "L 97.912455 -68.541769 \n", "L 98.331479 -68.819126 \n", "L 98.750502 -69.098652 \n", "L 99.169525 -69.380327 \n", "L 99.588549 -69.664193 \n", "L 100.007572 -69.950255 \n", "L 100.426606 -70.238497 \n", "L 100.845629 -70.528968 \n", "L 101.264652 -70.821638 \n", "L 101.683676 -71.116538 \n", "L 102.102699 -71.413682 \n", "L 102.521722 -71.713082 \n", "L 102.940746 -72.014734 \n", "L 103.359769 -72.318653 \n", "L 103.778793 -72.624853 \n", "L 104.197816 -72.933343 \n", "L 104.616839 -73.244121 \n", "L 105.035863 -73.557201 \n", "L 105.454886 -73.872595 \n", "L 105.873909 -74.190314 \n", "L 106.292933 -74.510372 \n", "L 106.711956 -74.832766 \n", "L 107.13098 -75.157506 \n", "L 107.550003 -75.48462 \n", "L 107.969026 -75.814071 \n", "L 108.38805 -76.145923 \n", "L 108.807073 -76.480137 \n", "L 109.226096 -76.816757 \n", "L 109.64512 -77.155756 \n", "L 110.064143 -77.497171 \n", "L 110.483177 -77.841001 \n", "L 110.9022 -78.187259 \n", "L 111.321223 -78.535929 \n", "L 111.740247 -78.887013 \n", "L 112.15927 -79.240554 \n", "L 112.578294 -79.596555 \n", "L 112.997317 -79.954966 \n", "L 113.41634 -80.31587 \n", "L 113.835364 -80.679224 \n", "L 114.254387 -81.045044 \n", "L 114.67341 -81.413338 \n", "L 115.092434 -81.7841 \n", "L 115.511457 -82.15736 \n", "L 115.930481 -82.533102 \n", "L 116.349504 -82.911318 \n", "L 116.768527 -83.292039 \n", "L 117.187551 -83.675275 \n", "L 117.606574 -84.060989 \n", "L 118.025597 -84.449235 \n", "L 118.444621 -84.839956 \n", "L 118.863644 -85.233209 \n", "L 119.282668 -85.628971 \n", "L 119.701691 -86.027235 \n", "L 120.120714 -86.428031 \n", "L 120.539748 -86.83135 \n", "L 120.958771 -87.23718 \n", "L 121.377794 -87.645519 \n", "L 121.796818 -88.056395 \n", "L 122.215841 -88.469795 \n", "L 122.634865 -88.885691 \n", "L 123.053888 -89.304124 \n", "L 123.472911 -89.725049 \n", "L 123.891935 -90.14852 \n", "L 124.310958 -90.574491 \n", "L 124.729982 -91.002995 \n", "L 125.149005 -91.433987 \n", "L 125.568028 -91.867497 \n", "L 125.987052 -92.3035 \n", "L 126.406075 -92.742007 \n", "L 126.825098 -93.183016 \n", "L 127.244122 -93.626534 \n", "L 127.663145 -94.072509 \n", "L 128.082169 -94.521002 \n", "L 128.501192 -94.971956 \n", "L 128.920215 -95.425379 \n", "L 129.339239 -95.881266 \n", "L 129.758262 -96.339601 \n", "L 130.177285 -96.800405 \n", "L 130.596319 -97.263638 \n", "L 131.015342 -97.729304 \n", "L 131.434366 -98.197412 \n", "L 131.853389 -98.667913 \n", "L 132.272412 -99.140829 \n", "L 132.691436 -99.616166 \n", "L 133.110459 -100.093858 \n", "L 133.529482 -100.57393 \n", "L 133.948506 -101.056359 \n", "L 134.367529 -101.541172 \n", "L 134.786553 -102.028269 \n", "L 135.205576 -102.517709 \n", "L 135.624599 -103.009493 \n", "L 136.043623 -103.503525 \n", "L 136.043623 -37.55625 \n", "L 136.043623 -37.55625 \n", "L 135.624599 -37.55625 \n", "L 135.205576 -37.55625 \n", "L 134.786553 -37.55625 \n", "L 134.367529 -37.55625 \n", "L 133.948506 -37.55625 \n", "L 133.529482 -37.55625 \n", "L 133.110459 -37.55625 \n", "L 132.691436 -37.55625 \n", "L 132.272412 -37.55625 \n", "L 131.853389 -37.55625 \n", "L 131.434366 -37.55625 \n", "L 131.015342 -37.55625 \n", "L 130.596319 -37.55625 \n", "L 130.177285 -37.55625 \n", "L 129.758262 -37.55625 \n", "L 129.339239 -37.55625 \n", "L 128.920215 -37.55625 \n", "L 128.501192 -37.55625 \n", "L 128.082169 -37.55625 \n", "L 127.663145 -37.55625 \n", "L 127.244122 -37.55625 \n", "L 126.825098 -37.55625 \n", "L 126.406075 -37.55625 \n", "L 125.987052 -37.55625 \n", "L 125.568028 -37.55625 \n", "L 125.149005 -37.55625 \n", "L 124.729982 -37.55625 \n", "L 124.310958 -37.55625 \n", "L 123.891935 -37.55625 \n", "L 123.472911 -37.55625 \n", "L 123.053888 -37.55625 \n", "L 122.634865 -37.55625 \n", "L 122.215841 -37.55625 \n", "L 121.796818 -37.55625 \n", "L 121.377794 -37.55625 \n", "L 120.958771 -37.55625 \n", "L 120.539748 -37.55625 \n", "L 120.120714 -37.55625 \n", "L 119.701691 -37.55625 \n", "L 119.282668 -37.55625 \n", "L 118.863644 -37.55625 \n", "L 118.444621 -37.55625 \n", "L 118.025597 -37.55625 \n", "L 117.606574 -37.55625 \n", "L 117.187551 -37.55625 \n", "L 116.768527 -37.55625 \n", "L 116.349504 -37.55625 \n", "L 115.930481 -37.55625 \n", "L 115.511457 -37.55625 \n", "L 115.092434 -37.55625 \n", "L 114.67341 -37.55625 \n", "L 114.254387 -37.55625 \n", "L 113.835364 -37.55625 \n", "L 113.41634 -37.55625 \n", "L 112.997317 -37.55625 \n", "L 112.578294 -37.55625 \n", "L 112.15927 -37.55625 \n", "L 111.740247 -37.55625 \n", "L 111.321223 -37.55625 \n", "L 110.9022 -37.55625 \n", "L 110.483177 -37.55625 \n", "L 110.064143 -37.55625 \n", "L 109.64512 -37.55625 \n", "L 109.226096 -37.55625 \n", "L 108.807073 -37.55625 \n", "L 108.38805 -37.55625 \n", "L 107.969026 -37.55625 \n", "L 107.550003 -37.55625 \n", "L 107.13098 -37.55625 \n", "L 106.711956 -37.55625 \n", "L 106.292933 -37.55625 \n", "L 105.873909 -37.55625 \n", "L 105.454886 -37.55625 \n", "L 105.035863 -37.55625 \n", "L 104.616839 -37.55625 \n", "L 104.197816 -37.55625 \n", "L 103.778793 -37.55625 \n", "L 103.359769 -37.55625 \n", "L 102.940746 -37.55625 \n", "L 102.521722 -37.55625 \n", "L 102.102699 -37.55625 \n", "L 101.683676 -37.55625 \n", "L 101.264652 -37.55625 \n", "L 100.845629 -37.55625 \n", "L 100.426606 -37.55625 \n", "L 100.007572 -37.55625 \n", "L 99.588549 -37.55625 \n", "L 99.169525 -37.55625 \n", "L 98.750502 -37.55625 \n", "L 98.331479 -37.55625 \n", "L 97.912455 -37.55625 \n", "L 97.493432 -37.55625 \n", "L 97.074408 -37.55625 \n", "L 96.655385 -37.55625 \n", "L 96.236362 -37.55625 \n", "L 95.817338 -37.55625 \n", "L 95.398315 -37.55625 \n", "L 94.979292 -37.55625 \n", "L 94.560268 -37.55625 \n", "L 94.141245 -37.55625 \n", "L 93.722221 -37.55625 \n", "L 93.303198 -37.55625 \n", "L 92.884175 -37.55625 \n", "L 92.465151 -37.55625 \n", "L 92.046128 -37.55625 \n", "L 91.627105 -37.55625 \n", "L 91.208081 -37.55625 \n", "L 90.789058 -37.55625 \n", "L 90.370034 -37.55625 \n", "L 89.951011 -37.55625 \n", "L 89.531988 -37.55625 \n", "L 89.112964 -37.55625 \n", "L 88.693941 -37.55625 \n", "L 88.274918 -37.55625 \n", "L 87.855894 -37.55625 \n", "L 87.436871 -37.55625 \n", "L 87.017847 -37.55625 \n", "L 86.598814 -37.55625 \n", "L 86.179791 -37.55625 \n", "L 85.760767 -37.55625 \n", "L 85.341744 -37.55625 \n", "L 84.92272 -37.55625 \n", "L 84.503697 -37.55625 \n", "L 84.084674 -37.55625 \n", "L 83.66565 -37.55625 \n", "L 83.246627 -37.55625 \n", "L 82.827604 -37.55625 \n", "L 82.40858 -37.55625 \n", "L 81.989557 -37.55625 \n", "L 81.570533 -37.55625 \n", "L 81.15151 -37.55625 \n", "L 80.732487 -37.55625 \n", "L 80.313463 -37.55625 \n", "L 79.89444 -37.55625 \n", "L 79.475417 -37.55625 \n", "L 79.056393 -37.55625 \n", "L 78.63737 -37.55625 \n", "L 78.218346 -37.55625 \n", "L 77.799323 -37.55625 \n", "L 77.3803 -37.55625 \n", "L 76.961276 -37.55625 \n", "L 76.542243 -37.55625 \n", "L 76.12322 -37.55625 \n", "L 75.704196 -37.55625 \n", "L 75.285173 -37.55625 \n", "L 74.866149 -37.55625 \n", "L 74.447126 -37.55625 \n", "L 74.028103 -37.55625 \n", "L 73.609079 -37.55625 \n", "L 73.190056 -37.55625 \n", "L 72.771032 -37.55625 \n", "L 72.352009 -37.55625 \n", "L 71.932986 -37.55625 \n", "L 71.513962 -37.55625 \n", "L 71.094939 -37.55625 \n", "L 70.675916 -37.55625 \n", "L 70.256892 -37.55625 \n", "L 69.837869 -37.55625 \n", "L 69.418845 -37.55625 \n", "L 68.999822 -37.55625 \n", "L 68.580799 -37.55625 \n", "L 68.161775 -37.55625 \n", "L 67.742752 -37.55625 \n", "L 67.323729 -37.55625 \n", "L 66.904705 -37.55625 \n", "L 66.485672 -37.55625 \n", "L 66.066648 -37.55625 \n", "L 65.647625 -37.55625 \n", "L 65.228602 -37.55625 \n", "L 64.809578 -37.55625 \n", "L 64.390555 -37.55625 \n", "L 63.971532 -37.55625 \n", "L 63.552508 -37.55625 \n", "L 63.133485 -37.55625 \n", "L 62.714461 -37.55625 \n", "L 62.295438 -37.55625 \n", "L 61.876415 -37.55625 \n", "L 61.457391 -37.55625 \n", "L 61.038368 -37.55625 \n", "L 60.619344 -37.55625 \n", "L 60.200321 -37.55625 \n", "L 59.781298 -37.55625 \n", "L 59.362274 -37.55625 \n", "L 58.943251 -37.55625 \n", "L 58.524228 -37.55625 \n", "L 58.105204 -37.55625 \n", "L 57.686181 -37.55625 \n", "L 57.267157 -37.55625 \n", "L 56.848134 -37.55625 \n", "L 56.429101 -37.55625 \n", "L 56.010077 -37.55625 \n", "L 55.591054 -37.55625 \n", "L 55.172031 -37.55625 \n", "L 54.753007 -37.55625 \n", "L 54.333984 -37.55625 \n", "L 53.91496 -37.55625 \n", "L 53.495937 -37.55625 \n", "L 53.076914 -37.55625 \n", "L 52.65789 -37.55625 \n", "L 52.238867 -37.55625 \n", "L 51.819844 -37.55625 \n", "L 51.40082 -37.55625 \n", "L 50.981797 -37.55625 \n", "L 50.562773 -37.55625 \n", "L 50.14375 -37.55625 \n", "z\n", "\" style=\"stroke: #1f77b4; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#pa9450da409)\">\n", " <use xlink:href=\"#m64202ac6c4\" x=\"0\" y=\"226.194375\" style=\"fill: #1f77b4; fill-opacity: 0.5; stroke: #1f77b4; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_2\">\n", " <defs>\n", " <path id=\"m701ade630a\" d=\"M 136.462646 -37.55625 \n", "L 136.462646 -103.999859 \n", "L 136.881674 -104.498474 \n", "L 137.300698 -104.999319 \n", "L 137.719721 -105.50239 \n", "L 138.138745 -106.007679 \n", "L 138.557768 -106.515148 \n", "L 138.976791 -107.024821 \n", "L 139.395815 -107.536625 \n", "L 139.814838 -108.050623 \n", "L 140.233867 -108.566699 \n", "L 140.652885 -109.084884 \n", "L 141.071908 -109.605137 \n", "L 141.490932 -110.127436 \n", "L 141.909955 -110.651785 \n", "L 142.328978 -111.178162 \n", "L 142.748002 -111.706494 \n", "L 143.167025 -112.236801 \n", "L 143.586054 -112.769035 \n", "L 144.005077 -113.303185 \n", "L 144.4241 -113.839214 \n", "L 144.843124 -114.377082 \n", "L 145.262147 -114.916806 \n", "L 145.68117 -115.458314 \n", "L 146.100194 -116.001589 \n", "L 146.519217 -116.546603 \n", "L 146.938246 -117.09332 \n", "L 147.357269 -117.641759 \n", "L 147.776292 -118.191784 \n", "L 148.195316 -118.743458 \n", "L 148.614339 -119.296692 \n", "L 149.033362 -119.851484 \n", "L 149.452386 -120.40779 \n", "L 149.871409 -120.965566 \n", "L 150.290438 -121.524792 \n", "L 150.709456 -122.085398 \n", "L 151.128479 -122.647373 \n", "L 151.547503 -123.210664 \n", "L 151.966526 -123.77527 \n", "L 152.38555 -124.341103 \n", "L 152.804573 -124.908143 \n", "L 153.223596 -125.476354 \n", "L 153.642625 -126.04572 \n", "L 154.061648 -126.61613 \n", "L 154.480671 -127.187586 \n", "L 154.899695 -127.760024 \n", "L 155.318718 -128.333409 \n", "L 155.737742 -128.907722 \n", "L 156.156765 -129.482882 \n", "L 156.575788 -130.058835 \n", "L 156.994817 -130.635572 \n", "L 157.413835 -131.213003 \n", "L 157.832858 -131.791083 \n", "L 158.251882 -132.369812 \n", "L 158.670905 -132.949073 \n", "L 159.089929 -133.528874 \n", "L 159.508952 -134.109117 \n", "L 159.927975 -134.689757 \n", "L 160.347004 -135.270784 \n", "L 160.766027 -135.85209 \n", "L 161.18505 -136.433649 \n", "L 161.604074 -137.015397 \n", "L 162.023097 -137.597253 \n", "L 162.442121 -138.179199 \n", "L 162.861144 -138.761181 \n", "L 163.280167 -139.3431 \n", "L 163.699196 -139.92492 \n", "L 164.118219 -140.506587 \n", "L 164.537243 -141.088038 \n", "L 164.956266 -141.669209 \n", "L 165.375289 -142.250011 \n", "L 165.794313 -142.830434 \n", "L 166.213336 -143.410388 \n", "L 166.632359 -143.989802 \n", "L 167.051388 -144.56863 \n", "L 167.470406 -145.146809 \n", "L 167.88943 -145.724258 \n", "L 168.308453 -146.300896 \n", "L 168.727476 -146.876687 \n", "L 169.1465 -147.45155 \n", "L 169.565523 -148.025439 \n", "L 169.984546 -148.598265 \n", "L 170.403575 -149.169946 \n", "L 170.822598 -149.740447 \n", "L 171.241622 -150.309668 \n", "L 171.660645 -150.877564 \n", "L 171.660645 -37.55625 \n", "L 171.660645 -37.55625 \n", "L 171.241622 -37.55625 \n", "L 170.822598 -37.55625 \n", "L 170.403575 -37.55625 \n", "L 169.984546 -37.55625 \n", "L 169.565523 -37.55625 \n", "L 169.1465 -37.55625 \n", "L 168.727476 -37.55625 \n", "L 168.308453 -37.55625 \n", "L 167.88943 -37.55625 \n", "L 167.470406 -37.55625 \n", "L 167.051388 -37.55625 \n", "L 166.632359 -37.55625 \n", "L 166.213336 -37.55625 \n", "L 165.794313 -37.55625 \n", "L 165.375289 -37.55625 \n", "L 164.956266 -37.55625 \n", "L 164.537243 -37.55625 \n", "L 164.118219 -37.55625 \n", "L 163.699196 -37.55625 \n", "L 163.280167 -37.55625 \n", "L 162.861144 -37.55625 \n", "L 162.442121 -37.55625 \n", "L 162.023097 -37.55625 \n", "L 161.604074 -37.55625 \n", "L 161.18505 -37.55625 \n", "L 160.766027 -37.55625 \n", "L 160.347004 -37.55625 \n", "L 159.927975 -37.55625 \n", "L 159.508952 -37.55625 \n", "L 159.089929 -37.55625 \n", "L 158.670905 -37.55625 \n", "L 158.251882 -37.55625 \n", "L 157.832858 -37.55625 \n", "L 157.413835 -37.55625 \n", "L 156.994817 -37.55625 \n", "L 156.575788 -37.55625 \n", "L 156.156765 -37.55625 \n", "L 155.737742 -37.55625 \n", "L 155.318718 -37.55625 \n", "L 154.899695 -37.55625 \n", "L 154.480671 -37.55625 \n", "L 154.061648 -37.55625 \n", "L 153.642625 -37.55625 \n", "L 153.223596 -37.55625 \n", "L 152.804573 -37.55625 \n", "L 152.38555 -37.55625 \n", "L 151.966526 -37.55625 \n", "L 151.547503 -37.55625 \n", "L 151.128479 -37.55625 \n", "L 150.709456 -37.55625 \n", "L 150.290438 -37.55625 \n", "L 149.871409 -37.55625 \n", "L 149.452386 -37.55625 \n", "L 149.033362 -37.55625 \n", "L 148.614339 -37.55625 \n", "L 148.195316 -37.55625 \n", "L 147.776292 -37.55625 \n", "L 147.357269 -37.55625 \n", "L 146.938246 -37.55625 \n", "L 146.519217 -37.55625 \n", "L 146.100194 -37.55625 \n", "L 145.68117 -37.55625 \n", "L 145.262147 -37.55625 \n", "L 144.843124 -37.55625 \n", "L 144.4241 -37.55625 \n", "L 144.005077 -37.55625 \n", "L 143.586054 -37.55625 \n", "L 143.167025 -37.55625 \n", "L 142.748002 -37.55625 \n", "L 142.328978 -37.55625 \n", "L 141.909955 -37.55625 \n", "L 141.490932 -37.55625 \n", "L 141.071908 -37.55625 \n", "L 140.652885 -37.55625 \n", "L 140.233867 -37.55625 \n", "L 139.814838 -37.55625 \n", "L 139.395815 -37.55625 \n", "L 138.976791 -37.55625 \n", "L 138.557768 -37.55625 \n", "L 138.138745 -37.55625 \n", "L 137.719721 -37.55625 \n", "L 137.300698 -37.55625 \n", "L 136.881674 -37.55625 \n", "L 136.462646 -37.55625 \n", "z\n", "\" style=\"stroke: #ff7f0e; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#pa9450da409)\">\n", " <use xlink:href=\"#m701ade630a\" x=\"0\" y=\"226.194375\" style=\"fill: #ff7f0e; fill-opacity: 0.5; stroke: #ff7f0e; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_3\">\n", " <defs>\n", " <path id=\"m3801318fb3\" d=\"M 172.079668 -37.55625 \n", "L 172.079668 -151.444028 \n", "L 172.498692 -152.00904 \n", "L 172.917715 -152.572493 \n", "L 173.336738 -153.134306 \n", "L 173.755767 -153.694452 \n", "L 174.17479 -154.252822 \n", "L 174.593814 -154.809345 \n", "L 175.012837 -155.363948 \n", "L 175.43186 -155.916595 \n", "L 175.850886 -156.467161 \n", "L 176.26991 -157.015591 \n", "L 176.688933 -157.561794 \n", "L 177.107956 -158.105727 \n", "L 177.52698 -158.647308 \n", "L 177.946003 -159.186419 \n", "L 178.365027 -159.723033 \n", "L 178.78405 -160.257071 \n", "L 179.203076 -160.788431 \n", "L 179.622099 -161.317034 \n", "L 180.041123 -161.842843 \n", "L 180.460146 -162.365732 \n", "L 180.879169 -162.885684 \n", "L 181.298193 -163.402553 \n", "L 181.717216 -163.916303 \n", "L 182.136239 -164.426864 \n", "L 182.555265 -164.934126 \n", "L 182.974289 -165.438008 \n", "L 183.393312 -165.938493 \n", "L 183.812335 -166.435463 \n", "L 184.231359 -166.928846 \n", "L 184.650382 -167.418534 \n", "L 185.069406 -167.904482 \n", "L 185.488429 -168.386609 \n", "L 185.907455 -168.864879 \n", "L 186.326478 -169.339147 \n", "L 186.745502 -169.809359 \n", "L 187.164525 -170.275463 \n", "L 187.583548 -170.73733 \n", "L 188.002572 -171.194944 \n", "L 188.421595 -171.648213 \n", "L 188.840619 -172.097022 \n", "L 189.259644 -172.541352 \n", "L 189.678668 -172.981103 \n", "L 190.097691 -173.416204 \n", "L 190.516715 -173.846556 \n", "L 190.93574 -174.272122 \n", "L 191.354764 -174.692803 \n", "L 191.773787 -175.108564 \n", "L 192.192811 -175.519314 \n", "L 192.611836 -175.924936 \n", "L 193.03086 -176.325448 \n", "L 193.449883 -176.720716 \n", "L 193.868907 -177.110692 \n", "L 194.28793 -177.49528 \n", "L 194.706953 -177.874478 \n", "L 195.125977 -178.248161 \n", "L 195.545 -178.616238 \n", "L 195.964026 -178.978728 \n", "L 195.964026 -37.55625 \n", "L 195.964026 -37.55625 \n", "L 195.545 -37.55625 \n", "L 195.125977 -37.55625 \n", "L 194.706953 -37.55625 \n", "L 194.28793 -37.55625 \n", "L 193.868907 -37.55625 \n", "L 193.449883 -37.55625 \n", "L 193.03086 -37.55625 \n", "L 192.611836 -37.55625 \n", "L 192.192811 -37.55625 \n", "L 191.773787 -37.55625 \n", "L 191.354764 -37.55625 \n", "L 190.93574 -37.55625 \n", "L 190.516715 -37.55625 \n", "L 190.097691 -37.55625 \n", "L 189.678668 -37.55625 \n", "L 189.259644 -37.55625 \n", "L 188.840619 -37.55625 \n", "L 188.421595 -37.55625 \n", "L 188.002572 -37.55625 \n", "L 187.583548 -37.55625 \n", "L 187.164525 -37.55625 \n", "L 186.745502 -37.55625 \n", "L 186.326478 -37.55625 \n", "L 185.907455 -37.55625 \n", "L 185.488429 -37.55625 \n", "L 185.069406 -37.55625 \n", "L 184.650382 -37.55625 \n", "L 184.231359 -37.55625 \n", "L 183.812335 -37.55625 \n", "L 183.393312 -37.55625 \n", "L 182.974289 -37.55625 \n", "L 182.555265 -37.55625 \n", "L 182.136239 -37.55625 \n", "L 181.717216 -37.55625 \n", "L 181.298193 -37.55625 \n", "L 180.879169 -37.55625 \n", "L 180.460146 -37.55625 \n", "L 180.041123 -37.55625 \n", "L 179.622099 -37.55625 \n", "L 179.203076 -37.55625 \n", "L 178.78405 -37.55625 \n", "L 178.365027 -37.55625 \n", "L 177.946003 -37.55625 \n", "L 177.52698 -37.55625 \n", "L 177.107956 -37.55625 \n", "L 176.688933 -37.55625 \n", "L 176.26991 -37.55625 \n", "L 175.850886 -37.55625 \n", "L 175.43186 -37.55625 \n", "L 175.012837 -37.55625 \n", "L 174.593814 -37.55625 \n", "L 174.17479 -37.55625 \n", "L 173.755767 -37.55625 \n", "L 173.336738 -37.55625 \n", "L 172.917715 -37.55625 \n", "L 172.498692 -37.55625 \n", "L 172.079668 -37.55625 \n", "z\n", "\" style=\"stroke: #2ca02c; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#pa9450da409)\">\n", " <use xlink:href=\"#m3801318fb3\" x=\"0\" y=\"226.194375\" style=\"fill: #2ca02c; fill-opacity: 0.5; stroke: #2ca02c; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_4\">\n", " <defs>\n", " <path id=\"m0ae9659b56\" d=\"M 196.383049 -37.55625 \n", "L 196.383049 -179.335495 \n", "L 196.802073 -179.686494 \n", "L 197.221096 -180.031671 \n", "L 197.640121 -180.370972 \n", "L 198.059144 -180.704307 \n", "L 198.478169 -181.031604 \n", "L 198.897192 -181.352863 \n", "L 199.316216 -181.668002 \n", "L 199.73524 -181.976914 \n", "L 200.154264 -182.279562 \n", "L 200.573287 -182.575938 \n", "L 200.99231 -182.865952 \n", "L 201.411334 -183.14953 \n", "L 201.830358 -183.426656 \n", "L 202.249382 -183.697257 \n", "L 202.668405 -183.96127 \n", "L 203.08743 -184.218668 \n", "L 203.506453 -184.469415 \n", "L 203.925476 -184.713421 \n", "L 204.344501 -184.95065 \n", "L 204.763524 -185.181074 \n", "L 205.182549 -185.404641 \n", "L 205.601572 -185.621303 \n", "L 206.020596 -185.831036 \n", "L 206.43962 -186.033775 \n", "L 206.858644 -186.229484 \n", "L 207.277667 -186.418146 \n", "L 207.696691 -186.599706 \n", "L 208.115715 -186.774138 \n", "L 208.534739 -186.941387 \n", "L 208.953763 -187.101444 \n", "L 209.372787 -187.254282 \n", "L 209.79181 -187.399829 \n", "L 210.210834 -187.538113 \n", "L 210.629857 -187.66907 \n", "L 211.048881 -187.792681 \n", "L 211.467905 -187.908921 \n", "L 211.886929 -188.017779 \n", "L 212.305953 -188.119221 \n", "L 212.724976 -188.213228 \n", "L 213.144 -188.299808 \n", "L 213.563024 -188.378872 \n", "L 213.982048 -188.450483 \n", "L 214.401072 -188.514587 \n", "L 214.820095 -188.571184 \n", "L 215.239119 -188.620229 \n", "L 215.658143 -188.661775 \n", "L 216.077167 -188.695769 \n", "L 216.49619 -188.722238 \n", "L 216.915214 -188.741127 \n", "L 217.334238 -188.752465 \n", "L 217.334238 -37.55625 \n", "L 217.334238 -37.55625 \n", "L 216.915214 -37.55625 \n", "L 216.49619 -37.55625 \n", "L 216.077167 -37.55625 \n", "L 215.658143 -37.55625 \n", "L 215.239119 -37.55625 \n", "L 214.820095 -37.55625 \n", "L 214.401072 -37.55625 \n", "L 213.982048 -37.55625 \n", "L 213.563024 -37.55625 \n", "L 213.144 -37.55625 \n", "L 212.724976 -37.55625 \n", "L 212.305953 -37.55625 \n", "L 211.886929 -37.55625 \n", "L 211.467905 -37.55625 \n", "L 211.048881 -37.55625 \n", "L 210.629857 -37.55625 \n", "L 210.210834 -37.55625 \n", "L 209.79181 -37.55625 \n", "L 209.372787 -37.55625 \n", "L 208.953763 -37.55625 \n", "L 208.534739 -37.55625 \n", "L 208.115715 -37.55625 \n", "L 207.696691 -37.55625 \n", "L 207.277667 -37.55625 \n", "L 206.858644 -37.55625 \n", "L 206.43962 -37.55625 \n", "L 206.020596 -37.55625 \n", "L 205.601572 -37.55625 \n", "L 205.182549 -37.55625 \n", "L 204.763524 -37.55625 \n", "L 204.344501 -37.55625 \n", "L 203.925476 -37.55625 \n", "L 203.506453 -37.55625 \n", "L 203.08743 -37.55625 \n", "L 202.668405 -37.55625 \n", "L 202.249382 -37.55625 \n", "L 201.830358 -37.55625 \n", "L 201.411334 -37.55625 \n", "L 200.99231 -37.55625 \n", "L 200.573287 -37.55625 \n", "L 200.154264 -37.55625 \n", "L 199.73524 -37.55625 \n", "L 199.316216 -37.55625 \n", "L 198.897192 -37.55625 \n", "L 198.478169 -37.55625 \n", "L 198.059144 -37.55625 \n", "L 197.640121 -37.55625 \n", "L 197.221096 -37.55625 \n", "L 196.802073 -37.55625 \n", "L 196.383049 -37.55625 \n", "z\n", "\" style=\"stroke: #d62728; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#pa9450da409)\">\n", " <use xlink:href=\"#m0ae9659b56\" x=\"0\" y=\"226.194375\" style=\"fill: #d62728; fill-opacity: 0.5; stroke: #d62728; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_5\">\n", " <defs>\n", " <path id=\"md9d39bb012\" d=\"M 217.753262 -37.55625 \n", "L 217.753262 -188.75625 \n", "L 218.172285 -188.752465 \n", "L 218.591309 -188.741127 \n", "L 219.010333 -188.722238 \n", "L 219.429357 -188.695787 \n", "L 219.848381 -188.661793 \n", "L 220.267404 -188.620265 \n", "L 220.686428 -188.571184 \n", "L 221.105452 -188.514587 \n", "L 221.524476 -188.450483 \n", "L 221.9435 -188.378872 \n", "L 222.362523 -188.29979 \n", "L 222.781547 -188.213228 \n", "L 223.200571 -188.119221 \n", "L 223.619595 -188.017779 \n", "L 224.038618 -187.908921 \n", "L 224.457642 -187.792699 \n", "L 224.876666 -187.66907 \n", "L 225.295689 -187.538113 \n", "L 225.714713 -187.399829 \n", "L 226.133737 -187.254264 \n", "L 226.552761 -187.101444 \n", "L 226.971785 -186.941387 \n", "L 227.390808 -186.77412 \n", "L 227.809832 -186.599706 \n", "L 228.228856 -186.418146 \n", "L 228.64788 -186.229484 \n", "L 229.066903 -186.033775 \n", "L 229.485928 -185.831036 \n", "L 229.904951 -185.621303 \n", "L 230.323974 -185.404641 \n", "L 230.742999 -185.181074 \n", "L 231.162022 -184.95065 \n", "L 231.581046 -184.713421 \n", "L 232.00007 -184.469397 \n", "L 232.419094 -184.218686 \n", "L 232.838117 -183.96127 \n", "L 233.257142 -183.697257 \n", "L 233.676165 -183.426656 \n", "L 234.095188 -183.14953 \n", "L 234.514213 -182.865952 \n", "L 234.933236 -182.575947 \n", "L 235.352261 -182.27958 \n", "L 235.771284 -181.976914 \n", "L 236.190308 -181.667984 \n", "L 236.609333 -181.352863 \n", "L 237.028356 -181.031622 \n", "L 237.447379 -180.704298 \n", "L 237.866403 -180.370972 \n", "L 238.285426 -180.031671 \n", "L 238.704451 -179.686494 \n", "L 239.123474 -179.335495 \n", "L 239.123474 -37.55625 \n", "L 239.123474 -37.55625 \n", "L 238.704451 -37.55625 \n", "L 238.285426 -37.55625 \n", "L 237.866403 -37.55625 \n", "L 237.447379 -37.55625 \n", "L 237.028356 -37.55625 \n", "L 236.609333 -37.55625 \n", "L 236.190308 -37.55625 \n", "L 235.771284 -37.55625 \n", "L 235.352261 -37.55625 \n", "L 234.933236 -37.55625 \n", "L 234.514213 -37.55625 \n", "L 234.095188 -37.55625 \n", "L 233.676165 -37.55625 \n", "L 233.257142 -37.55625 \n", "L 232.838117 -37.55625 \n", "L 232.419094 -37.55625 \n", "L 232.00007 -37.55625 \n", "L 231.581046 -37.55625 \n", "L 231.162022 -37.55625 \n", "L 230.742999 -37.55625 \n", "L 230.323974 -37.55625 \n", "L 229.904951 -37.55625 \n", "L 229.485928 -37.55625 \n", "L 229.066903 -37.55625 \n", "L 228.64788 -37.55625 \n", "L 228.228856 -37.55625 \n", "L 227.809832 -37.55625 \n", "L 227.390808 -37.55625 \n", "L 226.971785 -37.55625 \n", "L 226.552761 -37.55625 \n", "L 226.133737 -37.55625 \n", "L 225.714713 -37.55625 \n", "L 225.295689 -37.55625 \n", "L 224.876666 -37.55625 \n", "L 224.457642 -37.55625 \n", "L 224.038618 -37.55625 \n", "L 223.619595 -37.55625 \n", "L 223.200571 -37.55625 \n", "L 222.781547 -37.55625 \n", "L 222.362523 -37.55625 \n", "L 221.9435 -37.55625 \n", "L 221.524476 -37.55625 \n", "L 221.105452 -37.55625 \n", "L 220.686428 -37.55625 \n", "L 220.267404 -37.55625 \n", "L 219.848381 -37.55625 \n", "L 219.429357 -37.55625 \n", "L 219.010333 -37.55625 \n", "L 218.591309 -37.55625 \n", "L 218.172285 -37.55625 \n", "L 217.753262 -37.55625 \n", "z\n", "\" style=\"stroke: #9467bd; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#pa9450da409)\">\n", " <use xlink:href=\"#md9d39bb012\" x=\"0\" y=\"226.194375\" style=\"fill: #9467bd; fill-opacity: 0.5; stroke: #9467bd; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_6\">\n", " <defs>\n", " <path id=\"m5c69c01b69\" d=\"M 239.542497 -37.55625 \n", "L 239.542497 -178.978719 \n", "L 239.961521 -178.616238 \n", "L 240.380544 -178.248143 \n", "L 240.79957 -177.874478 \n", "L 241.218593 -177.495298 \n", "L 241.637617 -177.110692 \n", "L 242.05664 -176.720716 \n", "L 242.475664 -176.325448 \n", "L 242.894689 -175.924972 \n", "L 243.313713 -175.519296 \n", "L 243.732736 -175.108564 \n", "L 244.15176 -174.692812 \n", "L 244.570783 -174.272113 \n", "L 244.989806 -173.846556 \n", "L 245.40883 -173.416186 \n", "L 245.827853 -172.981085 \n", "L 246.246879 -172.541352 \n", "L 246.665902 -172.097022 \n", "L 247.084926 -171.648195 \n", "L 247.503949 -171.194944 \n", "L 247.922975 -170.73733 \n", "L 248.341998 -170.275445 \n", "L 248.761022 -169.809359 \n", "L 249.180045 -169.339147 \n", "L 249.599071 -168.864879 \n", "L 250.018094 -168.386636 \n", "L 250.437118 -167.904482 \n", "L 250.856141 -167.418534 \n", "L 251.275165 -166.928846 \n", "L 251.694188 -166.435463 \n", "L 252.113211 -165.938511 \n", "L 252.532235 -165.438035 \n", "L 252.951261 -164.934126 \n", "L 253.370284 -164.426855 \n", "L 253.789307 -163.916294 \n", "L 254.208331 -163.402553 \n", "L 254.627354 -162.885675 \n", "L 255.046377 -162.36575 \n", "L 255.465401 -161.842825 \n", "L 255.884424 -161.317034 \n", "L 256.30345 -160.788422 \n", "L 256.722473 -160.257053 \n", "L 257.141497 -159.723033 \n", "L 257.56052 -159.186419 \n", "L 257.979544 -158.647281 \n", "L 258.398567 -158.105727 \n", "L 258.81759 -157.561794 \n", "L 259.236614 -157.015573 \n", "L 259.65564 -156.467152 \n", "L 260.074663 -155.916586 \n", "L 260.493686 -155.363957 \n", "L 260.91271 -154.809345 \n", "L 261.331733 -154.252822 \n", "L 261.750757 -153.694452 \n", "L 262.16978 -153.134324 \n", "L 262.588803 -152.572493 \n", "L 263.007827 -152.00904 \n", "L 263.42685 -151.444037 \n", "L 263.42685 -37.55625 \n", "L 263.42685 -37.55625 \n", "L 263.007827 -37.55625 \n", "L 262.588803 -37.55625 \n", "L 262.16978 -37.55625 \n", "L 261.750757 -37.55625 \n", "L 261.331733 -37.55625 \n", "L 260.91271 -37.55625 \n", "L 260.493686 -37.55625 \n", "L 260.074663 -37.55625 \n", "L 259.65564 -37.55625 \n", "L 259.236614 -37.55625 \n", "L 258.81759 -37.55625 \n", "L 258.398567 -37.55625 \n", "L 257.979544 -37.55625 \n", "L 257.56052 -37.55625 \n", "L 257.141497 -37.55625 \n", "L 256.722473 -37.55625 \n", "L 256.30345 -37.55625 \n", "L 255.884424 -37.55625 \n", "L 255.465401 -37.55625 \n", "L 255.046377 -37.55625 \n", "L 254.627354 -37.55625 \n", "L 254.208331 -37.55625 \n", "L 253.789307 -37.55625 \n", "L 253.370284 -37.55625 \n", "L 252.951261 -37.55625 \n", "L 252.532235 -37.55625 \n", "L 252.113211 -37.55625 \n", "L 251.694188 -37.55625 \n", "L 251.275165 -37.55625 \n", "L 250.856141 -37.55625 \n", "L 250.437118 -37.55625 \n", "L 250.018094 -37.55625 \n", "L 249.599071 -37.55625 \n", "L 249.180045 -37.55625 \n", "L 248.761022 -37.55625 \n", "L 248.341998 -37.55625 \n", "L 247.922975 -37.55625 \n", "L 247.503949 -37.55625 \n", "L 247.084926 -37.55625 \n", "L 246.665902 -37.55625 \n", "L 246.246879 -37.55625 \n", "L 245.827853 -37.55625 \n", "L 245.40883 -37.55625 \n", "L 244.989806 -37.55625 \n", "L 244.570783 -37.55625 \n", "L 244.15176 -37.55625 \n", "L 243.732736 -37.55625 \n", "L 243.313713 -37.55625 \n", "L 242.894689 -37.55625 \n", "L 242.475664 -37.55625 \n", "L 242.05664 -37.55625 \n", "L 241.637617 -37.55625 \n", "L 241.218593 -37.55625 \n", "L 240.79957 -37.55625 \n", "L 240.380544 -37.55625 \n", "L 239.961521 -37.55625 \n", "L 239.542497 -37.55625 \n", "z\n", "\" style=\"stroke: #8c564b; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#pa9450da409)\">\n", " <use xlink:href=\"#m5c69c01b69\" x=\"0\" y=\"226.194375\" style=\"fill: #8c564b; fill-opacity: 0.5; stroke: #8c564b; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_7\">\n", " <defs>\n", " <path id=\"m73de46e4f3\" d=\"M 263.845873 -37.55625 \n", "L 263.845873 -150.877564 \n", "L 264.264902 -150.309659 \n", "L 264.683925 -149.740438 \n", "L 265.102949 -149.169937 \n", "L 265.521972 -148.598265 \n", "L 265.940995 -148.025439 \n", "L 266.360019 -147.451568 \n", "L 266.779042 -146.876687 \n", "L 267.198065 -146.300905 \n", "L 267.617094 -145.724249 \n", "L 268.036117 -145.146809 \n", "L 268.455141 -144.568648 \n", "L 268.874164 -143.98982 \n", "L 269.293187 -143.410397 \n", "L 269.712211 -142.830443 \n", "L 270.131234 -142.250038 \n", "L 270.550257 -141.6692 \n", "L 270.969286 -141.088038 \n", "L 271.388304 -140.506587 \n", "L 271.807328 -139.924929 \n", "L 272.226351 -139.3431 \n", "L 272.645374 -138.761181 \n", "L 273.064398 -138.179208 \n", "L 273.483421 -137.597262 \n", "L 273.902445 -137.015397 \n", "L 274.321473 -136.433649 \n", "L 274.740496 -135.852099 \n", "L 275.15952 -135.270784 \n", "L 275.578543 -134.689784 \n", "L 275.997566 -134.109126 \n", "L 276.41659 -133.528874 \n", "L 276.835613 -132.949091 \n", "L 277.254637 -132.369812 \n", "L 277.673665 -131.791092 \n", "L 278.092688 -131.212994 \n", "L 278.511712 -130.635563 \n", "L 278.930735 -130.058835 \n", "L 279.349758 -129.482864 \n", "L 279.768782 -128.907722 \n", "L 280.187805 -128.333409 \n", "L 280.606829 -127.760024 \n", "L 281.025857 -127.187568 \n", "L 281.444875 -126.61613 \n", "L 281.863899 -126.045711 \n", "L 282.282922 -125.476363 \n", "L 282.701945 -124.90817 \n", "L 283.120969 -124.341112 \n", "L 283.539992 -123.77527 \n", "L 283.959016 -123.210682 \n", "L 284.378044 -122.647364 \n", "L 284.797067 -122.085389 \n", "L 285.216091 -121.524774 \n", "L 285.635114 -120.965566 \n", "L 286.054138 -120.407781 \n", "L 286.473161 -119.851493 \n", "L 286.892184 -119.296692 \n", "L 287.311208 -118.743458 \n", "L 287.730236 -118.191784 \n", "L 288.149254 -117.641741 \n", "L 288.568278 -117.093338 \n", "L 288.987301 -116.546603 \n", "L 289.406325 -116.001589 \n", "L 289.825348 -115.458314 \n", "L 290.244371 -114.916806 \n", "L 290.663395 -114.3771 \n", "L 291.082423 -113.839196 \n", "L 291.501446 -113.303185 \n", "L 291.92047 -112.769035 \n", "L 292.339493 -112.236801 \n", "L 292.758517 -111.706494 \n", "L 293.17754 -111.178162 \n", "L 293.596563 -110.651803 \n", "L 294.015587 -110.127454 \n", "L 294.434615 -109.605137 \n", "L 294.853638 -109.084884 \n", "L 295.272662 -108.566699 \n", "L 295.691685 -108.050623 \n", "L 296.110709 -107.536643 \n", "L 296.529732 -107.024821 \n", "L 296.948755 -106.515166 \n", "L 297.367779 -106.007679 \n", "L 297.786807 -105.502372 \n", "L 298.205826 -104.999301 \n", "L 298.624849 -104.498456 \n", "L 299.043872 -103.999873 \n", "L 299.043872 -37.55625 \n", "L 299.043872 -37.55625 \n", "L 298.624849 -37.55625 \n", "L 298.205826 -37.55625 \n", "L 297.786807 -37.55625 \n", "L 297.367779 -37.55625 \n", "L 296.948755 -37.55625 \n", "L 296.529732 -37.55625 \n", "L 296.110709 -37.55625 \n", "L 295.691685 -37.55625 \n", "L 295.272662 -37.55625 \n", "L 294.853638 -37.55625 \n", "L 294.434615 -37.55625 \n", "L 294.015587 -37.55625 \n", "L 293.596563 -37.55625 \n", "L 293.17754 -37.55625 \n", "L 292.758517 -37.55625 \n", "L 292.339493 -37.55625 \n", "L 291.92047 -37.55625 \n", "L 291.501446 -37.55625 \n", "L 291.082423 -37.55625 \n", "L 290.663395 -37.55625 \n", "L 290.244371 -37.55625 \n", "L 289.825348 -37.55625 \n", "L 289.406325 -37.55625 \n", "L 288.987301 -37.55625 \n", "L 288.568278 -37.55625 \n", "L 288.149254 -37.55625 \n", "L 287.730236 -37.55625 \n", "L 287.311208 -37.55625 \n", "L 286.892184 -37.55625 \n", "L 286.473161 -37.55625 \n", "L 286.054138 -37.55625 \n", "L 285.635114 -37.55625 \n", "L 285.216091 -37.55625 \n", "L 284.797067 -37.55625 \n", "L 284.378044 -37.55625 \n", "L 283.959016 -37.55625 \n", "L 283.539992 -37.55625 \n", "L 283.120969 -37.55625 \n", "L 282.701945 -37.55625 \n", "L 282.282922 -37.55625 \n", "L 281.863899 -37.55625 \n", "L 281.444875 -37.55625 \n", "L 281.025857 -37.55625 \n", "L 280.606829 -37.55625 \n", "L 280.187805 -37.55625 \n", "L 279.768782 -37.55625 \n", "L 279.349758 -37.55625 \n", "L 278.930735 -37.55625 \n", "L 278.511712 -37.55625 \n", "L 278.092688 -37.55625 \n", "L 277.673665 -37.55625 \n", "L 277.254637 -37.55625 \n", "L 276.835613 -37.55625 \n", "L 276.41659 -37.55625 \n", "L 275.997566 -37.55625 \n", "L 275.578543 -37.55625 \n", "L 275.15952 -37.55625 \n", "L 274.740496 -37.55625 \n", "L 274.321473 -37.55625 \n", "L 273.902445 -37.55625 \n", "L 273.483421 -37.55625 \n", "L 273.064398 -37.55625 \n", "L 272.645374 -37.55625 \n", "L 272.226351 -37.55625 \n", "L 271.807328 -37.55625 \n", "L 271.388304 -37.55625 \n", "L 270.969286 -37.55625 \n", "L 270.550257 -37.55625 \n", "L 270.131234 -37.55625 \n", "L 269.712211 -37.55625 \n", "L 269.293187 -37.55625 \n", "L 268.874164 -37.55625 \n", "L 268.455141 -37.55625 \n", "L 268.036117 -37.55625 \n", "L 267.617094 -37.55625 \n", "L 267.198065 -37.55625 \n", "L 266.779042 -37.55625 \n", "L 266.360019 -37.55625 \n", "L 265.940995 -37.55625 \n", "L 265.521972 -37.55625 \n", "L 265.102949 -37.55625 \n", "L 264.683925 -37.55625 \n", "L 264.264902 -37.55625 \n", "L 263.845873 -37.55625 \n", "z\n", "\" style=\"stroke: #e377c2; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#pa9450da409)\">\n", " <use xlink:href=\"#m73de46e4f3\" x=\"0\" y=\"226.194375\" style=\"fill: #e377c2; fill-opacity: 0.5; stroke: #e377c2; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_8\">\n", " <defs>\n", " <path id=\"m2a5e73abe7\" d=\"M 299.462896 -37.55625 \n", "L 299.462896 -103.503538 \n", "L 299.881919 -103.009493 \n", "L 300.300942 -102.517727 \n", "L 300.719966 -102.028282 \n", "L 301.138994 -101.541154 \n", "L 301.558018 -101.056377 \n", "L 301.977041 -100.57393 \n", "L 302.396064 -100.093858 \n", "L 302.815088 -99.616166 \n", "L 303.234111 -99.140847 \n", "L 303.653134 -98.667927 \n", "L 304.072158 -98.197412 \n", "L 304.491181 -97.729317 \n", "L 304.910205 -97.263651 \n", "L 305.329228 -96.800405 \n", "L 305.748251 -96.339614 \n", "L 306.167275 -95.881266 \n", "L 306.586298 -95.425379 \n", "L 307.005321 -94.971956 \n", "L 307.424345 -94.521002 \n", "L 307.843368 -94.072522 \n", "L 308.262402 -93.626521 \n", "L 308.681425 -93.18303 \n", "L 309.100448 -92.742021 \n", "L 309.519472 -92.3035 \n", "L 309.938495 -91.867484 \n", "L 310.357518 -91.433973 \n", "L 310.776542 -91.002982 \n", "L 311.195565 -90.574491 \n", "L 311.614589 -90.14852 \n", "L 312.033612 -89.725049 \n", "L 312.452635 -89.304115 \n", "L 312.871659 -88.885691 \n", "L 313.290682 -88.469781 \n", "L 313.709706 -88.056395 \n", "L 314.128729 -87.645533 \n", "L 314.547752 -87.23718 \n", "L 314.966776 -86.83135 \n", "L 315.385799 -86.42804 \n", "L 315.804822 -86.027257 \n", "L 316.223846 -85.628985 \n", "L 316.642869 -85.233218 \n", "L 317.061893 -84.839969 \n", "L 317.480916 -84.449235 \n", "L 317.899939 -84.060998 \n", "L 318.318973 -83.675275 \n", "L 318.737996 -83.292048 \n", "L 319.157019 -82.911318 \n", "L 319.576043 -82.533093 \n", "L 319.995066 -82.15736 \n", "L 320.41409 -81.7841 \n", "L 320.833113 -81.413329 \n", "L 321.252136 -81.045044 \n", "L 321.67116 -80.679224 \n", "L 322.090183 -80.31587 \n", "L 322.509206 -79.95498 \n", "L 322.92823 -79.596546 \n", "L 323.347253 -79.240563 \n", "L 323.766277 -78.887022 \n", "L 324.1853 -78.535929 \n", "L 324.604323 -78.18725 \n", "L 325.023347 -77.841014 \n", "L 325.44237 -77.497185 \n", "L 325.861394 -77.155779 \n", "L 326.280417 -76.816766 \n", "L 326.69944 -76.480155 \n", "L 327.118464 -76.145932 \n", "L 327.537487 -75.814089 \n", "L 327.95651 -75.48462 \n", "L 328.375544 -75.157515 \n", "L 328.794567 -74.832766 \n", "L 329.213591 -74.510372 \n", "L 329.632614 -74.190323 \n", "L 330.051637 -73.872595 \n", "L 330.470661 -73.557201 \n", "L 330.889684 -73.244112 \n", "L 331.308707 -72.933334 \n", "L 331.727731 -72.624853 \n", "L 332.146754 -72.318653 \n", "L 332.565778 -72.014734 \n", "L 332.984801 -71.713082 \n", "L 333.403824 -71.413689 \n", "L 333.822848 -71.116547 \n", "L 334.241871 -70.821638 \n", "L 334.660894 -70.528959 \n", "L 335.079918 -70.238506 \n", "L 335.498941 -69.950255 \n", "L 335.917965 -69.664202 \n", "L 336.336988 -69.38034 \n", "L 336.756011 -69.098652 \n", "L 337.175035 -68.819135 \n", "L 337.594058 -68.541769 \n", "L 338.013082 -68.266558 \n", "L 338.432115 -67.993472 \n", "L 338.851138 -67.72251 \n", "L 339.270162 -67.453671 \n", "L 339.689185 -67.18693 \n", "L 340.108208 -66.922281 \n", "L 340.527232 -66.659719 \n", "L 340.946255 -66.399223 \n", "L 341.365279 -66.140784 \n", "L 341.784302 -65.884393 \n", "L 342.203325 -65.630046 \n", "L 342.622349 -65.377717 \n", "L 343.041372 -65.1274 \n", "L 343.460395 -64.879095 \n", "L 343.879419 -64.632773 \n", "L 344.298442 -64.388436 \n", "L 344.717466 -64.146071 \n", "L 345.136489 -63.905661 \n", "L 345.555512 -63.667193 \n", "L 345.974536 -63.430662 \n", "L 346.393559 -63.196054 \n", "L 346.812582 -62.963361 \n", "L 347.231606 -62.732564 \n", "L 347.650629 -62.503661 \n", "L 348.069653 -62.276627 \n", "L 348.488676 -62.051468 \n", "L 348.907699 -61.828161 \n", "L 349.326723 -61.606694 \n", "L 349.745746 -61.387058 \n", "L 350.16477 -61.169246 \n", "L 350.583793 -60.953234 \n", "L 351.002816 -60.739027 \n", "L 351.42184 -60.5266 \n", "L 351.840873 -60.315941 \n", "L 352.259896 -60.107054 \n", "L 352.67892 -59.899913 \n", "L 353.097943 -59.694515 \n", "L 353.516967 -59.490845 \n", "L 353.93599 -59.288886 \n", "L 354.355013 -59.088635 \n", "L 354.774037 -58.890075 \n", "L 355.19306 -58.693198 \n", "L 355.612083 -58.497991 \n", "L 356.031107 -58.304447 \n", "L 356.45013 -58.112546 \n", "L 356.869154 -57.922284 \n", "L 357.288177 -57.733647 \n", "L 357.7072 -57.546623 \n", "L 358.126224 -57.361201 \n", "L 358.545247 -57.177374 \n", "L 358.96427 -56.995122 \n", "L 359.383294 -56.814445 \n", "L 359.802317 -56.635318 \n", "L 360.221341 -56.457746 \n", "L 360.640364 -56.281706 \n", "L 361.059387 -56.10719 \n", "L 361.478411 -55.934187 \n", "L 361.897444 -55.762684 \n", "L 362.316468 -55.592677 \n", "L 362.735491 -55.424149 \n", "L 363.154514 -55.257094 \n", "L 363.573538 -55.0915 \n", "L 363.992561 -54.927351 \n", "L 364.411584 -54.764638 \n", "L 364.830608 -54.603354 \n", "L 365.249631 -54.44349 \n", "L 365.668655 -54.285028 \n", "L 366.087678 -54.127959 \n", "L 366.506701 -53.972279 \n", "L 366.925725 -53.817971 \n", "L 367.344748 -53.665026 \n", "L 367.763771 -53.513441 \n", "L 368.182795 -53.36319 \n", "L 368.601818 -53.21428 \n", "L 369.020842 -53.066687 \n", "L 369.439865 -52.920409 \n", "L 369.858888 -52.77543 \n", "L 370.277912 -52.631744 \n", "L 370.696935 -52.489343 \n", "L 371.115958 -52.348214 \n", "L 371.534982 -52.208345 \n", "L 371.954015 -52.069725 \n", "L 372.373039 -51.93235 \n", "L 372.792062 -51.796209 \n", "L 373.211085 -51.66129 \n", "L 373.630109 -51.527586 \n", "L 374.049132 -51.395085 \n", "L 374.468156 -51.263777 \n", "L 374.887179 -51.133654 \n", "L 375.306202 -51.004705 \n", "L 375.725226 -50.876921 \n", "L 376.144249 -50.750293 \n", "L 376.563272 -50.624814 \n", "L 376.982296 -50.500472 \n", "L 377.401319 -50.377256 \n", "L 377.820343 -50.255161 \n", "L 378.239366 -50.134174 \n", "L 378.658389 -50.01429 \n", "L 379.077413 -49.895495 \n", "L 379.496436 -49.777787 \n", "L 379.915459 -49.661149 \n", "L 380.334483 -49.54558 \n", "L 380.753506 -49.431065 \n", "L 381.17253 -49.317595 \n", "L 381.591553 -49.205167 \n", "L 382.010586 -49.093766 \n", "L 382.42961 -48.983392 \n", "L 382.848633 -48.874029 \n", "L 383.267656 -48.765669 \n", "L 383.68668 -48.658306 \n", "L 384.105703 -48.551931 \n", "L 384.524727 -48.446538 \n", "L 384.94375 -48.342115 \n", "L 384.94375 -37.55625 \n", "L 384.94375 -37.55625 \n", "L 384.524727 -37.55625 \n", "L 384.105703 -37.55625 \n", "L 383.68668 -37.55625 \n", "L 383.267656 -37.55625 \n", "L 382.848633 -37.55625 \n", "L 382.42961 -37.55625 \n", "L 382.010586 -37.55625 \n", "L 381.591553 -37.55625 \n", "L 381.17253 -37.55625 \n", "L 380.753506 -37.55625 \n", "L 380.334483 -37.55625 \n", "L 379.915459 -37.55625 \n", "L 379.496436 -37.55625 \n", "L 379.077413 -37.55625 \n", "L 378.658389 -37.55625 \n", "L 378.239366 -37.55625 \n", "L 377.820343 -37.55625 \n", "L 377.401319 -37.55625 \n", "L 376.982296 -37.55625 \n", "L 376.563272 -37.55625 \n", "L 376.144249 -37.55625 \n", "L 375.725226 -37.55625 \n", "L 375.306202 -37.55625 \n", "L 374.887179 -37.55625 \n", "L 374.468156 -37.55625 \n", "L 374.049132 -37.55625 \n", "L 373.630109 -37.55625 \n", "L 373.211085 -37.55625 \n", "L 372.792062 -37.55625 \n", "L 372.373039 -37.55625 \n", "L 371.954015 -37.55625 \n", "L 371.534982 -37.55625 \n", "L 371.115958 -37.55625 \n", "L 370.696935 -37.55625 \n", "L 370.277912 -37.55625 \n", "L 369.858888 -37.55625 \n", "L 369.439865 -37.55625 \n", "L 369.020842 -37.55625 \n", "L 368.601818 -37.55625 \n", "L 368.182795 -37.55625 \n", "L 367.763771 -37.55625 \n", "L 367.344748 -37.55625 \n", "L 366.925725 -37.55625 \n", "L 366.506701 -37.55625 \n", "L 366.087678 -37.55625 \n", "L 365.668655 -37.55625 \n", "L 365.249631 -37.55625 \n", "L 364.830608 -37.55625 \n", "L 364.411584 -37.55625 \n", "L 363.992561 -37.55625 \n", "L 363.573538 -37.55625 \n", "L 363.154514 -37.55625 \n", "L 362.735491 -37.55625 \n", "L 362.316468 -37.55625 \n", "L 361.897444 -37.55625 \n", "L 361.478411 -37.55625 \n", "L 361.059387 -37.55625 \n", "L 360.640364 -37.55625 \n", "L 360.221341 -37.55625 \n", "L 359.802317 -37.55625 \n", "L 359.383294 -37.55625 \n", "L 358.96427 -37.55625 \n", "L 358.545247 -37.55625 \n", "L 358.126224 -37.55625 \n", "L 357.7072 -37.55625 \n", "L 357.288177 -37.55625 \n", "L 356.869154 -37.55625 \n", "L 356.45013 -37.55625 \n", "L 356.031107 -37.55625 \n", "L 355.612083 -37.55625 \n", "L 355.19306 -37.55625 \n", "L 354.774037 -37.55625 \n", "L 354.355013 -37.55625 \n", "L 353.93599 -37.55625 \n", "L 353.516967 -37.55625 \n", "L 353.097943 -37.55625 \n", "L 352.67892 -37.55625 \n", "L 352.259896 -37.55625 \n", "L 351.840873 -37.55625 \n", "L 351.42184 -37.55625 \n", "L 351.002816 -37.55625 \n", "L 350.583793 -37.55625 \n", "L 350.16477 -37.55625 \n", "L 349.745746 -37.55625 \n", "L 349.326723 -37.55625 \n", "L 348.907699 -37.55625 \n", "L 348.488676 -37.55625 \n", "L 348.069653 -37.55625 \n", "L 347.650629 -37.55625 \n", "L 347.231606 -37.55625 \n", "L 346.812582 -37.55625 \n", "L 346.393559 -37.55625 \n", "L 345.974536 -37.55625 \n", "L 345.555512 -37.55625 \n", "L 345.136489 -37.55625 \n", "L 344.717466 -37.55625 \n", "L 344.298442 -37.55625 \n", "L 343.879419 -37.55625 \n", "L 343.460395 -37.55625 \n", "L 343.041372 -37.55625 \n", "L 342.622349 -37.55625 \n", "L 342.203325 -37.55625 \n", "L 341.784302 -37.55625 \n", "L 341.365279 -37.55625 \n", "L 340.946255 -37.55625 \n", "L 340.527232 -37.55625 \n", "L 340.108208 -37.55625 \n", "L 339.689185 -37.55625 \n", "L 339.270162 -37.55625 \n", "L 338.851138 -37.55625 \n", "L 338.432115 -37.55625 \n", "L 338.013082 -37.55625 \n", "L 337.594058 -37.55625 \n", "L 337.175035 -37.55625 \n", "L 336.756011 -37.55625 \n", "L 336.336988 -37.55625 \n", "L 335.917965 -37.55625 \n", "L 335.498941 -37.55625 \n", "L 335.079918 -37.55625 \n", "L 334.660894 -37.55625 \n", "L 334.241871 -37.55625 \n", "L 333.822848 -37.55625 \n", "L 333.403824 -37.55625 \n", "L 332.984801 -37.55625 \n", "L 332.565778 -37.55625 \n", "L 332.146754 -37.55625 \n", "L 331.727731 -37.55625 \n", "L 331.308707 -37.55625 \n", "L 330.889684 -37.55625 \n", "L 330.470661 -37.55625 \n", "L 330.051637 -37.55625 \n", "L 329.632614 -37.55625 \n", "L 329.213591 -37.55625 \n", "L 328.794567 -37.55625 \n", "L 328.375544 -37.55625 \n", "L 327.95651 -37.55625 \n", "L 327.537487 -37.55625 \n", "L 327.118464 -37.55625 \n", "L 326.69944 -37.55625 \n", "L 326.280417 -37.55625 \n", "L 325.861394 -37.55625 \n", "L 325.44237 -37.55625 \n", "L 325.023347 -37.55625 \n", "L 324.604323 -37.55625 \n", "L 324.1853 -37.55625 \n", "L 323.766277 -37.55625 \n", "L 323.347253 -37.55625 \n", "L 322.92823 -37.55625 \n", "L 322.509206 -37.55625 \n", "L 322.090183 -37.55625 \n", "L 321.67116 -37.55625 \n", "L 321.252136 -37.55625 \n", "L 320.833113 -37.55625 \n", "L 320.41409 -37.55625 \n", "L 319.995066 -37.55625 \n", "L 319.576043 -37.55625 \n", "L 319.157019 -37.55625 \n", "L 318.737996 -37.55625 \n", "L 318.318973 -37.55625 \n", "L 317.899939 -37.55625 \n", "L 317.480916 -37.55625 \n", "L 317.061893 -37.55625 \n", "L 316.642869 -37.55625 \n", "L 316.223846 -37.55625 \n", "L 315.804822 -37.55625 \n", "L 315.385799 -37.55625 \n", "L 314.966776 -37.55625 \n", "L 314.547752 -37.55625 \n", "L 314.128729 -37.55625 \n", "L 313.709706 -37.55625 \n", "L 313.290682 -37.55625 \n", "L 312.871659 -37.55625 \n", "L 312.452635 -37.55625 \n", "L 312.033612 -37.55625 \n", "L 311.614589 -37.55625 \n", "L 311.195565 -37.55625 \n", "L 310.776542 -37.55625 \n", "L 310.357518 -37.55625 \n", "L 309.938495 -37.55625 \n", "L 309.519472 -37.55625 \n", "L 309.100448 -37.55625 \n", "L 308.681425 -37.55625 \n", "L 308.262402 -37.55625 \n", "L 307.843368 -37.55625 \n", "L 307.424345 -37.55625 \n", "L 307.005321 -37.55625 \n", "L 306.586298 -37.55625 \n", "L 306.167275 -37.55625 \n", "L 305.748251 -37.55625 \n", "L 305.329228 -37.55625 \n", "L 304.910205 -37.55625 \n", "L 304.491181 -37.55625 \n", "L 304.072158 -37.55625 \n", "L 303.653134 -37.55625 \n", "L 303.234111 -37.55625 \n", "L 302.815088 -37.55625 \n", "L 302.396064 -37.55625 \n", "L 301.977041 -37.55625 \n", "L 301.558018 -37.55625 \n", "L 301.138994 -37.55625 \n", "L 300.719966 -37.55625 \n", "L 300.300942 -37.55625 \n", "L 299.881919 -37.55625 \n", "L 299.462896 -37.55625 \n", "z\n", "\" style=\"stroke: #7f7f7f; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#pa9450da409)\">\n", " <use xlink:href=\"#m2a5e73abe7\" x=\"0\" y=\"226.194375\" style=\"fill: #7f7f7f; fill-opacity: 0.5; stroke: #7f7f7f; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"line2d_1\">\n", " <path d=\"M 50.14375 188.638125 \n", "L 50.14375 177.955718 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #1f77b4; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_2\">\n", " <path d=\"M 136.043623 188.638125 \n", "L 136.043623 122.69085 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #1f77b4; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_3\">\n", " <path d=\"M 136.462646 188.638125 \n", "L 136.462646 122.194516 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #ff7f0e; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_4\">\n", " <path d=\"M 171.660645 188.638125 \n", "L 171.660645 75.316811 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #ff7f0e; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_5\">\n", " <path d=\"M 172.079668 188.638125 \n", "L 172.079668 74.750347 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #2ca02c; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_6\">\n", " <path d=\"M 195.964026 188.638125 \n", "L 195.964026 47.215647 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #2ca02c; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_7\">\n", " <path d=\"M 196.383049 188.638125 \n", "L 196.383049 46.85888 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #d62728; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_8\">\n", " <path d=\"M 217.334238 188.638125 \n", "L 217.334238 37.44191 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #d62728; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_9\">\n", " <path d=\"M 217.753262 188.638125 \n", "L 217.753262 37.438125 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #9467bd; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_10\">\n", " <path d=\"M 239.123474 188.638125 \n", "L 239.123474 46.85888 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #9467bd; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_11\">\n", " <path d=\"M 239.542497 188.638125 \n", "L 239.542497 47.215656 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #8c564b; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_12\">\n", " <path d=\"M 263.42685 188.638125 \n", "L 263.42685 74.750338 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #8c564b; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_13\">\n", " <path d=\"M 263.845873 188.638125 \n", "L 263.845873 75.316811 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #e377c2; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_14\">\n", " <path d=\"M 299.043872 188.638125 \n", "L 299.043872 122.194502 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #e377c2; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_15\">\n", " <path d=\"M 299.462896 188.638125 \n", "L 299.462896 122.690837 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #7f7f7f; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_16\">\n", " <path d=\"M 384.94375 188.638125 \n", "L 384.94375 177.85226 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #7f7f7f; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_17\">\n", " <path d=\"M 50.14375 177.955718 \n", "L 56.429101 176.29888 \n", "L 62.295438 174.533085 \n", "L 68.161775 172.529344 \n", "L 73.609079 170.431691 \n", "L 78.63737 168.272087 \n", "L 83.66565 165.878427 \n", "L 88.693941 163.231008 \n", "L 93.303198 160.564336 \n", "L 97.912455 157.652606 \n", "L 102.521722 154.481293 \n", "L 107.13098 151.036869 \n", "L 111.740247 147.307362 \n", "L 116.349504 143.283057 \n", "L 120.958771 138.957195 \n", "L 125.568028 134.326878 \n", "L 130.177285 129.39397 \n", "L 135.205576 123.676666 \n", "L 140.233867 117.627676 \n", "L 145.68117 110.736061 \n", "L 151.966526 102.419105 \n", "L 160.347004 90.923591 \n", "L 173.755767 72.499923 \n", "L 179.203076 65.405944 \n", "L 183.812335 59.758912 \n", "L 187.583548 55.457045 \n", "L 191.354764 51.501572 \n", "L 194.706953 48.319897 \n", "L 197.640121 45.823403 \n", "L 200.573287 43.618437 \n", "L 203.08743 41.975707 \n", "L 205.601572 40.573072 \n", "L 208.115715 39.420237 \n", "L 210.629857 38.525305 \n", "L 213.144 37.894567 \n", "L 215.658143 37.5326 \n", "L 217.753262 37.438125 \n", "L 219.848381 37.532582 \n", "L 221.9435 37.815503 \n", "L 224.457642 38.401676 \n", "L 226.971785 39.252988 \n", "L 229.485928 40.363339 \n", "L 232.00007 41.724978 \n", "L 234.514213 43.328423 \n", "L 237.447379 45.490077 \n", "L 240.380544 47.946232 \n", "L 243.313713 50.675079 \n", "L 246.665902 54.097353 \n", "L 250.437118 58.289893 \n", "L 254.627354 63.3087 \n", "L 259.236614 69.178802 \n", "L 265.102949 77.024438 \n", "L 275.15952 90.923591 \n", "L 284.797067 104.108986 \n", "L 291.082423 112.355179 \n", "L 296.948755 119.679209 \n", "L 301.977041 125.620445 \n", "L 307.005321 131.222419 \n", "L 311.614589 136.045855 \n", "L 316.223846 140.56539 \n", "L 320.833113 144.781046 \n", "L 325.44237 148.69719 \n", "L 330.051637 152.32178 \n", "L 334.660894 155.665416 \n", "L 339.270162 158.740704 \n", "L 343.879419 161.561602 \n", "L 348.907699 164.366214 \n", "L 353.93599 166.905489 \n", "L 358.96427 169.199253 \n", "L 364.411584 171.429737 \n", "L 369.858888 173.418945 \n", "L 375.725226 175.317454 \n", "L 381.591553 176.989208 \n", "L 384.94375 177.85226 \n", "L 384.94375 177.85226 \n", "\" clip-path=\"url(#pa9450da409)\" style=\"fill: none; stroke: #000000; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"patch_3\">\n", " <path d=\"M 50.14375 188.638125 \n", "L 50.14375 22.318125 \n", "\" style=\"fill: none; stroke: #262626; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_4\">\n", " <path d=\"M 384.94375 188.638125 \n", "L 384.94375 22.318125 \n", "\" style=\"fill: none; stroke: #262626; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_5\">\n", " <path d=\"M 50.14375 188.638125 \n", "L 384.94375 188.638125 \n", "\" style=\"fill: none; stroke: #262626; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_6\">\n", " <path d=\"M 50.14375 22.318125 \n", "L 384.94375 22.318125 \n", "\" style=\"fill: none; stroke: #262626; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"text_18\">\n", " <!-- Dequantization distribution for 8 discrete values -->\n", " <g style=\"fill: #262626\" transform=\"translate(72.526563 16.318125) scale(0.12 -0.12)\">\n", " <defs>\n", " <path id=\"DejaVuSans-44\" d=\"M 1259 4147 \n", "L 1259 519 \n", "L 2022 519 \n", "Q 2988 519 3436 956 \n", "Q 3884 1394 3884 2338 \n", "Q 3884 3275 3436 3711 \n", "Q 2988 4147 2022 4147 \n", "L 1259 4147 \n", "z\n", "M 628 4666 \n", "L 1925 4666 \n", "Q 3281 4666 3915 4102 \n", "Q 4550 3538 4550 2338 \n", "Q 4550 1131 3912 565 \n", "Q 3275 0 1925 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-65\" d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-71\" d=\"M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "M 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "L 2906 3500 \n", "L 3481 3500 \n", "L 3481 -1331 \n", "L 2906 -1331 \n", "L 2906 525 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-75\" d=\"M 544 1381 \n", "L 544 3500 \n", "L 1119 3500 \n", "L 1119 1403 \n", "Q 1119 906 1312 657 \n", "Q 1506 409 1894 409 \n", "Q 2359 409 2629 706 \n", "Q 2900 1003 2900 1516 \n", "L 2900 3500 \n", "L 3475 3500 \n", "L 3475 0 \n", "L 2900 0 \n", "L 2900 538 \n", "Q 2691 219 2414 64 \n", "Q 2138 -91 1772 -91 \n", "Q 1169 -91 856 284 \n", "Q 544 659 544 1381 \n", "z\n", "M 1991 3584 \n", "L 1991 3584 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6e\" d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-64\" d=\"M 2906 2969 \n", "L 2906 4863 \n", "L 3481 4863 \n", "L 3481 0 \n", "L 2906 0 \n", "L 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "z\n", "M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-73\" d=\"M 2834 3397 \n", "L 2834 2853 \n", "Q 2591 2978 2328 3040 \n", "Q 2066 3103 1784 3103 \n", "Q 1356 3103 1142 2972 \n", "Q 928 2841 928 2578 \n", "Q 928 2378 1081 2264 \n", "Q 1234 2150 1697 2047 \n", "L 1894 2003 \n", "Q 2506 1872 2764 1633 \n", "Q 3022 1394 3022 966 \n", "Q 3022 478 2636 193 \n", "Q 2250 -91 1575 -91 \n", "Q 1294 -91 989 -36 \n", "Q 684 19 347 128 \n", "L 347 722 \n", "Q 666 556 975 473 \n", "Q 1284 391 1588 391 \n", "Q 1994 391 2212 530 \n", "Q 2431 669 2431 922 \n", "Q 2431 1156 2273 1281 \n", "Q 2116 1406 1581 1522 \n", "L 1381 1569 \n", "Q 847 1681 609 1914 \n", "Q 372 2147 372 2553 \n", "Q 372 3047 722 3315 \n", "Q 1072 3584 1716 3584 \n", "Q 2034 3584 2315 3537 \n", "Q 2597 3491 2834 3397 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-66\" d=\"M 2375 4863 \n", "L 2375 4384 \n", "L 1825 4384 \n", "Q 1516 4384 1395 4259 \n", "Q 1275 4134 1275 3809 \n", "L 1275 3500 \n", "L 2222 3500 \n", "L 2222 3053 \n", "L 1275 3053 \n", "L 1275 0 \n", "L 697 0 \n", "L 697 3053 \n", "L 147 3053 \n", "L 147 3500 \n", "L 697 3500 \n", "L 697 3744 \n", "Q 697 4328 969 4595 \n", "Q 1241 4863 1831 4863 \n", "L 2375 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-38\" d=\"M 2034 2216 \n", "Q 1584 2216 1326 1975 \n", "Q 1069 1734 1069 1313 \n", "Q 1069 891 1326 650 \n", "Q 1584 409 2034 409 \n", "Q 2484 409 2743 651 \n", "Q 3003 894 3003 1313 \n", "Q 3003 1734 2745 1975 \n", "Q 2488 2216 2034 2216 \n", "z\n", "M 1403 2484 \n", "Q 997 2584 770 2862 \n", "Q 544 3141 544 3541 \n", "Q 544 4100 942 4425 \n", "Q 1341 4750 2034 4750 \n", "Q 2731 4750 3128 4425 \n", "Q 3525 4100 3525 3541 \n", "Q 3525 3141 3298 2862 \n", "Q 3072 2584 2669 2484 \n", "Q 3125 2378 3379 2068 \n", "Q 3634 1759 3634 1313 \n", "Q 3634 634 3220 271 \n", "Q 2806 -91 2034 -91 \n", "Q 1263 -91 848 271 \n", "Q 434 634 434 1313 \n", "Q 434 1759 690 2068 \n", "Q 947 2378 1403 2484 \n", "z\n", "M 1172 3481 \n", "Q 1172 3119 1398 2916 \n", "Q 1625 2713 2034 2713 \n", "Q 2441 2713 2670 2916 \n", "Q 2900 3119 2900 3481 \n", "Q 2900 3844 2670 4047 \n", "Q 2441 4250 2034 4250 \n", "Q 1625 4250 1398 4047 \n", "Q 1172 3844 1172 3481 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-63\" d=\"M 3122 3366 \n", "L 3122 2828 \n", "Q 2878 2963 2633 3030 \n", "Q 2388 3097 2138 3097 \n", "Q 1578 3097 1268 2742 \n", "Q 959 2388 959 1747 \n", "Q 959 1106 1268 751 \n", "Q 1578 397 2138 397 \n", "Q 2388 397 2633 464 \n", "Q 2878 531 3122 666 \n", "L 3122 134 \n", "Q 2881 22 2623 -34 \n", "Q 2366 -91 2075 -91 \n", "Q 1284 -91 818 406 \n", "Q 353 903 353 1747 \n", "Q 353 2603 823 3093 \n", "Q 1294 3584 2113 3584 \n", "Q 2378 3584 2631 3529 \n", "Q 2884 3475 3122 3366 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-76\" d=\"M 191 3500 \n", "L 800 3500 \n", "L 1894 563 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2284 0 \n", "L 1503 0 \n", "L 191 3500 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-44\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"77.001953\"/>\n", " <use xlink:href=\"#DejaVuSans-71\" x=\"138.525391\"/>\n", " <use xlink:href=\"#DejaVuSans-75\" x=\"202.001953\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"265.380859\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"326.660156\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"390.039062\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"429.248047\"/>\n", " <use xlink:href=\"#DejaVuSans-7a\" x=\"457.03125\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"509.521484\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"570.800781\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"610.009766\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"637.792969\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"698.974609\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"762.353516\"/>\n", " <use xlink:href=\"#DejaVuSans-64\" x=\"794.140625\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"857.617188\"/>\n", " <use xlink:href=\"#DejaVuSans-73\" x=\"885.400391\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"937.5\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"976.708984\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"1017.822266\"/>\n", " <use xlink:href=\"#DejaVuSans-62\" x=\"1045.605469\"/>\n", " <use xlink:href=\"#DejaVuSans-75\" x=\"1109.082031\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"1172.460938\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"1211.669922\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"1239.453125\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"1300.634766\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"1364.013672\"/>\n", " <use xlink:href=\"#DejaVuSans-66\" x=\"1395.800781\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"1431.005859\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"1492.1875\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"1533.300781\"/>\n", " <use xlink:href=\"#DejaVuSans-38\" x=\"1565.087891\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"1628.710938\"/>\n", " <use xlink:href=\"#DejaVuSans-64\" x=\"1660.498047\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"1723.974609\"/>\n", " <use xlink:href=\"#DejaVuSans-73\" x=\"1751.757812\"/>\n", " <use xlink:href=\"#DejaVuSans-63\" x=\"1803.857422\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"1858.837891\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"1897.701172\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"1959.224609\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"1998.433594\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"2059.957031\"/>\n", " <use xlink:href=\"#DejaVuSans-76\" x=\"2091.744141\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"2150.923828\"/>\n", " <use xlink:href=\"#DejaVuSans-6c\" x=\"2212.203125\"/>\n", " <use xlink:href=\"#DejaVuSans-75\" x=\"2239.986328\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"2303.365234\"/>\n", " <use xlink:href=\"#DejaVuSans-73\" x=\"2364.888672\"/>\n", " </g>\n", " </g>\n", " <g id=\"legend_1\">\n", " <g id=\"patch_7\">\n", " <path d=\"M 339.58125 147.743125 \n", "L 377.94375 147.743125 \n", "Q 379.94375 147.743125 379.94375 145.743125 \n", "L 379.94375 29.318125 \n", "Q 379.94375 27.318125 377.94375 27.318125 \n", "L 339.58125 27.318125 \n", "Q 337.58125 27.318125 337.58125 29.318125 \n", "L 337.58125 145.743125 \n", "Q 337.58125 147.743125 339.58125 147.743125 \n", "z\n", "\" style=\"fill: #ffffff; opacity: 0.8; stroke: #cccccc; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_8\">\n", " <path d=\"M 341.58125 38.916562 \n", "L 361.58125 38.916562 \n", "L 361.58125 31.916562 \n", "L 341.58125 31.916562 \n", "z\n", "\" style=\"fill: #1f77b4; fill-opacity: 0.5; stroke: #1f77b4; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_19\">\n", " <!-- 0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(369.58125 38.916562) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_9\">\n", " <path d=\"M 341.58125 53.594688 \n", "L 361.58125 53.594688 \n", "L 361.58125 46.594688 \n", "L 341.58125 46.594688 \n", "z\n", "\" style=\"fill: #ff7f0e; fill-opacity: 0.5; stroke: #ff7f0e; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_20\">\n", " <!-- 1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(369.58125 53.594688) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_10\">\n", " <path d=\"M 341.58125 68.272812 \n", "L 361.58125 68.272812 \n", "L 361.58125 61.272812 \n", "L 341.58125 61.272812 \n", "z\n", "\" style=\"fill: #2ca02c; fill-opacity: 0.5; stroke: #2ca02c; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_21\">\n", " <!-- 2 -->\n", " <g style=\"fill: #262626\" transform=\"translate(369.58125 68.272812) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-32\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_11\">\n", " <path d=\"M 341.58125 82.950938 \n", "L 361.58125 82.950938 \n", "L 361.58125 75.950938 \n", "L 341.58125 75.950938 \n", "z\n", "\" style=\"fill: #d62728; fill-opacity: 0.5; stroke: #d62728; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_22\">\n", " <!-- 3 -->\n", " <g style=\"fill: #262626\" transform=\"translate(369.58125 82.950938) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-33\" d=\"M 2597 2516 \n", "Q 3050 2419 3304 2112 \n", "Q 3559 1806 3559 1356 \n", "Q 3559 666 3084 287 \n", "Q 2609 -91 1734 -91 \n", "Q 1441 -91 1130 -33 \n", "Q 819 25 488 141 \n", "L 488 750 \n", "Q 750 597 1062 519 \n", "Q 1375 441 1716 441 \n", "Q 2309 441 2620 675 \n", "Q 2931 909 2931 1356 \n", "Q 2931 1769 2642 2001 \n", "Q 2353 2234 1838 2234 \n", "L 1294 2234 \n", "L 1294 2753 \n", "L 1863 2753 \n", "Q 2328 2753 2575 2939 \n", "Q 2822 3125 2822 3475 \n", "Q 2822 3834 2567 4026 \n", "Q 2313 4219 1838 4219 \n", "Q 1578 4219 1281 4162 \n", "Q 984 4106 628 3988 \n", "L 628 4550 \n", "Q 988 4650 1302 4700 \n", "Q 1616 4750 1894 4750 \n", "Q 2613 4750 3031 4423 \n", "Q 3450 4097 3450 3541 \n", "Q 3450 3153 3228 2886 \n", "Q 3006 2619 2597 2516 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-33\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_12\">\n", " <path d=\"M 341.58125 97.629063 \n", "L 361.58125 97.629063 \n", "L 361.58125 90.629063 \n", "L 341.58125 90.629063 \n", "z\n", "\" style=\"fill: #9467bd; fill-opacity: 0.5; stroke: #9467bd; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_23\">\n", " <!-- 4 -->\n", " <g style=\"fill: #262626\" transform=\"translate(369.58125 97.629063) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-34\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_13\">\n", " <path d=\"M 341.58125 112.307187 \n", "L 361.58125 112.307187 \n", "L 361.58125 105.307187 \n", "L 341.58125 105.307187 \n", "z\n", "\" style=\"fill: #8c564b; fill-opacity: 0.5; stroke: #8c564b; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_24\">\n", " <!-- 5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(369.58125 112.307187) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-35\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_14\">\n", " <path d=\"M 341.58125 126.985312 \n", "L 361.58125 126.985312 \n", "L 361.58125 119.985312 \n", "L 341.58125 119.985312 \n", "z\n", "\" style=\"fill: #e377c2; fill-opacity: 0.5; stroke: #e377c2; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_25\">\n", " <!-- 6 -->\n", " <g style=\"fill: #262626\" transform=\"translate(369.58125 126.985312) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-36\" d=\"M 2113 2584 \n", "Q 1688 2584 1439 2293 \n", "Q 1191 2003 1191 1497 \n", "Q 1191 994 1439 701 \n", "Q 1688 409 2113 409 \n", "Q 2538 409 2786 701 \n", "Q 3034 994 3034 1497 \n", "Q 3034 2003 2786 2293 \n", "Q 2538 2584 2113 2584 \n", "z\n", "M 3366 4563 \n", "L 3366 3988 \n", "Q 3128 4100 2886 4159 \n", "Q 2644 4219 2406 4219 \n", "Q 1781 4219 1451 3797 \n", "Q 1122 3375 1075 2522 \n", "Q 1259 2794 1537 2939 \n", "Q 1816 3084 2150 3084 \n", "Q 2853 3084 3261 2657 \n", "Q 3669 2231 3669 1497 \n", "Q 3669 778 3244 343 \n", "Q 2819 -91 2113 -91 \n", "Q 1303 -91 875 529 \n", "Q 447 1150 447 2328 \n", "Q 447 3434 972 4092 \n", "Q 1497 4750 2381 4750 \n", "Q 2619 4750 2861 4703 \n", "Q 3103 4656 3366 4563 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-36\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_15\">\n", " <path d=\"M 341.58125 141.663437 \n", "L 361.58125 141.663437 \n", "L 361.58125 134.663437 \n", "L 341.58125 134.663437 \n", "z\n", "\" style=\"fill: #7f7f7f; fill-opacity: 0.5; stroke: #7f7f7f; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_26\">\n", " <!-- 7 -->\n", " <g style=\"fill: #262626\" transform=\"translate(369.58125 141.663437) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-37\" d=\"M 525 4666 \n", "L 3525 4666 \n", "L 3525 4397 \n", "L 1831 0 \n", "L 1172 0 \n", "L 2766 4134 \n", "L 525 4134 \n", "L 525 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-37\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"pa9450da409\">\n", " <rect x=\"50.14375\" y=\"22.318125\" width=\"334.8\" height=\"166.32\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 600x300 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["\n", "\n", "def visualize_dequantization(quants, prior=None):\n", " \"\"\"Function for visualizing the dequantization values of discrete values in continuous space.\"\"\"\n", " # Prior over discrete values. If not given, a uniform is assumed\n", " if prior is None:\n", " prior = np.ones(quants, dtype=np.float32) / quants\n", " prior = prior / prior.sum() # Ensure proper categorical distribution\n", "\n", " inp = torch.arange(-4, 4, 0.01).view(-1, 1, 1, 1) # Possible continuous values we want to consider\n", " ldj = torch.zeros(inp.shape[0])\n", " dequant_module = Dequantization(quants=quants)\n", " # Invert dequantization on continuous values to find corresponding discrete value\n", " out, ldj = dequant_module.forward(inp, ldj, reverse=True)\n", " inp, out, prob = inp.squeeze().numpy(), out.squeeze().numpy(), ldj.exp().numpy()\n", " prob = prob * prior[out] # Probability scaled by categorical prior\n", "\n", " # Plot volumes and continuous distribution\n", " sns.set_style(\"white\")\n", " _ = plt.figure(figsize=(6, 3))\n", " x_ticks = []\n", " for v in np.unique(out):\n", " indices = np.where(out == v)\n", " color = to_rgb(\"C%i\" % v)\n", " plt.fill_between(inp[indices], prob[indices], np.zeros(indices[0].shape[0]), color=color + (0.5,), label=str(v))\n", " plt.plot([inp[indices[0][0]]] * 2, [0, prob[indices[0][0]]], color=color)\n", " plt.plot([inp[indices[0][-1]]] * 2, [0, prob[indices[0][-1]]], color=color)\n", " x_ticks.append(inp[indices[0][0]])\n", " x_ticks.append(inp.max())\n", " plt.xticks(x_ticks, [\"%.1f\" % x for x in x_ticks])\n", " plt.plot(inp, prob, color=(0.0, 0.0, 0.0))\n", " # Set final plot properties\n", " plt.ylim(0, prob.max() * 1.1)\n", " plt.xlim(inp.min(), inp.max())\n", " plt.xlabel(\"z\")\n", " plt.ylabel(\"Probability\")\n", " plt.title(\"Dequantization distribution for %i discrete values\" % quants)\n", " plt.legend()\n", " plt.show()\n", " plt.close()\n", "\n", "\n", "visualize_dequantization(quants=8)"]}, {"cell_type": "markdown", "id": "044aceb3", "metadata": {"papermill": {"duration": 0.019884, "end_time": "2023-03-14T16:08:52.969239", "exception": false, "start_time": "2023-03-14T16:08:52.949355", "status": "completed"}, "tags": []}, "source": ["The visualized distribution show the sub-volumes that are assigned to the different discrete values.\n", "The value $0$ has its volume between $[-\\infty, -1.9)$, the value $1$ is represented by the interval $[-1.9, -1.1)$, etc.\n", "The volume for each discrete value has the same probability mass.\n", "That's why the volumes close to the center (e.g. 3 and 4) have a smaller area on the z-axis as others\n", "($z$ is being used to denote the output of the whole dequantization flow).\n", "\n", "Effectively, the consecutive normalizing flow models discrete images by the following objective:\n", "\n", "$$\\log p(x) = \\log \\mathbb{E}_{u\\sim q(u|x)}\\left[\\frac{p(x+u)}{q(u|x)} \\right] \\geq \\mathbb{E}_{u}\\left[\\log \\frac{p(x+u)}{q(u|x)} \\right]$$\n", "\n", "Although normalizing flows are exact in likelihood, we have a lower bound.\n", "Specifically, this is an example of the Jensen inequality because we need to move the log into the expectation so we can use Monte-carlo estimates.\n", "In general, this bound is considerably smaller than the ELBO in variational autoencoders.\n", "Actually, we can reduce the bound ourselves by estimating the expectation not by one, but by $M$ samples.\n", "In other words, we can apply importance sampling which leads to the following inequality:\n", "\n", "$$\\log p(x) = \\log \\mathbb{E}_{u\\sim q(u|x)}\\left[\\frac{p(x+u)}{q(u|x)} \\right] \\geq \\mathbb{E}_{u}\\left[\\log \\frac{1}{M} \\sum_{m=1}^{M} \\frac{p(x+u_m)}{q(u_m|x)} \\right] \\geq \\mathbb{E}_{u}\\left[\\log \\frac{p(x+u)}{q(u|x)} \\right]$$\n", "\n", "The importance sampling $\\frac{1}{M} \\sum_{m=1}^{M} \\frac{p(x+u_m)}{q(u_m|x)}$ becomes\n", "$\\mathbb{E}_{u\\sim q(u|x)}\\left[\\frac{p(x+u)}{q(u|x)} \\right]$ if $M\\to \\infty$,\n", "so that the more samples we use, the tighter the bound is.\n", "During testing, we can make use of this property and have it implemented in `test_step` in `ImageFlow`.\n", "In theory, we could also use this tighter bound during training.\n", "However, related work has shown that this does not necessarily lead to\n", "an improvement given the additional computational cost, and it is more\n", "efficient to stick with a single estimate [5]."]}, {"cell_type": "markdown", "id": "aca798a1", "metadata": {"papermill": {"duration": 0.014861, "end_time": "2023-03-14T16:08:53.000621", "exception": false, "start_time": "2023-03-14T16:08:52.985760", "status": "completed"}, "tags": []}, "source": ["### Variational Dequantization\n", "\n", "Dequantization uses a uniform distribution for the noise $u$ which effectively leads to images being represented as hypercubes\n", "(cube in high dimensions) with sharp borders.\n", "However, modeling such sharp borders is not easy for a flow as it uses smooth transformations to convert it into a Gaussian distribution.\n", "\n", "Another way of looking at it is if we change the prior distribution in the previous visualization.\n", "Imagine we have independent Gaussian noise on pixels which is commonly the case for any real-world taken picture.\n", "Therefore, the flow would have to model a distribution as above, but with the individual volumes scaled as follows:"]}, {"cell_type": "code", "execution_count": 10, "id": "320081f9", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:53.040814Z", "iopub.status.busy": "2023-03-14T16:08:53.040389Z", "iopub.status.idle": "2023-03-14T16:08:53.454171Z", "shell.execute_reply": "2023-03-14T16:08:53.453564Z"}, "papermill": {"duration": 0.439315, "end_time": "2023-03-14T16:08:53.458705", "exception": false, "start_time": "2023-03-14T16:08:53.019390", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"393.732813pt\" height=\"226.194375pt\" viewBox=\"0 0 393.732813 226.194375\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:08:53.205021</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 226.194375 \n", "L 393.732813 226.194375 \n", "L 393.732813 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g id=\"patch_2\">\n", " <path d=\"M 43.78125 188.638125 \n", "L 378.58125 188.638125 \n", "L 378.58125 22.318125 \n", "L 43.78125 22.318125 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"matplotlib.axis_1\">\n", " <g id=\"xtick_1\">\n", " <g id=\"text_1\">\n", " <!-- -4.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(34.025781 203.236563) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-2d\" d=\"M 313 2009 \n", "L 1997 2009 \n", "L 1997 1497 \n", "L 313 1497 \n", "L 313 2009 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-34\" d=\"M 2419 4116 \n", "L 825 1625 \n", "L 2419 1625 \n", "L 2419 4116 \n", "z\n", "M 2253 4666 \n", "L 3047 4666 \n", "L 3047 1625 \n", "L 3713 1625 \n", "L 3713 1100 \n", "L 3047 1100 \n", "L 3047 0 \n", "L 2419 0 \n", "L 2419 1100 \n", "L 313 1100 \n", "L 313 1709 \n", "L 2253 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-2e\" d=\"M 684 794 \n", "L 1344 794 \n", "L 1344 0 \n", "L 684 0 \n", "L 684 794 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-30\" d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2d\"/>\n", " <use xlink:href=\"#DejaVuSans-34\" x=\"36.083984\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"99.707031\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"131.494141\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_2\">\n", " <g id=\"text_2\">\n", " <!-- -1.9 -->\n", " <g style=\"fill: #262626\" transform=\"translate(120.344677 203.236563) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-31\" d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-39\" d=\"M 703 97 \n", "L 703 672 \n", "Q 941 559 1184 500 \n", "Q 1428 441 1663 441 \n", "Q 2288 441 2617 861 \n", "Q 2947 1281 2994 2138 \n", "Q 2813 1869 2534 1725 \n", "Q 2256 1581 1919 1581 \n", "Q 1219 1581 811 2004 \n", "Q 403 2428 403 3163 \n", "Q 403 3881 828 4315 \n", "Q 1253 4750 1959 4750 \n", "Q 2769 4750 3195 4129 \n", "Q 3622 3509 3622 2328 \n", "Q 3622 1225 3098 567 \n", "Q 2575 -91 1691 -91 \n", "Q 1453 -91 1209 -44 \n", "Q 966 3 703 97 \n", "z\n", "M 1959 2075 \n", "Q 2384 2075 2632 2365 \n", "Q 2881 2656 2881 3163 \n", "Q 2881 3666 2632 3958 \n", "Q 2384 4250 1959 4250 \n", "Q 1534 4250 1286 3958 \n", "Q 1038 3666 1038 3163 \n", "Q 1038 2656 1286 2365 \n", "Q 1534 2075 1959 2075 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2d\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"36.083984\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"99.707031\"/>\n", " <use xlink:href=\"#DejaVuSans-39\" x=\"131.494141\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_3\">\n", " <g id=\"text_3\">\n", " <!-- -1.1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(155.9617 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-2d\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"36.083984\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"99.707031\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"131.494141\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_4\">\n", " <g id=\"text_4\">\n", " <!-- -0.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(180.265081 203.236563) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-35\" d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2d\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"36.083984\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"99.707031\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"131.494141\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_5\">\n", " <g id=\"text_5\">\n", " <!-- 0.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(203.439199 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_6\">\n", " <g id=\"text_6\">\n", " <!-- 0.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(225.228435 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_7\">\n", " <g id=\"text_7\">\n", " <!-- 1.1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(249.531811 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_8\">\n", " <g id=\"text_8\">\n", " <!-- 1.9 -->\n", " <g style=\"fill: #262626\" transform=\"translate(285.148833 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-39\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_9\">\n", " <g id=\"text_9\">\n", " <!-- 4.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(370.629688 203.236563) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-34\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"text_10\">\n", " <!-- z -->\n", " <g style=\"fill: #262626\" transform=\"translate(208.557031 216.914688) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-7a\" d=\"M 353 3500 \n", "L 3084 3500 \n", "L 3084 2975 \n", "L 922 459 \n", "L 3084 459 \n", "L 3084 0 \n", "L 275 0 \n", "L 275 525 \n", "L 2438 3041 \n", "L 353 3041 \n", "L 353 3500 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-7a\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"matplotlib.axis_2\">\n", " <g id=\"ytick_1\">\n", " <g id=\"text_11\">\n", " <!-- 0.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 192.437344) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_2\">\n", " <g id=\"text_12\">\n", " <!-- 0.2 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 152.023966) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-32\" d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_3\">\n", " <g id=\"text_13\">\n", " <!-- 0.4 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 111.610589) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-34\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_4\">\n", " <g id=\"text_14\">\n", " <!-- 0.6 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 71.197211) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-36\" d=\"M 2113 2584 \n", "Q 1688 2584 1439 2293 \n", "Q 1191 2003 1191 1497 \n", "Q 1191 994 1439 701 \n", "Q 1688 409 2113 409 \n", "Q 2538 409 2786 701 \n", "Q 3034 994 3034 1497 \n", "Q 3034 2003 2786 2293 \n", "Q 2538 2584 2113 2584 \n", "z\n", "M 3366 4563 \n", "L 3366 3988 \n", "Q 3128 4100 2886 4159 \n", "Q 2644 4219 2406 4219 \n", "Q 1781 4219 1451 3797 \n", "Q 1122 3375 1075 2522 \n", "Q 1259 2794 1537 2939 \n", "Q 1816 3084 2150 3084 \n", "Q 2853 3084 3261 2657 \n", "Q 3669 2231 3669 1497 \n", "Q 3669 778 3244 343 \n", "Q 2819 -91 2113 -91 \n", "Q 1303 -91 875 529 \n", "Q 447 1150 447 2328 \n", "Q 447 3434 972 4092 \n", "Q 1497 4750 2381 4750 \n", "Q 2619 4750 2861 4703 \n", "Q 3103 4656 3366 4563 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-36\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_5\">\n", " <g id=\"text_15\">\n", " <!-- 0.8 -->\n", " <g style=\"fill: #262626\" transform=\"translate(20.878125 30.783833) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-38\" d=\"M 2034 2216 \n", "Q 1584 2216 1326 1975 \n", "Q 1069 1734 1069 1313 \n", "Q 1069 891 1326 650 \n", "Q 1584 409 2034 409 \n", "Q 2484 409 2743 651 \n", "Q 3003 894 3003 1313 \n", "Q 3003 1734 2745 1975 \n", "Q 2488 2216 2034 2216 \n", "z\n", "M 1403 2484 \n", "Q 997 2584 770 2862 \n", "Q 544 3141 544 3541 \n", "Q 544 4100 942 4425 \n", "Q 1341 4750 2034 4750 \n", "Q 2731 4750 3128 4425 \n", "Q 3525 4100 3525 3541 \n", "Q 3525 3141 3298 2862 \n", "Q 3072 2584 2669 2484 \n", "Q 3125 2378 3379 2068 \n", "Q 3634 1759 3634 1313 \n", "Q 3634 634 3220 271 \n", "Q 2806 -91 2034 -91 \n", "Q 1263 -91 848 271 \n", "Q 434 634 434 1313 \n", "Q 434 1759 690 2068 \n", "Q 947 2378 1403 2484 \n", "z\n", "M 1172 3481 \n", "Q 1172 3119 1398 2916 \n", "Q 1625 2713 2034 2713 \n", "Q 2441 2713 2670 2916 \n", "Q 2900 3119 2900 3481 \n", "Q 2900 3844 2670 4047 \n", "Q 2441 4250 2034 4250 \n", "Q 1625 4250 1398 4047 \n", "Q 1172 3844 1172 3481 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-38\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"text_16\">\n", " <!-- Probability -->\n", " <g style=\"fill: #262626\" transform=\"translate(14.798438 131.907031) rotate(-90) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-50\" d=\"M 1259 4147 \n", "L 1259 2394 \n", "L 2053 2394 \n", "Q 2494 2394 2734 2622 \n", "Q 2975 2850 2975 3272 \n", "Q 2975 3691 2734 3919 \n", "Q 2494 4147 2053 4147 \n", "L 1259 4147 \n", "z\n", "M 628 4666 \n", "L 2053 4666 \n", "Q 2838 4666 3239 4311 \n", "Q 3641 3956 3641 3272 \n", "Q 3641 2581 3239 2228 \n", "Q 2838 1875 2053 1875 \n", "L 1259 1875 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-72\" d=\"M 2631 2963 \n", "Q 2534 3019 2420 3045 \n", "Q 2306 3072 2169 3072 \n", "Q 1681 3072 1420 2755 \n", "Q 1159 2438 1159 1844 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1341 3275 1631 3429 \n", "Q 1922 3584 2338 3584 \n", "Q 2397 3584 2469 3576 \n", "Q 2541 3569 2628 3553 \n", "L 2631 2963 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6f\" d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-62\" d=\"M 3116 1747 \n", "Q 3116 2381 2855 2742 \n", "Q 2594 3103 2138 3103 \n", "Q 1681 3103 1420 2742 \n", "Q 1159 2381 1159 1747 \n", "Q 1159 1113 1420 752 \n", "Q 1681 391 2138 391 \n", "Q 2594 391 2855 752 \n", "Q 3116 1113 3116 1747 \n", "z\n", "M 1159 2969 \n", "Q 1341 3281 1617 3432 \n", "Q 1894 3584 2278 3584 \n", "Q 2916 3584 3314 3078 \n", "Q 3713 2572 3713 1747 \n", "Q 3713 922 3314 415 \n", "Q 2916 -91 2278 -91 \n", "Q 1894 -91 1617 61 \n", "Q 1341 213 1159 525 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "L 1159 4863 \n", "L 1159 2969 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-61\" d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-69\" d=\"M 603 3500 \n", "L 1178 3500 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 3500 \n", "z\n", "M 603 4863 \n", "L 1178 4863 \n", "L 1178 4134 \n", "L 603 4134 \n", "L 603 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6c\" d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-74\" d=\"M 1172 4494 \n", "L 1172 3500 \n", "L 2356 3500 \n", "L 2356 3053 \n", "L 1172 3053 \n", "L 1172 1153 \n", "Q 1172 725 1289 603 \n", "Q 1406 481 1766 481 \n", "L 2356 481 \n", "L 2356 0 \n", "L 1766 0 \n", "Q 1100 0 847 248 \n", "Q 594 497 594 1153 \n", "L 594 3053 \n", "L 172 3053 \n", "L 172 3500 \n", "L 594 3500 \n", "L 594 4494 \n", "L 1172 4494 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-79\" d=\"M 2059 -325 \n", "Q 1816 -950 1584 -1140 \n", "Q 1353 -1331 966 -1331 \n", "L 506 -1331 \n", "L 506 -850 \n", "L 844 -850 \n", "Q 1081 -850 1212 -737 \n", "Q 1344 -625 1503 -206 \n", "L 1606 56 \n", "L 191 3500 \n", "L 800 3500 \n", "L 1894 763 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2059 -325 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-50\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"58.552734\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"97.416016\"/>\n", " <use xlink:href=\"#DejaVuSans-62\" x=\"158.597656\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"222.074219\"/>\n", " <use xlink:href=\"#DejaVuSans-62\" x=\"283.353516\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"346.830078\"/>\n", " <use xlink:href=\"#DejaVuSans-6c\" x=\"374.613281\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"402.396484\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"430.179688\"/>\n", " <use xlink:href=\"#DejaVuSans-79\" x=\"469.388672\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_1\">\n", " <defs>\n", " <path id=\"mca15354889\" d=\"M 43.78125 -37.55625 \n", "L 43.78125 -39.697679 \n", "L 44.200273 -39.718418 \n", "L 44.619297 -39.739352 \n", "L 45.03832 -39.76048 \n", "L 45.457344 -39.781804 \n", "L 45.876367 -39.803325 \n", "L 46.29539 -39.825048 \n", "L 46.714414 -39.846971 \n", "L 47.133437 -39.869097 \n", "L 47.55246 -39.891429 \n", "L 47.971484 -39.913966 \n", "L 48.390507 -39.936713 \n", "L 48.809531 -39.959668 \n", "L 49.228554 -39.982837 \n", "L 49.647577 -40.006218 \n", "L 50.066601 -40.029814 \n", "L 50.485634 -40.053628 \n", "L 50.904657 -40.077661 \n", "L 51.323681 -40.101914 \n", "L 51.742704 -40.12639 \n", "L 52.161728 -40.151089 \n", "L 52.580751 -40.176016 \n", "L 52.999774 -40.201171 \n", "L 53.418798 -40.226554 \n", "L 53.837821 -40.252171 \n", "L 54.256844 -40.27802 \n", "L 54.675868 -40.304104 \n", "L 55.094891 -40.330427 \n", "L 55.513915 -40.356988 \n", "L 55.932938 -40.383791 \n", "L 56.351961 -40.410837 \n", "L 56.770985 -40.438129 \n", "L 57.190008 -40.465667 \n", "L 57.609032 -40.493456 \n", "L 58.028055 -40.521493 \n", "L 58.447078 -40.549785 \n", "L 58.866102 -40.578331 \n", "L 59.285125 -40.607135 \n", "L 59.704148 -40.636197 \n", "L 60.123172 -40.665521 \n", "L 60.542205 -40.695109 \n", "L 60.961229 -40.72496 \n", "L 61.380252 -40.755079 \n", "L 61.799275 -40.785467 \n", "L 62.218299 -40.816126 \n", "L 62.637322 -40.847059 \n", "L 63.056345 -40.878268 \n", "L 63.475369 -40.909754 \n", "L 63.894392 -40.94152 \n", "L 64.313416 -40.973567 \n", "L 64.732439 -41.005899 \n", "L 65.151462 -41.038516 \n", "L 65.570486 -41.071422 \n", "L 65.989509 -41.104617 \n", "L 66.408532 -41.138106 \n", "L 66.827556 -41.17189 \n", "L 67.246579 -41.20597 \n", "L 67.665603 -41.24035 \n", "L 68.084626 -41.275029 \n", "L 68.503649 -41.310013 \n", "L 68.922673 -41.345302 \n", "L 69.341696 -41.3809 \n", "L 69.76072 -41.416808 \n", "L 70.179743 -41.453027 \n", "L 70.598776 -41.489563 \n", "L 71.0178 -41.526414 \n", "L 71.436823 -41.563585 \n", "L 71.855846 -41.601075 \n", "L 72.27487 -41.638891 \n", "L 72.693893 -41.67703 \n", "L 73.112917 -41.715499 \n", "L 73.53194 -41.754298 \n", "L 73.950963 -41.793431 \n", "L 74.369987 -41.832896 \n", "L 74.78901 -41.8727 \n", "L 75.208033 -41.912843 \n", "L 75.627057 -41.953329 \n", "L 76.04608 -41.994156 \n", "L 76.465104 -42.035331 \n", "L 76.884127 -42.076855 \n", "L 77.30315 -42.118732 \n", "L 77.722174 -42.160959 \n", "L 78.141197 -42.203541 \n", "L 78.56022 -42.246484 \n", "L 78.979244 -42.289785 \n", "L 79.398267 -42.33345 \n", "L 79.817291 -42.377478 \n", "L 80.236314 -42.421872 \n", "L 80.655347 -42.466639 \n", "L 81.074371 -42.511777 \n", "L 81.493394 -42.557286 \n", "L 81.912418 -42.603175 \n", "L 82.331441 -42.649442 \n", "L 82.750464 -42.696088 \n", "L 83.169488 -42.743117 \n", "L 83.588511 -42.790534 \n", "L 84.007534 -42.838337 \n", "L 84.426558 -42.88653 \n", "L 84.845581 -42.935117 \n", "L 85.264605 -42.984097 \n", "L 85.683628 -43.033475 \n", "L 86.102651 -43.083251 \n", "L 86.521675 -43.133428 \n", "L 86.940698 -43.184011 \n", "L 87.359721 -43.234998 \n", "L 87.778745 -43.286395 \n", "L 88.197768 -43.338203 \n", "L 88.616792 -43.390423 \n", "L 89.035815 -43.443058 \n", "L 89.454838 -43.496112 \n", "L 89.873862 -43.549584 \n", "L 90.292885 -43.603476 \n", "L 90.711908 -43.657792 \n", "L 91.130932 -43.712535 \n", "L 91.549955 -43.767706 \n", "L 91.968979 -43.823306 \n", "L 92.388002 -43.87934 \n", "L 92.807025 -43.935806 \n", "L 93.226049 -43.992711 \n", "L 93.645072 -44.050055 \n", "L 94.064106 -44.107837 \n", "L 94.483129 -44.166066 \n", "L 94.902152 -44.224735 \n", "L 95.321176 -44.283852 \n", "L 95.740199 -44.343419 \n", "L 96.159222 -44.403437 \n", "L 96.578246 -44.463907 \n", "L 96.997269 -44.524832 \n", "L 97.416293 -44.586214 \n", "L 97.835316 -44.648055 \n", "L 98.254339 -44.710354 \n", "L 98.673363 -44.773115 \n", "L 99.092386 -44.83634 \n", "L 99.511409 -44.900031 \n", "L 99.930433 -44.964191 \n", "L 100.349456 -45.028819 \n", "L 100.76848 -45.093917 \n", "L 101.187503 -45.159492 \n", "L 101.606526 -45.225535 \n", "L 102.02555 -45.292059 \n", "L 102.444573 -45.359056 \n", "L 102.863596 -45.426536 \n", "L 103.28262 -45.494493 \n", "L 103.701643 -45.562934 \n", "L 104.120677 -45.631859 \n", "L 104.5397 -45.701271 \n", "L 104.958723 -45.771167 \n", "L 105.377747 -45.841546 \n", "L 105.79677 -45.912418 \n", "L 106.215794 -45.983783 \n", "L 106.634817 -46.055632 \n", "L 107.05384 -46.127979 \n", "L 107.472864 -46.200819 \n", "L 107.891887 -46.274152 \n", "L 108.31091 -46.347981 \n", "L 108.729934 -46.422306 \n", "L 109.148957 -46.49713 \n", "L 109.567981 -46.572453 \n", "L 109.987004 -46.648271 \n", "L 110.406027 -46.724592 \n", "L 110.825051 -46.801416 \n", "L 111.244074 -46.878738 \n", "L 111.663097 -46.956567 \n", "L 112.082121 -47.034892 \n", "L 112.501144 -47.113725 \n", "L 112.920168 -47.193061 \n", "L 113.339191 -47.272898 \n", "L 113.758214 -47.353243 \n", "L 114.177248 -47.434093 \n", "L 114.596271 -47.515447 \n", "L 115.015294 -47.597304 \n", "L 115.434318 -47.67967 \n", "L 115.853341 -47.762541 \n", "L 116.272365 -47.845913 \n", "L 116.691388 -47.929794 \n", "L 117.110411 -48.014173 \n", "L 117.529435 -48.099064 \n", "L 117.948458 -48.184455 \n", "L 118.367482 -48.270355 \n", "L 118.786505 -48.356753 \n", "L 119.205528 -48.443656 \n", "L 119.624552 -48.531058 \n", "L 120.043575 -48.618963 \n", "L 120.462598 -48.707369 \n", "L 120.881622 -48.796278 \n", "L 121.300645 -48.885679 \n", "L 121.719669 -48.975585 \n", "L 122.138692 -49.065985 \n", "L 122.557715 -49.15688 \n", "L 122.976739 -49.248268 \n", "L 123.395762 -49.340148 \n", "L 123.814785 -49.432522 \n", "L 124.233819 -49.525383 \n", "L 124.652842 -49.618732 \n", "L 125.071866 -49.71257 \n", "L 125.490889 -49.806888 \n", "L 125.909912 -49.901691 \n", "L 126.328936 -49.996978 \n", "L 126.747959 -50.092738 \n", "L 127.166982 -50.188975 \n", "L 127.586006 -50.285684 \n", "L 128.005029 -50.382871 \n", "L 128.424053 -50.480516 \n", "L 128.843076 -50.578631 \n", "L 129.262099 -50.677215 \n", "L 129.681123 -50.776251 \n", "L 129.681123 -37.55625 \n", "L 129.681123 -37.55625 \n", "L 129.262099 -37.55625 \n", "L 128.843076 -37.55625 \n", "L 128.424053 -37.55625 \n", "L 128.005029 -37.55625 \n", "L 127.586006 -37.55625 \n", "L 127.166982 -37.55625 \n", "L 126.747959 -37.55625 \n", "L 126.328936 -37.55625 \n", "L 125.909912 -37.55625 \n", "L 125.490889 -37.55625 \n", "L 125.071866 -37.55625 \n", "L 124.652842 -37.55625 \n", "L 124.233819 -37.55625 \n", "L 123.814785 -37.55625 \n", "L 123.395762 -37.55625 \n", "L 122.976739 -37.55625 \n", "L 122.557715 -37.55625 \n", "L 122.138692 -37.55625 \n", "L 121.719669 -37.55625 \n", "L 121.300645 -37.55625 \n", "L 120.881622 -37.55625 \n", "L 120.462598 -37.55625 \n", "L 120.043575 -37.55625 \n", "L 119.624552 -37.55625 \n", "L 119.205528 -37.55625 \n", "L 118.786505 -37.55625 \n", "L 118.367482 -37.55625 \n", "L 117.948458 -37.55625 \n", "L 117.529435 -37.55625 \n", "L 117.110411 -37.55625 \n", "L 116.691388 -37.55625 \n", "L 116.272365 -37.55625 \n", "L 115.853341 -37.55625 \n", "L 115.434318 -37.55625 \n", "L 115.015294 -37.55625 \n", "L 114.596271 -37.55625 \n", "L 114.177248 -37.55625 \n", "L 113.758214 -37.55625 \n", "L 113.339191 -37.55625 \n", "L 112.920168 -37.55625 \n", "L 112.501144 -37.55625 \n", "L 112.082121 -37.55625 \n", "L 111.663097 -37.55625 \n", "L 111.244074 -37.55625 \n", "L 110.825051 -37.55625 \n", "L 110.406027 -37.55625 \n", "L 109.987004 -37.55625 \n", "L 109.567981 -37.55625 \n", "L 109.148957 -37.55625 \n", "L 108.729934 -37.55625 \n", "L 108.31091 -37.55625 \n", "L 107.891887 -37.55625 \n", "L 107.472864 -37.55625 \n", "L 107.05384 -37.55625 \n", "L 106.634817 -37.55625 \n", "L 106.215794 -37.55625 \n", "L 105.79677 -37.55625 \n", "L 105.377747 -37.55625 \n", "L 104.958723 -37.55625 \n", "L 104.5397 -37.55625 \n", "L 104.120677 -37.55625 \n", "L 103.701643 -37.55625 \n", "L 103.28262 -37.55625 \n", "L 102.863596 -37.55625 \n", "L 102.444573 -37.55625 \n", "L 102.02555 -37.55625 \n", "L 101.606526 -37.55625 \n", "L 101.187503 -37.55625 \n", "L 100.76848 -37.55625 \n", "L 100.349456 -37.55625 \n", "L 99.930433 -37.55625 \n", "L 99.511409 -37.55625 \n", "L 99.092386 -37.55625 \n", "L 98.673363 -37.55625 \n", "L 98.254339 -37.55625 \n", "L 97.835316 -37.55625 \n", "L 97.416293 -37.55625 \n", "L 96.997269 -37.55625 \n", "L 96.578246 -37.55625 \n", "L 96.159222 -37.55625 \n", "L 95.740199 -37.55625 \n", "L 95.321176 -37.55625 \n", "L 94.902152 -37.55625 \n", "L 94.483129 -37.55625 \n", "L 94.064106 -37.55625 \n", "L 93.645072 -37.55625 \n", "L 93.226049 -37.55625 \n", "L 92.807025 -37.55625 \n", "L 92.388002 -37.55625 \n", "L 91.968979 -37.55625 \n", "L 91.549955 -37.55625 \n", "L 91.130932 -37.55625 \n", "L 90.711908 -37.55625 \n", "L 90.292885 -37.55625 \n", "L 89.873862 -37.55625 \n", "L 89.454838 -37.55625 \n", "L 89.035815 -37.55625 \n", "L 88.616792 -37.55625 \n", "L 88.197768 -37.55625 \n", "L 87.778745 -37.55625 \n", "L 87.359721 -37.55625 \n", "L 86.940698 -37.55625 \n", "L 86.521675 -37.55625 \n", "L 86.102651 -37.55625 \n", "L 85.683628 -37.55625 \n", "L 85.264605 -37.55625 \n", "L 84.845581 -37.55625 \n", "L 84.426558 -37.55625 \n", "L 84.007534 -37.55625 \n", "L 83.588511 -37.55625 \n", "L 83.169488 -37.55625 \n", "L 82.750464 -37.55625 \n", "L 82.331441 -37.55625 \n", "L 81.912418 -37.55625 \n", "L 81.493394 -37.55625 \n", "L 81.074371 -37.55625 \n", "L 80.655347 -37.55625 \n", "L 80.236314 -37.55625 \n", "L 79.817291 -37.55625 \n", "L 79.398267 -37.55625 \n", "L 78.979244 -37.55625 \n", "L 78.56022 -37.55625 \n", "L 78.141197 -37.55625 \n", "L 77.722174 -37.55625 \n", "L 77.30315 -37.55625 \n", "L 76.884127 -37.55625 \n", "L 76.465104 -37.55625 \n", "L 76.04608 -37.55625 \n", "L 75.627057 -37.55625 \n", "L 75.208033 -37.55625 \n", "L 74.78901 -37.55625 \n", "L 74.369987 -37.55625 \n", "L 73.950963 -37.55625 \n", "L 73.53194 -37.55625 \n", "L 73.112917 -37.55625 \n", "L 72.693893 -37.55625 \n", "L 72.27487 -37.55625 \n", "L 71.855846 -37.55625 \n", "L 71.436823 -37.55625 \n", "L 71.0178 -37.55625 \n", "L 70.598776 -37.55625 \n", "L 70.179743 -37.55625 \n", "L 69.76072 -37.55625 \n", "L 69.341696 -37.55625 \n", "L 68.922673 -37.55625 \n", "L 68.503649 -37.55625 \n", "L 68.084626 -37.55625 \n", "L 67.665603 -37.55625 \n", "L 67.246579 -37.55625 \n", "L 66.827556 -37.55625 \n", "L 66.408532 -37.55625 \n", "L 65.989509 -37.55625 \n", "L 65.570486 -37.55625 \n", "L 65.151462 -37.55625 \n", "L 64.732439 -37.55625 \n", "L 64.313416 -37.55625 \n", "L 63.894392 -37.55625 \n", "L 63.475369 -37.55625 \n", "L 63.056345 -37.55625 \n", "L 62.637322 -37.55625 \n", "L 62.218299 -37.55625 \n", "L 61.799275 -37.55625 \n", "L 61.380252 -37.55625 \n", "L 60.961229 -37.55625 \n", "L 60.542205 -37.55625 \n", "L 60.123172 -37.55625 \n", "L 59.704148 -37.55625 \n", "L 59.285125 -37.55625 \n", "L 58.866102 -37.55625 \n", "L 58.447078 -37.55625 \n", "L 58.028055 -37.55625 \n", "L 57.609032 -37.55625 \n", "L 57.190008 -37.55625 \n", "L 56.770985 -37.55625 \n", "L 56.351961 -37.55625 \n", "L 55.932938 -37.55625 \n", "L 55.513915 -37.55625 \n", "L 55.094891 -37.55625 \n", "L 54.675868 -37.55625 \n", "L 54.256844 -37.55625 \n", "L 53.837821 -37.55625 \n", "L 53.418798 -37.55625 \n", "L 52.999774 -37.55625 \n", "L 52.580751 -37.55625 \n", "L 52.161728 -37.55625 \n", "L 51.742704 -37.55625 \n", "L 51.323681 -37.55625 \n", "L 50.904657 -37.55625 \n", "L 50.485634 -37.55625 \n", "L 50.066601 -37.55625 \n", "L 49.647577 -37.55625 \n", "L 49.228554 -37.55625 \n", "L 48.809531 -37.55625 \n", "L 48.390507 -37.55625 \n", "L 47.971484 -37.55625 \n", "L 47.55246 -37.55625 \n", "L 47.133437 -37.55625 \n", "L 46.714414 -37.55625 \n", "L 46.29539 -37.55625 \n", "L 45.876367 -37.55625 \n", "L 45.457344 -37.55625 \n", "L 45.03832 -37.55625 \n", "L 44.619297 -37.55625 \n", "L 44.200273 -37.55625 \n", "L 43.78125 -37.55625 \n", "z\n", "\" style=\"stroke: #1f77b4; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#p1f674292d2)\">\n", " <use xlink:href=\"#mca15354889\" x=\"0\" y=\"226.194375\" style=\"fill: #1f77b4; fill-opacity: 0.5; stroke: #1f77b4; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_2\">\n", " <defs>\n", " <path id=\"m9add99e08e\" d=\"M 130.100146 -37.55625 \n", "L 130.100146 -73.07491 \n", "L 130.519174 -73.341453 \n", "L 130.938198 -73.609189 \n", "L 131.357221 -73.878115 \n", "L 131.776245 -74.148227 \n", "L 132.195268 -74.419504 \n", "L 132.614291 -74.691959 \n", "L 133.033315 -74.965553 \n", "L 133.452338 -75.24032 \n", "L 133.871367 -75.516198 \n", "L 134.290385 -75.793204 \n", "L 134.709408 -76.071315 \n", "L 135.128432 -76.350519 \n", "L 135.547455 -76.63082 \n", "L 135.966478 -76.912204 \n", "L 136.385502 -77.194634 \n", "L 136.804525 -77.478119 \n", "L 137.223554 -77.762635 \n", "L 137.642577 -78.048175 \n", "L 138.0616 -78.334719 \n", "L 138.480624 -78.622246 \n", "L 138.899647 -78.910765 \n", "L 139.31867 -79.200239 \n", "L 139.737694 -79.490656 \n", "L 140.156717 -79.782003 \n", "L 140.575746 -80.074261 \n", "L 140.994769 -80.367439 \n", "L 141.413792 -80.661465 \n", "L 141.832816 -80.956373 \n", "L 142.251839 -81.252114 \n", "L 142.670862 -81.548689 \n", "L 143.089886 -81.846073 \n", "L 143.508909 -82.144242 \n", "L 143.927938 -82.443187 \n", "L 144.346956 -82.742869 \n", "L 144.765979 -83.043283 \n", "L 145.185003 -83.3444 \n", "L 145.604026 -83.646221 \n", "L 146.02305 -83.948697 \n", "L 146.442073 -84.251819 \n", "L 146.861096 -84.555567 \n", "L 147.280125 -84.859932 \n", "L 147.699148 -85.164855 \n", "L 148.118171 -85.470338 \n", "L 148.537195 -85.776345 \n", "L 148.956218 -86.082859 \n", "L 149.375242 -86.389868 \n", "L 149.794265 -86.697331 \n", "L 150.213288 -87.005217 \n", "L 150.632317 -87.313522 \n", "L 151.051335 -87.622199 \n", "L 151.470358 -87.931222 \n", "L 151.889382 -88.240593 \n", "L 152.308405 -88.550247 \n", "L 152.727429 -88.86019 \n", "L 153.146452 -89.17037 \n", "L 153.565475 -89.480762 \n", "L 153.984504 -89.79136 \n", "L 154.403527 -90.102108 \n", "L 154.82255 -90.412991 \n", "L 155.241574 -90.723975 \n", "L 155.660597 -91.035017 \n", "L 156.079621 -91.346108 \n", "L 156.498644 -91.657217 \n", "L 156.917667 -91.968293 \n", "L 157.336696 -92.279315 \n", "L 157.755719 -92.590256 \n", "L 158.174743 -92.901081 \n", "L 158.593766 -93.211757 \n", "L 159.012789 -93.522235 \n", "L 159.431813 -93.832511 \n", "L 159.850836 -94.142537 \n", "L 160.269859 -94.452273 \n", "L 160.688888 -94.761696 \n", "L 161.107906 -95.070773 \n", "L 161.52693 -95.379459 \n", "L 161.945953 -95.687711 \n", "L 162.364976 -95.995511 \n", "L 162.784 -96.302814 \n", "L 163.203023 -96.609597 \n", "L 163.622046 -96.915812 \n", "L 164.041075 -97.221415 \n", "L 164.460098 -97.526387 \n", "L 164.879122 -97.830674 \n", "L 165.298145 -98.134254 \n", "L 165.298145 -37.55625 \n", "L 165.298145 -37.55625 \n", "L 164.879122 -37.55625 \n", "L 164.460098 -37.55625 \n", "L 164.041075 -37.55625 \n", "L 163.622046 -37.55625 \n", "L 163.203023 -37.55625 \n", "L 162.784 -37.55625 \n", "L 162.364976 -37.55625 \n", "L 161.945953 -37.55625 \n", "L 161.52693 -37.55625 \n", "L 161.107906 -37.55625 \n", "L 160.688888 -37.55625 \n", "L 160.269859 -37.55625 \n", "L 159.850836 -37.55625 \n", "L 159.431813 -37.55625 \n", "L 159.012789 -37.55625 \n", "L 158.593766 -37.55625 \n", "L 158.174743 -37.55625 \n", "L 157.755719 -37.55625 \n", "L 157.336696 -37.55625 \n", "L 156.917667 -37.55625 \n", "L 156.498644 -37.55625 \n", "L 156.079621 -37.55625 \n", "L 155.660597 -37.55625 \n", "L 155.241574 -37.55625 \n", "L 154.82255 -37.55625 \n", "L 154.403527 -37.55625 \n", "L 153.984504 -37.55625 \n", "L 153.565475 -37.55625 \n", "L 153.146452 -37.55625 \n", "L 152.727429 -37.55625 \n", "L 152.308405 -37.55625 \n", "L 151.889382 -37.55625 \n", "L 151.470358 -37.55625 \n", "L 151.051335 -37.55625 \n", "L 150.632317 -37.55625 \n", "L 150.213288 -37.55625 \n", "L 149.794265 -37.55625 \n", "L 149.375242 -37.55625 \n", "L 148.956218 -37.55625 \n", "L 148.537195 -37.55625 \n", "L 148.118171 -37.55625 \n", "L 147.699148 -37.55625 \n", "L 147.280125 -37.55625 \n", "L 146.861096 -37.55625 \n", "L 146.442073 -37.55625 \n", "L 146.02305 -37.55625 \n", "L 145.604026 -37.55625 \n", "L 145.185003 -37.55625 \n", "L 144.765979 -37.55625 \n", "L 144.346956 -37.55625 \n", "L 143.927938 -37.55625 \n", "L 143.508909 -37.55625 \n", "L 143.089886 -37.55625 \n", "L 142.670862 -37.55625 \n", "L 142.251839 -37.55625 \n", "L 141.832816 -37.55625 \n", "L 141.413792 -37.55625 \n", "L 140.994769 -37.55625 \n", "L 140.575746 -37.55625 \n", "L 140.156717 -37.55625 \n", "L 139.737694 -37.55625 \n", "L 139.31867 -37.55625 \n", "L 138.899647 -37.55625 \n", "L 138.480624 -37.55625 \n", "L 138.0616 -37.55625 \n", "L 137.642577 -37.55625 \n", "L 137.223554 -37.55625 \n", "L 136.804525 -37.55625 \n", "L 136.385502 -37.55625 \n", "L 135.966478 -37.55625 \n", "L 135.547455 -37.55625 \n", "L 135.128432 -37.55625 \n", "L 134.709408 -37.55625 \n", "L 134.290385 -37.55625 \n", "L 133.871367 -37.55625 \n", "L 133.452338 -37.55625 \n", "L 133.033315 -37.55625 \n", "L 132.614291 -37.55625 \n", "L 132.195268 -37.55625 \n", "L 131.776245 -37.55625 \n", "L 131.357221 -37.55625 \n", "L 130.938198 -37.55625 \n", "L 130.519174 -37.55625 \n", "L 130.100146 -37.55625 \n", "z\n", "\" style=\"stroke: #ff7f0e; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#p1f674292d2)\">\n", " <use xlink:href=\"#m9add99e08e\" x=\"0\" y=\"226.194375\" style=\"fill: #ff7f0e; fill-opacity: 0.5; stroke: #ff7f0e; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_3\">\n", " <defs>\n", " <path id=\"mb440b8eb31\" d=\"M 165.717168 -37.55625 \n", "L 165.717168 -159.317884 \n", "L 166.136192 -159.921959 \n", "L 166.555215 -160.524368 \n", "L 166.974238 -161.125023 \n", "L 167.393267 -161.723895 \n", "L 167.81229 -162.32087 \n", "L 168.231314 -162.915869 \n", "L 168.650337 -163.508815 \n", "L 169.06936 -164.099671 \n", "L 169.488386 -164.688301 \n", "L 169.90741 -165.274648 \n", "L 170.326433 -165.858615 \n", "L 170.745456 -166.440153 \n", "L 171.16448 -167.019177 \n", "L 171.583503 -167.59556 \n", "L 172.002527 -168.169275 \n", "L 172.42155 -168.740234 \n", "L 172.840576 -169.308331 \n", "L 173.259599 -169.87348 \n", "L 173.678623 -170.435642 \n", "L 174.097646 -170.994682 \n", "L 174.516669 -171.550581 \n", "L 174.935693 -172.103185 \n", "L 175.354716 -172.652455 \n", "L 175.773739 -173.198314 \n", "L 176.192765 -173.740647 \n", "L 176.611789 -174.279366 \n", "L 177.030812 -174.814453 \n", "L 177.449835 -175.345782 \n", "L 177.868859 -175.873276 \n", "L 178.287882 -176.396819 \n", "L 178.706906 -176.916364 \n", "L 179.125929 -177.431824 \n", "L 179.544955 -177.94316 \n", "L 179.963978 -178.450217 \n", "L 180.383002 -178.952939 \n", "L 180.802025 -179.451267 \n", "L 181.221048 -179.945067 \n", "L 181.640072 -180.434318 \n", "L 182.059095 -180.918926 \n", "L 182.478119 -181.398764 \n", "L 182.897144 -181.873813 \n", "L 183.316168 -182.343967 \n", "L 183.735191 -182.80915 \n", "L 184.154215 -183.269255 \n", "L 184.57324 -183.724243 \n", "L 184.992264 -184.17401 \n", "L 185.411287 -184.618515 \n", "L 185.830311 -185.057663 \n", "L 186.249336 -185.491329 \n", "L 186.66836 -185.919531 \n", "L 187.087383 -186.342126 \n", "L 187.506407 -186.759064 \n", "L 187.92543 -187.170241 \n", "L 188.344453 -187.575656 \n", "L 188.763477 -187.975174 \n", "L 189.1825 -188.368699 \n", "L 189.601526 -188.75625 \n", "L 189.601526 -37.55625 \n", "L 189.601526 -37.55625 \n", "L 189.1825 -37.55625 \n", "L 188.763477 -37.55625 \n", "L 188.344453 -37.55625 \n", "L 187.92543 -37.55625 \n", "L 187.506407 -37.55625 \n", "L 187.087383 -37.55625 \n", "L 186.66836 -37.55625 \n", "L 186.249336 -37.55625 \n", "L 185.830311 -37.55625 \n", "L 185.411287 -37.55625 \n", "L 184.992264 -37.55625 \n", "L 184.57324 -37.55625 \n", "L 184.154215 -37.55625 \n", "L 183.735191 -37.55625 \n", "L 183.316168 -37.55625 \n", "L 182.897144 -37.55625 \n", "L 182.478119 -37.55625 \n", "L 182.059095 -37.55625 \n", "L 181.640072 -37.55625 \n", "L 181.221048 -37.55625 \n", "L 180.802025 -37.55625 \n", "L 180.383002 -37.55625 \n", "L 179.963978 -37.55625 \n", "L 179.544955 -37.55625 \n", "L 179.125929 -37.55625 \n", "L 178.706906 -37.55625 \n", "L 178.287882 -37.55625 \n", "L 177.868859 -37.55625 \n", "L 177.449835 -37.55625 \n", "L 177.030812 -37.55625 \n", "L 176.611789 -37.55625 \n", "L 176.192765 -37.55625 \n", "L 175.773739 -37.55625 \n", "L 175.354716 -37.55625 \n", "L 174.935693 -37.55625 \n", "L 174.516669 -37.55625 \n", "L 174.097646 -37.55625 \n", "L 173.678623 -37.55625 \n", "L 173.259599 -37.55625 \n", "L 172.840576 -37.55625 \n", "L 172.42155 -37.55625 \n", "L 172.002527 -37.55625 \n", "L 171.583503 -37.55625 \n", "L 171.16448 -37.55625 \n", "L 170.745456 -37.55625 \n", "L 170.326433 -37.55625 \n", "L 169.90741 -37.55625 \n", "L 169.488386 -37.55625 \n", "L 169.06936 -37.55625 \n", "L 168.650337 -37.55625 \n", "L 168.231314 -37.55625 \n", "L 167.81229 -37.55625 \n", "L 167.393267 -37.55625 \n", "L 166.974238 -37.55625 \n", "L 166.555215 -37.55625 \n", "L 166.136192 -37.55625 \n", "L 165.717168 -37.55625 \n", "z\n", "\" style=\"stroke: #2ca02c; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#p1f674292d2)\">\n", " <use xlink:href=\"#mb440b8eb31\" x=\"0\" y=\"226.194375\" style=\"fill: #2ca02c; fill-opacity: 0.5; stroke: #2ca02c; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_4\">\n", " <defs>\n", " <path id=\"m793e4ead1c\" d=\"M 190.020549 -37.55625 \n", "L 190.020549 -113.346966 \n", "L 190.439573 -113.534599 \n", "L 190.858596 -113.71912 \n", "L 191.277621 -113.9005 \n", "L 191.696644 -114.07869 \n", "L 192.115669 -114.253653 \n", "L 192.534692 -114.425388 \n", "L 192.953716 -114.593851 \n", "L 193.37274 -114.758986 \n", "L 193.791764 -114.920772 \n", "L 194.210787 -115.079205 \n", "L 194.62981 -115.234237 \n", "L 195.048834 -115.38583 \n", "L 195.467858 -115.533972 \n", "L 195.886882 -115.678627 \n", "L 196.305905 -115.81976 \n", "L 196.72493 -115.957357 \n", "L 197.143953 -116.091398 \n", "L 197.562976 -116.221836 \n", "L 197.982001 -116.348651 \n", "L 198.401024 -116.471829 \n", "L 198.820049 -116.59134 \n", "L 199.239072 -116.707162 \n", "L 199.658096 -116.819278 \n", "L 200.07712 -116.927656 \n", "L 200.496144 -117.032276 \n", "L 200.915167 -117.133129 \n", "L 201.334191 -117.230185 \n", "L 201.753215 -117.323431 \n", "L 202.172239 -117.412837 \n", "L 202.591263 -117.498398 \n", "L 203.010287 -117.580101 \n", "L 203.42931 -117.657906 \n", "L 203.848334 -117.731828 \n", "L 204.267357 -117.801833 \n", "L 204.686381 -117.867912 \n", "L 205.105405 -117.93005 \n", "L 205.524429 -117.988242 \n", "L 205.943453 -118.04247 \n", "L 206.362476 -118.092723 \n", "L 206.7815 -118.139006 \n", "L 207.200524 -118.181271 \n", "L 207.619548 -118.219552 \n", "L 208.038572 -118.25382 \n", "L 208.457595 -118.284075 \n", "L 208.876619 -118.310292 \n", "L 209.295643 -118.332502 \n", "L 209.714667 -118.350674 \n", "L 210.13369 -118.364823 \n", "L 210.552714 -118.374921 \n", "L 210.971738 -118.380982 \n", "L 210.971738 -37.55625 \n", "L 210.971738 -37.55625 \n", "L 210.552714 -37.55625 \n", "L 210.13369 -37.55625 \n", "L 209.714667 -37.55625 \n", "L 209.295643 -37.55625 \n", "L 208.876619 -37.55625 \n", "L 208.457595 -37.55625 \n", "L 208.038572 -37.55625 \n", "L 207.619548 -37.55625 \n", "L 207.200524 -37.55625 \n", "L 206.7815 -37.55625 \n", "L 206.362476 -37.55625 \n", "L 205.943453 -37.55625 \n", "L 205.524429 -37.55625 \n", "L 205.105405 -37.55625 \n", "L 204.686381 -37.55625 \n", "L 204.267357 -37.55625 \n", "L 203.848334 -37.55625 \n", "L 203.42931 -37.55625 \n", "L 203.010287 -37.55625 \n", "L 202.591263 -37.55625 \n", "L 202.172239 -37.55625 \n", "L 201.753215 -37.55625 \n", "L 201.334191 -37.55625 \n", "L 200.915167 -37.55625 \n", "L 200.496144 -37.55625 \n", "L 200.07712 -37.55625 \n", "L 199.658096 -37.55625 \n", "L 199.239072 -37.55625 \n", "L 198.820049 -37.55625 \n", "L 198.401024 -37.55625 \n", "L 197.982001 -37.55625 \n", "L 197.562976 -37.55625 \n", "L 197.143953 -37.55625 \n", "L 196.72493 -37.55625 \n", "L 196.305905 -37.55625 \n", "L 195.886882 -37.55625 \n", "L 195.467858 -37.55625 \n", "L 195.048834 -37.55625 \n", "L 194.62981 -37.55625 \n", "L 194.210787 -37.55625 \n", "L 193.791764 -37.55625 \n", "L 193.37274 -37.55625 \n", "L 192.953716 -37.55625 \n", "L 192.534692 -37.55625 \n", "L 192.115669 -37.55625 \n", "L 191.696644 -37.55625 \n", "L 191.277621 -37.55625 \n", "L 190.858596 -37.55625 \n", "L 190.439573 -37.55625 \n", "L 190.020549 -37.55625 \n", "z\n", "\" style=\"stroke: #d62728; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#p1f674292d2)\">\n", " <use xlink:href=\"#m793e4ead1c\" x=\"0\" y=\"226.194375\" style=\"fill: #d62728; fill-opacity: 0.5; stroke: #d62728; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_5\">\n", " <defs>\n", " <path id=\"m2650d80dd3\" d=\"M 211.390762 -37.55625 \n", "L 211.390762 -67.866283 \n", "L 211.809785 -67.865524 \n", "L 212.228809 -67.863252 \n", "L 212.647833 -67.859465 \n", "L 213.066857 -67.854163 \n", "L 213.485881 -67.847348 \n", "L 213.904904 -67.839023 \n", "L 214.323928 -67.829184 \n", "L 214.742952 -67.817839 \n", "L 215.161976 -67.804988 \n", "L 215.581 -67.790633 \n", "L 216.000023 -67.77478 \n", "L 216.419047 -67.757427 \n", "L 216.838071 -67.738582 \n", "L 217.257095 -67.718247 \n", "L 217.676118 -67.696425 \n", "L 218.095142 -67.673127 \n", "L 218.514166 -67.648344 \n", "L 218.933189 -67.622092 \n", "L 219.352213 -67.594371 \n", "L 219.771237 -67.56519 \n", "L 220.190261 -67.534555 \n", "L 220.609285 -67.50247 \n", "L 221.028308 -67.468939 \n", "L 221.447332 -67.433976 \n", "L 221.866356 -67.397579 \n", "L 222.28538 -67.35976 \n", "L 222.704403 -67.320527 \n", "L 223.123428 -67.279885 \n", "L 223.542451 -67.237842 \n", "L 223.961474 -67.194409 \n", "L 224.380499 -67.149592 \n", "L 224.799522 -67.103401 \n", "L 225.218546 -67.055845 \n", "L 225.63757 -67.006927 \n", "L 226.056594 -66.956669 \n", "L 226.475617 -66.905066 \n", "L 226.894642 -66.852141 \n", "L 227.313665 -66.797896 \n", "L 227.732688 -66.742342 \n", "L 228.151713 -66.685495 \n", "L 228.570736 -66.62736 \n", "L 228.989761 -66.567949 \n", "L 229.408784 -66.507276 \n", "L 229.827808 -66.445347 \n", "L 230.246833 -66.382177 \n", "L 230.665856 -66.31778 \n", "L 231.084879 -66.252163 \n", "L 231.503903 -66.185344 \n", "L 231.922926 -66.117326 \n", "L 232.341951 -66.048131 \n", "L 232.760974 -65.977769 \n", "L 232.760974 -37.55625 \n", "L 232.760974 -37.55625 \n", "L 232.341951 -37.55625 \n", "L 231.922926 -37.55625 \n", "L 231.503903 -37.55625 \n", "L 231.084879 -37.55625 \n", "L 230.665856 -37.55625 \n", "L 230.246833 -37.55625 \n", "L 229.827808 -37.55625 \n", "L 229.408784 -37.55625 \n", "L 228.989761 -37.55625 \n", "L 228.570736 -37.55625 \n", "L 228.151713 -37.55625 \n", "L 227.732688 -37.55625 \n", "L 227.313665 -37.55625 \n", "L 226.894642 -37.55625 \n", "L 226.475617 -37.55625 \n", "L 226.056594 -37.55625 \n", "L 225.63757 -37.55625 \n", "L 225.218546 -37.55625 \n", "L 224.799522 -37.55625 \n", "L 224.380499 -37.55625 \n", "L 223.961474 -37.55625 \n", "L 223.542451 -37.55625 \n", "L 223.123428 -37.55625 \n", "L 222.704403 -37.55625 \n", "L 222.28538 -37.55625 \n", "L 221.866356 -37.55625 \n", "L 221.447332 -37.55625 \n", "L 221.028308 -37.55625 \n", "L 220.609285 -37.55625 \n", "L 220.190261 -37.55625 \n", "L 219.771237 -37.55625 \n", "L 219.352213 -37.55625 \n", "L 218.933189 -37.55625 \n", "L 218.514166 -37.55625 \n", "L 218.095142 -37.55625 \n", "L 217.676118 -37.55625 \n", "L 217.257095 -37.55625 \n", "L 216.838071 -37.55625 \n", "L 216.419047 -37.55625 \n", "L 216.000023 -37.55625 \n", "L 215.581 -37.55625 \n", "L 215.161976 -37.55625 \n", "L 214.742952 -37.55625 \n", "L 214.323928 -37.55625 \n", "L 213.904904 -37.55625 \n", "L 213.485881 -37.55625 \n", "L 213.066857 -37.55625 \n", "L 212.647833 -37.55625 \n", "L 212.228809 -37.55625 \n", "L 211.809785 -37.55625 \n", "L 211.390762 -37.55625 \n", "z\n", "\" style=\"stroke: #9467bd; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#p1f674292d2)\">\n", " <use xlink:href=\"#m2650d80dd3\" x=\"0\" y=\"226.194375\" style=\"fill: #9467bd; fill-opacity: 0.5; stroke: #9467bd; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_6\">\n", " <defs>\n", " <path id=\"m81cedd8bc8\" d=\"M 233.179997 -37.55625 \n", "L 233.179997 -47.006249 \n", "L 233.599021 -46.982028 \n", "L 234.018044 -46.957432 \n", "L 234.43707 -46.932463 \n", "L 234.856093 -46.907126 \n", "L 235.275117 -46.881426 \n", "L 235.69414 -46.855367 \n", "L 236.113164 -46.828955 \n", "L 236.532189 -46.802195 \n", "L 236.951213 -46.775087 \n", "L 237.370236 -46.747642 \n", "L 237.78926 -46.719861 \n", "L 238.208283 -46.691749 \n", "L 238.627306 -46.663313 \n", "L 239.04633 -46.634555 \n", "L 239.465353 -46.605481 \n", "L 239.884379 -46.576098 \n", "L 240.303402 -46.546407 \n", "L 240.722426 -46.516416 \n", "L 241.141449 -46.486129 \n", "L 241.560475 -46.455551 \n", "L 241.979498 -46.424687 \n", "L 242.398522 -46.393543 \n", "L 242.817545 -46.362123 \n", "L 243.236571 -46.330432 \n", "L 243.655594 -46.298475 \n", "L 244.074618 -46.266257 \n", "L 244.493641 -46.233786 \n", "L 244.912665 -46.201064 \n", "L 245.331688 -46.168096 \n", "L 245.750711 -46.134889 \n", "L 246.169735 -46.101447 \n", "L 246.588761 -46.067775 \n", "L 247.007784 -46.033878 \n", "L 247.426807 -45.999762 \n", "L 247.845831 -45.965433 \n", "L 248.264854 -45.930895 \n", "L 248.683877 -45.896153 \n", "L 249.102901 -45.861211 \n", "L 249.521924 -45.826077 \n", "L 249.94095 -45.790754 \n", "L 250.359973 -45.755248 \n", "L 250.778997 -45.719564 \n", "L 251.19802 -45.683707 \n", "L 251.617044 -45.647681 \n", "L 252.036067 -45.611494 \n", "L 252.45509 -45.575148 \n", "L 252.874114 -45.538649 \n", "L 253.29314 -45.502003 \n", "L 253.712163 -45.465213 \n", "L 254.131186 -45.428286 \n", "L 254.55021 -45.391226 \n", "L 254.969233 -45.354039 \n", "L 255.388257 -45.316728 \n", "L 255.80728 -45.2793 \n", "L 256.226303 -45.241757 \n", "L 256.645327 -45.204107 \n", "L 257.06435 -45.166353 \n", "L 257.06435 -37.55625 \n", "L 257.06435 -37.55625 \n", "L 256.645327 -37.55625 \n", "L 256.226303 -37.55625 \n", "L 255.80728 -37.55625 \n", "L 255.388257 -37.55625 \n", "L 254.969233 -37.55625 \n", "L 254.55021 -37.55625 \n", "L 254.131186 -37.55625 \n", "L 253.712163 -37.55625 \n", "L 253.29314 -37.55625 \n", "L 252.874114 -37.55625 \n", "L 252.45509 -37.55625 \n", "L 252.036067 -37.55625 \n", "L 251.617044 -37.55625 \n", "L 251.19802 -37.55625 \n", "L 250.778997 -37.55625 \n", "L 250.359973 -37.55625 \n", "L 249.94095 -37.55625 \n", "L 249.521924 -37.55625 \n", "L 249.102901 -37.55625 \n", "L 248.683877 -37.55625 \n", "L 248.264854 -37.55625 \n", "L 247.845831 -37.55625 \n", "L 247.426807 -37.55625 \n", "L 247.007784 -37.55625 \n", "L 246.588761 -37.55625 \n", "L 246.169735 -37.55625 \n", "L 245.750711 -37.55625 \n", "L 245.331688 -37.55625 \n", "L 244.912665 -37.55625 \n", "L 244.493641 -37.55625 \n", "L 244.074618 -37.55625 \n", "L 243.655594 -37.55625 \n", "L 243.236571 -37.55625 \n", "L 242.817545 -37.55625 \n", "L 242.398522 -37.55625 \n", "L 241.979498 -37.55625 \n", "L 241.560475 -37.55625 \n", "L 241.141449 -37.55625 \n", "L 240.722426 -37.55625 \n", "L 240.303402 -37.55625 \n", "L 239.884379 -37.55625 \n", "L 239.465353 -37.55625 \n", "L 239.04633 -37.55625 \n", "L 238.627306 -37.55625 \n", "L 238.208283 -37.55625 \n", "L 237.78926 -37.55625 \n", "L 237.370236 -37.55625 \n", "L 236.951213 -37.55625 \n", "L 236.532189 -37.55625 \n", "L 236.113164 -37.55625 \n", "L 235.69414 -37.55625 \n", "L 235.275117 -37.55625 \n", "L 234.856093 -37.55625 \n", "L 234.43707 -37.55625 \n", "L 234.018044 -37.55625 \n", "L 233.599021 -37.55625 \n", "L 233.179997 -37.55625 \n", "z\n", "\" style=\"stroke: #8c564b; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#p1f674292d2)\">\n", " <use xlink:href=\"#m81cedd8bc8\" x=\"0\" y=\"226.194375\" style=\"fill: #8c564b; fill-opacity: 0.5; stroke: #8c564b; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_7\">\n", " <defs>\n", " <path id=\"mc97384097f\" d=\"M 257.483373 -37.55625 \n", "L 257.483373 -41.342375 \n", "L 257.902402 -41.323401 \n", "L 258.321425 -41.304383 \n", "L 258.740449 -41.285323 \n", "L 259.159472 -41.266223 \n", "L 259.578495 -41.247084 \n", "L 259.997519 -41.227911 \n", "L 260.416542 -41.208704 \n", "L 260.835565 -41.189467 \n", "L 261.254594 -41.1702 \n", "L 261.673617 -41.150908 \n", "L 262.092641 -41.131591 \n", "L 262.511664 -41.112252 \n", "L 262.930687 -41.092893 \n", "L 263.349711 -41.073517 \n", "L 263.768734 -41.054125 \n", "L 264.187757 -41.034719 \n", "L 264.606786 -41.015302 \n", "L 265.025804 -40.995875 \n", "L 265.444828 -40.976442 \n", "L 265.863851 -40.957003 \n", "L 266.282874 -40.93756 \n", "L 266.701898 -40.918116 \n", "L 267.120921 -40.898673 \n", "L 267.539945 -40.879233 \n", "L 267.958973 -40.859796 \n", "L 268.377996 -40.840366 \n", "L 268.79702 -40.820944 \n", "L 269.216043 -40.801533 \n", "L 269.635066 -40.782133 \n", "L 270.05409 -40.762746 \n", "L 270.473113 -40.743375 \n", "L 270.892137 -40.724021 \n", "L 271.311165 -40.704686 \n", "L 271.730188 -40.685372 \n", "L 272.149212 -40.666079 \n", "L 272.568235 -40.64681 \n", "L 272.987258 -40.627567 \n", "L 273.406282 -40.608351 \n", "L 273.825305 -40.589163 \n", "L 274.244329 -40.570006 \n", "L 274.663357 -40.55088 \n", "L 275.082375 -40.531788 \n", "L 275.501399 -40.51273 \n", "L 275.920422 -40.493708 \n", "L 276.339445 -40.474724 \n", "L 276.758469 -40.455778 \n", "L 277.177492 -40.436873 \n", "L 277.596516 -40.41801 \n", "L 278.015544 -40.399189 \n", "L 278.434567 -40.380413 \n", "L 278.853591 -40.361683 \n", "L 279.272614 -40.342999 \n", "L 279.691638 -40.324364 \n", "L 280.110661 -40.305778 \n", "L 280.529684 -40.287242 \n", "L 280.948708 -40.268758 \n", "L 281.367736 -40.250326 \n", "L 281.786754 -40.231949 \n", "L 282.205778 -40.213626 \n", "L 282.624801 -40.19536 \n", "L 283.043825 -40.17715 \n", "L 283.462848 -40.158999 \n", "L 283.881871 -40.140907 \n", "L 284.300895 -40.122875 \n", "L 284.719923 -40.104904 \n", "L 285.138946 -40.086995 \n", "L 285.55797 -40.069149 \n", "L 285.976993 -40.051367 \n", "L 286.396017 -40.033649 \n", "L 286.81504 -40.015997 \n", "L 287.234063 -39.998411 \n", "L 287.653087 -39.980892 \n", "L 288.072115 -39.963442 \n", "L 288.491138 -39.94606 \n", "L 288.910162 -39.928747 \n", "L 289.329185 -39.911504 \n", "L 289.748209 -39.894332 \n", "L 290.167232 -39.877232 \n", "L 290.586255 -39.860204 \n", "L 291.005279 -39.843249 \n", "L 291.424307 -39.826366 \n", "L 291.843326 -39.809558 \n", "L 292.262349 -39.792825 \n", "L 292.681372 -39.776167 \n", "L 292.681372 -37.55625 \n", "L 292.681372 -37.55625 \n", "L 292.262349 -37.55625 \n", "L 291.843326 -37.55625 \n", "L 291.424307 -37.55625 \n", "L 291.005279 -37.55625 \n", "L 290.586255 -37.55625 \n", "L 290.167232 -37.55625 \n", "L 289.748209 -37.55625 \n", "L 289.329185 -37.55625 \n", "L 288.910162 -37.55625 \n", "L 288.491138 -37.55625 \n", "L 288.072115 -37.55625 \n", "L 287.653087 -37.55625 \n", "L 287.234063 -37.55625 \n", "L 286.81504 -37.55625 \n", "L 286.396017 -37.55625 \n", "L 285.976993 -37.55625 \n", "L 285.55797 -37.55625 \n", "L 285.138946 -37.55625 \n", "L 284.719923 -37.55625 \n", "L 284.300895 -37.55625 \n", "L 283.881871 -37.55625 \n", "L 283.462848 -37.55625 \n", "L 283.043825 -37.55625 \n", "L 282.624801 -37.55625 \n", "L 282.205778 -37.55625 \n", "L 281.786754 -37.55625 \n", "L 281.367736 -37.55625 \n", "L 280.948708 -37.55625 \n", "L 280.529684 -37.55625 \n", "L 280.110661 -37.55625 \n", "L 279.691638 -37.55625 \n", "L 279.272614 -37.55625 \n", "L 278.853591 -37.55625 \n", "L 278.434567 -37.55625 \n", "L 278.015544 -37.55625 \n", "L 277.596516 -37.55625 \n", "L 277.177492 -37.55625 \n", "L 276.758469 -37.55625 \n", "L 276.339445 -37.55625 \n", "L 275.920422 -37.55625 \n", "L 275.501399 -37.55625 \n", "L 275.082375 -37.55625 \n", "L 274.663357 -37.55625 \n", "L 274.244329 -37.55625 \n", "L 273.825305 -37.55625 \n", "L 273.406282 -37.55625 \n", "L 272.987258 -37.55625 \n", "L 272.568235 -37.55625 \n", "L 272.149212 -37.55625 \n", "L 271.730188 -37.55625 \n", "L 271.311165 -37.55625 \n", "L 270.892137 -37.55625 \n", "L 270.473113 -37.55625 \n", "L 270.05409 -37.55625 \n", "L 269.635066 -37.55625 \n", "L 269.216043 -37.55625 \n", "L 268.79702 -37.55625 \n", "L 268.377996 -37.55625 \n", "L 267.958973 -37.55625 \n", "L 267.539945 -37.55625 \n", "L 267.120921 -37.55625 \n", "L 266.701898 -37.55625 \n", "L 266.282874 -37.55625 \n", "L 265.863851 -37.55625 \n", "L 265.444828 -37.55625 \n", "L 265.025804 -37.55625 \n", "L 264.606786 -37.55625 \n", "L 264.187757 -37.55625 \n", "L 263.768734 -37.55625 \n", "L 263.349711 -37.55625 \n", "L 262.930687 -37.55625 \n", "L 262.511664 -37.55625 \n", "L 262.092641 -37.55625 \n", "L 261.673617 -37.55625 \n", "L 261.254594 -37.55625 \n", "L 260.835565 -37.55625 \n", "L 260.416542 -37.55625 \n", "L 259.997519 -37.55625 \n", "L 259.578495 -37.55625 \n", "L 259.159472 -37.55625 \n", "L 258.740449 -37.55625 \n", "L 258.321425 -37.55625 \n", "L 257.902402 -37.55625 \n", "L 257.483373 -37.55625 \n", "z\n", "\" style=\"stroke: #e377c2; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#p1f674292d2)\">\n", " <use xlink:href=\"#mc97384097f\" x=\"0\" y=\"226.194375\" style=\"fill: #e377c2; fill-opacity: 0.5; stroke: #e377c2; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"PolyCollection_8\">\n", " <defs>\n", " <path id=\"mded17763ad\" d=\"M 293.100396 -37.55625 \n", "L 293.100396 -39.759584 \n", "L 293.519419 -39.743078 \n", "L 293.938442 -39.726647 \n", "L 294.357466 -39.710295 \n", "L 294.776494 -39.69402 \n", "L 295.195518 -39.677823 \n", "L 295.614541 -39.661704 \n", "L 296.033564 -39.645665 \n", "L 296.452588 -39.629705 \n", "L 296.871611 -39.613824 \n", "L 297.290634 -39.598024 \n", "L 297.709658 -39.582303 \n", "L 298.128681 -39.566664 \n", "L 298.547705 -39.551106 \n", "L 298.966728 -39.535629 \n", "L 299.385751 -39.520233 \n", "L 299.804775 -39.50492 \n", "L 300.223798 -39.489688 \n", "L 300.642821 -39.474539 \n", "L 301.061845 -39.459473 \n", "L 301.480868 -39.444489 \n", "L 301.899902 -39.429587 \n", "L 302.318925 -39.41477 \n", "L 302.737948 -39.400036 \n", "L 303.156972 -39.385385 \n", "L 303.575995 -39.370817 \n", "L 303.995018 -39.356333 \n", "L 304.414042 -39.341934 \n", "L 304.833065 -39.327618 \n", "L 305.252089 -39.313386 \n", "L 305.671112 -39.299237 \n", "L 306.090135 -39.285174 \n", "L 306.509159 -39.271194 \n", "L 306.928182 -39.257298 \n", "L 307.347206 -39.243487 \n", "L 307.766229 -39.22976 \n", "L 308.185252 -39.216116 \n", "L 308.604276 -39.202557 \n", "L 309.023299 -39.189082 \n", "L 309.442322 -39.175692 \n", "L 309.861346 -39.162386 \n", "L 310.280369 -39.149163 \n", "L 310.699393 -39.136024 \n", "L 311.118416 -39.12297 \n", "L 311.537439 -39.109998 \n", "L 311.956473 -39.097111 \n", "L 312.375496 -39.084307 \n", "L 312.794519 -39.071587 \n", "L 313.213543 -39.05895 \n", "L 313.632566 -39.046397 \n", "L 314.05159 -39.033926 \n", "L 314.470613 -39.021538 \n", "L 314.889636 -39.009234 \n", "L 315.30866 -38.997011 \n", "L 315.727683 -38.984872 \n", "L 316.146706 -38.972814 \n", "L 316.56573 -38.960839 \n", "L 316.984753 -38.948945 \n", "L 317.403777 -38.937133 \n", "L 317.8228 -38.925403 \n", "L 318.241823 -38.913753 \n", "L 318.660847 -38.902185 \n", "L 319.07987 -38.890698 \n", "L 319.498894 -38.879291 \n", "L 319.917917 -38.867965 \n", "L 320.33694 -38.856718 \n", "L 320.755964 -38.845552 \n", "L 321.174987 -38.834465 \n", "L 321.59401 -38.823457 \n", "L 322.013044 -38.812528 \n", "L 322.432067 -38.801678 \n", "L 322.851091 -38.790907 \n", "L 323.270114 -38.780214 \n", "L 323.689137 -38.769598 \n", "L 324.108161 -38.759061 \n", "L 324.527184 -38.7486 \n", "L 324.946207 -38.738217 \n", "L 325.365231 -38.727911 \n", "L 325.784254 -38.71768 \n", "L 326.203278 -38.707526 \n", "L 326.622301 -38.697448 \n", "L 327.041324 -38.687445 \n", "L 327.460348 -38.677517 \n", "L 327.879371 -38.667664 \n", "L 328.298394 -38.657886 \n", "L 328.717418 -38.648182 \n", "L 329.136441 -38.638551 \n", "L 329.555465 -38.628994 \n", "L 329.974488 -38.61951 \n", "L 330.393511 -38.610098 \n", "L 330.812535 -38.60076 \n", "L 331.231558 -38.591493 \n", "L 331.650582 -38.582298 \n", "L 332.069615 -38.573174 \n", "L 332.488638 -38.564121 \n", "L 332.907662 -38.555139 \n", "L 333.326685 -38.546227 \n", "L 333.745708 -38.537385 \n", "L 334.164732 -38.528612 \n", "L 334.583755 -38.519909 \n", "L 335.002779 -38.511274 \n", "L 335.421802 -38.502708 \n", "L 335.840825 -38.49421 \n", "L 336.259849 -38.48578 \n", "L 336.678872 -38.477417 \n", "L 337.097895 -38.469121 \n", "L 337.516919 -38.460891 \n", "L 337.935942 -38.452728 \n", "L 338.354966 -38.44463 \n", "L 338.773989 -38.436598 \n", "L 339.193012 -38.42863 \n", "L 339.612036 -38.420728 \n", "L 340.031059 -38.412889 \n", "L 340.450082 -38.405115 \n", "L 340.869106 -38.397404 \n", "L 341.288129 -38.389756 \n", "L 341.707153 -38.382171 \n", "L 342.126176 -38.374648 \n", "L 342.545199 -38.367187 \n", "L 342.964223 -38.359788 \n", "L 343.383246 -38.35245 \n", "L 343.80227 -38.345173 \n", "L 344.221293 -38.337956 \n", "L 344.640316 -38.330799 \n", "L 345.05934 -38.323702 \n", "L 345.478373 -38.316663 \n", "L 345.897396 -38.309684 \n", "L 346.31642 -38.302764 \n", "L 346.735443 -38.295901 \n", "L 347.154467 -38.289096 \n", "L 347.57349 -38.282349 \n", "L 347.992513 -38.275658 \n", "L 348.411537 -38.269024 \n", "L 348.83056 -38.262447 \n", "L 349.249583 -38.255925 \n", "L 349.668607 -38.249458 \n", "L 350.08763 -38.243047 \n", "L 350.506654 -38.23669 \n", "L 350.925677 -38.230388 \n", "L 351.3447 -38.224139 \n", "L 351.763724 -38.217944 \n", "L 352.182747 -38.211802 \n", "L 352.60177 -38.205713 \n", "L 353.020794 -38.199677 \n", "L 353.439817 -38.193692 \n", "L 353.858841 -38.187759 \n", "L 354.277864 -38.181877 \n", "L 354.696887 -38.176047 \n", "L 355.115911 -38.170267 \n", "L 355.534944 -38.164537 \n", "L 355.953968 -38.158857 \n", "L 356.372991 -38.153226 \n", "L 356.792014 -38.147645 \n", "L 357.211038 -38.142112 \n", "L 357.630061 -38.136628 \n", "L 358.049084 -38.131191 \n", "L 358.468108 -38.125803 \n", "L 358.887131 -38.120462 \n", "L 359.306155 -38.115167 \n", "L 359.725178 -38.10992 \n", "L 360.144201 -38.104718 \n", "L 360.563225 -38.099563 \n", "L 360.982248 -38.094453 \n", "L 361.401271 -38.089388 \n", "L 361.820295 -38.084368 \n", "L 362.239318 -38.079393 \n", "L 362.658342 -38.074462 \n", "L 363.077365 -38.069575 \n", "L 363.496388 -38.064731 \n", "L 363.915412 -38.05993 \n", "L 364.334435 -38.055173 \n", "L 364.753458 -38.050457 \n", "L 365.172482 -38.045784 \n", "L 365.591515 -38.041153 \n", "L 366.010539 -38.036563 \n", "L 366.429562 -38.032015 \n", "L 366.848585 -38.027507 \n", "L 367.267609 -38.02304 \n", "L 367.686632 -38.018613 \n", "L 368.105656 -38.014226 \n", "L 368.524679 -38.009878 \n", "L 368.943702 -38.00557 \n", "L 369.362726 -38.001301 \n", "L 369.781749 -37.99707 \n", "L 370.200772 -37.992878 \n", "L 370.619796 -37.988723 \n", "L 371.038819 -37.984607 \n", "L 371.457843 -37.980527 \n", "L 371.876866 -37.976485 \n", "L 372.295889 -37.97248 \n", "L 372.714913 -37.968511 \n", "L 373.133936 -37.964578 \n", "L 373.552959 -37.960681 \n", "L 373.971983 -37.95682 \n", "L 374.391006 -37.952994 \n", "L 374.81003 -37.949203 \n", "L 375.229053 -37.945446 \n", "L 375.648086 -37.941725 \n", "L 376.06711 -37.938037 \n", "L 376.486133 -37.934383 \n", "L 376.905156 -37.930763 \n", "L 377.32418 -37.927176 \n", "L 377.743203 -37.923622 \n", "L 378.162227 -37.9201 \n", "L 378.58125 -37.916611 \n", "L 378.58125 -37.55625 \n", "L 378.58125 -37.55625 \n", "L 378.162227 -37.55625 \n", "L 377.743203 -37.55625 \n", "L 377.32418 -37.55625 \n", "L 376.905156 -37.55625 \n", "L 376.486133 -37.55625 \n", "L 376.06711 -37.55625 \n", "L 375.648086 -37.55625 \n", "L 375.229053 -37.55625 \n", "L 374.81003 -37.55625 \n", "L 374.391006 -37.55625 \n", "L 373.971983 -37.55625 \n", "L 373.552959 -37.55625 \n", "L 373.133936 -37.55625 \n", "L 372.714913 -37.55625 \n", "L 372.295889 -37.55625 \n", "L 371.876866 -37.55625 \n", "L 371.457843 -37.55625 \n", "L 371.038819 -37.55625 \n", "L 370.619796 -37.55625 \n", "L 370.200772 -37.55625 \n", "L 369.781749 -37.55625 \n", "L 369.362726 -37.55625 \n", "L 368.943702 -37.55625 \n", "L 368.524679 -37.55625 \n", "L 368.105656 -37.55625 \n", "L 367.686632 -37.55625 \n", "L 367.267609 -37.55625 \n", "L 366.848585 -37.55625 \n", "L 366.429562 -37.55625 \n", "L 366.010539 -37.55625 \n", "L 365.591515 -37.55625 \n", "L 365.172482 -37.55625 \n", "L 364.753458 -37.55625 \n", "L 364.334435 -37.55625 \n", "L 363.915412 -37.55625 \n", "L 363.496388 -37.55625 \n", "L 363.077365 -37.55625 \n", "L 362.658342 -37.55625 \n", "L 362.239318 -37.55625 \n", "L 361.820295 -37.55625 \n", "L 361.401271 -37.55625 \n", "L 360.982248 -37.55625 \n", "L 360.563225 -37.55625 \n", "L 360.144201 -37.55625 \n", "L 359.725178 -37.55625 \n", "L 359.306155 -37.55625 \n", "L 358.887131 -37.55625 \n", "L 358.468108 -37.55625 \n", "L 358.049084 -37.55625 \n", "L 357.630061 -37.55625 \n", "L 357.211038 -37.55625 \n", "L 356.792014 -37.55625 \n", "L 356.372991 -37.55625 \n", "L 355.953968 -37.55625 \n", "L 355.534944 -37.55625 \n", "L 355.115911 -37.55625 \n", "L 354.696887 -37.55625 \n", "L 354.277864 -37.55625 \n", "L 353.858841 -37.55625 \n", "L 353.439817 -37.55625 \n", "L 353.020794 -37.55625 \n", "L 352.60177 -37.55625 \n", "L 352.182747 -37.55625 \n", "L 351.763724 -37.55625 \n", "L 351.3447 -37.55625 \n", "L 350.925677 -37.55625 \n", "L 350.506654 -37.55625 \n", "L 350.08763 -37.55625 \n", "L 349.668607 -37.55625 \n", "L 349.249583 -37.55625 \n", "L 348.83056 -37.55625 \n", "L 348.411537 -37.55625 \n", "L 347.992513 -37.55625 \n", "L 347.57349 -37.55625 \n", "L 347.154467 -37.55625 \n", "L 346.735443 -37.55625 \n", "L 346.31642 -37.55625 \n", "L 345.897396 -37.55625 \n", "L 345.478373 -37.55625 \n", "L 345.05934 -37.55625 \n", "L 344.640316 -37.55625 \n", "L 344.221293 -37.55625 \n", "L 343.80227 -37.55625 \n", "L 343.383246 -37.55625 \n", "L 342.964223 -37.55625 \n", "L 342.545199 -37.55625 \n", "L 342.126176 -37.55625 \n", "L 341.707153 -37.55625 \n", "L 341.288129 -37.55625 \n", "L 340.869106 -37.55625 \n", "L 340.450082 -37.55625 \n", "L 340.031059 -37.55625 \n", "L 339.612036 -37.55625 \n", "L 339.193012 -37.55625 \n", "L 338.773989 -37.55625 \n", "L 338.354966 -37.55625 \n", "L 337.935942 -37.55625 \n", "L 337.516919 -37.55625 \n", "L 337.097895 -37.55625 \n", "L 336.678872 -37.55625 \n", "L 336.259849 -37.55625 \n", "L 335.840825 -37.55625 \n", "L 335.421802 -37.55625 \n", "L 335.002779 -37.55625 \n", "L 334.583755 -37.55625 \n", "L 334.164732 -37.55625 \n", "L 333.745708 -37.55625 \n", "L 333.326685 -37.55625 \n", "L 332.907662 -37.55625 \n", "L 332.488638 -37.55625 \n", "L 332.069615 -37.55625 \n", "L 331.650582 -37.55625 \n", "L 331.231558 -37.55625 \n", "L 330.812535 -37.55625 \n", "L 330.393511 -37.55625 \n", "L 329.974488 -37.55625 \n", "L 329.555465 -37.55625 \n", "L 329.136441 -37.55625 \n", "L 328.717418 -37.55625 \n", "L 328.298394 -37.55625 \n", "L 327.879371 -37.55625 \n", "L 327.460348 -37.55625 \n", "L 327.041324 -37.55625 \n", "L 326.622301 -37.55625 \n", "L 326.203278 -37.55625 \n", "L 325.784254 -37.55625 \n", "L 325.365231 -37.55625 \n", "L 324.946207 -37.55625 \n", "L 324.527184 -37.55625 \n", "L 324.108161 -37.55625 \n", "L 323.689137 -37.55625 \n", "L 323.270114 -37.55625 \n", "L 322.851091 -37.55625 \n", "L 322.432067 -37.55625 \n", "L 322.013044 -37.55625 \n", "L 321.59401 -37.55625 \n", "L 321.174987 -37.55625 \n", "L 320.755964 -37.55625 \n", "L 320.33694 -37.55625 \n", "L 319.917917 -37.55625 \n", "L 319.498894 -37.55625 \n", "L 319.07987 -37.55625 \n", "L 318.660847 -37.55625 \n", "L 318.241823 -37.55625 \n", "L 317.8228 -37.55625 \n", "L 317.403777 -37.55625 \n", "L 316.984753 -37.55625 \n", "L 316.56573 -37.55625 \n", "L 316.146706 -37.55625 \n", "L 315.727683 -37.55625 \n", "L 315.30866 -37.55625 \n", "L 314.889636 -37.55625 \n", "L 314.470613 -37.55625 \n", "L 314.05159 -37.55625 \n", "L 313.632566 -37.55625 \n", "L 313.213543 -37.55625 \n", "L 312.794519 -37.55625 \n", "L 312.375496 -37.55625 \n", "L 311.956473 -37.55625 \n", "L 311.537439 -37.55625 \n", "L 311.118416 -37.55625 \n", "L 310.699393 -37.55625 \n", "L 310.280369 -37.55625 \n", "L 309.861346 -37.55625 \n", "L 309.442322 -37.55625 \n", "L 309.023299 -37.55625 \n", "L 308.604276 -37.55625 \n", "L 308.185252 -37.55625 \n", "L 307.766229 -37.55625 \n", "L 307.347206 -37.55625 \n", "L 306.928182 -37.55625 \n", "L 306.509159 -37.55625 \n", "L 306.090135 -37.55625 \n", "L 305.671112 -37.55625 \n", "L 305.252089 -37.55625 \n", "L 304.833065 -37.55625 \n", "L 304.414042 -37.55625 \n", "L 303.995018 -37.55625 \n", "L 303.575995 -37.55625 \n", "L 303.156972 -37.55625 \n", "L 302.737948 -37.55625 \n", "L 302.318925 -37.55625 \n", "L 301.899902 -37.55625 \n", "L 301.480868 -37.55625 \n", "L 301.061845 -37.55625 \n", "L 300.642821 -37.55625 \n", "L 300.223798 -37.55625 \n", "L 299.804775 -37.55625 \n", "L 299.385751 -37.55625 \n", "L 298.966728 -37.55625 \n", "L 298.547705 -37.55625 \n", "L 298.128681 -37.55625 \n", "L 297.709658 -37.55625 \n", "L 297.290634 -37.55625 \n", "L 296.871611 -37.55625 \n", "L 296.452588 -37.55625 \n", "L 296.033564 -37.55625 \n", "L 295.614541 -37.55625 \n", "L 295.195518 -37.55625 \n", "L 294.776494 -37.55625 \n", "L 294.357466 -37.55625 \n", "L 293.938442 -37.55625 \n", "L 293.519419 -37.55625 \n", "L 293.100396 -37.55625 \n", "z\n", "\" style=\"stroke: #7f7f7f; stroke-opacity: 0.5\"/>\n", " </defs>\n", " <g clip-path=\"url(#p1f674292d2)\">\n", " <use xlink:href=\"#mded17763ad\" x=\"0\" y=\"226.194375\" style=\"fill: #7f7f7f; fill-opacity: 0.5; stroke: #7f7f7f; stroke-opacity: 0.5\"/>\n", " </g>\n", " </g>\n", " <g id=\"line2d_1\">\n", " <path d=\"M 43.78125 188.638125 \n", "L 43.78125 186.496696 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #1f77b4; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_2\">\n", " <path d=\"M 129.681123 188.638125 \n", "L 129.681123 175.418124 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #1f77b4; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_3\">\n", " <path d=\"M 130.100146 188.638125 \n", "L 130.100146 153.119465 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #ff7f0e; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_4\">\n", " <path d=\"M 165.298145 188.638125 \n", "L 165.298145 128.060121 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #ff7f0e; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_5\">\n", " <path d=\"M 165.717168 188.638125 \n", "L 165.717168 66.876491 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #2ca02c; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_6\">\n", " <path d=\"M 189.601526 188.638125 \n", "L 189.601526 37.438125 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #2ca02c; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_7\">\n", " <path d=\"M 190.020549 188.638125 \n", "L 190.020549 112.847409 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #d62728; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_8\">\n", " <path d=\"M 210.971738 188.638125 \n", "L 210.971738 107.813393 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #d62728; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_9\">\n", " <path d=\"M 211.390762 188.638125 \n", "L 211.390762 158.328092 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #9467bd; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_10\">\n", " <path d=\"M 232.760974 188.638125 \n", "L 232.760974 160.216606 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #9467bd; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_11\">\n", " <path d=\"M 233.179997 188.638125 \n", "L 233.179997 179.188126 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #8c564b; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_12\">\n", " <path d=\"M 257.06435 188.638125 \n", "L 257.06435 181.028022 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #8c564b; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_13\">\n", " <path d=\"M 257.483373 188.638125 \n", "L 257.483373 184.852 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #e377c2; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_14\">\n", " <path d=\"M 292.681372 188.638125 \n", "L 292.681372 186.418208 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #e377c2; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_15\">\n", " <path d=\"M 293.100396 188.638125 \n", "L 293.100396 186.434791 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #7f7f7f; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_16\">\n", " <path d=\"M 378.58125 188.638125 \n", "L 378.58125 188.277764 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #7f7f7f; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"line2d_17\">\n", " <path d=\"M 43.78125 186.496696 \n", "L 57.190008 185.728708 \n", "L 69.341696 184.813475 \n", "L 80.236314 183.772503 \n", "L 90.292885 182.590899 \n", "L 99.930433 181.230184 \n", "L 109.148957 179.697245 \n", "L 117.948458 178.00992 \n", "L 126.747959 176.101637 \n", "L 129.681123 175.418124 \n", "L 130.100146 153.119465 \n", "L 136.385502 148.999741 \n", "L 143.508909 144.050133 \n", "L 152.308405 137.644128 \n", "L 165.298145 128.060121 \n", "L 165.717168 66.876491 \n", "L 171.583503 58.598815 \n", "L 176.192765 52.453728 \n", "L 180.383002 47.241436 \n", "L 184.154215 42.92512 \n", "L 187.506407 39.435311 \n", "L 189.601526 37.438125 \n", "L 190.020549 112.847409 \n", "L 193.791764 111.273603 \n", "L 197.143953 110.102977 \n", "L 200.496144 109.162099 \n", "L 203.848334 108.462547 \n", "L 207.200524 108.013104 \n", "L 210.13369 107.829552 \n", "L 210.971738 107.813393 \n", "L 211.390762 158.328092 \n", "L 216.419047 158.436948 \n", "L 221.447332 158.760399 \n", "L 226.894642 159.342234 \n", "L 232.341951 160.146244 \n", "L 232.760974 160.216606 \n", "L 233.179997 179.188126 \n", "L 244.074618 179.928118 \n", "L 257.06435 181.028022 \n", "L 257.483373 184.852 \n", "L 303.156972 186.80899 \n", "L 324.946207 187.456158 \n", "L 348.411537 187.925351 \n", "L 376.905156 188.263612 \n", "L 378.58125 188.277764 \n", "L 378.58125 188.277764 \n", "\" clip-path=\"url(#p1f674292d2)\" style=\"fill: none; stroke: #000000; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"patch_3\">\n", " <path d=\"M 43.78125 188.638125 \n", "L 43.78125 22.318125 \n", "\" style=\"fill: none; stroke: #262626; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_4\">\n", " <path d=\"M 378.58125 188.638125 \n", "L 378.58125 22.318125 \n", "\" style=\"fill: none; stroke: #262626; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_5\">\n", " <path d=\"M 43.78125 188.638125 \n", "L 378.58125 188.638125 \n", "\" style=\"fill: none; stroke: #262626; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_6\">\n", " <path d=\"M 43.78125 22.318125 \n", "L 378.58125 22.318125 \n", "\" style=\"fill: none; stroke: #262626; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"text_17\">\n", " <!-- Dequantization distribution for 8 discrete values -->\n", " <g style=\"fill: #262626\" transform=\"translate(66.164062 16.318125) scale(0.12 -0.12)\">\n", " <defs>\n", " <path id=\"DejaVuSans-44\" d=\"M 1259 4147 \n", "L 1259 519 \n", "L 2022 519 \n", "Q 2988 519 3436 956 \n", "Q 3884 1394 3884 2338 \n", "Q 3884 3275 3436 3711 \n", "Q 2988 4147 2022 4147 \n", "L 1259 4147 \n", "z\n", "M 628 4666 \n", "L 1925 4666 \n", "Q 3281 4666 3915 4102 \n", "Q 4550 3538 4550 2338 \n", "Q 4550 1131 3912 565 \n", "Q 3275 0 1925 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-65\" d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-71\" d=\"M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "M 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "L 2906 3500 \n", "L 3481 3500 \n", "L 3481 -1331 \n", "L 2906 -1331 \n", "L 2906 525 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-75\" d=\"M 544 1381 \n", "L 544 3500 \n", "L 1119 3500 \n", "L 1119 1403 \n", "Q 1119 906 1312 657 \n", "Q 1506 409 1894 409 \n", "Q 2359 409 2629 706 \n", "Q 2900 1003 2900 1516 \n", "L 2900 3500 \n", "L 3475 3500 \n", "L 3475 0 \n", "L 2900 0 \n", "L 2900 538 \n", "Q 2691 219 2414 64 \n", "Q 2138 -91 1772 -91 \n", "Q 1169 -91 856 284 \n", "Q 544 659 544 1381 \n", "z\n", "M 1991 3584 \n", "L 1991 3584 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6e\" d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-64\" d=\"M 2906 2969 \n", "L 2906 4863 \n", "L 3481 4863 \n", "L 3481 0 \n", "L 2906 0 \n", "L 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "z\n", "M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-73\" d=\"M 2834 3397 \n", "L 2834 2853 \n", "Q 2591 2978 2328 3040 \n", "Q 2066 3103 1784 3103 \n", "Q 1356 3103 1142 2972 \n", "Q 928 2841 928 2578 \n", "Q 928 2378 1081 2264 \n", "Q 1234 2150 1697 2047 \n", "L 1894 2003 \n", "Q 2506 1872 2764 1633 \n", "Q 3022 1394 3022 966 \n", "Q 3022 478 2636 193 \n", "Q 2250 -91 1575 -91 \n", "Q 1294 -91 989 -36 \n", "Q 684 19 347 128 \n", "L 347 722 \n", "Q 666 556 975 473 \n", "Q 1284 391 1588 391 \n", "Q 1994 391 2212 530 \n", "Q 2431 669 2431 922 \n", "Q 2431 1156 2273 1281 \n", "Q 2116 1406 1581 1522 \n", "L 1381 1569 \n", "Q 847 1681 609 1914 \n", "Q 372 2147 372 2553 \n", "Q 372 3047 722 3315 \n", "Q 1072 3584 1716 3584 \n", "Q 2034 3584 2315 3537 \n", "Q 2597 3491 2834 3397 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-66\" d=\"M 2375 4863 \n", "L 2375 4384 \n", "L 1825 4384 \n", "Q 1516 4384 1395 4259 \n", "Q 1275 4134 1275 3809 \n", "L 1275 3500 \n", "L 2222 3500 \n", "L 2222 3053 \n", "L 1275 3053 \n", "L 1275 0 \n", "L 697 0 \n", "L 697 3053 \n", "L 147 3053 \n", "L 147 3500 \n", "L 697 3500 \n", "L 697 3744 \n", "Q 697 4328 969 4595 \n", "Q 1241 4863 1831 4863 \n", "L 2375 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-63\" d=\"M 3122 3366 \n", "L 3122 2828 \n", "Q 2878 2963 2633 3030 \n", "Q 2388 3097 2138 3097 \n", "Q 1578 3097 1268 2742 \n", "Q 959 2388 959 1747 \n", "Q 959 1106 1268 751 \n", "Q 1578 397 2138 397 \n", "Q 2388 397 2633 464 \n", "Q 2878 531 3122 666 \n", "L 3122 134 \n", "Q 2881 22 2623 -34 \n", "Q 2366 -91 2075 -91 \n", "Q 1284 -91 818 406 \n", "Q 353 903 353 1747 \n", "Q 353 2603 823 3093 \n", "Q 1294 3584 2113 3584 \n", "Q 2378 3584 2631 3529 \n", "Q 2884 3475 3122 3366 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-76\" d=\"M 191 3500 \n", "L 800 3500 \n", "L 1894 563 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2284 0 \n", "L 1503 0 \n", "L 191 3500 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-44\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"77.001953\"/>\n", " <use xlink:href=\"#DejaVuSans-71\" x=\"138.525391\"/>\n", " <use xlink:href=\"#DejaVuSans-75\" x=\"202.001953\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"265.380859\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"326.660156\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"390.039062\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"429.248047\"/>\n", " <use xlink:href=\"#DejaVuSans-7a\" x=\"457.03125\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"509.521484\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"570.800781\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"610.009766\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"637.792969\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"698.974609\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"762.353516\"/>\n", " <use xlink:href=\"#DejaVuSans-64\" x=\"794.140625\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"857.617188\"/>\n", " <use xlink:href=\"#DejaVuSans-73\" x=\"885.400391\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"937.5\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"976.708984\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"1017.822266\"/>\n", " <use xlink:href=\"#DejaVuSans-62\" x=\"1045.605469\"/>\n", " <use xlink:href=\"#DejaVuSans-75\" x=\"1109.082031\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"1172.460938\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"1211.669922\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"1239.453125\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"1300.634766\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"1364.013672\"/>\n", " <use xlink:href=\"#DejaVuSans-66\" x=\"1395.800781\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"1431.005859\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"1492.1875\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"1533.300781\"/>\n", " <use xlink:href=\"#DejaVuSans-38\" x=\"1565.087891\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"1628.710938\"/>\n", " <use xlink:href=\"#DejaVuSans-64\" x=\"1660.498047\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"1723.974609\"/>\n", " <use xlink:href=\"#DejaVuSans-73\" x=\"1751.757812\"/>\n", " <use xlink:href=\"#DejaVuSans-63\" x=\"1803.857422\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"1858.837891\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"1897.701172\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"1959.224609\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"1998.433594\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"2059.957031\"/>\n", " <use xlink:href=\"#DejaVuSans-76\" x=\"2091.744141\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"2150.923828\"/>\n", " <use xlink:href=\"#DejaVuSans-6c\" x=\"2212.203125\"/>\n", " <use xlink:href=\"#DejaVuSans-75\" x=\"2239.986328\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"2303.365234\"/>\n", " <use xlink:href=\"#DejaVuSans-73\" x=\"2364.888672\"/>\n", " </g>\n", " </g>\n", " <g id=\"legend_1\">\n", " <g id=\"patch_7\">\n", " <path d=\"M 333.21875 147.743125 \n", "L 371.58125 147.743125 \n", "Q 373.58125 147.743125 373.58125 145.743125 \n", "L 373.58125 29.318125 \n", "Q 373.58125 27.318125 371.58125 27.318125 \n", "L 333.21875 27.318125 \n", "Q 331.21875 27.318125 331.21875 29.318125 \n", "L 331.21875 145.743125 \n", "Q 331.21875 147.743125 333.21875 147.743125 \n", "z\n", "\" style=\"fill: #ffffff; opacity: 0.8; stroke: #cccccc; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_8\">\n", " <path d=\"M 335.21875 38.916562 \n", "L 355.21875 38.916562 \n", "L 355.21875 31.916562 \n", "L 335.21875 31.916562 \n", "z\n", "\" style=\"fill: #1f77b4; fill-opacity: 0.5; stroke: #1f77b4; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_18\">\n", " <!-- 0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(363.21875 38.916562) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_9\">\n", " <path d=\"M 335.21875 53.594688 \n", "L 355.21875 53.594688 \n", "L 355.21875 46.594688 \n", "L 335.21875 46.594688 \n", "z\n", "\" style=\"fill: #ff7f0e; fill-opacity: 0.5; stroke: #ff7f0e; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_19\">\n", " <!-- 1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(363.21875 53.594688) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_10\">\n", " <path d=\"M 335.21875 68.272812 \n", "L 355.21875 68.272812 \n", "L 355.21875 61.272812 \n", "L 335.21875 61.272812 \n", "z\n", "\" style=\"fill: #2ca02c; fill-opacity: 0.5; stroke: #2ca02c; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_20\">\n", " <!-- 2 -->\n", " <g style=\"fill: #262626\" transform=\"translate(363.21875 68.272812) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-32\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_11\">\n", " <path d=\"M 335.21875 82.950938 \n", "L 355.21875 82.950938 \n", "L 355.21875 75.950938 \n", "L 335.21875 75.950938 \n", "z\n", "\" style=\"fill: #d62728; fill-opacity: 0.5; stroke: #d62728; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_21\">\n", " <!-- 3 -->\n", " <g style=\"fill: #262626\" transform=\"translate(363.21875 82.950938) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-33\" d=\"M 2597 2516 \n", "Q 3050 2419 3304 2112 \n", "Q 3559 1806 3559 1356 \n", "Q 3559 666 3084 287 \n", "Q 2609 -91 1734 -91 \n", "Q 1441 -91 1130 -33 \n", "Q 819 25 488 141 \n", "L 488 750 \n", "Q 750 597 1062 519 \n", "Q 1375 441 1716 441 \n", "Q 2309 441 2620 675 \n", "Q 2931 909 2931 1356 \n", "Q 2931 1769 2642 2001 \n", "Q 2353 2234 1838 2234 \n", "L 1294 2234 \n", "L 1294 2753 \n", "L 1863 2753 \n", "Q 2328 2753 2575 2939 \n", "Q 2822 3125 2822 3475 \n", "Q 2822 3834 2567 4026 \n", "Q 2313 4219 1838 4219 \n", "Q 1578 4219 1281 4162 \n", "Q 984 4106 628 3988 \n", "L 628 4550 \n", "Q 988 4650 1302 4700 \n", "Q 1616 4750 1894 4750 \n", "Q 2613 4750 3031 4423 \n", "Q 3450 4097 3450 3541 \n", "Q 3450 3153 3228 2886 \n", "Q 3006 2619 2597 2516 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-33\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_12\">\n", " <path d=\"M 335.21875 97.629063 \n", "L 355.21875 97.629063 \n", "L 355.21875 90.629063 \n", "L 335.21875 90.629063 \n", "z\n", "\" style=\"fill: #9467bd; fill-opacity: 0.5; stroke: #9467bd; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_22\">\n", " <!-- 4 -->\n", " <g style=\"fill: #262626\" transform=\"translate(363.21875 97.629063) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-34\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_13\">\n", " <path d=\"M 335.21875 112.307187 \n", "L 355.21875 112.307187 \n", "L 355.21875 105.307187 \n", "L 335.21875 105.307187 \n", "z\n", "\" style=\"fill: #8c564b; fill-opacity: 0.5; stroke: #8c564b; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_23\">\n", " <!-- 5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(363.21875 112.307187) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-35\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_14\">\n", " <path d=\"M 335.21875 126.985312 \n", "L 355.21875 126.985312 \n", "L 355.21875 119.985312 \n", "L 335.21875 119.985312 \n", "z\n", "\" style=\"fill: #e377c2; fill-opacity: 0.5; stroke: #e377c2; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_24\">\n", " <!-- 6 -->\n", " <g style=\"fill: #262626\" transform=\"translate(363.21875 126.985312) scale(0.1 -0.1)\">\n", " <use xlink:href=\"#DejaVuSans-36\"/>\n", " </g>\n", " </g>\n", " <g id=\"patch_15\">\n", " <path d=\"M 335.21875 141.663437 \n", "L 355.21875 141.663437 \n", "L 355.21875 134.663437 \n", "L 335.21875 134.663437 \n", "z\n", "\" style=\"fill: #7f7f7f; fill-opacity: 0.5; stroke: #7f7f7f; stroke-opacity: 0.5; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"text_25\">\n", " <!-- 7 -->\n", " <g style=\"fill: #262626\" transform=\"translate(363.21875 141.663437) scale(0.1 -0.1)\">\n", " <defs>\n", " <path id=\"DejaVuSans-37\" d=\"M 525 4666 \n", "L 3525 4666 \n", "L 3525 4397 \n", "L 1831 0 \n", "L 1172 0 \n", "L 2766 4134 \n", "L 525 4134 \n", "L 525 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-37\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p1f674292d2\">\n", " <rect x=\"43.78125\" y=\"22.318125\" width=\"334.8\" height=\"166.32\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 600x300 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["visualize_dequantization(quants=8, prior=np.array([0.075, 0.2, 0.4, 0.2, 0.075, 0.025, 0.0125, 0.0125]))"]}, {"cell_type": "markdown", "id": "b202c9c8", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.015208, "end_time": "2023-03-14T16:08:53.492761", "exception": false, "start_time": "2023-03-14T16:08:53.477553", "status": "completed"}, "tags": []}, "source": ["Transforming such a probability into a Gaussian is a difficult task, especially with such hard borders.\n", "Dequantization has therefore been extended to more sophisticated, learnable distributions beyond uniform in a variational framework.\n", "In particular, if we remember the learning objective\n", "$\\log p(x) = \\log \\mathbb{E}_{u}\\left[\\frac{p(x+u)}{q(u|x)} \\right]$,\n", "the uniform distribution can be replaced by a learned distribution $q_{\\theta}(u|x)$ with support over $u\\in[0,1)^D$.\n", "This approach is called Variational Dequantization and has been proposed by Ho et al.\n", "[3].\n", "How can we learn such a distribution?\n", "We can use a second normalizing flow that takes $x$ as external input and learns a flexible distribution over $u$.\n", "To ensure a support over $[0,1)^D$, we can apply a sigmoid activation function as final flow transformation.\n", "\n", "Inheriting the original dequantization class, we can implement variational dequantization as follows:"]}, {"cell_type": "code", "execution_count": 11, "id": "9977763b", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:53.525421Z", "iopub.status.busy": "2023-03-14T16:08:53.525020Z", "iopub.status.idle": "2023-03-14T16:08:53.536012Z", "shell.execute_reply": "2023-03-14T16:08:53.535528Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.029932, "end_time": "2023-03-14T16:08:53.538205", "exception": false, "start_time": "2023-03-14T16:08:53.508273", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class VariationalDequantization(Dequantization):\n", " def __init__(self, var_flows, alpha=1e-5):\n", " \"\"\"\n", " Args:\n", " var_flows: A list of flow transformations to use for modeling q(u|x)\n", " alpha: Small constant, see Dequantization for details\n", " \"\"\"\n", " super().__init__(alpha=alpha)\n", " self.flows = nn.ModuleList(var_flows)\n", "\n", " def dequant(self, z, ldj):\n", " z = z.to(torch.float32)\n", " img = (z / 255.0) * 2 - 1 # We condition the flows on x, i.e. the original image\n", "\n", " # Prior of u is a uniform distribution as before\n", " # As most flow transformations are defined on [-infinity,+infinity], we apply an inverse sigmoid first.\n", " deq_noise = torch.rand_like(z).detach()\n", " deq_noise, ldj = self.sigmoid(deq_noise, ldj, reverse=True)\n", " for flow in self.flows:\n", " deq_noise, ldj = flow(deq_noise, ldj, reverse=False, orig_img=img)\n", " deq_noise, ldj = self.sigmoid(deq_noise, ldj, reverse=False)\n", "\n", " # After the flows, apply u as in standard dequantization\n", " z = (z + deq_noise) / 256.0\n", " ldj -= np.log(256.0) * np.prod(z.shape[1:])\n", " return z, ldj"]}, {"cell_type": "markdown", "id": "b13b49a8", "metadata": {"papermill": {"duration": 0.014961, "end_time": "2023-03-14T16:08:53.572621", "exception": false, "start_time": "2023-03-14T16:08:53.557660", "status": "completed"}, "tags": []}, "source": ["Variational dequantization can be used as a substitute for dequantization.\n", "We will compare dequantization and variational dequantization in later experiments."]}, {"cell_type": "markdown", "id": "4d25fabd", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.014996, "end_time": "2023-03-14T16:08:53.602877", "exception": false, "start_time": "2023-03-14T16:08:53.587881", "status": "completed"}, "tags": []}, "source": ["### Coupling layers\n", "\n", "<div class=\"center-wrapper\"><div class=\"video-wrapper\"><iframe src=\"https://www.youtube.com/embed/YoAWiaEt41Y\" title=\"YouTube video player\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe></div></div>\n", "\n", "Next, we look at possible transformations to apply inside the flow.\n", "A recent popular flow layer, which works well in combination with deep neural networks,\n", "is the coupling layer introduced by Dinh et al.\n", "[1].\n", "The input $z$ is arbitrarily split into two parts, $z_{1:j}$ and $z_{j+1:d}$, of which the first remains unchanged by the flow.\n", "Yet, $z_{1:j}$ is used to parameterize the transformation for the second part, $z_{j+1:d}$.\n", "Various transformations have been proposed in recent time [3,4], but here we will settle for the simplest and most efficient one: affine coupling.\n", "In this coupling layer, we apply an affine transformation by shifting the input by a bias $\\mu$ and scale it by $\\sigma$.\n", "In other words, our transformation looks as follows:\n", "\n", "$$z'_{j+1:d} = \\mu_{\\theta}(z_{1:j}) + \\sigma_{\\theta}(z_{1:j}) \\odot z_{j+1:d}$$\n", "\n", "The functions $\\mu$ and $\\sigma$ are implemented as a shared neural network,\n", "and the sum and multiplication are performed element-wise.\n", "The LDJ is thereby the sum of the logs of the scaling factors: $\\sum_i \\left[\\log \\sigma_{\\theta}(z_{1:j})\\right]_i$.\n", "Inverting the layer can as simply be done as subtracting the bias and dividing by the scale:\n", "\n", "$$z_{j+1:d} = \\left(z'_{j+1:d} - \\mu_{\\theta}(z_{1:j})\\right) / \\sigma_{\\theta}(z_{1:j})$$\n", "\n", "We can also visualize the coupling layer in form of a computation graph,\n", "where $z_1$ represents $z_{1:j}$, and $z_2$ represents $z_{j+1:d}$:\n", "\n", "<center width=\"100%\" style=\"padding: 10px\"><img src=\"https://github.com/Lightning-AI/lightning-tutorials/raw/main/course_UvA-DL/09-normalizing-flows/coupling_flow.svg\" width=\"450px\"></center>\n", "\n", "In our implementation, we will realize the splitting of variables as masking.\n", "The variables to be transformed, $z_{j+1:d}$, are masked when passing $z$ to the shared network to predict the transformation parameters.\n", "When applying the transformation, we mask the parameters for $z_{1:j}$\n", "so that we have an identity operation for those variables:"]}, {"cell_type": "code", "execution_count": 12, "id": "d18ee4c7", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:53.634921Z", "iopub.status.busy": "2023-03-14T16:08:53.634448Z", "iopub.status.idle": "2023-03-14T16:08:53.647226Z", "shell.execute_reply": "2023-03-14T16:08:53.646704Z"}, "papermill": {"duration": 0.031527, "end_time": "2023-03-14T16:08:53.649422", "exception": false, "start_time": "2023-03-14T16:08:53.617895", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class CouplingLayer(nn.Module):\n", " def __init__(self, network, mask, c_in):\n", " \"\"\"Coupling layer inside a normalizing flow.\n", "\n", " Args:\n", " network: A PyTorch nn.Module constituting the deep neural network for mu and sigma.\n", " Output shape should be twice the channel size as the input.\n", " mask: Binary mask (0 or 1) where 0 denotes that the element should be transformed,\n", " while 1 means the latent will be used as input to the NN.\n", " c_in: Number of input channels\n", " \"\"\"\n", " super().__init__()\n", " self.network = network\n", " self.scaling_factor = nn.Parameter(torch.zeros(c_in))\n", " # Register mask as buffer as it is a tensor which is not a parameter,\n", " # but should be part of the modules state.\n", " self.register_buffer(\"mask\", mask)\n", "\n", " def forward(self, z, ldj, reverse=False, orig_img=None):\n", " \"\"\"\n", " Args:\n", " z: Latent input to the flow\n", " ldj: The current ldj of the previous flows.\n", " The ldj of this layer will be added to this tensor.\n", " reverse: If True, we apply the inverse of the layer.\n", " orig_img (optional): Only needed in VarDeq. Allows external\n", " input to condition the flow on (e.g. original image)\n", " \"\"\"\n", " # Apply network to masked input\n", " z_in = z * self.mask\n", " if orig_img is None:\n", " nn_out = self.network(z_in)\n", " else:\n", " nn_out = self.network(torch.cat([z_in, orig_img], dim=1))\n", " s, t = nn_out.chunk(2, dim=1)\n", "\n", " # Stabilize scaling output\n", " s_fac = self.scaling_factor.exp().view(1, -1, 1, 1)\n", " s = torch.tanh(s / s_fac) * s_fac\n", "\n", " # Mask outputs (only transform the second part)\n", " s = s * (1 - self.mask)\n", " t = t * (1 - self.mask)\n", "\n", " # Affine transformation\n", " if not reverse:\n", " # Whether we first shift and then scale, or the other way round,\n", " # is a design choice, and usually does not have a big impact\n", " z = (z + t) * torch.exp(s)\n", " ldj += s.sum(dim=[1, 2, 3])\n", " else:\n", " z = (z * torch.exp(-s)) - t\n", " ldj -= s.sum(dim=[1, 2, 3])\n", "\n", " return z, ldj"]}, {"cell_type": "markdown", "id": "1e103dac", "metadata": {"papermill": {"duration": 0.014956, "end_time": "2023-03-14T16:08:53.684033", "exception": false, "start_time": "2023-03-14T16:08:53.669077", "status": "completed"}, "tags": []}, "source": ["For stabilization purposes, we apply a $\\tanh$ activation function on the scaling output.\n", "This prevents sudden large output values for the scaling that can destabilize training.\n", "To still allow scaling factors smaller or larger than -1 and 1 respectively,\n", "we have a learnable parameter per dimension, called `scaling_factor`.\n", "This scales the tanh to different limits.\n", "Below, we visualize the effect of the scaling factor on the output activation of the scaling terms:"]}, {"cell_type": "code", "execution_count": 13, "id": "44e8290a", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:53.715799Z", "iopub.status.busy": "2023-03-14T16:08:53.715417Z", "iopub.status.idle": "2023-03-14T16:08:54.573050Z", "shell.execute_reply": "2023-03-14T16:08:54.572427Z"}, "papermill": {"duration": 0.877475, "end_time": "2023-03-14T16:08:54.576709", "exception": false, "start_time": "2023-03-14T16:08:53.699234", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"710.613911pt\" height=\"215.984063pt\" viewBox=\"0 0 710.613911 215.984063\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:08:54.070086</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 215.984063 \n", "L 710.613911 215.984063 \n", "L 710.613911 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g id=\"patch_2\">\n", " <path d=\"M 32.916406 188.638125 \n", "L 209.126933 188.638125 \n", "L 209.126933 22.318125 \n", "L 32.916406 22.318125 \n", "z\n", "\" style=\"fill: #eaeaf2\"/>\n", " </g>\n", " <g id=\"matplotlib.axis_1\">\n", " <g id=\"xtick_1\">\n", " <g id=\"line2d_1\">\n", " <path d=\"M 40.925976 188.638125 \n", "L 40.925976 22.318125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_1\">\n", " <!-- \u22125.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(27.570429 206.496406) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-2212\" d=\"M 678 2272 \n", "L 4684 2272 \n", "L 4684 1741 \n", "L 678 1741 \n", "L 678 2272 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-35\" d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-2e\" d=\"M 684 794 \n", "L 1344 794 \n", "L 1344 0 \n", "L 684 0 \n", "L 684 794 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-30\" d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"83.789062\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"147.412109\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"179.199219\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_2\">\n", " <g id=\"line2d_2\">\n", " <path d=\"M 81.013911 188.638125 \n", "L 81.013911 22.318125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_2\">\n", " <!-- \u22122.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(67.658364 206.496406) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-32\" d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"83.789062\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"147.412109\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"179.199219\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_3\">\n", " <g id=\"line2d_3\">\n", " <path d=\"M 121.101847 188.638125 \n", "L 121.101847 22.318125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_3\">\n", " <!-- 0.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(112.355128 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_4\">\n", " <g id=\"line2d_4\">\n", " <path d=\"M 161.189783 188.638125 \n", "L 161.189783 22.318125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_4\">\n", " <!-- 2.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(152.443064 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-32\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_5\">\n", " <g id=\"line2d_5\">\n", " <path d=\"M 201.277719 188.638125 \n", "L 201.277719 22.318125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_5\">\n", " <!-- 5.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(192.531 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-35\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"matplotlib.axis_2\">\n", " <g id=\"ytick_1\">\n", " <g id=\"line2d_6\">\n", " <path d=\"M 32.916406 188.638125 \n", "L 209.126933 188.638125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_6\">\n", " <!-- \u22123 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 192.817266) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-33\" d=\"M 2597 2516 \n", "Q 3050 2419 3304 2112 \n", "Q 3559 1806 3559 1356 \n", "Q 3559 666 3084 287 \n", "Q 2609 -91 1734 -91 \n", "Q 1441 -91 1130 -33 \n", "Q 819 25 488 141 \n", "L 488 750 \n", "Q 750 597 1062 519 \n", "Q 1375 441 1716 441 \n", "Q 2309 441 2620 675 \n", "Q 2931 909 2931 1356 \n", "Q 2931 1769 2642 2001 \n", "Q 2353 2234 1838 2234 \n", "L 1294 2234 \n", "L 1294 2753 \n", "L 1863 2753 \n", "Q 2328 2753 2575 2939 \n", "Q 2822 3125 2822 3475 \n", "Q 2822 3834 2567 4026 \n", "Q 2313 4219 1838 4219 \n", "Q 1578 4219 1281 4162 \n", "Q 984 4106 628 3988 \n", "L 628 4550 \n", "Q 988 4650 1302 4700 \n", "Q 1616 4750 1894 4750 \n", "Q 2613 4750 3031 4423 \n", "Q 3450 4097 3450 3541 \n", "Q 3450 3153 3228 2886 \n", "Q 3006 2619 2597 2516 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-33\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_2\">\n", " <g id=\"line2d_7\">\n", " <path d=\"M 32.916406 160.918125 \n", "L 209.126933 160.918125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_7\">\n", " <!-- \u22122 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 165.097266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_3\">\n", " <g id=\"line2d_8\">\n", " <path d=\"M 32.916406 133.198125 \n", "L 209.126933 133.198125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_8\">\n", " <!-- \u22121 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 137.377266) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-31\" d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_4\">\n", " <g id=\"line2d_9\">\n", " <path d=\"M 32.916406 105.478125 \n", "L 209.126933 105.478125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_9\">\n", " <!-- 0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(16.417656 109.657266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_5\">\n", " <g id=\"line2d_10\">\n", " <path d=\"M 32.916406 77.758125 \n", "L 209.126933 77.758125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_10\">\n", " <!-- 1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(16.417656 81.937266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_6\">\n", " <g id=\"line2d_11\">\n", " <path d=\"M 32.916406 50.038125 \n", "L 209.126933 50.038125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_11\">\n", " <!-- 2 -->\n", " <g style=\"fill: #262626\" transform=\"translate(16.417656 54.217266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-32\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_7\">\n", " <g id=\"line2d_12\">\n", " <path d=\"M 32.916406 22.318125 \n", "L 209.126933 22.318125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_12\">\n", " <!-- 3 -->\n", " <g style=\"fill: #262626\" transform=\"translate(16.417656 26.497266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-33\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"line2d_13\">\n", " <path d=\"M 40.925976 119.338125 \n", "L 98.973307 119.227526 \n", "L 103.623509 118.988377 \n", "L 106.509838 118.629025 \n", "L 108.594412 118.165853 \n", "L 110.35828 117.559503 \n", "L 111.961797 116.765905 \n", "L 113.404964 115.793803 \n", "L 114.848129 114.52464 \n", "L 116.291295 112.921632 \n", "L 117.73446 110.979581 \n", "L 119.49833 108.213747 \n", "L 124.950289 99.293189 \n", "L 126.553806 97.279666 \n", "L 127.996972 95.827994 \n", "L 129.440137 94.696596 \n", "L 130.883304 93.840518 \n", "L 132.486821 93.148284 \n", "L 134.25069 92.623355 \n", "L 136.495615 92.201391 \n", "L 139.381946 91.905131 \n", "L 143.551091 91.720252 \n", "L 151.408326 91.632556 \n", "L 186.84606 91.618127 \n", "L 201.117363 91.618125 \n", "L 201.117363 91.618125 \n", "\" clip-path=\"url(#p81e22cd740)\" style=\"fill: none; stroke: #4c72b0; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"patch_3\">\n", " <path d=\"M 32.916406 188.638125 \n", "L 32.916406 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_4\">\n", " <path d=\"M 209.126933 188.638125 \n", "L 209.126933 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_5\">\n", " <path d=\"M 32.916406 188.638125 \n", "L 209.126933 188.638125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_6\">\n", " <path d=\"M 32.916406 22.318125 \n", "L 209.126933 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"text_13\">\n", " <!-- Scaling factor: 0.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(66.441357 16.318125) scale(0.12 -0.12)\">\n", " <defs>\n", " <path id=\"DejaVuSans-53\" d=\"M 3425 4513 \n", "L 3425 3897 \n", "Q 3066 4069 2747 4153 \n", "Q 2428 4238 2131 4238 \n", "Q 1616 4238 1336 4038 \n", "Q 1056 3838 1056 3469 \n", "Q 1056 3159 1242 3001 \n", "Q 1428 2844 1947 2747 \n", "L 2328 2669 \n", "Q 3034 2534 3370 2195 \n", "Q 3706 1856 3706 1288 \n", "Q 3706 609 3251 259 \n", "Q 2797 -91 1919 -91 \n", "Q 1588 -91 1214 -16 \n", "Q 841 59 441 206 \n", "L 441 856 \n", "Q 825 641 1194 531 \n", "Q 1563 422 1919 422 \n", "Q 2459 422 2753 634 \n", "Q 3047 847 3047 1241 \n", "Q 3047 1584 2836 1778 \n", "Q 2625 1972 2144 2069 \n", "L 1759 2144 \n", "Q 1053 2284 737 2584 \n", "Q 422 2884 422 3419 \n", "Q 422 4038 858 4394 \n", "Q 1294 4750 2059 4750 \n", "Q 2388 4750 2728 4690 \n", "Q 3069 4631 3425 4513 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-63\" d=\"M 3122 3366 \n", "L 3122 2828 \n", "Q 2878 2963 2633 3030 \n", "Q 2388 3097 2138 3097 \n", "Q 1578 3097 1268 2742 \n", "Q 959 2388 959 1747 \n", "Q 959 1106 1268 751 \n", "Q 1578 397 2138 397 \n", "Q 2388 397 2633 464 \n", "Q 2878 531 3122 666 \n", "L 3122 134 \n", "Q 2881 22 2623 -34 \n", "Q 2366 -91 2075 -91 \n", "Q 1284 -91 818 406 \n", "Q 353 903 353 1747 \n", "Q 353 2603 823 3093 \n", "Q 1294 3584 2113 3584 \n", "Q 2378 3584 2631 3529 \n", "Q 2884 3475 3122 3366 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-61\" d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6c\" d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-69\" d=\"M 603 3500 \n", "L 1178 3500 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 3500 \n", "z\n", "M 603 4863 \n", "L 1178 4863 \n", "L 1178 4134 \n", "L 603 4134 \n", "L 603 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6e\" d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-67\" d=\"M 2906 1791 \n", "Q 2906 2416 2648 2759 \n", "Q 2391 3103 1925 3103 \n", "Q 1463 3103 1205 2759 \n", "Q 947 2416 947 1791 \n", "Q 947 1169 1205 825 \n", "Q 1463 481 1925 481 \n", "Q 2391 481 2648 825 \n", "Q 2906 1169 2906 1791 \n", "z\n", "M 3481 434 \n", "Q 3481 -459 3084 -895 \n", "Q 2688 -1331 1869 -1331 \n", "Q 1566 -1331 1297 -1286 \n", "Q 1028 -1241 775 -1147 \n", "L 775 -588 \n", "Q 1028 -725 1275 -790 \n", "Q 1522 -856 1778 -856 \n", "Q 2344 -856 2625 -561 \n", "Q 2906 -266 2906 331 \n", "L 2906 616 \n", "Q 2728 306 2450 153 \n", "Q 2172 0 1784 0 \n", "Q 1141 0 747 490 \n", "Q 353 981 353 1791 \n", "Q 353 2603 747 3093 \n", "Q 1141 3584 1784 3584 \n", "Q 2172 3584 2450 3431 \n", "Q 2728 3278 2906 2969 \n", "L 2906 3500 \n", "L 3481 3500 \n", "L 3481 434 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-66\" d=\"M 2375 4863 \n", "L 2375 4384 \n", "L 1825 4384 \n", "Q 1516 4384 1395 4259 \n", "Q 1275 4134 1275 3809 \n", "L 1275 3500 \n", "L 2222 3500 \n", "L 2222 3053 \n", "L 1275 3053 \n", "L 1275 0 \n", "L 697 0 \n", "L 697 3053 \n", "L 147 3053 \n", "L 147 3500 \n", "L 697 3500 \n", "L 697 3744 \n", "Q 697 4328 969 4595 \n", "Q 1241 4863 1831 4863 \n", "L 2375 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-74\" d=\"M 1172 4494 \n", "L 1172 3500 \n", "L 2356 3500 \n", "L 2356 3053 \n", "L 1172 3053 \n", "L 1172 1153 \n", "Q 1172 725 1289 603 \n", "Q 1406 481 1766 481 \n", "L 2356 481 \n", "L 2356 0 \n", "L 1766 0 \n", "Q 1100 0 847 248 \n", "Q 594 497 594 1153 \n", "L 594 3053 \n", "L 172 3053 \n", "L 172 3500 \n", "L 594 3500 \n", "L 594 4494 \n", "L 1172 4494 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6f\" d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-72\" d=\"M 2631 2963 \n", "Q 2534 3019 2420 3045 \n", "Q 2306 3072 2169 3072 \n", "Q 1681 3072 1420 2755 \n", "Q 1159 2438 1159 1844 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1341 3275 1631 3429 \n", "Q 1922 3584 2338 3584 \n", "Q 2397 3584 2469 3576 \n", "Q 2541 3569 2628 3553 \n", "L 2631 2963 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-3a\" d=\"M 750 794 \n", "L 1409 794 \n", "L 1409 0 \n", "L 750 0 \n", "L 750 794 \n", "z\n", "M 750 3309 \n", "L 1409 3309 \n", "L 1409 2516 \n", "L 750 2516 \n", "L 750 3309 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-53\"/>\n", " <use xlink:href=\"#DejaVuSans-63\" x=\"63.476562\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"118.457031\"/>\n", " <use xlink:href=\"#DejaVuSans-6c\" x=\"179.736328\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"207.519531\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"235.302734\"/>\n", " <use xlink:href=\"#DejaVuSans-67\" x=\"298.681641\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"362.158203\"/>\n", " <use xlink:href=\"#DejaVuSans-66\" x=\"393.945312\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"429.150391\"/>\n", " <use xlink:href=\"#DejaVuSans-63\" x=\"490.429688\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"545.410156\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"584.619141\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"645.800781\"/>\n", " <use xlink:href=\"#DejaVuSans-3a\" x=\"685.164062\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"718.855469\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"750.642578\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"814.265625\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"846.052734\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"axes_2\">\n", " <g id=\"patch_7\">\n", " <path d=\"M 279.611143 188.638125 \n", "L 455.821669 188.638125 \n", "L 455.821669 22.318125 \n", "L 279.611143 22.318125 \n", "z\n", "\" style=\"fill: #eaeaf2\"/>\n", " </g>\n", " <g id=\"matplotlib.axis_3\">\n", " <g id=\"xtick_6\">\n", " <g id=\"line2d_14\">\n", " <path d=\"M 287.620712 188.638125 \n", "L 287.620712 22.318125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_14\">\n", " <!-- \u22125.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(274.265166 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"83.789062\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"147.412109\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"179.199219\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_7\">\n", " <g id=\"line2d_15\">\n", " <path d=\"M 327.708648 188.638125 \n", "L 327.708648 22.318125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_15\">\n", " <!-- \u22122.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(314.353101 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"83.789062\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"147.412109\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"179.199219\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_8\">\n", " <g id=\"line2d_16\">\n", " <path d=\"M 367.796584 188.638125 \n", "L 367.796584 22.318125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_16\">\n", " <!-- 0.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(359.049865 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_9\">\n", " <g id=\"line2d_17\">\n", " <path d=\"M 407.88452 188.638125 \n", "L 407.88452 22.318125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_17\">\n", " <!-- 2.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(399.137801 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-32\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_10\">\n", " <g id=\"line2d_18\">\n", " <path d=\"M 447.972455 188.638125 \n", "L 447.972455 22.318125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_18\">\n", " <!-- 5.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(439.225737 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-35\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"matplotlib.axis_4\">\n", " <g id=\"ytick_8\">\n", " <g id=\"line2d_19\">\n", " <path d=\"M 279.611143 188.638125 \n", "L 455.821669 188.638125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_19\">\n", " <!-- \u22123 -->\n", " <g style=\"fill: #262626\" transform=\"translate(253.894737 192.817266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-33\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_9\">\n", " <g id=\"line2d_20\">\n", " <path d=\"M 279.611143 160.918125 \n", "L 455.821669 160.918125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_20\">\n", " <!-- \u22122 -->\n", " <g style=\"fill: #262626\" transform=\"translate(253.894737 165.097266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_10\">\n", " <g id=\"line2d_21\">\n", " <path d=\"M 279.611143 133.198125 \n", "L 455.821669 133.198125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_21\">\n", " <!-- \u22121 -->\n", " <g style=\"fill: #262626\" transform=\"translate(253.894737 137.377266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_11\">\n", " <g id=\"line2d_22\">\n", " <path d=\"M 279.611143 105.478125 \n", "L 455.821669 105.478125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_22\">\n", " <!-- 0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(263.112393 109.657266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_12\">\n", " <g id=\"line2d_23\">\n", " <path d=\"M 279.611143 77.758125 \n", "L 455.821669 77.758125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_23\">\n", " <!-- 1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(263.112393 81.937266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_13\">\n", " <g id=\"line2d_24\">\n", " <path d=\"M 279.611143 50.038125 \n", "L 455.821669 50.038125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_24\">\n", " <!-- 2 -->\n", " <g style=\"fill: #262626\" transform=\"translate(263.112393 54.217266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-32\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_14\">\n", " <g id=\"line2d_25\">\n", " <path d=\"M 279.611143 22.318125 \n", "L 455.821669 22.318125 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_25\">\n", " <!-- 3 -->\n", " <g style=\"fill: #262626\" transform=\"translate(263.112393 26.497266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-33\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"line2d_26\">\n", " <path d=\"M 287.620712 133.195609 \n", "L 318.728952 133.07651 \n", "L 327.548297 132.834373 \n", "L 333.160606 132.470457 \n", "L 337.329751 131.985028 \n", "L 340.697138 131.372686 \n", "L 343.583471 130.618475 \n", "L 345.988747 129.771741 \n", "L 348.233671 128.75334 \n", "L 350.318245 127.567586 \n", "L 352.242464 126.232209 \n", "L 354.166685 124.634571 \n", "L 356.090906 122.749497 \n", "L 358.015127 120.561328 \n", "L 360.0997 117.847998 \n", "L 362.344625 114.555798 \n", "L 365.070604 110.145648 \n", "L 374.371006 94.709662 \n", "L 376.615929 91.603706 \n", "L 378.700503 89.081207 \n", "L 380.785075 86.917084 \n", "L 382.709296 85.226062 \n", "L 384.793868 83.699523 \n", "L 386.87844 82.454479 \n", "L 389.123366 81.382533 \n", "L 391.528642 80.489433 \n", "L 394.254621 79.730192 \n", "L 397.301303 79.122084 \n", "L 400.989394 78.627052 \n", "L 405.479242 78.257822 \n", "L 411.57261 77.992943 \n", "L 421.033362 77.830491 \n", "L 440.75663 77.764314 \n", "L 447.8121 77.760693 \n", "L 447.8121 77.760693 \n", "\" clip-path=\"url(#pd0bf27a1e7)\" style=\"fill: none; stroke: #4c72b0; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"patch_8\">\n", " <path d=\"M 279.611143 188.638125 \n", "L 279.611143 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_9\">\n", " <path d=\"M 455.821669 188.638125 \n", "L 455.821669 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_10\">\n", " <path d=\"M 279.611143 188.638125 \n", "L 455.821669 188.638125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_11\">\n", " <path d=\"M 279.611143 22.318125 \n", "L 455.821669 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"text_26\">\n", " <!-- Scaling factor: 1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(318.860469 16.318125) scale(0.12 -0.12)\">\n", " <use xlink:href=\"#DejaVuSans-53\"/>\n", " <use xlink:href=\"#DejaVuSans-63\" x=\"63.476562\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"118.457031\"/>\n", " <use xlink:href=\"#DejaVuSans-6c\" x=\"179.736328\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"207.519531\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"235.302734\"/>\n", " <use xlink:href=\"#DejaVuSans-67\" x=\"298.681641\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"362.158203\"/>\n", " <use xlink:href=\"#DejaVuSans-66\" x=\"393.945312\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"429.150391\"/>\n", " <use xlink:href=\"#DejaVuSans-63\" x=\"490.429688\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"545.410156\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"584.619141\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"645.800781\"/>\n", " <use xlink:href=\"#DejaVuSans-3a\" x=\"685.164062\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"718.855469\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"750.642578\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"axes_3\">\n", " <g id=\"patch_12\">\n", " <path d=\"M 526.30588 188.638125 \n", "L 702.516406 188.638125 \n", "L 702.516406 22.318125 \n", "L 526.30588 22.318125 \n", "z\n", "\" style=\"fill: #eaeaf2\"/>\n", " </g>\n", " <g id=\"matplotlib.axis_5\">\n", " <g id=\"xtick_11\">\n", " <g id=\"line2d_27\">\n", " <path d=\"M 534.315449 188.638125 \n", "L 534.315449 22.318125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_27\">\n", " <!-- \u22125.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(520.959902 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"83.789062\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"147.412109\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"179.199219\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_12\">\n", " <g id=\"line2d_28\">\n", " <path d=\"M 574.403385 188.638125 \n", "L 574.403385 22.318125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_28\">\n", " <!-- \u22122.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(561.047838 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"83.789062\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"147.412109\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"179.199219\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_13\">\n", " <g id=\"line2d_29\">\n", " <path d=\"M 614.491321 188.638125 \n", "L 614.491321 22.318125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_29\">\n", " <!-- 0.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(605.744602 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_14\">\n", " <g id=\"line2d_30\">\n", " <path d=\"M 654.579257 188.638125 \n", "L 654.579257 22.318125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_30\">\n", " <!-- 2.5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(645.832538 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-32\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_15\">\n", " <g id=\"line2d_31\">\n", " <path d=\"M 694.667192 188.638125 \n", "L 694.667192 22.318125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_31\">\n", " <!-- 5.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(685.920474 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-35\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"matplotlib.axis_6\">\n", " <g id=\"ytick_15\">\n", " <g id=\"line2d_32\">\n", " <path d=\"M 526.30588 188.638125 \n", "L 702.516406 188.638125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_32\">\n", " <!-- \u22123 -->\n", " <g style=\"fill: #262626\" transform=\"translate(500.589474 192.817266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-33\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_16\">\n", " <g id=\"line2d_33\">\n", " <path d=\"M 526.30588 160.918125 \n", "L 702.516406 160.918125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_33\">\n", " <!-- \u22122 -->\n", " <g style=\"fill: #262626\" transform=\"translate(500.589474 165.097266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_17\">\n", " <g id=\"line2d_34\">\n", " <path d=\"M 526.30588 133.198125 \n", "L 702.516406 133.198125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_34\">\n", " <!-- \u22121 -->\n", " <g style=\"fill: #262626\" transform=\"translate(500.589474 137.377266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_18\">\n", " <g id=\"line2d_35\">\n", " <path d=\"M 526.30588 105.478125 \n", "L 702.516406 105.478125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_35\">\n", " <!-- 0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(509.80713 109.657266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_19\">\n", " <g id=\"line2d_36\">\n", " <path d=\"M 526.30588 77.758125 \n", "L 702.516406 77.758125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_36\">\n", " <!-- 1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(509.80713 81.937266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_20\">\n", " <g id=\"line2d_37\">\n", " <path d=\"M 526.30588 50.038125 \n", "L 702.516406 50.038125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_37\">\n", " <!-- 2 -->\n", " <g style=\"fill: #262626\" transform=\"translate(509.80713 54.217266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-32\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_21\">\n", " <g id=\"line2d_38\">\n", " <path d=\"M 526.30588 22.318125 \n", "L 702.516406 22.318125 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_38\">\n", " <!-- 3 -->\n", " <g style=\"fill: #262626\" transform=\"translate(509.80713 26.497266) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-33\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"line2d_39\">\n", " <path d=\"M 534.315449 160.176021 \n", "L 542.493392 159.687784 \n", "L 548.907463 159.092637 \n", "L 554.359417 158.370393 \n", "L 559.009617 157.539385 \n", "L 563.178762 156.575428 \n", "L 567.027204 155.45551 \n", "L 570.554943 154.192821 \n", "L 573.761979 152.812668 \n", "L 576.808663 151.264271 \n", "L 579.694991 149.555474 \n", "L 582.581324 147.584043 \n", "L 585.307303 145.457699 \n", "L 588.033284 143.054366 \n", "L 590.759263 140.357932 \n", "L 593.485241 137.357585 \n", "L 596.371574 133.845542 \n", "L 599.418257 129.771895 \n", "L 602.625292 125.103426 \n", "L 606.313382 119.316667 \n", "L 610.803231 111.825767 \n", "L 623.952073 89.581798 \n", "L 627.640164 83.9412 \n", "L 630.847198 79.424364 \n", "L 633.89388 75.50738 \n", "L 636.780215 72.148454 \n", "L 639.666543 69.133481 \n", "L 642.392524 66.593944 \n", "L 645.118503 64.339521 \n", "L 648.004834 62.242973 \n", "L 650.891166 60.42073 \n", "L 653.93785 58.765528 \n", "L 657.144882 57.286941 \n", "L 660.512269 55.987576 \n", "L 664.040008 54.863805 \n", "L 667.88845 53.869721 \n", "L 672.217947 52.9872 \n", "L 677.028502 52.238017 \n", "L 682.640812 51.5975 \n", "L 689.215231 51.077923 \n", "L 694.506837 50.787638 \n", "L 694.506837 50.787638 \n", "\" clip-path=\"url(#p37f6f9c6dc)\" style=\"fill: none; stroke: #4c72b0; stroke-width: 1.5; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"patch_13\">\n", " <path d=\"M 526.30588 188.638125 \n", "L 526.30588 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_14\">\n", " <path d=\"M 702.516406 188.638125 \n", "L 702.516406 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_15\">\n", " <path d=\"M 526.30588 188.638125 \n", "L 702.516406 188.638125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_16\">\n", " <path d=\"M 526.30588 22.318125 \n", "L 702.516406 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"text_39\">\n", " <!-- Scaling factor: 2 -->\n", " <g style=\"fill: #262626\" transform=\"translate(565.555206 16.318125) scale(0.12 -0.12)\">\n", " <use xlink:href=\"#DejaVuSans-53\"/>\n", " <use xlink:href=\"#DejaVuSans-63\" x=\"63.476562\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"118.457031\"/>\n", " <use xlink:href=\"#DejaVuSans-6c\" x=\"179.736328\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"207.519531\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"235.302734\"/>\n", " <use xlink:href=\"#DejaVuSans-67\" x=\"298.681641\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"362.158203\"/>\n", " <use xlink:href=\"#DejaVuSans-66\" x=\"393.945312\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"429.150391\"/>\n", " <use xlink:href=\"#DejaVuSans-63\" x=\"490.429688\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"545.410156\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"584.619141\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"645.800781\"/>\n", " <use xlink:href=\"#DejaVuSans-3a\" x=\"685.164062\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"718.855469\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"750.642578\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p81e22cd740\">\n", " <rect x=\"32.916406\" y=\"22.318125\" width=\"176.210526\" height=\"166.32\"/>\n", " </clipPath>\n", " <clipPath id=\"pd0bf27a1e7\">\n", " <rect x=\"279.611143\" y=\"22.318125\" width=\"176.210526\" height=\"166.32\"/>\n", " </clipPath>\n", " <clipPath id=\"p37f6f9c6dc\">\n", " <rect x=\"526.30588\" y=\"22.318125\" width=\"176.210526\" height=\"166.32\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 1200x300 with 3 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["with torch.no_grad():\n", " x = torch.arange(-5, 5, 0.01)\n", " scaling_factors = [0.5, 1, 2]\n", " sns.set()\n", " fig, ax = plt.subplots(1, 3, figsize=(12, 3))\n", " for i, scale in enumerate(scaling_factors):\n", " y = torch.tanh(x / scale) * scale\n", " ax[i].plot(x.numpy(), y.numpy())\n", " ax[i].set_title(\"Scaling factor: \" + str(scale))\n", " ax[i].set_ylim(-3, 3)\n", " plt.subplots_adjust(wspace=0.4)\n", " sns.reset_orig()\n", " plt.show()"]}, {"cell_type": "markdown", "id": "0a4c5cae", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.016704, "end_time": "2023-03-14T16:08:54.614666", "exception": false, "start_time": "2023-03-14T16:08:54.597962", "status": "completed"}, "tags": []}, "source": ["Coupling layers generalize to any masking technique we could think of.\n", "However, the most common approach for images is to split the input $z$ in half, using a checkerboard mask or channel mask.\n", "A checkerboard mask splits the variables across the height and width dimensions and assigns each other pixel to $z_{j+1:d}$.\n", "Thereby, the mask is shared across channels.\n", "In contrast, the channel mask assigns half of the channels to $z_{j+1:d}$, and the other half to $z_{1:j+1}$.\n", "Note that when we apply multiple coupling layers, we invert the masking for each other layer so that each variable is transformed a similar amount of times.\n", "\n", "Let's implement a function that creates a checkerboard mask and a channel mask for us:"]}, {"cell_type": "code", "execution_count": 14, "id": "124363d3", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:54.649537Z", "iopub.status.busy": "2023-03-14T16:08:54.649056Z", "iopub.status.idle": "2023-03-14T16:08:54.656432Z", "shell.execute_reply": "2023-03-14T16:08:54.655621Z"}, "papermill": {"duration": 0.027594, "end_time": "2023-03-14T16:08:54.658995", "exception": false, "start_time": "2023-03-14T16:08:54.631401", "status": "completed"}, "tags": []}, "outputs": [], "source": ["def create_checkerboard_mask(h, w, invert=False):\n", " x, y = torch.arange(h, dtype=torch.int32), torch.arange(w, dtype=torch.int32)\n", " xx, yy = torch.meshgrid(x, y)\n", " mask = torch.fmod(xx + yy, 2)\n", " mask = mask.to(torch.float32).view(1, 1, h, w)\n", " if invert:\n", " mask = 1 - mask\n", " return mask\n", "\n", "\n", "def create_channel_mask(c_in, invert=False):\n", " mask = torch.cat([torch.ones(c_in // 2, dtype=torch.float32), torch.zeros(c_in - c_in // 2, dtype=torch.float32)])\n", " mask = mask.view(1, c_in, 1, 1)\n", " if invert:\n", " mask = 1 - mask\n", " return mask"]}, {"cell_type": "markdown", "id": "8d6f119f", "metadata": {"papermill": {"duration": 0.016328, "end_time": "2023-03-14T16:08:54.696519", "exception": false, "start_time": "2023-03-14T16:08:54.680191", "status": "completed"}, "tags": []}, "source": ["We can also visualize the corresponding masks for an image of size $8\\times 8\\times 2$ (2 channels):"]}, {"cell_type": "code", "execution_count": 15, "id": "e73db108", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:54.730666Z", "iopub.status.busy": "2023-03-14T16:08:54.730376Z", "iopub.status.idle": "2023-03-14T16:08:55.071855Z", "shell.execute_reply": "2023-03-14T16:08:55.071060Z"}, "papermill": {"duration": 0.361902, "end_time": "2023-03-14T16:08:55.074928", "exception": false, "start_time": "2023-03-14T16:08:54.713026", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["/usr/local/lib/python3.9/dist-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3190.)\n", " return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]\n"]}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"166.86pt\" height=\"112.678125pt\" viewBox=\"0 0 166.86 112.678125\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:08:54.954296</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 112.678125 \n", "L 166.86 112.678125 \n", "L 166.86 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#pac2b7f5386)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image5b7bfe28ae\" transform=\"scale(1 -1) translate(0 -83.52)\" x=\"7.2\" y=\"-21.958125\" width=\"152.64\" height=\"83.52\"/>\n", " </g>\n", " <g id=\"text_1\">\n", " <!-- Checkerboard mask -->\n", " <g transform=\"translate(23.675625 16.318125) scale(0.12 -0.12)\">\n", " <defs>\n", " <path id=\"DejaVuSans-43\" d=\"M 4122 4306 \n", "L 4122 3641 \n", "Q 3803 3938 3442 4084 \n", "Q 3081 4231 2675 4231 \n", "Q 1875 4231 1450 3742 \n", "Q 1025 3253 1025 2328 \n", "Q 1025 1406 1450 917 \n", "Q 1875 428 2675 428 \n", "Q 3081 428 3442 575 \n", "Q 3803 722 4122 1019 \n", "L 4122 359 \n", "Q 3791 134 3420 21 \n", "Q 3050 -91 2638 -91 \n", "Q 1578 -91 968 557 \n", "Q 359 1206 359 2328 \n", "Q 359 3453 968 4101 \n", "Q 1578 4750 2638 4750 \n", "Q 3056 4750 3426 4639 \n", "Q 3797 4528 4122 4306 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-68\" d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "L 1159 4863 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-65\" d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-63\" d=\"M 3122 3366 \n", "L 3122 2828 \n", "Q 2878 2963 2633 3030 \n", "Q 2388 3097 2138 3097 \n", "Q 1578 3097 1268 2742 \n", "Q 959 2388 959 1747 \n", "Q 959 1106 1268 751 \n", "Q 1578 397 2138 397 \n", "Q 2388 397 2633 464 \n", "Q 2878 531 3122 666 \n", "L 3122 134 \n", "Q 2881 22 2623 -34 \n", "Q 2366 -91 2075 -91 \n", "Q 1284 -91 818 406 \n", "Q 353 903 353 1747 \n", "Q 353 2603 823 3093 \n", "Q 1294 3584 2113 3584 \n", "Q 2378 3584 2631 3529 \n", "Q 2884 3475 3122 3366 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6b\" d=\"M 581 4863 \n", "L 1159 4863 \n", "L 1159 1991 \n", "L 2875 3500 \n", "L 3609 3500 \n", "L 1753 1863 \n", "L 3688 0 \n", "L 2938 0 \n", "L 1159 1709 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-72\" d=\"M 2631 2963 \n", "Q 2534 3019 2420 3045 \n", "Q 2306 3072 2169 3072 \n", "Q 1681 3072 1420 2755 \n", "Q 1159 2438 1159 1844 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1341 3275 1631 3429 \n", "Q 1922 3584 2338 3584 \n", "Q 2397 3584 2469 3576 \n", "Q 2541 3569 2628 3553 \n", "L 2631 2963 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-62\" d=\"M 3116 1747 \n", "Q 3116 2381 2855 2742 \n", "Q 2594 3103 2138 3103 \n", "Q 1681 3103 1420 2742 \n", "Q 1159 2381 1159 1747 \n", "Q 1159 1113 1420 752 \n", "Q 1681 391 2138 391 \n", "Q 2594 391 2855 752 \n", "Q 3116 1113 3116 1747 \n", "z\n", "M 1159 2969 \n", "Q 1341 3281 1617 3432 \n", "Q 1894 3584 2278 3584 \n", "Q 2916 3584 3314 3078 \n", "Q 3713 2572 3713 1747 \n", "Q 3713 922 3314 415 \n", "Q 2916 -91 2278 -91 \n", "Q 1894 -91 1617 61 \n", "Q 1341 213 1159 525 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "L 1159 4863 \n", "L 1159 2969 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6f\" d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-61\" d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-64\" d=\"M 2906 2969 \n", "L 2906 4863 \n", "L 3481 4863 \n", "L 3481 0 \n", "L 2906 0 \n", "L 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "z\n", "M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6d\" d=\"M 3328 2828 \n", "Q 3544 3216 3844 3400 \n", "Q 4144 3584 4550 3584 \n", "Q 5097 3584 5394 3201 \n", "Q 5691 2819 5691 2113 \n", "L 5691 0 \n", "L 5113 0 \n", "L 5113 2094 \n", "Q 5113 2597 4934 2840 \n", "Q 4756 3084 4391 3084 \n", "Q 3944 3084 3684 2787 \n", "Q 3425 2491 3425 1978 \n", "L 3425 0 \n", "L 2847 0 \n", "L 2847 2094 \n", "Q 2847 2600 2669 2842 \n", "Q 2491 3084 2119 3084 \n", "Q 1678 3084 1418 2786 \n", "Q 1159 2488 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1356 3278 1631 3431 \n", "Q 1906 3584 2284 3584 \n", "Q 2666 3584 2933 3390 \n", "Q 3200 3197 3328 2828 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-73\" d=\"M 2834 3397 \n", "L 2834 2853 \n", "Q 2591 2978 2328 3040 \n", "Q 2066 3103 1784 3103 \n", "Q 1356 3103 1142 2972 \n", "Q 928 2841 928 2578 \n", "Q 928 2378 1081 2264 \n", "Q 1234 2150 1697 2047 \n", "L 1894 2003 \n", "Q 2506 1872 2764 1633 \n", "Q 3022 1394 3022 966 \n", "Q 3022 478 2636 193 \n", "Q 2250 -91 1575 -91 \n", "Q 1294 -91 989 -36 \n", "Q 684 19 347 128 \n", "L 347 722 \n", "Q 666 556 975 473 \n", "Q 1284 391 1588 391 \n", "Q 1994 391 2212 530 \n", "Q 2431 669 2431 922 \n", "Q 2431 1156 2273 1281 \n", "Q 2116 1406 1581 1522 \n", "L 1381 1569 \n", "Q 847 1681 609 1914 \n", "Q 372 2147 372 2553 \n", "Q 372 3047 722 3315 \n", "Q 1072 3584 1716 3584 \n", "Q 2034 3584 2315 3537 \n", "Q 2597 3491 2834 3397 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-43\"/>\n", " <use xlink:href=\"#DejaVuSans-68\" x=\"69.824219\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"133.203125\"/>\n", " <use xlink:href=\"#DejaVuSans-63\" x=\"194.726562\"/>\n", " <use xlink:href=\"#DejaVuSans-6b\" x=\"249.707031\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"303.992188\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"365.515625\"/>\n", " <use xlink:href=\"#DejaVuSans-62\" x=\"406.628906\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"470.105469\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"531.287109\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"592.566406\"/>\n", " <use xlink:href=\"#DejaVuSans-64\" x=\"631.929688\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"695.40625\"/>\n", " <use xlink:href=\"#DejaVuSans-6d\" x=\"727.193359\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"824.605469\"/>\n", " <use xlink:href=\"#DejaVuSans-73\" x=\"885.884766\"/>\n", " <use xlink:href=\"#DejaVuSans-6b\" x=\"937.984375\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"pac2b7f5386\">\n", " <rect x=\"7.2\" y=\"22.318125\" width=\"152.46\" height=\"83.16\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 300x150 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"166.86pt\" height=\"112.678125pt\" viewBox=\"0 0 166.86 112.678125\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:08:55.028934</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 112.678125 \n", "L 166.86 112.678125 \n", "L 166.86 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#p80d5fd6ea7)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image31121e042c\" transform=\"scale(1 -1) translate(0 -83.52)\" x=\"7.2\" y=\"-21.958125\" width=\"152.64\" height=\"83.52\"/>\n", " </g>\n", " <g id=\"text_1\">\n", " <!-- Channel mask -->\n", " <g transform=\"translate(40.769063 16.318125) scale(0.12 -0.12)\">\n", " <defs>\n", " <path id=\"DejaVuSans-43\" d=\"M 4122 4306 \n", "L 4122 3641 \n", "Q 3803 3938 3442 4084 \n", "Q 3081 4231 2675 4231 \n", "Q 1875 4231 1450 3742 \n", "Q 1025 3253 1025 2328 \n", "Q 1025 1406 1450 917 \n", "Q 1875 428 2675 428 \n", "Q 3081 428 3442 575 \n", "Q 3803 722 4122 1019 \n", "L 4122 359 \n", "Q 3791 134 3420 21 \n", "Q 3050 -91 2638 -91 \n", "Q 1578 -91 968 557 \n", "Q 359 1206 359 2328 \n", "Q 359 3453 968 4101 \n", "Q 1578 4750 2638 4750 \n", "Q 3056 4750 3426 4639 \n", "Q 3797 4528 4122 4306 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-68\" d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "L 1159 4863 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-61\" d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6e\" d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-65\" d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6c\" d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6d\" d=\"M 3328 2828 \n", "Q 3544 3216 3844 3400 \n", "Q 4144 3584 4550 3584 \n", "Q 5097 3584 5394 3201 \n", "Q 5691 2819 5691 2113 \n", "L 5691 0 \n", "L 5113 0 \n", "L 5113 2094 \n", "Q 5113 2597 4934 2840 \n", "Q 4756 3084 4391 3084 \n", "Q 3944 3084 3684 2787 \n", "Q 3425 2491 3425 1978 \n", "L 3425 0 \n", "L 2847 0 \n", "L 2847 2094 \n", "Q 2847 2600 2669 2842 \n", "Q 2491 3084 2119 3084 \n", "Q 1678 3084 1418 2786 \n", "Q 1159 2488 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1356 3278 1631 3431 \n", "Q 1906 3584 2284 3584 \n", "Q 2666 3584 2933 3390 \n", "Q 3200 3197 3328 2828 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-73\" d=\"M 2834 3397 \n", "L 2834 2853 \n", "Q 2591 2978 2328 3040 \n", "Q 2066 3103 1784 3103 \n", "Q 1356 3103 1142 2972 \n", "Q 928 2841 928 2578 \n", "Q 928 2378 1081 2264 \n", "Q 1234 2150 1697 2047 \n", "L 1894 2003 \n", "Q 2506 1872 2764 1633 \n", "Q 3022 1394 3022 966 \n", "Q 3022 478 2636 193 \n", "Q 2250 -91 1575 -91 \n", "Q 1294 -91 989 -36 \n", "Q 684 19 347 128 \n", "L 347 722 \n", "Q 666 556 975 473 \n", "Q 1284 391 1588 391 \n", "Q 1994 391 2212 530 \n", "Q 2431 669 2431 922 \n", "Q 2431 1156 2273 1281 \n", "Q 2116 1406 1581 1522 \n", "L 1381 1569 \n", "Q 847 1681 609 1914 \n", "Q 372 2147 372 2553 \n", "Q 372 3047 722 3315 \n", "Q 1072 3584 1716 3584 \n", "Q 2034 3584 2315 3537 \n", "Q 2597 3491 2834 3397 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6b\" d=\"M 581 4863 \n", "L 1159 4863 \n", "L 1159 1991 \n", "L 2875 3500 \n", "L 3609 3500 \n", "L 1753 1863 \n", "L 3688 0 \n", "L 2938 0 \n", "L 1159 1709 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-43\"/>\n", " <use xlink:href=\"#DejaVuSans-68\" x=\"69.824219\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"133.203125\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"194.482422\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"257.861328\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"321.240234\"/>\n", " <use xlink:href=\"#DejaVuSans-6c\" x=\"382.763672\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"410.546875\"/>\n", " <use xlink:href=\"#DejaVuSans-6d\" x=\"442.333984\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"539.746094\"/>\n", " <use xlink:href=\"#DejaVuSans-73\" x=\"601.025391\"/>\n", " <use xlink:href=\"#DejaVuSans-6b\" x=\"653.125\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p80d5fd6ea7\">\n", " <rect x=\"7.2\" y=\"22.318125\" width=\"152.46\" height=\"83.16\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 300x150 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["checkerboard_mask = create_checkerboard_mask(h=8, w=8).expand(-1, 2, -1, -1)\n", "channel_mask = create_channel_mask(c_in=2).expand(-1, -1, 8, 8)\n", "\n", "show_imgs(checkerboard_mask.transpose(0, 1), \"Checkerboard mask\")\n", "show_imgs(channel_mask.transpose(0, 1), \"Channel mask\")"]}, {"cell_type": "markdown", "id": "1bda3665", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.017332, "end_time": "2023-03-14T16:08:55.118805", "exception": false, "start_time": "2023-03-14T16:08:55.101473", "status": "completed"}, "tags": []}, "source": ["As a last aspect of coupling layers, we need to decide for the deep neural network we want to apply in the coupling layers.\n", "The input to the layers is an image, and hence we stick with a CNN.\n", "Because the input to a transformation depends on all transformations before,\n", "it is crucial to ensure a good gradient flow through the CNN back to the input,\n", "which can be optimally achieved by a ResNet-like architecture.\n", "Specifically, we use a Gated ResNet that adds a $\\sigma$-gate to the skip connection,\n", "similarly to the input gate in LSTMs.\n", "The details are not necessarily important here, and the network is\n", "strongly inspired from Flow++ [3] in case you are interested in building\n", "even stronger models."]}, {"cell_type": "code", "execution_count": 16, "id": "de6ca2e1", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:55.155408Z", "iopub.status.busy": "2023-03-14T16:08:55.154889Z", "iopub.status.idle": "2023-03-14T16:08:55.171000Z", "shell.execute_reply": "2023-03-14T16:08:55.170454Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.037079, "end_time": "2023-03-14T16:08:55.173218", "exception": false, "start_time": "2023-03-14T16:08:55.136139", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class ConcatELU(nn.Module):\n", " \"\"\"Activation function that applies ELU in both direction (inverted and plain).\n", "\n", " Allows non-linearity while providing strong gradients for any input (important for final convolution)\n", " \"\"\"\n", "\n", " def forward(self, x):\n", " return torch.cat([F.elu(x), F.elu(-x)], dim=1)\n", "\n", "\n", "class LayerNormChannels(nn.Module):\n", " def __init__(self, c_in, eps=1e-5):\n", " \"\"\"\n", " This module applies layer norm across channels in an image.\n", " Inputs:\n", " c_in - Number of channels of the input\n", " eps - Small constant to stabilize std\n", " \"\"\"\n", " super().__init__()\n", " self.gamma = nn.Parameter(torch.ones(1, c_in, 1, 1))\n", " self.beta = nn.Parameter(torch.zeros(1, c_in, 1, 1))\n", " self.eps = eps\n", "\n", " def forward(self, x):\n", " mean = x.mean(dim=1, keepdim=True)\n", " var = x.var(dim=1, unbiased=False, keepdim=True)\n", " y = (x - mean) / torch.sqrt(var + self.eps)\n", " y = y * self.gamma + self.beta\n", " return y\n", "\n", "\n", "class GatedConv(nn.Module):\n", " def __init__(self, c_in, c_hidden):\n", " \"\"\"\n", " This module applies a two-layer convolutional ResNet block with input gate\n", " Args:\n", " c_in: Number of channels of the input\n", " c_hidden: Number of hidden dimensions we want to model (usually similar to c_in)\n", " \"\"\"\n", " super().__init__()\n", " self.net = nn.Sequential(\n", " ConcatELU(),\n", " nn.Conv2d(2 * c_in, c_hidden, kernel_size=3, padding=1),\n", " ConcatELU(),\n", " nn.Conv2d(2 * c_hidden, 2 * c_in, kernel_size=1),\n", " )\n", "\n", " def forward(self, x):\n", " out = self.net(x)\n", " val, gate = out.chunk(2, dim=1)\n", " return x + val * torch.sigmoid(gate)\n", "\n", "\n", "class GatedConvNet(nn.Module):\n", " def __init__(self, c_in, c_hidden=32, c_out=-1, num_layers=3):\n", " \"\"\"Module that summarizes the previous blocks to a full convolutional neural network.\n", "\n", " Args:\n", " c_in: Number of input channels\n", " c_hidden: Number of hidden dimensions to use within the network\n", " c_out: Number of output channels. If -1, 2 times the input channels are used (affine coupling)\n", " num_layers: Number of gated ResNet blocks to apply\n", " \"\"\"\n", " super().__init__()\n", " c_out = c_out if c_out > 0 else 2 * c_in\n", " layers = []\n", " layers += [nn.Conv2d(c_in, c_hidden, kernel_size=3, padding=1)]\n", " for layer_index in range(num_layers):\n", " layers += [GatedConv(c_hidden, c_hidden), LayerNormChannels(c_hidden)]\n", " layers += [ConcatELU(), nn.Conv2d(2 * c_hidden, c_out, kernel_size=3, padding=1)]\n", " self.nn = nn.Sequential(*layers)\n", "\n", " self.nn[-1].weight.data.zero_()\n", " self.nn[-1].bias.data.zero_()\n", "\n", " def forward(self, x):\n", " return self.nn(x)"]}, {"cell_type": "markdown", "id": "3084a0b1", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.017371, "end_time": "2023-03-14T16:08:55.211629", "exception": false, "start_time": "2023-03-14T16:08:55.194258", "status": "completed"}, "tags": []}, "source": ["### Training loop\n", "\n", "Finally, we can add Dequantization, Variational Dequantization and Coupling Layers together to build our full normalizing flow on MNIST images.\n", "We apply 8 coupling layers in the main flow, and 4 for variational dequantization if applied.\n", "We apply a checkerboard mask throughout the network as with a single channel (black-white images),\n", "we cannot apply channel mask.\n", "The overall architecture is visualized below.\n", "\n", "\n", "<center width=\"100%\" style=\"padding: 20px\"><img src=\"https://github.com/Lightning-AI/lightning-tutorials/raw/main/course_UvA-DL/09-normalizing-flows/vanilla_flow.svg\" width=\"900px\"></center>"]}, {"cell_type": "code", "execution_count": 17, "id": "1bec6c41", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:55.248636Z", "iopub.status.busy": "2023-03-14T16:08:55.248203Z", "iopub.status.idle": "2023-03-14T16:08:55.257903Z", "shell.execute_reply": "2023-03-14T16:08:55.257293Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.030947, "end_time": "2023-03-14T16:08:55.260082", "exception": false, "start_time": "2023-03-14T16:08:55.229135", "status": "completed"}, "tags": []}, "outputs": [], "source": ["def create_simple_flow(use_vardeq=True):\n", " flow_layers = []\n", " if use_vardeq:\n", " vardeq_layers = [\n", " CouplingLayer(\n", " network=GatedConvNet(c_in=2, c_out=2, c_hidden=16),\n", " mask=create_checkerboard_mask(h=28, w=28, invert=(i % 2 == 1)),\n", " c_in=1,\n", " )\n", " for i in range(4)\n", " ]\n", " flow_layers += [VariationalDequantization(var_flows=vardeq_layers)]\n", " else:\n", " flow_layers += [Dequantization()]\n", "\n", " for i in range(8):\n", " flow_layers += [\n", " CouplingLayer(\n", " network=GatedConvNet(c_in=1, c_hidden=32),\n", " mask=create_checkerboard_mask(h=28, w=28, invert=(i % 2 == 1)),\n", " c_in=1,\n", " )\n", " ]\n", "\n", " flow_model = ImageFlow(flow_layers).to(device)\n", " return flow_model"]}, {"cell_type": "markdown", "id": "a2bc5ef0", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.017328, "end_time": "2023-03-14T16:08:55.296857", "exception": false, "start_time": "2023-03-14T16:08:55.279529", "status": "completed"}, "tags": []}, "source": ["For implementing the training loop, we use the framework of PyTorch Lightning and reduce the code overhead.\n", "If interested, you can take a look at the generated tensorboard file,\n", "in particularly the graph to see an overview of flow transformations that are applied.\n", "Note that we again provide pre-trained models (see later on in the notebook)\n", "as normalizing flows are particularly expensive to train.\n", "We have also run validation and testing as this can take some time as well with the added importance sampling."]}, {"cell_type": "code", "execution_count": 18, "id": "25bb5564", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:55.333029Z", "iopub.status.busy": "2023-03-14T16:08:55.332680Z", "iopub.status.idle": "2023-03-14T16:08:55.346583Z", "shell.execute_reply": "2023-03-14T16:08:55.345982Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.034613, "end_time": "2023-03-14T16:08:55.348820", "exception": false, "start_time": "2023-03-14T16:08:55.314207", "status": "completed"}, "tags": []}, "outputs": [], "source": ["def train_flow(flow, model_name=\"MNISTFlow\"):\n", " # Create a PyTorch Lightning trainer\n", " trainer = L.Trainer(\n", " default_root_dir=os.path.join(CHECKPOINT_PATH, model_name),\n", " accelerator=\"auto\",\n", " devices=1,\n", " max_epochs=200,\n", " gradient_clip_val=1.0,\n", " callbacks=[\n", " ModelCheckpoint(save_weights_only=True, mode=\"min\", monitor=\"val_bpd\"),\n", " LearningRateMonitor(\"epoch\"),\n", " ],\n", " )\n", " trainer.logger._log_graph = True\n", " trainer.logger._default_hp_metric = None # Optional logging argument that we don't need\n", "\n", " train_data_loader = data.DataLoader(\n", " train_set, batch_size=128, shuffle=True, drop_last=True, pin_memory=True, num_workers=8\n", " )\n", " result = None\n", "\n", " # Check whether pretrained model exists. If yes, load it and skip training\n", " pretrained_filename = os.path.join(CHECKPOINT_PATH, model_name + \".ckpt\")\n", " if os.path.isfile(pretrained_filename):\n", " print(\"Found pretrained model, loading...\")\n", " ckpt = torch.load(pretrained_filename, map_location=device)\n", " flow.load_state_dict(ckpt[\"state_dict\"])\n", " result = ckpt.get(\"result\", None)\n", " else:\n", " print(\"Start training\", model_name)\n", " trainer.fit(flow, train_data_loader, val_loader)\n", "\n", " # Test best model on validation and test set if no result has been found\n", " # Testing can be expensive due to the importance sampling.\n", " if result is None:\n", " val_result = trainer.test(flow, dataloaders=val_loader, verbose=False)\n", " start_time = time.time()\n", " test_result = trainer.test(flow, dataloaders=test_loader, verbose=False)\n", " duration = time.time() - start_time\n", " result = {\"test\": test_result, \"val\": val_result, \"time\": duration / len(test_loader) / flow.import_samples}\n", "\n", " return flow, result"]}, {"cell_type": "markdown", "id": "321c2785", "metadata": {"papermill": {"duration": 0.017358, "end_time": "2023-03-14T16:08:55.387653", "exception": false, "start_time": "2023-03-14T16:08:55.370295", "status": "completed"}, "tags": []}, "source": ["## Multi-scale architecture\n", "\n", "<div class=\"center-wrapper\"><div class=\"video-wrapper\"><iframe src=\"https://www.youtube.com/embed/nTyDvn-ADJ4\" title=\"YouTube video player\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe></div></div>\n", "\n", "One disadvantage of normalizing flows is that they operate on the exact same dimensions as the input.\n", "If the input is high-dimensional, so is the latent space, which requires larger computational cost to learn suitable transformations.\n", "However, particularly in the image domain, many pixels contain less information in the sense\n", "that we could remove them without loosing the semantical information of the image.\n", "\n", "Based on this intuition, deep normalizing flows on images commonly apply a multi-scale architecture [1].\n", "After the first $N$ flow transformations, we split off half of the latent dimensions and directly evaluate them on the prior.\n", "The other half is run through $N$ more flow transformations, and depending on the size of the input,\n", "we split it again in half or stop overall at this position.\n", "The two operations involved in this setup is `Squeeze` and `Split` which\n", "we will review more closely and implement below."]}, {"cell_type": "markdown", "id": "b67b73bc", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.017403, "end_time": "2023-03-14T16:08:55.422536", "exception": false, "start_time": "2023-03-14T16:08:55.405133", "status": "completed"}, "tags": []}, "source": ["### Squeeze and Split\n", "\n", "When we want to remove half of the pixels in an image, we have the problem of deciding which variables to cut,\n", "and how to rearrange the image.\n", "Thus, the squeezing operation is commonly used before split, which divides the image into subsquares\n", "of shape $2\\times 2\\times C$, and reshapes them into $1\\times 1\\times 4C$ blocks.\n", "Effectively, we reduce the height and width of the image by a factor of 2 while scaling the number of channels by 4.\n", "Afterwards, we can perform the split operation over channels without the need of rearranging the pixels.\n", "The smaller scale also makes the overall architecture more efficient.\n", "Visually, the squeeze operation should transform the input as follows:\n", "\n", "<center><img src=\"https://github.com/Lightning-AI/lightning-tutorials/raw/main/course_UvA-DL/09-normalizing-flows/Squeeze_operation.svg\" width=\"40%\"/></center>\n", "\n", "The input of $4\\times 4\\times 1$ is scaled to $2\\times 2\\times 4$ following\n", "the idea of grouping the pixels in $2\\times 2\\times 1$ subsquares.\n", "Next, let's try to implement this layer:"]}, {"cell_type": "code", "execution_count": 19, "id": "1ae89a3f", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:55.458800Z", "iopub.status.busy": "2023-03-14T16:08:55.458447Z", "iopub.status.idle": "2023-03-14T16:08:55.467921Z", "shell.execute_reply": "2023-03-14T16:08:55.467065Z"}, "papermill": {"duration": 0.030217, "end_time": "2023-03-14T16:08:55.470193", "exception": false, "start_time": "2023-03-14T16:08:55.439976", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class SqueezeFlow(nn.Module):\n", " def forward(self, z, ldj, reverse=False):\n", " B, C, H, W = z.shape\n", " if not reverse:\n", " # Forward direction: H x W x C => H/2 x W/2 x 4C\n", " z = z.reshape(B, C, H // 2, 2, W // 2, 2)\n", " z = z.permute(0, 1, 3, 5, 2, 4)\n", " z = z.reshape(B, 4 * C, H // 2, W // 2)\n", " else:\n", " # Reverse direction: H/2 x W/2 x 4C => H x W x C\n", " z = z.reshape(B, C // 4, 2, 2, H, W)\n", " z = z.permute(0, 1, 4, 2, 5, 3)\n", " z = z.reshape(B, C // 4, H * 2, W * 2)\n", " return z, ldj"]}, {"cell_type": "markdown", "id": "414c6bf6", "metadata": {"papermill": {"duration": 0.017403, "end_time": "2023-03-14T16:08:55.508292", "exception": false, "start_time": "2023-03-14T16:08:55.490889", "status": "completed"}, "tags": []}, "source": ["Before moving on, we can verify our implementation by comparing our output with the example figure above:"]}, {"cell_type": "code", "execution_count": 20, "id": "c1f0cc17", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:55.544965Z", "iopub.status.busy": "2023-03-14T16:08:55.544742Z", "iopub.status.idle": "2023-03-14T16:08:55.551366Z", "shell.execute_reply": "2023-03-14T16:08:55.550861Z"}, "papermill": {"duration": 0.026587, "end_time": "2023-03-14T16:08:55.552899", "exception": false, "start_time": "2023-03-14T16:08:55.526312", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Image (before)\n", " tensor([[[[ 1, 2, 3, 4],\n", " [ 5, 6, 7, 8],\n", " [ 9, 10, 11, 12],\n", " [13, 14, 15, 16]]]])\n", "\n", "Image (forward)\n", " tensor([[[[ 1, 2, 5, 6],\n", " [ 3, 4, 7, 8]],\n", "\n", " [[ 9, 10, 13, 14],\n", " [11, 12, 15, 16]]]])\n", "\n", "Image (reverse)\n", " tensor([[[[ 1, 2, 3, 4],\n", " [ 5, 6, 7, 8],\n", " [ 9, 10, 11, 12],\n", " [13, 14, 15, 16]]]])\n"]}], "source": ["sq_flow = SqueezeFlow()\n", "rand_img = torch.arange(1, 17).view(1, 1, 4, 4)\n", "print(\"Image (before)\\n\", rand_img)\n", "forward_img, _ = sq_flow(rand_img, ldj=None, reverse=False)\n", "print(\"\\nImage (forward)\\n\", forward_img.permute(0, 2, 3, 1)) # Permute for readability\n", "reconst_img, _ = sq_flow(forward_img, ldj=None, reverse=True)\n", "print(\"\\nImage (reverse)\\n\", reconst_img)"]}, {"cell_type": "markdown", "id": "b64f0fc8", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.017584, "end_time": "2023-03-14T16:08:55.591185", "exception": false, "start_time": "2023-03-14T16:08:55.573601", "status": "completed"}, "tags": []}, "source": ["The split operation divides the input into two parts, and evaluates one part directly on the prior.\n", "So that our flow operation fits to the implementation of the previous layers,\n", "we will return the prior probability of the first part as the log determinant jacobian of the layer.\n", "It has the same effect as if we would combine all variable splits at the\n", "end of the flow, and evaluate them together on the prior."]}, {"cell_type": "code", "execution_count": 21, "id": "e144a578", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:55.628014Z", "iopub.status.busy": "2023-03-14T16:08:55.627560Z", "iopub.status.idle": "2023-03-14T16:08:55.634432Z", "shell.execute_reply": "2023-03-14T16:08:55.633786Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.027109, "end_time": "2023-03-14T16:08:55.636027", "exception": false, "start_time": "2023-03-14T16:08:55.608918", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class SplitFlow(nn.Module):\n", " def __init__(self):\n", " super().__init__()\n", " self.prior = torch.distributions.normal.Normal(loc=0.0, scale=1.0)\n", "\n", " def forward(self, z, ldj, reverse=False):\n", " if not reverse:\n", " z, z_split = z.chunk(2, dim=1)\n", " ldj += self.prior.log_prob(z_split).sum(dim=[1, 2, 3])\n", " else:\n", " z_split = self.prior.sample(sample_shape=z.shape).to(device)\n", " z = torch.cat([z, z_split], dim=1)\n", " ldj -= self.prior.log_prob(z_split).sum(dim=[1, 2, 3])\n", " return z, ldj"]}, {"cell_type": "markdown", "id": "63b1fe64", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.017596, "end_time": "2023-03-14T16:08:55.676678", "exception": false, "start_time": "2023-03-14T16:08:55.659082", "status": "completed"}, "tags": []}, "source": ["### Building a multi-scale flow\n", "\n", "After defining the squeeze and split operation, we are finally able to build our own multi-scale flow.\n", "Deep normalizing flows such as Glow and Flow++ [2,3] often apply a split operation directly after squeezing.\n", "However, with shallow flows, we need to be more thoughtful about where to place the split operation as we need at least a minimum amount of transformations on each variable.\n", "Our setup is inspired by the original RealNVP architecture [1] which is shallower than other,\n", "more recent state-of-the-art architectures.\n", "\n", "Hence, for the MNIST dataset, we will apply the first squeeze operation after two coupling layers, but don't apply a split operation yet.\n", "Because we have only used two coupling layers and each the variable has been only transformed once, a split operation would be too early.\n", "We apply two more coupling layers before finally applying a split flow and squeeze again.\n", "The last four coupling layers operate on a scale of $7\\times 7\\times 8$.\n", "The full flow architecture is shown below.\n", "\n", "<center width=\"100%\" style=\"padding: 20px\"><img src=\"https://github.com/Lightning-AI/lightning-tutorials/raw/main/course_UvA-DL/09-normalizing-flows/multiscale_flow.svg\" width=\"1100px\"></center>\n", "\n", "Note that while the feature maps inside the coupling layers reduce with the height and width of the input,\n", "the increased number of channels is not directly considered.\n", "To counteract this, we increase the hidden dimensions for the coupling layers on the squeezed input.\n", "The dimensions are often scaled by 2 as this approximately increases the computation cost by 4 canceling with the squeezing operation.\n", "However, we will choose the hidden dimensionalities $32, 48, 64$ for the\n", "three scales respectively to keep the number of parameters reasonable\n", "and show the efficiency of multi-scale architectures."]}, {"cell_type": "code", "execution_count": 22, "id": "f65414af", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:55.713291Z", "iopub.status.busy": "2023-03-14T16:08:55.712818Z", "iopub.status.idle": "2023-03-14T16:08:55.723271Z", "shell.execute_reply": "2023-03-14T16:08:55.722130Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.031541, "end_time": "2023-03-14T16:08:55.725764", "exception": false, "start_time": "2023-03-14T16:08:55.694223", "status": "completed"}, "tags": []}, "outputs": [], "source": ["def create_multiscale_flow():\n", " flow_layers = []\n", "\n", " vardeq_layers = [\n", " CouplingLayer(\n", " network=GatedConvNet(c_in=2, c_out=2, c_hidden=16),\n", " mask=create_checkerboard_mask(h=28, w=28, invert=(i % 2 == 1)),\n", " c_in=1,\n", " )\n", " for i in range(4)\n", " ]\n", " flow_layers += [VariationalDequantization(vardeq_layers)]\n", "\n", " flow_layers += [\n", " CouplingLayer(\n", " network=GatedConvNet(c_in=1, c_hidden=32),\n", " mask=create_checkerboard_mask(h=28, w=28, invert=(i % 2 == 1)),\n", " c_in=1,\n", " )\n", " for i in range(2)\n", " ]\n", " flow_layers += [SqueezeFlow()]\n", " for i in range(2):\n", " flow_layers += [\n", " CouplingLayer(\n", " network=GatedConvNet(c_in=4, c_hidden=48), mask=create_channel_mask(c_in=4, invert=(i % 2 == 1)), c_in=4\n", " )\n", " ]\n", " flow_layers += [SplitFlow(), SqueezeFlow()]\n", " for i in range(4):\n", " flow_layers += [\n", " CouplingLayer(\n", " network=GatedConvNet(c_in=8, c_hidden=64), mask=create_channel_mask(c_in=8, invert=(i % 2 == 1)), c_in=8\n", " )\n", " ]\n", "\n", " flow_model = ImageFlow(flow_layers).to(device)\n", " return flow_model"]}, {"cell_type": "markdown", "id": "4d5371d1", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.017539, "end_time": "2023-03-14T16:08:55.765523", "exception": false, "start_time": "2023-03-14T16:08:55.747984", "status": "completed"}, "tags": []}, "source": ["We can show the difference in number of parameters below:"]}, {"cell_type": "code", "execution_count": 23, "id": "3fd1623f", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:55.802358Z", "iopub.status.busy": "2023-03-14T16:08:55.801981Z", "iopub.status.idle": "2023-03-14T16:08:57.208234Z", "shell.execute_reply": "2023-03-14T16:08:57.207398Z"}, "papermill": {"duration": 1.426841, "end_time": "2023-03-14T16:08:57.209967", "exception": false, "start_time": "2023-03-14T16:08:55.783126", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Number of parameters: 556,312\n", "Number of parameters: 628,388\n", "Number of parameters: 1,711,818\n"]}], "source": ["def print_num_params(model):\n", " num_params = sum(np.prod(p.shape) for p in model.parameters())\n", " print(f\"Number of parameters: {num_params:,}\")\n", "\n", "\n", "print_num_params(create_simple_flow(use_vardeq=False))\n", "print_num_params(create_simple_flow(use_vardeq=True))\n", "print_num_params(create_multiscale_flow())"]}, {"cell_type": "markdown", "id": "ee63fa46", "metadata": {"papermill": {"duration": 0.028226, "end_time": "2023-03-14T16:08:57.262815", "exception": false, "start_time": "2023-03-14T16:08:57.234589", "status": "completed"}, "tags": []}, "source": ["Although the multi-scale flow has almost 3 times the parameters of the single scale flow,\n", "it is not necessarily more computationally expensive than its counterpart.\n", "We will compare the runtime in the following experiments as well."]}, {"cell_type": "markdown", "id": "fa5919dc", "metadata": {"papermill": {"duration": 0.017593, "end_time": "2023-03-14T16:08:57.301622", "exception": false, "start_time": "2023-03-14T16:08:57.284029", "status": "completed"}, "tags": []}, "source": ["## Analysing the flows\n", "\n", "In the last part of the notebook, we will train all the models we have implemented above,\n", "and try to analyze the effect of the multi-scale architecture and variational dequantization.\n", "\n", "### Training flow variants\n", "\n", "Before we can analyse the flow models, we need to train them first.\n", "We provide pre-trained models that contain the validation and test performance, and run-time information.\n", "As flow models are computationally expensive, we advice you to rely on\n", "those pretrained models for a first run through the notebook."]}, {"cell_type": "code", "execution_count": 24, "id": "655f8984", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:57.338023Z", "iopub.status.busy": "2023-03-14T16:08:57.337827Z", "iopub.status.idle": "2023-03-14T16:08:57.789595Z", "shell.execute_reply": "2023-03-14T16:08:57.788785Z"}, "papermill": {"duration": 0.472976, "end_time": "2023-03-14T16:08:57.792209", "exception": false, "start_time": "2023-03-14T16:08:57.319233", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["GPU available: True (cuda), used: True\n"]}, {"name": "stderr", "output_type": "stream", "text": ["TPU available: False, using: 0 TPU cores\n"]}, {"name": "stderr", "output_type": "stream", "text": ["IPU available: False, using: 0 IPUs\n"]}, {"name": "stderr", "output_type": "stream", "text": ["HPU available: False, using: 0 HPUs\n"]}, {"name": "stderr", "output_type": "stream", "text": ["GPU available: True (cuda), used: True\n"]}, {"name": "stderr", "output_type": "stream", "text": ["TPU available: False, using: 0 TPU cores\n"]}, {"name": "stderr", "output_type": "stream", "text": ["IPU available: False, using: 0 IPUs\n"]}, {"name": "stderr", "output_type": "stream", "text": ["HPU available: False, using: 0 HPUs\n"]}, {"name": "stderr", "output_type": "stream", "text": ["GPU available: True (cuda), used: True\n"]}, {"name": "stderr", "output_type": "stream", "text": ["TPU available: False, using: 0 TPU cores\n"]}, {"name": "stderr", "output_type": "stream", "text": ["IPU available: False, using: 0 IPUs\n"]}, {"name": "stderr", "output_type": "stream", "text": ["HPU available: False, using: 0 HPUs\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Found pretrained model, loading...\n", "Found pretrained model, loading...\n", "Found pretrained model, loading...\n"]}], "source": ["flow_dict = {\"simple\": {}, \"vardeq\": {}, \"multiscale\": {}}\n", "flow_dict[\"simple\"][\"model\"], flow_dict[\"simple\"][\"result\"] = train_flow(\n", " create_simple_flow(use_vardeq=False), model_name=\"MNISTFlow_simple\"\n", ")\n", "flow_dict[\"vardeq\"][\"model\"], flow_dict[\"vardeq\"][\"result\"] = train_flow(\n", " create_simple_flow(use_vardeq=True), model_name=\"MNISTFlow_vardeq\"\n", ")\n", "flow_dict[\"multiscale\"][\"model\"], flow_dict[\"multiscale\"][\"result\"] = train_flow(\n", " create_multiscale_flow(), model_name=\"MNISTFlow_multiscale\"\n", ")"]}, {"cell_type": "markdown", "id": "f704f49e", "metadata": {"papermill": {"duration": 0.017977, "end_time": "2023-03-14T16:08:57.833000", "exception": false, "start_time": "2023-03-14T16:08:57.815023", "status": "completed"}, "tags": []}, "source": ["### Density modeling and sampling\n", "\n", "Firstly, we can compare the models on their quantitative results.\n", "The following table shows all important statistics.\n", "The inference time specifies the time needed to determine the\n", "probability for a batch of 64 images for each model, and the sampling\n", "time the duration it took to sample a batch of 64 images."]}, {"cell_type": "code", "execution_count": 25, "id": "5e593b47", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:57.870186Z", "iopub.status.busy": "2023-03-14T16:08:57.869973Z", "iopub.status.idle": "2023-03-14T16:08:57.878622Z", "shell.execute_reply": "2023-03-14T16:08:57.878204Z"}, "papermill": {"duration": 0.029186, "end_time": "2023-03-14T16:08:57.880201", "exception": false, "start_time": "2023-03-14T16:08:57.851015", "status": "completed"}, "tags": []}, "outputs": [{"data": {"text/html": ["<!-- Some HTML code to increase font size in the following table -->\n", "<style>\n", "th {font-size: 120%;}\n", "td {font-size: 120%;}\n", "</style>\n"], "text/plain": ["<IPython.core.display.HTML object>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["%%html\n", "<!-- Some HTML code to increase font size in the following table -->\n", "<style>\n", "th {font-size: 120%;}\n", "td {font-size: 120%;}\n", "</style>"]}, {"cell_type": "code", "execution_count": 26, "id": "80d4f2a9", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:57.922444Z", "iopub.status.busy": "2023-03-14T16:08:57.922013Z", "iopub.status.idle": "2023-03-14T16:08:57.936216Z", "shell.execute_reply": "2023-03-14T16:08:57.935832Z"}, "papermill": {"duration": 0.035789, "end_time": "2023-03-14T16:08:57.938405", "exception": false, "start_time": "2023-03-14T16:08:57.902616", "status": "completed"}, "tags": []}, "outputs": [{"data": {"text/html": ["<table>\n", "<thead>\n", "<tr><th>Model </th><th>Validation Bpd </th><th>Test Bpd </th><th>Inference time </th><th>Sampling time </th><th>Num Parameters </th></tr>\n", "</thead>\n", "<tbody>\n", "<tr><td>simple </td><td>1.080 bpd </td><td>1.078 bpd </td><td>20 ms </td><td>18 ms </td><td>556,312 </td></tr>\n", "<tr><td>vardeq </td><td>1.045 bpd </td><td>1.043 bpd </td><td>26 ms </td><td>18 ms </td><td>628,388 </td></tr>\n", "<tr><td>multiscale</td><td>1.022 bpd </td><td>1.020 bpd </td><td>23 ms </td><td>15 ms </td><td>1,711,818 </td></tr>\n", "</tbody>\n", "</table>"], "text/plain": ["<IPython.core.display.HTML object>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["\n", "table = [\n", " [\n", " key,\n", " \"%4.3f bpd\" % flow_dict[key][\"result\"][\"val\"][0][\"test_bpd\"],\n", " \"%4.3f bpd\" % flow_dict[key][\"result\"][\"test\"][0][\"test_bpd\"],\n", " \"%2.0f ms\" % (1000 * flow_dict[key][\"result\"][\"time\"]),\n", " \"%2.0f ms\" % (1000 * flow_dict[key][\"result\"].get(\"samp_time\", 0)),\n", " \"{:,}\".format(sum(np.prod(p.shape) for p in flow_dict[key][\"model\"].parameters())),\n", " ]\n", " for key in flow_dict\n", "]\n", "display(\n", " HTML(\n", " tabulate.tabulate(\n", " table,\n", " tablefmt=\"html\",\n", " headers=[\"Model\", \"Validation Bpd\", \"Test Bpd\", \"Inference time\", \"Sampling time\", \"Num Parameters\"],\n", " )\n", " )\n", ")"]}, {"cell_type": "markdown", "id": "b4bc8486", "metadata": {"papermill": {"duration": 0.018627, "end_time": "2023-03-14T16:08:57.980586", "exception": false, "start_time": "2023-03-14T16:08:57.961959", "status": "completed"}, "tags": []}, "source": ["As we have intially expected, using variational dequantization improves upon standard dequantization in terms of bits per dimension.\n", "Although the difference with 0.04bpd doesn't seem impressive first, it is a considerably step for generative models\n", "(most state-of-the-art models improve upon previous models in a range of 0.02-0.1bpd on CIFAR with three times as high bpd).\n", "While it takes longer to evaluate the probability of an image due to the variational dequantization,\n", "which also leads to a longer training time, it does not have an effect on the sampling time.\n", "This is because inverting variational dequantization is the same as dequantization: finding the next lower integer.\n", "\n", "When we compare the two models to multi-scale architecture, we can see that the bits per dimension score again dropped by about 0.04bpd.\n", "Additionally, the inference time and sampling time improved notably despite having more parameters.\n", "Thus, we see that the multi-scale flow is not only stronger for density modeling, but also more efficient.\n", "\n", "Next, we can test the sampling quality of the models.\n", "We should note that the samples for variational dequantization and standard dequantization are very similar,\n", "and hence we visualize here only the ones for variational dequantization and the multi-scale model.\n", "However, feel free to also test out the `\"simple\"` model.\n", "The seeds are set to obtain reproducable generations and are not cherry picked."]}, {"cell_type": "code", "execution_count": 27, "id": "e1cbb1be", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:08:58.019235Z", "iopub.status.busy": "2023-03-14T16:08:58.018946Z", "iopub.status.idle": "2023-03-14T16:09:00.213140Z", "shell.execute_reply": "2023-03-14T16:09:00.212673Z"}, "papermill": {"duration": 2.214889, "end_time": "2023-03-14T16:09:00.214392", "exception": false, "start_time": "2023-03-14T16:08:57.999503", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Global seed set to 44\n"]}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"347.04pt\" height=\"347.04pt\" viewBox=\"0 0 347.04 347.04\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:00.147318</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 347.04 \n", "L 347.04 347.04 \n", "L 347.04 -0 \n", "L 0 -0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#p98af48a74d)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image396079d911\" transform=\"scale(1 -1) translate(0 -333.36)\" x=\"7.2\" y=\"-6.48\" width=\"332.64\" height=\"333.36\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p98af48a74d\">\n", " <rect x=\"7.2\" y=\"7.2\" width=\"332.64\" height=\"332.64\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 600x600 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["L.seed_everything(44)\n", "samples = flow_dict[\"vardeq\"][\"model\"].sample(img_shape=[16, 1, 28, 28])\n", "show_imgs(samples.cpu())"]}, {"cell_type": "code", "execution_count": 28, "id": "e60cb58e", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:09:00.254458Z", "iopub.status.busy": "2023-03-14T16:09:00.254291Z", "iopub.status.idle": "2023-03-14T16:09:00.375395Z", "shell.execute_reply": "2023-03-14T16:09:00.374906Z"}, "papermill": {"duration": 0.142231, "end_time": "2023-03-14T16:09:00.376562", "exception": false, "start_time": "2023-03-14T16:09:00.234331", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Global seed set to 44\n"]}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"347.04pt\" height=\"347.04pt\" viewBox=\"0 0 347.04 347.04\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:00.310180</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 347.04 \n", "L 347.04 347.04 \n", "L 347.04 -0 \n", "L 0 -0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#pe88a2625e2)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image4fc24825f2\" transform=\"scale(1 -1) translate(0 -333.36)\" x=\"7.2\" y=\"-6.48\" width=\"332.64\" height=\"333.36\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"pe88a2625e2\">\n", " <rect x=\"7.2\" y=\"7.2\" width=\"332.64\" height=\"332.64\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 600x600 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["L.seed_everything(44)\n", "samples = flow_dict[\"multiscale\"][\"model\"].sample(img_shape=[16, 8, 7, 7])\n", "show_imgs(samples.cpu())"]}, {"cell_type": "markdown", "id": "9c6d84f7", "metadata": {"papermill": {"duration": 0.019612, "end_time": "2023-03-14T16:09:00.415899", "exception": false, "start_time": "2023-03-14T16:09:00.396287", "status": "completed"}, "tags": []}, "source": ["From the few samples, we can see a clear difference between the simple and the multi-scale model.\n", "The single-scale model has only learned local, small correlations while the multi-scale model was able to learn full,\n", "global relations that form digits.\n", "This show-cases another benefit of the multi-scale model.\n", "In contrast to VAEs, the outputs are sharp as normalizing flows can naturally model complex,\n", "multi-modal distributions while VAEs have the independent decoder output noise.\n", "Nevertheless, the samples from this flow are far from perfect as not all samples show true digits."]}, {"cell_type": "markdown", "id": "944d6269", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.019671, "end_time": "2023-03-14T16:09:00.455179", "exception": false, "start_time": "2023-03-14T16:09:00.435508", "status": "completed"}, "tags": []}, "source": ["### Interpolation in latent space\n", "\n", "Another popular test for the smoothness of the latent space of generative models is to interpolate between two training examples.\n", "As normalizing flows are strictly invertible, we can guarantee that any image is represented in the latent space.\n", "We again compare the variational dequantization model with the multi-scale model below."]}, {"cell_type": "code", "execution_count": 29, "id": "7970cd2a", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:09:00.495723Z", "iopub.status.busy": "2023-03-14T16:09:00.495365Z", "iopub.status.idle": "2023-03-14T16:09:00.530122Z", "shell.execute_reply": "2023-03-14T16:09:00.529642Z"}, "papermill": {"duration": 0.056622, "end_time": "2023-03-14T16:09:00.531336", "exception": false, "start_time": "2023-03-14T16:09:00.474714", "status": "completed"}, "tags": []}, "outputs": [], "source": ["@torch.no_grad()\n", "def interpolate(model, img1, img2, num_steps=8):\n", " \"\"\"\n", " Args:\n", " model: object of ImageFlow class that represents the (trained) flow model\n", " img1, img2: Image tensors of shape [1, 28, 28]. Images between which should be interpolated.\n", " num_steps: Number of interpolation steps. 8 interpolation steps mean 6 intermediate pictures besides img1 and img2\n", " \"\"\"\n", " imgs = torch.stack([img1, img2], dim=0).to(model.device)\n", " z, _ = model.encode(imgs)\n", " alpha = torch.linspace(0, 1, steps=num_steps, device=z.device).view(-1, 1, 1, 1)\n", " interpolations = z[0:1] * alpha + z[1:2] * (1 - alpha)\n", " interp_imgs = model.sample(interpolations.shape[:1] + imgs.shape[1:], z_init=interpolations)\n", " show_imgs(interp_imgs, row_size=8)\n", "\n", "\n", "exmp_imgs, _ = next(iter(train_loader))"]}, {"cell_type": "code", "execution_count": 30, "id": "2e17956c", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:09:00.571381Z", "iopub.status.busy": "2023-03-14T16:09:00.571218Z", "iopub.status.idle": "2023-03-14T16:09:00.781262Z", "shell.execute_reply": "2023-03-14T16:09:00.780473Z"}, "papermill": {"duration": 0.231591, "end_time": "2023-03-14T16:09:00.782599", "exception": false, "start_time": "2023-03-14T16:09:00.551008", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Global seed set to 42\n"]}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"643.2975pt\" height=\"97.56pt\" viewBox=\"0 0 643.2975 97.56\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:00.640028</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 97.56 \n", "L 643.2975 97.56 \n", "L 643.2975 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#p82959a0854)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image97226e550f\" transform=\"scale(1 -1) translate(0 -83.52)\" x=\"7.2\" y=\"-6.84\" width=\"629.28\" height=\"83.52\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p82959a0854\">\n", " <rect x=\"7.2\" y=\"7.2\" width=\"628.8975\" height=\"83.16\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 1200x150 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"643.2975pt\" height=\"97.56pt\" viewBox=\"0 0 643.2975 97.56\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:00.743094</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 97.56 \n", "L 643.2975 97.56 \n", "L 643.2975 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#p845b65d645)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image79ad4fd30c\" transform=\"scale(1 -1) translate(0 -83.52)\" x=\"7.2\" y=\"-6.84\" width=\"629.28\" height=\"83.52\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p845b65d645\">\n", " <rect x=\"7.2\" y=\"7.2\" width=\"628.8975\" height=\"83.16\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 1200x150 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["L.seed_everything(42)\n", "for i in range(2):\n", " interpolate(flow_dict[\"vardeq\"][\"model\"], exmp_imgs[2 * i], exmp_imgs[2 * i + 1])"]}, {"cell_type": "code", "execution_count": 31, "id": "3ca1ae47", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:09:00.828856Z", "iopub.status.busy": "2023-03-14T16:09:00.828634Z", "iopub.status.idle": "2023-03-14T16:09:01.038969Z", "shell.execute_reply": "2023-03-14T16:09:01.038355Z"}, "papermill": {"duration": 0.236091, "end_time": "2023-03-14T16:09:01.041318", "exception": false, "start_time": "2023-03-14T16:09:00.805227", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Global seed set to 42\n"]}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"643.2975pt\" height=\"97.56pt\" viewBox=\"0 0 643.2975 97.56\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:00.902316</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 97.56 \n", "L 643.2975 97.56 \n", "L 643.2975 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#p239c71d8ba)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image0a678695ab\" transform=\"scale(1 -1) translate(0 -83.52)\" x=\"7.2\" y=\"-6.84\" width=\"629.28\" height=\"83.52\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p239c71d8ba\">\n", " <rect x=\"7.2\" y=\"7.2\" width=\"628.8975\" height=\"83.16\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 1200x150 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"643.2975pt\" height=\"97.56pt\" viewBox=\"0 0 643.2975 97.56\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:01.001884</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 97.56 \n", "L 643.2975 97.56 \n", "L 643.2975 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#ped89224d06)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image1400979f3c\" transform=\"scale(1 -1) translate(0 -83.52)\" x=\"7.2\" y=\"-6.84\" width=\"629.28\" height=\"83.52\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"ped89224d06\">\n", " <rect x=\"7.2\" y=\"7.2\" width=\"628.8975\" height=\"83.16\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 1200x150 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["L.seed_everything(42)\n", "for i in range(2):\n", " interpolate(flow_dict[\"multiscale\"][\"model\"], exmp_imgs[2 * i], exmp_imgs[2 * i + 1])"]}, {"cell_type": "markdown", "id": "648f4caa", "metadata": {"papermill": {"duration": 0.020808, "end_time": "2023-03-14T16:09:01.086975", "exception": false, "start_time": "2023-03-14T16:09:01.066167", "status": "completed"}, "tags": []}, "source": ["The interpolations of the multi-scale model result in more realistic digits\n", "(first row $7\\leftrightarrow 8\\leftrightarrow 6$, second row $9\\leftrightarrow 4\\leftrightarrow 6$),\n", "while the variational dequantization model focuses on local patterns that globally do not form a digit.\n", "For the multi-scale model, we actually did not do the \"true\" interpolation between the two images\n", "as we did not consider the variables that were split along the flow (they have been sampled randomly for all samples).\n", "However, as we will see in the next experiment, the early variables do not effect the overall image much."]}, {"cell_type": "markdown", "id": "2628a523", "metadata": {"papermill": {"duration": 0.020664, "end_time": "2023-03-14T16:09:01.128363", "exception": false, "start_time": "2023-03-14T16:09:01.107699", "status": "completed"}, "tags": []}, "source": ["### Visualization of latents in different levels of multi-scale\n", "\n", "In the following we will focus more on the multi-scale flow.\n", "We want to analyse what information is being stored in the variables split at early layers,\n", "and what information for the final variables.\n", "For this, we sample 8 images where each of them share the same final latent variables,\n", "but differ in the other part of the latent variables.\n", "Below we visualize three examples of this:"]}, {"cell_type": "code", "execution_count": 32, "id": "52225998", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:09:01.171113Z", "iopub.status.busy": "2023-03-14T16:09:01.170822Z", "iopub.status.idle": "2023-03-14T16:09:01.406005Z", "shell.execute_reply": "2023-03-14T16:09:01.405490Z"}, "papermill": {"duration": 0.259501, "end_time": "2023-03-14T16:09:01.408520", "exception": false, "start_time": "2023-03-14T16:09:01.149019", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Global seed set to 44\n"]}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"341.674839pt\" height=\"180.72pt\" viewBox=\"0 0 341.674839 180.72\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:01.214433</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 180.72 \n", "L 341.674839 180.72 \n", "L 341.674839 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#p9835edab5b)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "iVBORw0KGgoAAAANSUhEUgAAAccAAADnCAYAAABrJ50wAAAchklEQVR4nO3deZCVxdXH8UZkkUXWAQIaNkEWZSegIMUYCbtAgmiIiAQikIpoJbgEsTKBgIAGRIFETUIhopEApQEEghEBCSIBIiKChk02WWUVkMX3j/d92z6/4T5z78DM3Mt8P3+dU32XLh7udD19nu4ukJGR8Y0DAADeVXndAQAAkg2DIwAAgsERAADB4AgAgGBwBABAMDgCACCujmrMyMjIpW4gu6KuEdcv+XH9UhvXL7VFXSPuHAEAEAyOAAAIBkcAAASDIwAAgsERAADB4AgAgGBwBABARK5zTAUVKlQwed26dU3eoEEDk589e9bHf//7303bnj17LnPvgCtbiRIlTN6pU6eY7dOnTzdt4W8ReaNw4cIm/9WvfmXyUqVK+bhgwYKmbd26dSZ/9dVXL3Pv8hZ3jgAACAZHAAAEgyMAACIla45hHWP27Nmm7dZbbzV5gQIFYn7OiBEjTD537lyTv/jiiyZftWpVQv3ExZUtW9bHCxYsMG3NmzeP+3PWrl1r8hUrVpg8/L+xbNmyRLqICKVLl/bx/PnzTVvLli1NHv7+/vSnP5k2rfGPHj3a5B999JGPly9fnq2+wgpriM45t3r1apPXrFnT5OH1++abb0zbuXPnTP7FF1+YfPPmzT7evXt34p3NY9w5AgAgGBwBABApOa06aNAgH7dq1SrytTp1c/z4cR/feOONpu2nP/2pyXWK7/777/exTukhfm+88YaPmzVrFvnaIUOGmLxq1ao+1sfOmzRpYvI+ffr4uHXr1qZt48aNcfUVmc2YMcPHt9xyS+Rrhw8f7uOBAweatuuuu87kzz//vMnDaboePXqYtg8++CC+zsL4wx/+YPIaNWqYXKdODx8+7OOrr7bDRcmSJU2+aNEik0+aNMnHem23bt0aZ4/zDneOAAAIBkcAAASDIwAAIiVqjhUrVjT5Qw895GOdI9dHhuvXr2/ya6+91sc6/96lS5fI97700ks+btq0aVbdxv8pV66cyevVqxfztR9++KHJJ0+ebPLw+hUpUsS0/eIXvzB5+Nj6lClTTFvbtm1jdxiGLoe64YYbfKy/v23btpl8zJgxPtZlV6+99prJGzVqZPJKlSr5+De/+Y1p69y5cxa9xsW0b9/e5Hpt9+/fb/IWLVr4+NSpU6Zt6dKlJq9Tp47Jw7/T+ntr3LhxfB3OQ9w5AgAgGBwBABAMjgAAiJSoOZ4+fTpmrjWPkydPmjxc16j5nDlzTJtufaW1soYNG140di5zrQzf0vVQ4fZxKtyazLnM1/fo0aM+Dmsaztn1r87ZI3bC9ZFIjF6DQoUKxXxtWlqayS9cuODjcDsx55wbPHiwyZcsWWLysKZcq1Yt0xbWI53LvHUZLk7/PpYpU8bk4XMVzjn3+eefx/ysJ5980uSvvPKKycPjsGrXrm3avvOd75h87969Mb8nr3DnCACAYHAEAEAwOAIAIFKi5hjWmZxz7t133/Vx9erVTZvm7dq1M/nixYt9PHPmTNP285//3ORacwzXBB08eDCLXuP/bd++3eQTJ0708YMPPmjadL/N7t27mzzcl1VrYUeOHDF5eP0qV65s2m6++WaTh8cjIdqBAwd8rNerWLFiJg/XDs+bN8+06f6oW7ZsMXm4HlaPUqpSpYrJqTnGR/+fV6hQweRaxw+vmV4vfWZj/fr1Jg/3TS5atKhp0/831BwBAEgBDI4AAIiUmFZV4SP7V11lx/e+ffuaXB8ZDp09e9bk+/bti7sP4XFIztltshDtkUce8bFOl+kWfjotHk6rKt0KK6TH7YwdO9bknTp1ivleWOGWYnqSvB4bFh4Lp9OqOi2+c+dOk4fTqnpttXyyZs2arLoNl3nbPf13023dwqlTnQrNauvAqOPoxo0bZ/L09PSYr80r3DkCACAYHAEAEAyOAACIlKw5nj9/3sd6lE3x4sVN/r3vfc/kL7/8so/PnTtn2nQpQJTy5cvH/VpY4b+7LuUIt5xyLvOxOFF0m8GwJqI1qxMnTsT9uYjtnnvuMfmECRNMvnXr1mx/tta0QlFb2CF+9957r8lHjhxpcj1WLIpu0Rj1+9NnRZJR8vcQAIBcxuAIAIBgcAQAQKRkzTG0a9cuk2sNRGtY4TFGeuRK79694/7eM2fOxP1axLZjxw6Td+jQIe736jE4etxV1LrHN998M+7vQWy65dudd94Z93u17qS/qajrx+/v8vjkk09M3rNnz7jfq2vKteaYyLrjZMSdIwAAgsERAACR/Pe2l+ixxx4z+e233+7jqK3lsqLLQJAzhg0bZvJwe7lSpUqZNj0RIkoqPEp+JWjZsqWPH374YdN24cIFk3fr1s3kUUs59JQH5Ixwq0c9IUe3fkxLS4v7c2fNmnVJ/coN/IUAAEAwOAIAIBgcAQAQKVlzrFixoo9r1Khh2mrVqmXy++67z+T6+kSEdcZNmzZl+3PwrSFDhphctwV7/PHHTa7bA8ZrxowZJp89e3a2PgfWpEmTTK5HHh08eNDHehyZiqoxfv311ybXJSTInqFDh5o8PGLMOed69erl4xIlSmT7e95//32TT5w4MduflVu4cwQAQDA4AgAgGBwBABApUXNMT083+R133OHjRx991LTl5Pq1UaNG+TiRo1zyu7Bu4ZxzDzzwgI/btm1r2qK2nLoUixcvNvlXX32VI99zJdItxcJjxlq3bp0rfdCtHletWpUr33sluOuuu3ysNcZmzZrlSh+mTJlicl3jmoy4cwQAQDA4AgAgGBwBABBJWXOsVKmSyfUYqgEDBuRmd7xL2Ys1P6lQoYLJf/e735lc92TMKWFd4/Tp07nynVcCXUuakZFh8nr16vk4am3ipTp58qSPX3755Rz7nivNzTffbPJwP+ncqjE659zhw4d9vHDhwlz73suFO0cAAASDIwAAIimnVfVom0uZRg2nZpxLbPuxffv2mfy5557Ldj/ykyeeeMLkiUyj6jTd2bNnTR5uL5fVso/w+n388cdx9yG/0y376tata/JEplLDqe1El1mFy21S4eT4ZNG/f3+Th0unclO43WZOTr/nFO4cAQAQDI4AAAgGRwAARNJM5If1iDZt2sT9vl27dpl88uTJJn/hhRdMvmPHDh+XLFky8rN1SUL58uXj7ld+duutt8b92pEjR5pcH9nXJRjPP/+8j7t37x752cWKFfNxWP+Apf+Ow4YNi/u97777rsknTJhg8g0bNvh4zJgxpi3c1uxi0tLSfFy0aNG4+5TfVK5c2eRacwxp7W/EiBEmX7RokcnDo8L02t52222R/dK/n6mGO0cAAASDIwAAgsERAACRNDXHsmXL+rhJkyaRrw3rR+FWVs5lXteoOnXq5ONly5aZNl03p/l1110Xsy0V1/FcLmFtzznn6tevH/n6gwcP+lhrHlkdZbNu3Toft2jRwrTp9n6lSpXy8bXXXhv5ufnZmjVrEnr9zp07fdy5c2fTFrVN37Rp00yuR2FFrVsNf3vOObd169Ys+5lf6G9Gf48hfUZDt3aM+v098sgjJn///ffj7WJKrlPlzhEAAMHgCACAYHAEAEAkzUTwsWPHfKw1kJYtW5q8YMGCPm7durVp03U6Klx39eWXX5q2sO7pXOY6YsOGDX08c+ZM03b+/PnI772SnTlzxuT/+Mc/TN61a1eTh//OjRo1Mm1r166N/K6wRtKgQQPT9qMf/cjk4fXLah/W/Gzv3r0mnzdvnsm7dOli8hIlSvi4WrVqpm3Tpk0xv+ezzz6L/F5drxcK1zzCCo+Gcs65xYsXm7xdu3Y+LlOmjGlr3ry5yVetWhXze7Zt22by/fv3m1yv0dSpU3186tSpmJ+brLhzBABAMDgCACCSZlo13KZo4sSJpk2nVUN/+9vfTK5TeocOHTJ5xYoVfZzVrf6WLVtM/vTTT/s4P0+jKv23GDt2rMl1WjXcKlC3H1u6dKnJP//8c5OHSwV0Sl2Fj5rrtcS3dGs9PZpNp1XDqbmVK1eattmzZ5s8/L9x/Phx06bT8erNN9/0sU4V4lvh307nnBs1apTJw2nVcErcOefefvttk0+fPt3k4ZFxut3miRMnTK7bxYVLrXQ6V/8vJCPuHAEAEAyOAAAIBkcAAETS1BxDui3Ro48+avJx48b5uHjx4qZNj9+JeoQ/qy3fdCs6fWQaF7d69WqTv/XWWybv2LGjj/X6hdv7Xart27f7mGsXv3feecfk6enpJl+yZImPdVu+fv36Zft79fdYq1YtH4dLvRBtxYoVJg+PCnv88cdNm241N3DgwMvWj7p16140di7zswTJiDtHAAAEgyMAAILBEQAAkZQ1R52P/v3vf2/yBx980Md6lE0iwpqUc3YNpHN2qznn8vexVInQdXO6zvG9997zcZEiRUxb48aNTZ5IzfjIkSNxvxex6b/r8uXLTT5+/Hgf6/FyrVq1Mnl4VFFWx7zpcUnly5ePs8cI6b/j8OHDfVypUiXTFm6J6ZxzN910k8kLFSoU83uy+nsYrlPNalvPZMSdIwAAgsERAACRlNOqWQl3ktdHj3XaQHeZ//TTT328fv1605aKO8enonDbt6JFi5q2cKsr5+wJLM45V6dOHR/rtdVpcj1FANmj02d6InyUcuXK+bh69eqmTafBw63KnHOucOHCcX8PYguvX//+/SNfq1t1Dh061Me67OOpp54yuf6Ww/JJKuLOEQAAweAIAIBgcAQAQKRkzfHAgQM+Dk+GR+oJj6Byzrm5c+fmUU+QE8Ij4/T4OCQf3bqzZ8+eedSTvMedIwAAgsERAADB4AgAgGBwBABAMDgCACAYHAEAEAyOAAAIBkcAAASDIwAAgsERAADB4AgAgGBwBABAMDgCACAYHAEAEAyOAAAIBkcAAASDIwAAgsERAABRICMj45u87gQAAMmEO0cAAASDIwAAgsERAADB4AgAgGBwBABAMDgCACCujmrMyMjIpW4gu6KuEdcv+XH9UhvXL7VFXSPuHAEAEAyOAAAIBkcAAASDIwAAgsERAADB4AgAgGBwBABARK5zTEVr1qwxeZEiRUw+aNAgH3/66aembf/+/TnXMVyUXp8uXbqYfPDgwSZfuXKlj5988smc6xjiUqBAAZNXrFjR5E2bNvXxtm3bTNvGjRtzrmOIS/ny5U0+YMAAk48ePdrHb731lmnTv7W6ZvCbb1L7NETuHAEAEAyOAACIlJxWLVOmjI/DaTbnnKtVq5bJddpn6dKlPj548KBpmzx5ssnfffddky9btizhviKztLQ0Hy9fvty0ZXX90tPTfXz//febtgULFpj8hRde8LFOASH7SpUq5eMlS5aYtptvvtnkBQsWjPk5u3btMvmsWbNM/pe//MXHGzZsSLifyKxkyZImX716tcm/+93vxnxvx44dTR7+Fp1z7qqr7L1W+Pdy8eLFCfUzGXDnCACAYHAEAEAwOAIAIFKy5jhhwgQfa41Kvffeeya/7rrrfFy1alXTpo8i61KP73//+z7evXt3XH1F5jpUWKcK68cXc+bMGZN//fXXPq5cubJp08fQO3To4OOf/OQnpk1rnYjfuHHjfNywYUPTpjXi9evX+/jYsWOmrXXr1iZ/+OGHTV6tWrWYbZ9//nm83UWgb9++Jr/++usjXx8uxzh58qRpK168uMmfeOIJkxcrVszHWvM/fPhw1p3NY9w5AgAgGBwBABAMjgAAiJSoOYa1B+dsLUmdPXvW5A888IDJCxcu7OOFCxeatkqVKplc65kzZszwcdu2bWP2AdapU6dMrrWK0N69e01+0003mbxEiRI+njNnjmlr1qyZyatUqeLjxx57zLRRc4xf+Jtxzrm6devGfK2uXbzlllt8HK6PdM5uTeZc5nWr3bp187E+HxBuS4doYV3/0UcfNW1aIz5y5IjJw9+f1v91Xar+TQzrxN27dzdtNWvWjOpyUuDOEQAAweAIAIBgcAQAQKREzVHX14TrpcJ9Op3LXB9p1aqVyf/85z/7eNWqVabtzjvvjOxHWDMJa1/OOXfixInI9+ZnO3fuNHlY7wvXjjqX+fodPXrU5GFNJNx70znnmjRpYvKwnqJ7RpYuXTrm58IK15ZeLA/pEUht2rTx8aJFi0ybHkd2++23mzxcg5cKNapkFf476tpgPVZK/9Z+8cUXMV/7s5/9zOSbNm0yebjXqv6/CNebO5e5Vp0MuHMEAEAwOAIAIFJiWvXAgQMmP3TokI91uqxQoUIm18fHQ/379zf5zJkzTa5HsjRo0MDHderUMW3//ve/Y35PfqePgJ8+fdrHOlVTtmxZk//whz80+ezZs308bdo003bXXXeZPHy0vH79+qZNt81iWjV+UVNtOi0eLofSaVX9f3Hu3LmY36nLf1q0aGFyLZHgW+EWfrr8qUePHibX5WydO3f28bx580zbli1bTL5582aTh0t+tAylvz+mVQEASAEMjgAACAZHAABEStQcVbglVbg0w7nMW1D94Ac/MPn48eN9/OWXX5q2q6+2/xxaTwmXBoTHZjnn3G233ZZFr/H/evbs6WOtY+jSjt69e5s8rDnqtnThETlZ0WO0Pvroo7jfm9/169fPxxcuXDBter10qVWUokWLxmwLlwU459yQIUNMrkeS4eJ69epl8o0bN5r8xhtvNLku/Yii1yhKu3btTL5y5cq435tbuHMEAEAwOAIAIBgcAQAQKVlzDD311FMm1/U0x48fj/lerSkqPc4lFLUmC9HC7cfuu+8+06Y15LDGmJXz58+bPLy+ei2HDx9u8ldffTXu78nvwmPhfvvb35o2rRtGbTWnNf61a9eaPFxjp3Q9JbKna9euJv/1r39t8qi/gSpcv+xc9O8vkVpmXuHOEQAAweAIAIBI+WnV//73vya/++67TR6egu2cvb1v3769adMtjaLs378/7tcitnArMucyT6Xp1FuoefPmJtetBKOmhK655pp4u4gIuoWYLhUITZ061eStW7c2uZ68EVX2KFKkSLxdRAS9foMGDTJ5uFSnYMGCpu3HP/6xyWvUqGHyqN+fTsEmI+4cAQAQDI4AAAgGRwAARMrXHLPSp08fk4enjTdu3Ni06enUUZJxu6Mr0cCBA00e1pS1xlilSpW4P3fUqFGX1jHE5cUXX/Sx/hZVVkurQmvWrMl2nxCbLlF78MEHfdyxY0fTVrt2bZOXLFky7u/RZ0WSEXeOAAAIBkcAAASDIwAAIiVrjuH6GZ337tChg8nD462cy7xdUiJWrVrl42effTbbn5PfhdevadOmpk3riFpzrF+/fra+8/XXXzf5rFmzsvU5sPSIozfeeCNmeyI1RaXb0L300kvZ/ix8K3wGwznn+vbta/IuXbr4uHTp0tn+nvnz55t80qRJ2f6s3MKdIwAAgsERAADB4AgAgEiJmmObNm1Mfscdd/j48ccfN226/9/l9Mc//jHHPvtKlp6ebvK0tDQf61FRiRyRk4iFCxea/MiRIznyPVci3e923LhxPtaao16/S6kzhoYMGWLyPXv2XJbPzQ/uueceH+sRf7q2+6qrcuZ+KZGj55IFd44AAAgGRwAARFJOq+pxQoMHDzZ51LE4OemTTz7Jk+9NNRUqVDB5RkaGyfWoopwSHrfDNGr8qlWrZvLnnnsusj2nHDp0yMcrVqzIle+8Eugxb6NHj/axLpXKSefPn/dxKv7+uHMEAEAwOAIAIBgcAQAQSVlzfOaZZ0x+KTXGM2fOmLxQoUI+zuqxZT1W5ejRo9nuR37Sv39/k19KjTGsWzhnr1lWyz4OHz7s4127dmW7D/mNbtmXSI1Rl2589dVXPi5WrJhpy+r67d2718f79u2Luw/53Zw5c0xetWrVuN+r1y88wkprmVldv7BmvGXLlrj7kCy4cwQAQDA4AgAgGBwBABBJU3MsV66cjxNZi/Pmm2+afMyYMSb/4IMPTP7QQw/5ePz48ZGffcMNN5i8YcOGPv7000/j7mN+U7Ro0bhfq9v/rVu3zuRvv/22yceOHevjoUOHRn52eMROqVKl4u5Tfhduz5iVhx9+2OQff/yxycPr+corr5g2PV5O1atXz8cnT56Mu0/5jf7eov5+ak0x/HvonHOvvfaaycPnLPS3OmLEiMh+hc8H6LMfqYA7RwAABIMjAACCwREAAJE0NcfChQv7uH379pGvDdes9enTx7RlVZto1qyZj7/++uuYfbiYAwcORLbnV1rz6NevX+Trw/WjWvfVdY1q7ty5Ps6q5hiuy9I1dvhWpUqVTN6oUaPI12/atMnHU6ZMMW1R12/nzp2Rr9Xj5sKaVZcuXUzbrFmzIvuYn+jvr379+jFfG65bdM656dOnm/zYsWMx37t27dqE+lW+fHkf69Fmn332WUKflRe4cwQAQDA4AgAgkmZadf/+/T7WW269Jf/www99nOgjwuE0bLiVnHPO3XXXXSbXaR+dhsX/On36tMknTpxo8vDkeOfsUVJZTaOqDRs2+DjcHs4558qWLWvy8LH1tm3bmrb58+cn9L1XshMnTph848aNJr/ppptMHk7NFS9e3LRFTcvp0XM6fdu8eXOTh9ePpRyxnTp1yuTbtm0zec2aNX2sf/PS09NNrkvjQuFWgM5lXhai28mF7RUrVoz5ucmKO0cAAASDIwAAgsERAACRNDXHsPY0Y8YM06bbFHXq1MnHe/bsMW3Tpk0zeZEiRUwePt7fuHHjyD5p7XPz5s2Rr8f/0pqVql27to93795t2hYvXmxyrZ+EW2OFdWrnMtcc//Of//hY6574ltYcR44cafLXX3/d5GENUn8jCxYsMHlYg9SlUlltExle39WrV0e+Nj/T5y4GDBhg8iVLlsR879SpU02uv93wN1SmTBnTtmPHDpPr0Wbhkrt58+bF7EOy4s4RAADB4AgAgGBwBABAJE3NMTR69GiT6/FQYQ0kPOrKOed++ctfXrZ+VK9e3eRHjhy5bJ99JfvnP/9pct3m7ZlnnvGxbl2m2wFGrZ3KSrhN3cGDB+N+X363bNkyk+uxVM8++6yPwy3CnMt8/UKJXDvn7JFjUesnYf3rX/8yee/evX2sz3PoUW633HKLyW+99VYfJ3r9wuOu9u3bl9B7kwF3jgAACAZHAABEUk6rqtmzZ5s8PA2+R48epq1WrVom12m5kC7NqFy5ssnnzJlj8kS3OsuvdJu9cBrOOTt1k5aWZtratGlj8qipHG3bsmWLyQ8dOhTX58DSJTKTJk0yeXhChm5Hptcv/P1lNUWuZYu//vWvPmbrxvjpyRszZ870cdeuXU2bljV0m8UoWf2mtm/fHvdnJSPuHAEAEAyOAAAIBkcAAERK1Bx1bnvYsGE+fvrpp03b9ddfb/K7777b5GFdY/LkyaZNj36hTnV56L9jr169fKynv4fX1jnn2rVrZ/KMjAwf65ZiWpdK9DgzXJxev/bt2/tYa47dunUzebgcQ7d61Bq+LtnSrQORPeH1u/fee01buJ2mc5mfAWjWrJmPr7nmmpif61zmI+TeeeedxDubRLhzBABAMDgCACAYHAEAEClRc4zy5ZdfRubr16/Pze4gQVp30uOSNEdyOXv2rMlnzZqVRz1BduiayL1795p87ty5udmdpMKdIwAAgsERAADB4AgAgGBwBABAMDgCACAYHAEAEAyOAAAIBkcAAASDIwAAgsERAADB4AgAgGBwBABAMDgCACAYHAEAEAyOAAAIBkcAAASDIwAAgsERAABRICMj45u87gQAAMmEO0cAAASDIwAAgsERAADB4AgAgGBwBABAMDgCACD+B65ZQl4Cb07/AAAAAElFTkSuQmCC\" id=\"image2eeb26dcc0\" transform=\"scale(1 -1) translate(0 -166.32)\" x=\"7.2\" y=\"-7.2\" width=\"327.6\" height=\"166.32\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p9835edab5b\">\n", " <rect x=\"7.2\" y=\"7.2\" width=\"327.274839\" height=\"166.32\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 600x300 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"341.674839pt\" height=\"180.72pt\" viewBox=\"0 0 341.674839 180.72\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:01.290435</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 180.72 \n", "L 341.674839 180.72 \n", "L 341.674839 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#p35b632d51d)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image3b2db92977\" transform=\"scale(1 -1) translate(0 -166.32)\" x=\"7.2\" y=\"-7.2\" width=\"327.6\" height=\"166.32\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p35b632d51d\">\n", " <rect x=\"7.2\" y=\"7.2\" width=\"327.274839\" height=\"166.32\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 600x300 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"341.674839pt\" height=\"180.72pt\" viewBox=\"0 0 341.674839 180.72\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:01.368132</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 180.72 \n", "L 341.674839 180.72 \n", "L 341.674839 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g clip-path=\"url(#p52d0b6ff6c)\">\n", " <image xlink:href=\"data:image/png;base64,\n", "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\" id=\"image9d49837c82\" transform=\"scale(1 -1) translate(0 -166.32)\" x=\"7.2\" y=\"-7.2\" width=\"327.6\" height=\"166.32\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p52d0b6ff6c\">\n", " <rect x=\"7.2\" y=\"7.2\" width=\"327.274839\" height=\"166.32\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 600x300 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["L.seed_everything(44)\n", "for _ in range(3):\n", " z_init = flow_dict[\"multiscale\"][\"model\"].prior.sample(sample_shape=[1, 8, 7, 7])\n", " z_init = z_init.expand(8, -1, -1, -1)\n", " samples = flow_dict[\"multiscale\"][\"model\"].sample(img_shape=z_init.shape, z_init=z_init)\n", " show_imgs(samples.cpu())"]}, {"cell_type": "markdown", "id": "994633e5", "metadata": {"papermill": {"duration": 0.021725, "end_time": "2023-03-14T16:09:01.456409", "exception": false, "start_time": "2023-03-14T16:09:01.434684", "status": "completed"}, "tags": []}, "source": ["We see that the early split variables indeed have a smaller effect on the image.\n", "Still, small differences can be spot when we look carefully at the borders of the digits.\n", "For instance, the hole at the top of the 8 changes for different samples although all of them represent the same coarse structure.\n", "This shows that the flow indeed learns to separate the higher-level\n", "information in the final variables, while the early split ones contain\n", "local noise patterns."]}, {"cell_type": "markdown", "id": "5df5dcc5", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.021783, "end_time": "2023-03-14T16:09:01.499950", "exception": false, "start_time": "2023-03-14T16:09:01.478167", "status": "completed"}, "tags": []}, "source": ["### Visualizing Dequantization\n", "\n", "As a final part of this notebook, we will look at the effect of variational dequantization.\n", "We have motivated variational dequantization by the issue of sharp edges/boarders being difficult to model,\n", "and a flow would rather prefer smooth, prior-like distributions.\n", "To check how what noise distribution $q(u|x)$ the flows in the\n", "variational dequantization module have learned, we can plot a histogram\n", "of output values from the dequantization and variational dequantization\n", "module."]}, {"cell_type": "code", "execution_count": 33, "id": "c062358b", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:09:01.545124Z", "iopub.status.busy": "2023-03-14T16:09:01.544837Z", "iopub.status.idle": "2023-03-14T16:09:01.574131Z", "shell.execute_reply": "2023-03-14T16:09:01.573585Z"}, "papermill": {"duration": 0.054855, "end_time": "2023-03-14T16:09:01.576533", "exception": false, "start_time": "2023-03-14T16:09:01.521678", "status": "completed"}, "tags": []}, "outputs": [], "source": ["def visualize_dequant_distribution(model: ImageFlow, imgs: Tensor, title: str = None):\n", " \"\"\"\n", " Args:\n", " model: The flow of which we want to visualize the dequantization distribution\n", " imgs: Example training images of which we want to visualize the dequantization distribution\n", " \"\"\"\n", " imgs = imgs.to(device)\n", " ldj = torch.zeros(imgs.shape[0], dtype=torch.float32).to(device)\n", " with torch.no_grad():\n", " dequant_vals = []\n", " for _ in tqdm(range(8), leave=False):\n", " d, _ = model.flows[0](imgs, ldj, reverse=False)\n", " dequant_vals.append(d)\n", " dequant_vals = torch.cat(dequant_vals, dim=0)\n", " dequant_vals = dequant_vals.view(-1).cpu().numpy()\n", " sns.set()\n", " plt.figure(figsize=(10, 3))\n", " plt.hist(dequant_vals, bins=256, color=to_rgb(\"C0\") + (0.5,), edgecolor=\"C0\", density=True)\n", " if title is not None:\n", " plt.title(title)\n", " plt.show()\n", " plt.close()\n", "\n", "\n", "sample_imgs, _ = next(iter(train_loader))"]}, {"cell_type": "code", "execution_count": 34, "id": "e66ef8de", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:09:01.626826Z", "iopub.status.busy": "2023-03-14T16:09:01.626504Z", "iopub.status.idle": "2023-03-14T16:09:02.283549Z", "shell.execute_reply": "2023-03-14T16:09:02.282977Z"}, "papermill": {"duration": 0.684094, "end_time": "2023-03-14T16:09:02.288395", "exception": false, "start_time": "2023-03-14T16:09:01.604301", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "bbe213511b3245368a116d011cf7a97d", "version_major": 2, "version_minor": 0}, "text/plain": [" 0%| | 0/8 [00:00<?, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"599.393438pt\" height=\"215.984063pt\" viewBox=\"0 0 599.393438 215.984063\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:01.959626</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 215.984063 \n", "L 599.393438 215.984063 \n", "L 599.393438 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g id=\"patch_2\">\n", " <path d=\"M 34.193438 188.638125 \n", "L 592.193437 188.638125 \n", "L 592.193437 22.318125 \n", "L 34.193438 22.318125 \n", "z\n", "\" style=\"fill: #eaeaf2\"/>\n", " </g>\n", " <g id=\"matplotlib.axis_1\">\n", " <g id=\"xtick_1\">\n", " <g id=\"line2d_1\">\n", " <path d=\"M 105.444914 188.638125 \n", "L 105.444914 22.318125 \n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_1\">\n", " <!-- \u221210 -->\n", " <g style=\"fill: #262626\" transform=\"translate(93.837336 206.496406) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-2212\" d=\"M 678 2272 \n", "L 4684 2272 \n", "L 4684 1741 \n", "L 678 1741 \n", "L 678 2272 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-31\" d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-30\" d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"83.789062\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"147.412109\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_2\">\n", " <g id=\"line2d_2\">\n", " <path d=\"M 209.448598 188.638125 \n", "L 209.448598 22.318125 \n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_2\">\n", " <!-- \u22125 -->\n", " <g style=\"fill: #262626\" transform=\"translate(201.340395 206.496406) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-35\" d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_3\">\n", " <g id=\"line2d_3\">\n", " <path d=\"M 313.452282 188.638125 \n", "L 313.452282 22.318125 \n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_3\">\n", " <!-- 0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(309.952907 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_4\">\n", " <g id=\"line2d_4\">\n", " <path d=\"M 417.455966 188.638125 \n", "L 417.455966 22.318125 \n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_4\">\n", " <!-- 5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(413.956591 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-35\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_5\">\n", " <g id=\"line2d_5\">\n", " <path d=\"M 521.45965 188.638125 \n", "L 521.45965 22.318125 \n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_5\">\n", " <!-- 10 -->\n", " <g style=\"fill: #262626\" transform=\"translate(514.4609 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"63.623047\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"matplotlib.axis_2\">\n", " <g id=\"ytick_1\">\n", " <g id=\"line2d_6\">\n", " <path d=\"M 34.193438 188.638125 \n", "L 592.193437 188.638125 \n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_6\">\n", " <!-- 0.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 192.817266) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-2e\" d=\"M 684 794 \n", "L 1344 794 \n", "L 1344 0 \n", "L 684 0 \n", "L 684 794 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_2\">\n", " <g id=\"line2d_7\">\n", " <path d=\"M 34.193438 146.886907 \n", "L 592.193437 146.886907 \n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_7\">\n", " <!-- 0.2 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 151.066047) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-32\" d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_3\">\n", " <g id=\"line2d_8\">\n", " <path d=\"M 34.193438 105.135688 \n", "L 592.193437 105.135688 \n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_8\">\n", " <!-- 0.4 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 109.314829) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-34\" d=\"M 2419 4116 \n", "L 825 1625 \n", "L 2419 1625 \n", "L 2419 4116 \n", "z\n", "M 2253 4666 \n", "L 3047 4666 \n", "L 3047 1625 \n", "L 3713 1625 \n", "L 3713 1100 \n", "L 3047 1100 \n", "L 3047 0 \n", "L 2419 0 \n", "L 2419 1100 \n", "L 313 1100 \n", "L 313 1709 \n", "L 2253 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-34\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_4\">\n", " <g id=\"line2d_9\">\n", " <path d=\"M 34.193438 63.38447 \n", "L 592.193437 63.38447 \n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_9\">\n", " <!-- 0.6 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 67.563611) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-36\" d=\"M 2113 2584 \n", "Q 1688 2584 1439 2293 \n", "Q 1191 2003 1191 1497 \n", "Q 1191 994 1439 701 \n", "Q 1688 409 2113 409 \n", "Q 2538 409 2786 701 \n", "Q 3034 994 3034 1497 \n", "Q 3034 2003 2786 2293 \n", "Q 2538 2584 2113 2584 \n", "z\n", "M 3366 4563 \n", "L 3366 3988 \n", "Q 3128 4100 2886 4159 \n", "Q 2644 4219 2406 4219 \n", "Q 1781 4219 1451 3797 \n", "Q 1122 3375 1075 2522 \n", "Q 1259 2794 1537 2939 \n", "Q 1816 3084 2150 3084 \n", "Q 2853 3084 3261 2657 \n", "Q 3669 2231 3669 1497 \n", "Q 3669 778 3244 343 \n", "Q 2819 -91 2113 -91 \n", "Q 1303 -91 875 529 \n", "Q 447 1150 447 2328 \n", "Q 447 3434 972 4092 \n", "Q 1497 4750 2381 4750 \n", "Q 2619 4750 2861 4703 \n", "Q 3103 4656 3366 4563 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-36\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"patch_3\">\n", " <path d=\"M 59.557074 188.638125 \n", "L 61.538605 188.638125 \n", "L 61.538605 188.415662 \n", "L 59.557074 188.415662 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_4\">\n", " <path d=\"M 61.538605 188.638125 \n", "L 63.520135 188.638125 \n", "L 63.520135 188.39246 \n", "L 61.538605 188.39246 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_5\">\n", " <path d=\"M 63.520135 188.638125 \n", "L 65.501686 188.638125 \n", "L 65.501686 188.341965 \n", "L 63.520135 188.341965 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_6\">\n", " <path d=\"M 65.501686 188.638125 \n", "L 67.483217 188.638125 \n", "L 67.483217 188.32422 \n", "L 65.501686 188.32422 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_7\">\n", " <path d=\"M 67.483217 188.638125 \n", "L 69.464747 188.638125 \n", "L 69.464747 188.296923 \n", "L 67.483217 188.296923 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_8\">\n", " <path d=\"M 69.464747 188.638125 \n", "L 71.446278 188.638125 \n", "L 71.446278 188.277816 \n", "L 69.464747 188.277816 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_9\">\n", " <path d=\"M 71.446278 188.638125 \n", "L 73.427809 188.638125 \n", "L 73.427809 188.254614 \n", "L 71.446278 188.254614 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_10\">\n", " <path d=\"M 73.427809 188.638125 \n", "L 75.40934 188.638125 \n", "L 75.40934 188.185009 \n", "L 73.427809 188.185009 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_11\">\n", " <path d=\"M 75.40934 188.638125 \n", "L 77.39089 188.638125 \n", "L 77.39089 188.14134 \n", "L 75.40934 188.14134 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_12\">\n", " <path d=\"M 77.39089 188.638125 \n", "L 79.372421 188.638125 \n", "L 79.372421 188.063542 \n", "L 77.39089 188.063542 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_13\">\n", " <path d=\"M 79.372421 188.638125 \n", "L 81.353952 188.638125 \n", "L 81.353952 188.075825 \n", "L 79.372421 188.075825 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_14\">\n", " <path d=\"M 81.353952 188.638125 \n", "L 83.335483 188.638125 \n", "L 83.335483 187.974829 \n", "L 81.353952 187.974829 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_15\">\n", " <path d=\"M 83.335483 188.638125 \n", "L 85.317013 188.638125 \n", "L 85.317013 187.851997 \n", "L 83.335483 187.851997 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_16\">\n", " <path d=\"M 85.317013 188.638125 \n", "L 87.298544 188.638125 \n", "L 87.298544 187.806958 \n", "L 85.317013 187.806958 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_17\">\n", " <path d=\"M 87.298544 188.638125 \n", "L 89.280095 188.638125 \n", "L 89.280095 187.827438 \n", "L 87.298544 187.827438 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_18\">\n", " <path d=\"M 89.280095 188.638125 \n", "L 91.261626 188.638125 \n", "L 91.261626 187.699138 \n", "L 89.280095 187.699138 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_19\">\n", " <path d=\"M 91.261626 188.638125 \n", "L 93.243156 188.638125 \n", "L 93.243156 187.604967 \n", "L 91.261626 187.604967 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_20\">\n", " <path d=\"M 93.243156 188.638125 \n", "L 95.224687 188.638125 \n", "L 95.224687 187.490323 \n", "L 93.243156 187.490323 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_21\">\n", " <path d=\"M 95.224687 188.638125 \n", "L 97.206218 188.638125 \n", "L 97.206218 187.377044 \n", "L 95.224687 187.377044 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_22\">\n", " <path d=\"M 97.206218 188.638125 \n", "L 99.187749 188.638125 \n", "L 99.187749 187.281507 \n", "L 97.206218 187.281507 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_23\">\n", " <path d=\"M 99.187749 188.638125 \n", "L 101.169299 188.638125 \n", "L 101.169299 187.042682 \n", "L 99.187749 187.042682 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_24\">\n", " <path d=\"M 101.169299 188.638125 \n", "L 103.15083 188.638125 \n", "L 103.15083 186.918469 \n", "L 101.169299 186.918469 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_25\">\n", " <path d=\"M 103.15083 188.638125 \n", "L 105.132361 188.638125 \n", "L 105.132361 186.711018 \n", "L 103.15083 186.711018 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_26\">\n", " <path d=\"M 105.132361 188.638125 \n", "L 107.113891 188.638125 \n", "L 107.113891 186.548606 \n", "L 105.132361 186.548606 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_27\">\n", " <path d=\"M 107.113891 188.638125 \n", "L 109.095422 188.638125 \n", "L 109.095422 186.443516 \n", "L 107.113891 186.443516 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_28\">\n", " <path d=\"M 109.095422 188.638125 \n", "L 111.076953 188.638125 \n", "L 111.076953 186.184203 \n", "L 109.095422 186.184203 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_29\">\n", " <path d=\"M 111.076953 188.638125 \n", "L 113.058504 188.638125 \n", "L 113.058504 185.933106 \n", "L 111.076953 185.933106 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_30\">\n", " <path d=\"M 113.058504 188.638125 \n", "L 115.040034 188.638125 \n", "L 115.040034 185.694238 \n", "L 113.058504 185.694238 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_31\">\n", " <path d=\"M 115.040034 188.638125 \n", "L 117.021565 188.638125 \n", "L 117.021565 185.43356 \n", "L 115.040034 185.43356 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_32\">\n", " <path d=\"M 117.021565 188.638125 \n", "L 119.003096 188.638125 \n", "L 119.003096 185.116925 \n", "L 117.021565 185.116925 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_33\">\n", " <path d=\"M 119.003096 188.638125 \n", "L 120.984627 188.638125 \n", "L 120.984627 184.669268 \n", "L 119.003096 184.669268 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_34\">\n", " <path d=\"M 120.984627 188.638125 \n", "L 122.966157 188.638125 \n", "L 122.966157 184.26938 \n", "L 120.984627 184.26938 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_35\">\n", " <path d=\"M 122.966157 188.638125 \n", "L 124.947708 188.638125 \n", "L 124.947708 183.874998 \n", "L 122.966157 183.874998 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_36\">\n", " <path d=\"M 124.947708 188.638125 \n", "L 126.929239 188.638125 \n", "L 126.929239 183.46005 \n", "L 124.947708 183.46005 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_37\">\n", " <path d=\"M 126.929239 188.638125 \n", "L 128.910769 188.638125 \n", "L 128.910769 182.897749 \n", "L 126.929239 182.897749 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_38\">\n", " <path d=\"M 128.910769 188.638125 \n", "L 130.8923 188.638125 \n", "L 130.8923 182.148471 \n", "L 128.910769 182.148471 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_39\">\n", " <path d=\"M 130.8923 188.638125 \n", "L 132.873831 188.638125 \n", "L 132.873831 181.599819 \n", "L 130.8923 181.599819 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_40\">\n", " <path d=\"M 132.873831 188.638125 \n", "L 134.855362 188.638125 \n", "L 134.855362 180.899673 \n", "L 132.873831 180.899673 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_41\">\n", " <path d=\"M 134.855362 188.638125 \n", "L 136.836912 188.638125 \n", "L 136.836912 180.337456 \n", "L 134.855362 180.337456 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_42\">\n", " <path d=\"M 136.836912 188.638125 \n", "L 138.818443 188.638125 \n", "L 138.818443 179.624944 \n", "L 136.836912 179.624944 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_43\">\n", " <path d=\"M 138.818443 188.638125 \n", "L 140.799974 188.638125 \n", "L 140.799974 178.227382 \n", "L 138.818443 178.227382 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_44\">\n", " <path d=\"M 140.799974 188.638125 \n", "L 142.781505 188.638125 \n", "L 142.781505 177.348447 \n", "L 140.799974 177.348447 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_45\">\n", " <path d=\"M 142.781505 188.638125 \n", "L 144.763035 188.638125 \n", "L 144.763035 176.122851 \n", "L 142.781505 176.122851 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_46\">\n", " <path d=\"M 144.763035 188.638125 \n", "L 146.744566 188.638125 \n", "L 146.744566 174.988696 \n", "L 144.763035 174.988696 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_47\">\n", " <path d=\"M 146.744566 188.638125 \n", "L 148.726107 188.638125 \n", "L 148.726107 173.801389 \n", "L 146.744566 173.801389 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_48\">\n", " <path d=\"M 148.726107 188.638125 \n", "L 150.707638 188.638125 \n", "L 150.707638 172.376457 \n", "L 148.726107 172.376457 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_49\">\n", " <path d=\"M 150.707638 188.638125 \n", "L 152.689178 188.638125 \n", "L 152.689178 170.510857 \n", "L 150.707638 170.510857 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_50\">\n", " <path d=\"M 152.689178 188.638125 \n", "L 154.670709 188.638125 \n", "L 154.670709 169.04087 \n", "L 152.689178 169.04087 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_51\">\n", " <path d=\"M 154.670709 188.638125 \n", "L 156.65224 188.638125 \n", "L 156.65224 166.647 \n", "L 154.670709 166.647 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_52\">\n", " <path d=\"M 156.65224 188.638125 \n", "L 158.63378 188.638125 \n", "L 158.63378 164.582168 \n", "L 156.65224 164.582168 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_53\">\n", " <path d=\"M 158.63378 188.638125 \n", "L 160.615311 188.638125 \n", "L 160.615311 161.972538 \n", "L 158.63378 161.972538 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_54\">\n", " <path d=\"M 160.615311 188.638125 \n", "L 162.596842 188.638125 \n", "L 162.596842 159.137835 \n", "L 160.615311 159.137835 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_55\">\n", " <path d=\"M 162.596842 188.638125 \n", "L 164.578383 188.638125 \n", "L 164.578383 156.506649 \n", "L 162.596842 156.506649 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_56\">\n", " <path d=\"M 164.578383 188.638125 \n", "L 166.559913 188.638125 \n", "L 166.559913 153.21594 \n", "L 164.578383 153.21594 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_57\">\n", " <path d=\"M 166.559913 188.638125 \n", "L 168.541444 188.638125 \n", "L 168.541444 149.960877 \n", "L 166.559913 149.960877 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_58\">\n", " <path d=\"M 168.541444 188.638125 \n", "L 170.522985 188.638125 \n", "L 170.522985 145.821634 \n", "L 168.541444 145.821634 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_59\">\n", " <path d=\"M 170.522985 188.638125 \n", "L 172.504516 188.638125 \n", "L 172.504516 141.205644 \n", "L 170.522985 141.205644 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_60\">\n", " <path d=\"M 172.504516 188.638125 \n", "L 174.486046 188.638125 \n", "L 174.486046 137.051174 \n", "L 172.504516 137.051174 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_61\">\n", " <path d=\"M 174.486046 188.638125 \n", "L 176.467587 188.638125 \n", "L 176.467587 132.164085 \n", "L 174.486046 132.164085 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_62\">\n", " <path d=\"M 176.467587 188.638125 \n", "L 178.449118 188.638125 \n", "L 178.449118 125.574517 \n", "L 176.467587 125.574517 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_63\">\n", " <path d=\"M 178.449118 188.638125 \n", "L 180.430649 188.638125 \n", "L 180.430649 120.224476 \n", "L 178.449118 120.224476 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_64\">\n", " <path d=\"M 180.430649 188.638125 \n", "L 182.412189 188.638125 \n", "L 182.412189 113.511369 \n", "L 180.430649 113.511369 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_65\">\n", " <path d=\"M 182.412189 188.638125 \n", "L 184.39372 188.638125 \n", "L 184.39372 105.395854 \n", "L 182.412189 105.395854 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_66\">\n", " <path d=\"M 184.39372 188.638125 \n", "L 186.375261 188.638125 \n", "L 186.375261 97.855754 \n", "L 184.39372 97.855754 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_67\">\n", " <path d=\"M 186.375261 188.638125 \n", "L 188.356791 188.638125 \n", "L 188.356791 88.05326 \n", "L 186.375261 88.05326 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_68\">\n", " <path d=\"M 188.356791 188.638125 \n", "L 190.338322 188.638125 \n", "L 190.338322 78.644285 \n", "L 188.356791 78.644285 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_69\">\n", " <path d=\"M 190.338322 188.638125 \n", "L 192.319863 188.638125 \n", "L 192.319863 67.353849 \n", "L 190.338322 67.353849 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_70\">\n", " <path d=\"M 192.319863 188.638125 \n", "L 194.301394 188.638125 \n", "L 194.301394 55.34431 \n", "L 192.319863 55.34431 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_71\">\n", " <path d=\"M 194.301394 188.638125 \n", "L 196.282924 188.638125 \n", "L 196.282924 42.487834 \n", "L 194.301394 42.487834 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_72\">\n", " <path d=\"M 196.282924 188.638125 \n", "L 198.264465 188.638125 \n", "L 198.264465 30.238125 \n", "L 196.282924 30.238125 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_73\">\n", " <path d=\"M 198.264465 188.638125 \n", "L 200.245996 188.638125 \n", "L 200.245996 188.538494 \n", "L 198.264465 188.538494 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_74\">\n", " <path d=\"M 200.245996 188.638125 \n", "L 202.227527 188.638125 \n", "L 202.227527 188.549413 \n", "L 200.245996 188.549413 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_75\">\n", " <path d=\"M 202.227527 188.638125 \n", "L 204.209067 188.638125 \n", "L 204.209067 188.553507 \n", "L 202.227527 188.553507 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_76\">\n", " <path d=\"M 204.209067 188.638125 \n", "L 206.190598 188.638125 \n", "L 206.190598 188.549413 \n", "L 204.209067 188.549413 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_77\">\n", " <path d=\"M 206.190598 188.638125 \n", "L 208.172129 188.638125 \n", "L 208.172129 188.523481 \n", "L 206.190598 188.523481 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_78\">\n", " <path d=\"M 208.172129 188.638125 \n", "L 210.153669 188.638125 \n", "L 210.153669 188.522117 \n", "L 208.172129 188.522117 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_79\">\n", " <path d=\"M 210.153669 188.638125 \n", "L 212.1352 188.638125 \n", "L 212.1352 188.479807 \n", "L 210.153669 188.479807 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_80\">\n", " <path d=\"M 212.1352 188.638125 \n", "L 214.116731 188.638125 \n", "L 214.116731 188.35834 \n", "L 212.1352 188.35834 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_81\">\n", " <path d=\"M 214.116731 188.638125 \n", "L 216.098272 188.638125 \n", "L 216.098272 188.26144 \n", "L 214.116731 188.26144 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_82\">\n", " <path d=\"M 216.098272 188.638125 \n", "L 218.079802 188.638125 \n", "L 218.079802 188.243696 \n", "L 216.098272 188.243696 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_83\">\n", " <path d=\"M 218.079802 188.638125 \n", "L 220.061333 188.638125 \n", "L 220.061333 188.231413 \n", "L 218.079802 188.231413 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_84\">\n", " <path d=\"M 220.061333 188.638125 \n", "L 222.042874 188.638125 \n", "L 222.042874 188.172728 \n", "L 220.061333 188.172728 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_85\">\n", " <path d=\"M 222.042874 188.638125 \n", "L 224.024405 188.638125 \n", "L 224.024405 188.198657 \n", "L 222.042874 188.198657 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_86\">\n", " <path d=\"M 224.024405 188.638125 \n", "L 226.005935 188.638125 \n", "L 226.005935 188.186374 \n", "L 224.024405 188.186374 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_87\">\n", " <path d=\"M 226.005935 188.638125 \n", "L 227.987476 188.638125 \n", "L 227.987476 188.082652 \n", "L 226.005935 188.082652 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_88\">\n", " <path d=\"M 227.987476 188.638125 \n", "L 229.969007 188.638125 \n", "L 229.969007 187.913413 \n", "L 227.987476 187.913413 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_89\">\n", " <path d=\"M 229.969007 188.638125 \n", "L 231.950538 188.638125 \n", "L 231.950538 187.910683 \n", "L 229.969007 187.910683 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_90\">\n", " <path d=\"M 231.950538 188.638125 \n", "L 233.932073 188.638125 \n", "L 233.932073 187.952994 \n", "L 231.950538 187.952994 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_91\">\n", " <path d=\"M 233.932073 188.638125 \n", "L 235.913609 188.638125 \n", "L 235.913609 187.865647 \n", "L 233.932073 187.865647 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_92\">\n", " <path d=\"M 235.913609 188.638125 \n", "L 237.89514 188.638125 \n", "L 237.89514 187.417988 \n", "L 235.913609 187.417988 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_93\">\n", " <path d=\"M 237.89514 188.638125 \n", "L 239.876675 188.638125 \n", "L 239.876675 187.434369 \n", "L 237.89514 187.434369 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_94\">\n", " <path d=\"M 239.876675 188.638125 \n", "L 241.858211 188.638125 \n", "L 241.858211 187.508068 \n", "L 239.876675 187.508068 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_95\">\n", " <path d=\"M 241.858211 188.638125 \n", "L 243.839742 188.638125 \n", "L 243.839742 187.426177 \n", "L 241.858211 187.426177 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_96\">\n", " <path d=\"M 243.839742 188.638125 \n", "L 245.821278 188.638125 \n", "L 245.821278 187.115005 \n", "L 243.839742 187.115005 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_97\">\n", " <path d=\"M 245.821278 188.638125 \n", "L 247.802813 188.638125 \n", "L 247.802813 186.888448 \n", "L 245.821278 186.888448 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_98\">\n", " <path d=\"M 247.802813 188.638125 \n", "L 249.784344 188.638125 \n", "L 249.784344 186.797001 \n", "L 247.802813 186.797001 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_99\">\n", " <path d=\"M 249.784344 188.638125 \n", "L 251.76588 188.638125 \n", "L 251.76588 186.945769 \n", "L 249.784344 186.945769 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_100\">\n", " <path d=\"M 251.76588 188.638125 \n", "L 253.747416 188.638125 \n", "L 253.747416 186.704199 \n", "L 251.76588 186.704199 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_101\">\n", " <path d=\"M 253.747416 188.638125 \n", "L 255.728951 188.638125 \n", "L 255.728951 186.760156 \n", "L 253.747416 186.760156 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_102\">\n", " <path d=\"M 255.728951 188.638125 \n", "L 257.710482 188.638125 \n", "L 257.710482 186.780624 \n", "L 255.728951 186.780624 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_103\">\n", " <path d=\"M 257.710482 188.638125 \n", "L 259.692018 188.638125 \n", "L 259.692018 186.724671 \n", "L 257.710482 186.724671 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_104\">\n", " <path d=\"M 259.692018 188.638125 \n", "L 261.673553 188.638125 \n", "L 261.673553 186.240166 \n", "L 259.692018 186.240166 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_105\">\n", " <path d=\"M 261.673553 188.638125 \n", "L 263.655084 188.638125 \n", "L 263.655084 185.964469 \n", "L 261.673553 185.964469 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_106\">\n", " <path d=\"M 263.655084 188.638125 \n", "L 265.63662 188.638125 \n", "L 265.63662 185.894871 \n", "L 263.655084 185.894871 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_107\">\n", " <path d=\"M 265.63662 188.638125 \n", "L 267.618156 188.638125 \n", "L 267.618156 186.266097 \n", "L 265.63662 186.266097 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_108\">\n", " <path d=\"M 267.618156 188.638125 \n", "L 269.599686 188.638125 \n", "L 269.599686 186.210134 \n", "L 267.618156 186.210134 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_109\">\n", " <path d=\"M 269.599686 188.638125 \n", "L 271.581222 188.638125 \n", "L 271.581222 185.149689 \n", "L 269.599686 185.149689 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_110\">\n", " <path d=\"M 271.581222 188.638125 \n", "L 273.562755 188.638125 \n", "L 273.562755 185.127847 \n", "L 271.581222 185.127847 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_111\">\n", " <path d=\"M 273.562755 188.638125 \n", "L 275.544289 188.638125 \n", "L 275.544289 186.219691 \n", "L 273.562755 186.219691 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_112\">\n", " <path d=\"M 275.544289 188.638125 \n", "L 277.525824 188.638125 \n", "L 277.525824 185.103285 \n", "L 275.544289 185.103285 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_113\">\n", " <path d=\"M 277.525824 188.638125 \n", "L 279.507358 188.638125 \n", "L 279.507358 185.398079 \n", "L 277.525824 185.398079 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_114\">\n", " <path d=\"M 279.507358 188.638125 \n", "L 281.488891 188.638125 \n", "L 281.488891 185.086903 \n", "L 279.507358 185.086903 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_115\">\n", " <path d=\"M 281.488891 188.638125 \n", "L 283.470427 188.638125 \n", "L 283.470427 185.276615 \n", "L 281.488891 185.276615 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_116\">\n", " <path d=\"M 283.470427 188.638125 \n", "L 285.45196 188.638125 \n", "L 285.45196 184.875359 \n", "L 283.470427 184.875359 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_117\">\n", " <path d=\"M 285.45196 188.638125 \n", "L 287.433495 188.638125 \n", "L 287.433495 185.051423 \n", "L 285.45196 185.051423 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_118\">\n", " <path d=\"M 287.433495 188.638125 \n", "L 289.415029 188.638125 \n", "L 289.415029 184.89856 \n", "L 287.433495 184.89856 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_119\">\n", " <path d=\"M 289.415029 188.638125 \n", "L 291.396562 188.638125 \n", "L 291.396562 183.213026 \n", "L 289.415029 183.213026 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_120\">\n", " <path d=\"M 291.396562 188.638125 \n", "L 293.378096 188.638125 \n", "L 293.378096 184.689748 \n", "L 291.396562 184.689748 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_121\">\n", " <path d=\"M 293.378096 188.638125 \n", "L 295.359631 188.638125 \n", "L 295.359631 184.407233 \n", "L 293.378096 184.407233 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_122\">\n", " <path d=\"M 295.359631 188.638125 \n", "L 297.341164 188.638125 \n", "L 297.341164 184.153377 \n", "L 295.359631 184.153377 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_123\">\n", " <path d=\"M 297.341164 188.638125 \n", "L 299.322699 188.638125 \n", "L 299.322699 183.324944 \n", "L 297.341164 183.324944 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_124\">\n", " <path d=\"M 299.322699 188.638125 \n", "L 301.304233 188.638125 \n", "L 301.304233 184.25301 \n", "L 299.322699 184.25301 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_125\">\n", " <path d=\"M 301.304233 188.638125 \n", "L 303.285767 188.638125 \n", "L 303.285767 183.902254 \n", "L 301.304233 183.902254 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_126\">\n", " <path d=\"M 303.285767 188.638125 \n", "L 305.267301 188.638125 \n", "L 305.267301 184.141095 \n", "L 303.285767 184.141095 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_127\">\n", " <path d=\"M 305.267301 188.638125 \n", "L 307.248835 188.638125 \n", "L 307.248835 183.997792 \n", "L 305.267301 183.997792 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_128\">\n", " <path d=\"M 307.248835 188.638125 \n", "L 309.230369 188.638125 \n", "L 309.230369 183.416384 \n", "L 307.248835 183.416384 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_129\">\n", " <path d=\"M 309.230369 188.638125 \n", "L 311.211903 188.638125 \n", "L 311.211903 183.794436 \n", "L 309.230369 183.794436 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_130\">\n", " <path d=\"M 311.211903 188.638125 \n", "L 313.193438 188.638125 \n", "L 313.193438 183.817637 \n", "L 311.211903 183.817637 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_131\">\n", " <path d=\"M 313.193438 188.638125 \n", "L 315.174972 188.638125 \n", "L 315.174972 180.950184 \n", "L 313.193438 180.950184 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_132\">\n", " <path d=\"M 315.174972 188.638125 \n", "L 317.156506 188.638125 \n", "L 317.156506 183.734384 \n", "L 315.174972 183.734384 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_133\">\n", " <path d=\"M 317.156506 188.638125 \n", "L 319.13804 188.638125 \n", "L 319.13804 183.495543 \n", "L 317.156506 183.495543 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_134\">\n", " <path d=\"M 319.13804 188.638125 \n", "L 321.119574 188.638125 \n", "L 321.119574 183.496909 \n", "L 319.13804 183.496909 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_135\">\n", " <path d=\"M 321.119574 188.638125 \n", "L 323.101108 188.638125 \n", "L 323.101108 184.128812 \n", "L 321.119574 184.128812 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_136\">\n", " <path d=\"M 323.101108 188.638125 \n", "L 325.082642 188.638125 \n", "L 325.082642 184.343086 \n", "L 323.101108 184.343086 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_137\">\n", " <path d=\"M 325.082642 188.638125 \n", "L 327.064176 188.638125 \n", "L 327.064176 184.278942 \n", "L 325.082642 184.278942 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_138\">\n", " <path d=\"M 327.064176 188.638125 \n", "L 329.045711 188.638125 \n", "L 329.045711 182.732619 \n", "L 327.064176 182.732619 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_139\">\n", " <path d=\"M 329.045711 188.638125 \n", "L 331.027244 188.638125 \n", "L 331.027244 184.284398 \n", "L 329.045711 184.284398 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_140\">\n", " <path d=\"M 331.027244 188.638125 \n", "L 333.008779 188.638125 \n", "L 333.008779 184.124719 \n", "L 331.027244 184.124719 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_141\">\n", " <path d=\"M 333.008779 188.638125 \n", "L 334.990313 188.638125 \n", "L 334.990313 185.103283 \n", "L 333.008779 185.103283 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_142\">\n", " <path d=\"M 334.990313 188.638125 \n", "L 336.971846 188.638125 \n", "L 336.971846 182.714873 \n", "L 334.990313 182.714873 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_143\">\n", " <path d=\"M 336.971846 188.638125 \n", "L 338.95338 188.638125 \n", "L 338.95338 184.216158 \n", "L 336.971846 184.216158 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_144\">\n", " <path d=\"M 338.95338 188.638125 \n", "L 340.934915 188.638125 \n", "L 340.934915 184.711587 \n", "L 338.95338 184.711587 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_145\">\n", " <path d=\"M 340.934915 188.638125 \n", "L 342.916448 188.638125 \n", "L 342.916448 185.137401 \n", "L 340.934915 185.137401 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_146\">\n", " <path d=\"M 342.916448 188.638125 \n", "L 344.897984 188.638125 \n", "L 344.897984 185.276615 \n", "L 342.916448 185.276615 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_147\">\n", " <path d=\"M 344.897984 188.638125 \n", "L 346.879517 188.638125 \n", "L 346.879517 184.890371 \n", "L 344.897984 184.890371 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_148\">\n", " <path d=\"M 346.879517 188.638125 \n", "L 348.861051 188.638125 \n", "L 348.861051 184.714312 \n", "L 346.879517 184.714312 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_149\">\n", " <path d=\"M 348.861051 188.638125 \n", "L 350.842586 188.638125 \n", "L 350.842586 185.449945 \n", "L 348.861051 185.449945 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_150\">\n", " <path d=\"M 350.842586 188.638125 \n", "L 352.82412 188.638125 \n", "L 352.82412 185.550937 \n", "L 350.842586 185.550937 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_151\">\n", " <path d=\"M 352.82412 188.638125 \n", "L 354.805653 188.638125 \n", "L 354.805653 185.548207 \n", "L 352.82412 185.548207 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_152\">\n", " <path d=\"M 354.805653 188.638125 \n", "L 356.787189 188.638125 \n", "L 356.787189 185.03914 \n", "L 354.805653 185.03914 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_153\">\n", " <path d=\"M 356.787189 188.638125 \n", "L 358.768719 188.638125 \n", "L 358.768719 186.03271 \n", "L 356.787189 186.03271 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_154\">\n", " <path d=\"M 358.768719 188.638125 \n", "L 360.750255 188.638125 \n", "L 360.750255 185.967206 \n", "L 358.768719 185.967206 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_155\">\n", " <path d=\"M 360.750255 188.638125 \n", "L 362.731791 188.638125 \n", "L 362.731791 185.586426 \n", "L 360.750255 185.586426 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_156\">\n", " <path d=\"M 362.731791 188.638125 \n", "L 364.713322 188.638125 \n", "L 364.713322 186.357534 \n", "L 362.731791 186.357534 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_157\">\n", " <path d=\"M 364.713322 188.638125 \n", "L 366.694857 188.638125 \n", "L 366.694857 185.859386 \n", "L 364.713322 185.859386 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_158\">\n", " <path d=\"M 366.694857 188.638125 \n", "L 368.676393 188.638125 \n", "L 368.676393 186.73286 \n", "L 366.694857 186.73286 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_159\">\n", " <path d=\"M 368.676393 188.638125 \n", "L 370.657924 188.638125 \n", "L 370.657924 186.588186 \n", "L 368.676393 186.588186 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_160\">\n", " <path d=\"M 370.657924 188.638125 \n", "L 372.639459 188.638125 \n", "L 372.639459 186.571813 \n", "L 370.657924 186.571813 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_161\">\n", " <path d=\"M 372.639459 188.638125 \n", "L 374.620995 188.638125 \n", "L 374.620995 186.691916 \n", "L 372.639459 186.691916 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_162\">\n", " <path d=\"M 374.620995 188.638125 \n", "L 376.602531 188.638125 \n", "L 376.602531 186.885718 \n", "L 374.620995 186.885718 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_163\">\n", " <path d=\"M 376.602531 188.638125 \n", "L 378.584062 188.638125 \n", "L 378.584062 187.016735 \n", "L 376.602531 187.016735 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_164\">\n", " <path d=\"M 378.584062 188.638125 \n", "L 380.565597 188.638125 \n", "L 380.565597 187.044035 \n", "L 378.584062 187.044035 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_165\">\n", " <path d=\"M 380.565597 188.638125 \n", "L 382.547133 188.638125 \n", "L 382.547133 187.506703 \n", "L 380.565597 187.506703 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_166\">\n", " <path d=\"M 382.547133 188.638125 \n", "L 384.528664 188.638125 \n", "L 384.528664 187.211902 \n", "L 382.547133 187.211902 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_167\">\n", " <path d=\"M 384.528664 188.638125 \n", "L 386.5102 188.638125 \n", "L 386.5102 187.407073 \n", "L 384.528664 187.407073 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_168\">\n", " <path d=\"M 386.5102 188.638125 \n", "L 388.491735 188.638125 \n", "L 388.491735 187.53127 \n", "L 386.5102 187.53127 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_169\">\n", " <path d=\"M 388.491735 188.638125 \n", "L 390.473266 188.638125 \n", "L 390.473266 187.550374 \n", "L 388.491735 187.550374 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_170\">\n", " <path d=\"M 390.473266 188.638125 \n", "L 392.454802 188.638125 \n", "L 392.454802 187.686857 \n", "L 390.473266 187.686857 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_171\">\n", " <path d=\"M 392.454802 188.638125 \n", "L 394.436337 188.638125 \n", "L 394.436337 187.742814 \n", "L 392.454802 187.742814 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_172\">\n", " <path d=\"M 394.436337 188.638125 \n", "L 396.417868 188.638125 \n", "L 396.417868 186.689181 \n", "L 394.436337 186.689181 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_173\">\n", " <path d=\"M 396.417868 188.638125 \n", "L 398.399399 188.638125 \n", "L 398.399399 186.517216 \n", "L 396.417868 186.517216 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_174\">\n", " <path d=\"M 398.399399 188.638125 \n", "L 400.38094 188.638125 \n", "L 400.38094 182.370965 \n", "L 398.399399 182.370965 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_175\">\n", " <path d=\"M 400.38094 188.638125 \n", "L 402.36247 188.638125 \n", "L 402.36247 176.337125 \n", "L 400.38094 176.337125 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_176\">\n", " <path d=\"M 402.36247 188.638125 \n", "L 404.344001 188.638125 \n", "L 404.344001 177.469914 \n", "L 402.36247 177.469914 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_177\">\n", " <path d=\"M 404.344001 188.638125 \n", "L 406.325542 188.638125 \n", "L 406.325542 176.177505 \n", "L 404.344001 176.177505 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_178\">\n", " <path d=\"M 406.325542 188.638125 \n", "L 408.307073 188.638125 \n", "L 408.307073 173.316809 \n", "L 406.325542 173.316809 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_179\">\n", " <path d=\"M 408.307073 188.638125 \n", "L 410.288603 188.638125 \n", "L 410.288603 174.774422 \n", "L 408.307073 174.774422 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_180\">\n", " <path d=\"M 410.288603 188.638125 \n", "L 412.270144 188.638125 \n", "L 412.270144 175.796726 \n", "L 410.288603 175.796726 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_181\">\n", " <path d=\"M 412.270144 188.638125 \n", "L 414.251675 188.638125 \n", "L 414.251675 177.322515 \n", "L 412.270144 177.322515 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_182\">\n", " <path d=\"M 414.251675 188.638125 \n", "L 416.233206 188.638125 \n", "L 416.233206 180.869647 \n", "L 414.251675 180.869647 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_183\">\n", " <path d=\"M 416.233206 188.638125 \n", "L 418.214746 188.638125 \n", "L 418.214746 181.65854 \n", "L 416.233206 181.65854 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_184\">\n", " <path d=\"M 418.214746 188.638125 \n", "L 420.196277 188.638125 \n", "L 420.196277 182.066582 \n", "L 418.214746 182.066582 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_185\">\n", " <path d=\"M 420.196277 188.638125 \n", "L 422.177808 188.638125 \n", "L 422.177808 182.884101 \n", "L 420.196277 182.884101 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_186\">\n", " <path d=\"M 422.177808 188.638125 \n", "L 424.159348 188.638125 \n", "L 424.159348 183.457346 \n", "L 422.177808 183.457346 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_187\">\n", " <path d=\"M 424.159348 188.638125 \n", "L 426.140879 188.638125 \n", "L 426.140879 183.70162 \n", "L 424.159348 183.70162 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_188\">\n", " <path d=\"M 426.140879 188.638125 \n", "L 428.12241 188.638125 \n", "L 428.12241 184.201139 \n", "L 426.140879 184.201139 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_189\">\n", " <path d=\"M 428.12241 188.638125 \n", "L 430.103951 188.638125 \n", "L 430.103951 186.455811 \n", "L 428.12241 186.455811 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_190\">\n", " <path d=\"M 430.103951 188.638125 \n", "L 432.085481 188.638125 \n", "L 432.085481 187.334735 \n", "L 430.103951 187.334735 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_191\">\n", " <path d=\"M 432.085481 188.638125 \n", "L 434.067012 188.638125 \n", "L 434.067012 187.517619 \n", "L 432.085481 187.517619 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_192\">\n", " <path d=\"M 434.067012 188.638125 \n", "L 436.048553 188.638125 \n", "L 436.048553 187.542191 \n", "L 434.067012 187.542191 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_193\">\n", " <path d=\"M 436.048553 188.638125 \n", "L 438.030084 188.638125 \n", "L 438.030084 187.630898 \n", "L 436.048553 187.630898 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_194\">\n", " <path d=\"M 438.030084 188.638125 \n", "L 440.011614 188.638125 \n", "L 440.011614 187.805593 \n", "L 438.030084 187.805593 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_195\">\n", " <path d=\"M 440.011614 188.638125 \n", "L 441.993155 188.638125 \n", "L 441.993155 187.781031 \n", "L 440.011614 187.781031 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_196\">\n", " <path d=\"M 441.993155 188.638125 \n", "L 443.974686 188.638125 \n", "L 443.974686 187.952992 \n", "L 441.993155 187.952992 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_197\">\n", " <path d=\"M 443.974686 188.638125 \n", "L 445.956226 188.638125 \n", "L 445.956226 187.965279 \n", "L 443.974686 187.965279 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_198\">\n", " <path d=\"M 445.956226 188.638125 \n", "L 447.937757 188.638125 \n", "L 447.937757 188.023962 \n", "L 445.956226 188.023962 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_199\">\n", " <path d=\"M 447.937757 188.638125 \n", "L 449.919288 188.638125 \n", "L 449.919288 188.07446 \n", "L 447.937757 188.07446 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_200\">\n", " <path d=\"M 449.919288 188.638125 \n", "L 451.900829 188.638125 \n", "L 451.900829 188.073098 \n", "L 449.919288 188.073098 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_201\">\n", " <path d=\"M 451.900829 188.638125 \n", "L 453.882359 188.638125 \n", "L 453.882359 188.200022 \n", "L 451.900829 188.200022 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_202\">\n", " <path d=\"M 453.882359 188.638125 \n", "L 455.86389 188.638125 \n", "L 455.86389 188.232778 \n", "L 453.882359 188.232778 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_203\">\n", " <path d=\"M 455.86389 188.638125 \n", "L 457.845431 188.638125 \n", "L 457.845431 188.208213 \n", "L 455.86389 188.208213 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_204\">\n", " <path d=\"M 457.845431 188.638125 \n", "L 459.826962 188.638125 \n", "L 459.826962 188.317396 \n", "L 457.845431 188.317396 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_205\">\n", " <path d=\"M 459.826962 188.638125 \n", "L 461.808492 188.638125 \n", "L 461.808492 188.288735 \n", "L 459.826962 188.288735 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_206\">\n", " <path d=\"M 461.808492 188.638125 \n", "L 463.790033 188.638125 \n", "L 463.790033 188.359706 \n", "L 461.808492 188.359706 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_207\">\n", " <path d=\"M 463.790033 188.638125 \n", "L 465.771564 188.638125 \n", "L 465.771564 188.370623 \n", "L 463.790033 188.370623 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_208\">\n", " <path d=\"M 465.771564 188.638125 \n", "L 467.753095 188.638125 \n", "L 467.753095 188.42385 \n", "L 465.771564 188.42385 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_209\">\n", " <path d=\"M 467.753095 188.638125 \n", "L 469.734635 188.638125 \n", "L 469.734635 188.408839 \n", "L 467.753095 188.408839 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_210\">\n", " <path d=\"M 469.734635 188.638125 \n", "L 471.716166 188.638125 \n", "L 471.716166 188.455241 \n", "L 469.734635 188.455241 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_211\">\n", " <path d=\"M 471.716166 188.638125 \n", "L 473.697697 188.638125 \n", "L 473.697697 188.442958 \n", "L 471.716166 188.442958 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_212\">\n", " <path d=\"M 473.697697 188.638125 \n", "L 475.679237 188.638125 \n", "L 475.679237 188.478443 \n", "L 473.697697 188.478443 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_213\">\n", " <path d=\"M 475.679237 188.638125 \n", "L 477.660768 188.638125 \n", "L 477.660768 188.507104 \n", "L 475.679237 188.507104 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_214\">\n", " <path d=\"M 477.660768 188.638125 \n", "L 479.642299 188.638125 \n", "L 479.642299 188.485267 \n", "L 477.660768 188.485267 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_215\">\n", " <path d=\"M 479.642299 188.638125 \n", "L 481.62384 188.638125 \n", "L 481.62384 188.504375 \n", "L 479.642299 188.504375 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_216\">\n", " <path d=\"M 481.62384 188.638125 \n", "L 483.60537 188.638125 \n", "L 483.60537 188.526211 \n", "L 481.62384 188.526211 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_217\">\n", " <path d=\"M 483.60537 188.638125 \n", "L 485.586901 188.638125 \n", "L 485.586901 188.542589 \n", "L 483.60537 188.542589 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_218\">\n", " <path d=\"M 485.586901 188.638125 \n", "L 487.568432 188.638125 \n", "L 487.568432 188.548048 \n", "L 485.586901 188.548048 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_219\">\n", " <path d=\"M 487.568432 188.638125 \n", "L 489.549963 188.638125 \n", "L 489.549963 188.564425 \n", "L 487.568432 188.564425 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_220\">\n", " <path d=\"M 489.549963 188.638125 \n", "L 491.531513 188.638125 \n", "L 491.531513 188.57125 \n", "L 489.549963 188.57125 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_221\">\n", " <path d=\"M 491.531513 188.638125 \n", "L 493.513044 188.638125 \n", "L 493.513044 188.564425 \n", "L 491.531513 188.564425 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_222\">\n", " <path d=\"M 493.513044 188.638125 \n", "L 495.494575 188.638125 \n", "L 495.494575 188.572614 \n", "L 493.513044 188.572614 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_223\">\n", " <path d=\"M 495.494575 188.638125 \n", "L 497.476106 188.638125 \n", "L 497.476106 188.564425 \n", "L 495.494575 188.564425 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_224\">\n", " <path d=\"M 497.476106 188.638125 \n", "L 499.457636 188.638125 \n", "L 499.457636 188.604005 \n", "L 497.476106 188.604005 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_225\">\n", " <path d=\"M 499.457636 188.638125 \n", "L 501.439167 188.638125 \n", "L 501.439167 188.598546 \n", "L 499.457636 188.598546 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_226\">\n", " <path d=\"M 501.439167 188.638125 \n", "L 503.420718 188.638125 \n", "L 503.420718 188.594452 \n", "L 501.439167 188.594452 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_227\">\n", " <path d=\"M 503.420718 188.638125 \n", "L 505.402248 188.638125 \n", "L 505.402248 188.604005 \n", "L 503.420718 188.604005 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_228\">\n", " <path d=\"M 505.402248 188.638125 \n", "L 507.383779 188.638125 \n", "L 507.383779 188.595816 \n", "L 505.402248 188.595816 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_229\">\n", " <path d=\"M 507.383779 188.638125 \n", "L 509.36531 188.638125 \n", "L 509.36531 188.612194 \n", "L 507.383779 188.612194 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_230\">\n", " <path d=\"M 509.36531 188.638125 \n", "L 511.346841 188.638125 \n", "L 511.346841 188.608099 \n", "L 509.36531 188.608099 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_231\">\n", " <path d=\"M 511.346841 188.638125 \n", "L 513.328371 188.638125 \n", "L 513.328371 188.619018 \n", "L 511.346841 188.619018 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_232\">\n", " <path d=\"M 513.328371 188.638125 \n", "L 515.309922 188.638125 \n", "L 515.309922 188.617653 \n", "L 513.328371 188.617653 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_233\">\n", " <path d=\"M 515.309922 188.638125 \n", "L 517.291453 188.638125 \n", "L 517.291453 188.621747 \n", "L 515.309922 188.621747 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_234\">\n", " <path d=\"M 517.291453 188.638125 \n", "L 519.272984 188.638125 \n", "L 519.272984 188.619018 \n", "L 517.291453 188.619018 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_235\">\n", " <path d=\"M 519.272984 188.638125 \n", "L 521.254514 188.638125 \n", "L 521.254514 188.629936 \n", "L 519.272984 188.629936 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_236\">\n", " <path d=\"M 521.254514 188.638125 \n", "L 523.236045 188.638125 \n", "L 523.236045 188.620383 \n", "L 521.254514 188.620383 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_237\">\n", " <path d=\"M 523.236045 188.638125 \n", "L 525.217576 188.638125 \n", "L 525.217576 188.625842 \n", "L 523.236045 188.625842 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_238\">\n", " <path d=\"M 525.217576 188.638125 \n", "L 527.199126 188.638125 \n", "L 527.199126 188.625842 \n", "L 525.217576 188.625842 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_239\">\n", " <path d=\"M 527.199126 188.638125 \n", "L 529.180657 188.638125 \n", "L 529.180657 188.628571 \n", "L 527.199126 188.628571 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_240\">\n", " <path d=\"M 529.180657 188.638125 \n", "L 531.162188 188.638125 \n", "L 531.162188 188.629936 \n", "L 529.180657 188.629936 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_241\">\n", " <path d=\"M 531.162188 188.638125 \n", "L 533.143719 188.638125 \n", "L 533.143719 188.625842 \n", "L 531.162188 188.625842 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_242\">\n", " <path d=\"M 533.143719 188.638125 \n", "L 535.125249 188.638125 \n", "L 535.125249 188.629936 \n", "L 533.143719 188.629936 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_243\">\n", " <path d=\"M 535.125249 188.638125 \n", "L 537.10678 188.638125 \n", "L 537.10678 188.635395 \n", "L 535.125249 188.635395 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_244\">\n", " <path d=\"M 537.10678 188.638125 \n", "L 539.088331 188.638125 \n", "L 539.088331 188.634031 \n", "L 537.10678 188.634031 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_245\">\n", " <path d=\"M 539.088331 188.638125 \n", "L 541.069862 188.638125 \n", "L 541.069862 188.628571 \n", "L 539.088331 188.628571 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_246\">\n", " <path d=\"M 541.069862 188.638125 \n", "L 543.051392 188.638125 \n", "L 543.051392 188.627207 \n", "L 541.069862 188.627207 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_247\">\n", " <path d=\"M 543.051392 188.638125 \n", "L 545.032923 188.638125 \n", "L 545.032923 188.632666 \n", "L 543.051392 188.632666 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_248\">\n", " <path d=\"M 545.032923 188.638125 \n", "L 547.014454 188.638125 \n", "L 547.014454 188.631301 \n", "L 545.032923 188.631301 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_249\">\n", " <path d=\"M 547.014454 188.638125 \n", "L 548.995985 188.638125 \n", "L 548.995985 188.634031 \n", "L 547.014454 188.634031 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_250\">\n", " <path d=\"M 548.995985 188.638125 \n", "L 550.977535 188.638125 \n", "L 550.977535 188.63676 \n", "L 548.995985 188.63676 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_251\">\n", " <path d=\"M 550.977535 188.638125 \n", "L 552.959066 188.638125 \n", "L 552.959066 188.638125 \n", "L 550.977535 188.638125 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_252\">\n", " <path d=\"M 552.959066 188.638125 \n", "L 554.940597 188.638125 \n", "L 554.940597 188.632666 \n", "L 552.959066 188.632666 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_253\">\n", " <path d=\"M 554.940597 188.638125 \n", "L 556.922128 188.638125 \n", "L 556.922128 188.635395 \n", "L 554.940597 188.635395 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_254\">\n", " <path d=\"M 556.922128 188.638125 \n", "L 558.903658 188.638125 \n", "L 558.903658 188.635395 \n", "L 556.922128 188.635395 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_255\">\n", " <path d=\"M 558.903658 188.638125 \n", "L 560.885189 188.638125 \n", "L 560.885189 188.635395 \n", "L 558.903658 188.635395 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_256\">\n", " <path d=\"M 560.885189 188.638125 \n", "L 562.86674 188.638125 \n", "L 562.86674 188.63676 \n", "L 560.885189 188.63676 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_257\">\n", " <path d=\"M 562.86674 188.638125 \n", "L 564.84827 188.638125 \n", "L 564.84827 188.638125 \n", "L 562.86674 188.638125 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_258\">\n", " <path d=\"M 564.84827 188.638125 \n", "L 566.829801 188.638125 \n", "L 566.829801 188.635395 \n", "L 564.84827 188.635395 \n", "z\n", "\" clip-path=\"url(#p7a7cd8ce2f)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_259\">\n", " <path d=\"M 34.193438 188.638125 \n", "L 34.193438 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_260\">\n", " <path d=\"M 592.193437 188.638125 \n", "L 592.193437 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_261\">\n", " <path d=\"M 34.193438 188.638125 \n", "L 592.193438 188.638125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_262\">\n", " <path d=\"M 34.193438 22.318125 \n", "L 592.193438 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"text_10\">\n", " <!-- Dequantization -->\n", " <g style=\"fill: #262626\" transform=\"translate(267.452812 16.318125) scale(0.12 -0.12)\">\n", " <defs>\n", " <path id=\"DejaVuSans-44\" d=\"M 1259 4147 \n", "L 1259 519 \n", "L 2022 519 \n", "Q 2988 519 3436 956 \n", "Q 3884 1394 3884 2338 \n", "Q 3884 3275 3436 3711 \n", "Q 2988 4147 2022 4147 \n", "L 1259 4147 \n", "z\n", "M 628 4666 \n", "L 1925 4666 \n", "Q 3281 4666 3915 4102 \n", "Q 4550 3538 4550 2338 \n", "Q 4550 1131 3912 565 \n", "Q 3275 0 1925 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-65\" d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-71\" d=\"M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "M 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "L 2906 3500 \n", "L 3481 3500 \n", "L 3481 -1331 \n", "L 2906 -1331 \n", "L 2906 525 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-75\" d=\"M 544 1381 \n", "L 544 3500 \n", "L 1119 3500 \n", "L 1119 1403 \n", "Q 1119 906 1312 657 \n", "Q 1506 409 1894 409 \n", "Q 2359 409 2629 706 \n", "Q 2900 1003 2900 1516 \n", "L 2900 3500 \n", "L 3475 3500 \n", "L 3475 0 \n", "L 2900 0 \n", "L 2900 538 \n", "Q 2691 219 2414 64 \n", "Q 2138 -91 1772 -91 \n", "Q 1169 -91 856 284 \n", "Q 544 659 544 1381 \n", "z\n", "M 1991 3584 \n", "L 1991 3584 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-61\" d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6e\" d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-74\" d=\"M 1172 4494 \n", "L 1172 3500 \n", "L 2356 3500 \n", "L 2356 3053 \n", "L 1172 3053 \n", "L 1172 1153 \n", "Q 1172 725 1289 603 \n", "Q 1406 481 1766 481 \n", "L 2356 481 \n", "L 2356 0 \n", "L 1766 0 \n", "Q 1100 0 847 248 \n", "Q 594 497 594 1153 \n", "L 594 3053 \n", "L 172 3053 \n", "L 172 3500 \n", "L 594 3500 \n", "L 594 4494 \n", "L 1172 4494 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-69\" d=\"M 603 3500 \n", "L 1178 3500 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 3500 \n", "z\n", "M 603 4863 \n", "L 1178 4863 \n", "L 1178 4134 \n", "L 603 4134 \n", "L 603 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-7a\" d=\"M 353 3500 \n", "L 3084 3500 \n", "L 3084 2975 \n", "L 922 459 \n", "L 3084 459 \n", "L 3084 0 \n", "L 275 0 \n", "L 275 525 \n", "L 2438 3041 \n", "L 353 3041 \n", "L 353 3500 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6f\" d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-44\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"77.001953\"/>\n", " <use xlink:href=\"#DejaVuSans-71\" x=\"138.525391\"/>\n", " <use xlink:href=\"#DejaVuSans-75\" x=\"202.001953\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"265.380859\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"326.660156\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"390.039062\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"429.248047\"/>\n", " <use xlink:href=\"#DejaVuSans-7a\" x=\"457.03125\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"509.521484\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"570.800781\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"610.009766\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"637.792969\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"698.974609\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"p7a7cd8ce2f\">\n", " <rect x=\"34.193438\" y=\"22.318125\" width=\"558\" height=\"166.32\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 1000x300 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["visualize_dequant_distribution(flow_dict[\"simple\"][\"model\"], sample_imgs, title=\"Dequantization\")"]}, {"cell_type": "code", "execution_count": 35, "id": "50826bcf", "metadata": {"execution": {"iopub.execute_input": "2023-03-14T16:09:02.341693Z", "iopub.status.busy": "2023-03-14T16:09:02.341310Z", "iopub.status.idle": "2023-03-14T16:09:03.127501Z", "shell.execute_reply": "2023-03-14T16:09:03.126890Z"}, "papermill": {"duration": 0.815664, "end_time": "2023-03-14T16:09:03.131581", "exception": false, "start_time": "2023-03-14T16:09:02.315917", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "b2b8c9cb3fdd4e77bf734fc7a847d4ff", "version_major": 2, "version_minor": 0}, "text/plain": [" 0%| | 0/8 [00:00<?, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/pdf": "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", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"599.393438pt\" height=\"215.984063pt\" viewBox=\"0 0 599.393438 215.984063\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n", " <metadata>\n", " <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", " <cc:Work>\n", " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", " <dc:date>2023-03-14T16:09:02.796830</dc:date>\n", " <dc:format>image/svg+xml</dc:format>\n", " <dc:creator>\n", " <cc:Agent>\n", " <dc:title>Matplotlib v3.7.1, https://matplotlib.org/</dc:title>\n", " </cc:Agent>\n", " </dc:creator>\n", " </cc:Work>\n", " </rdf:RDF>\n", " </metadata>\n", " <defs>\n", " <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", " <g id=\"patch_1\">\n", " <path d=\"M 0 215.984063 \n", "L 599.393438 215.984063 \n", "L 599.393438 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill: #ffffff\"/>\n", " </g>\n", " <g id=\"axes_1\">\n", " <g id=\"patch_2\">\n", " <path d=\"M 34.193438 188.638125 \n", "L 592.193437 188.638125 \n", "L 592.193437 22.318125 \n", "L 34.193438 22.318125 \n", "z\n", "\" style=\"fill: #eaeaf2\"/>\n", " </g>\n", " <g id=\"matplotlib.axis_1\">\n", " <g id=\"xtick_1\">\n", " <g id=\"line2d_1\">\n", " <path d=\"M 105.640487 188.638125 \n", "L 105.640487 22.318125 \n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_1\">\n", " <!-- \u221210 -->\n", " <g style=\"fill: #262626\" transform=\"translate(94.032909 206.496406) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-2212\" d=\"M 678 2272 \n", "L 4684 2272 \n", "L 4684 1741 \n", "L 678 1741 \n", "L 678 2272 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-31\" d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-30\" d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"83.789062\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"147.412109\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_2\">\n", " <g id=\"line2d_2\">\n", " <path d=\"M 210.215912 188.638125 \n", "L 210.215912 22.318125 \n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_2\">\n", " <!-- \u22125 -->\n", " <g style=\"fill: #262626\" transform=\"translate(202.107708 206.496406) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-35\" d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-2212\"/>\n", " <use xlink:href=\"#DejaVuSans-35\" x=\"83.789062\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_3\">\n", " <g id=\"line2d_3\">\n", " <path d=\"M 314.791336 188.638125 \n", "L 314.791336 22.318125 \n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_3\">\n", " <!-- 0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(311.291961 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_4\">\n", " <g id=\"line2d_4\">\n", " <path d=\"M 419.36676 188.638125 \n", "L 419.36676 22.318125 \n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_4\">\n", " <!-- 5 -->\n", " <g style=\"fill: #262626\" transform=\"translate(415.867385 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-35\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"xtick_5\">\n", " <g id=\"line2d_5\">\n", " <path d=\"M 523.942185 188.638125 \n", "L 523.942185 22.318125 \n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_5\">\n", " <!-- 10 -->\n", " <g style=\"fill: #262626\" transform=\"translate(516.943435 206.496406) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-31\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"63.623047\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"matplotlib.axis_2\">\n", " <g id=\"ytick_1\">\n", " <g id=\"line2d_6\">\n", " <path d=\"M 34.193438 188.638125 \n", "L 592.193437 188.638125 \n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_6\">\n", " <!-- 0.0 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 192.817266) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-2e\" d=\"M 684 794 \n", "L 1344 794 \n", "L 1344 0 \n", "L 684 0 \n", "L 684 794 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-30\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_2\">\n", " <g id=\"line2d_7\">\n", " <path d=\"M 34.193438 147.092059 \n", "L 592.193437 147.092059 \n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_7\">\n", " <!-- 0.1 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 151.2712) scale(0.11 -0.11)\">\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-31\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_3\">\n", " <g id=\"line2d_8\">\n", " <path d=\"M 34.193438 105.545994 \n", "L 592.193437 105.545994 \n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_8\">\n", " <!-- 0.2 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 109.725134) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-32\" d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-32\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_4\">\n", " <g id=\"line2d_9\">\n", " <path d=\"M 34.193438 63.999928 \n", "L 592.193437 63.999928 \n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_9\">\n", " <!-- 0.3 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 68.179068) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-33\" d=\"M 2597 2516 \n", "Q 3050 2419 3304 2112 \n", "Q 3559 1806 3559 1356 \n", "Q 3559 666 3084 287 \n", "Q 2609 -91 1734 -91 \n", "Q 1441 -91 1130 -33 \n", "Q 819 25 488 141 \n", "L 488 750 \n", "Q 750 597 1062 519 \n", "Q 1375 441 1716 441 \n", "Q 2309 441 2620 675 \n", "Q 2931 909 2931 1356 \n", "Q 2931 1769 2642 2001 \n", "Q 2353 2234 1838 2234 \n", "L 1294 2234 \n", "L 1294 2753 \n", "L 1863 2753 \n", "Q 2328 2753 2575 2939 \n", "Q 2822 3125 2822 3475 \n", "Q 2822 3834 2567 4026 \n", "Q 2313 4219 1838 4219 \n", "Q 1578 4219 1281 4162 \n", "Q 984 4106 628 3988 \n", "L 628 4550 \n", "Q 988 4650 1302 4700 \n", "Q 1616 4750 1894 4750 \n", "Q 2613 4750 3031 4423 \n", "Q 3450 4097 3450 3541 \n", "Q 3450 3153 3228 2886 \n", "Q 3006 2619 2597 2516 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-33\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"ytick_5\">\n", " <g id=\"line2d_10\">\n", " <path d=\"M 34.193438 22.453862 \n", "L 592.193437 22.453862 \n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: none; stroke: #ffffff; stroke-linecap: round\"/>\n", " </g>\n", " <g id=\"text_10\">\n", " <!-- 0.4 -->\n", " <g style=\"fill: #262626\" transform=\"translate(7.2 26.633003) scale(0.11 -0.11)\">\n", " <defs>\n", " <path id=\"DejaVuSans-34\" d=\"M 2419 4116 \n", "L 825 1625 \n", "L 2419 1625 \n", "L 2419 4116 \n", "z\n", "M 2253 4666 \n", "L 3047 4666 \n", "L 3047 1625 \n", "L 3713 1625 \n", "L 3713 1100 \n", "L 3047 1100 \n", "L 3047 0 \n", "L 2419 0 \n", "L 2419 1100 \n", "L 313 1100 \n", "L 313 1709 \n", "L 2253 4666 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-30\"/>\n", " <use xlink:href=\"#DejaVuSans-2e\" x=\"63.623047\"/>\n", " <use xlink:href=\"#DejaVuSans-34\" x=\"95.410156\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <g id=\"patch_3\">\n", " <path d=\"M 59.557074 188.638125 \n", "L 61.538607 188.638125 \n", "L 61.538607 188.534342 \n", "L 59.557074 188.534342 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_4\">\n", " <path d=\"M 61.538607 188.638125 \n", "L 63.52014 188.638125 \n", "L 63.52014 188.436021 \n", "L 61.538607 188.436021 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_5\">\n", " <path d=\"M 63.52014 188.638125 \n", "L 65.501674 188.638125 \n", "L 65.501674 188.302196 \n", "L 63.52014 188.302196 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_6\">\n", " <path d=\"M 65.501674 188.638125 \n", "L 67.483207 188.638125 \n", "L 67.483207 188.192951 \n", "L 65.501674 188.192951 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_7\">\n", " <path d=\"M 67.483207 188.638125 \n", "L 69.46474 188.638125 \n", "L 69.46474 188.061857 \n", "L 67.483207 188.061857 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_8\">\n", " <path d=\"M 69.46474 188.638125 \n", "L 71.446273 188.638125 \n", "L 71.446273 187.911645 \n", "L 69.46474 187.911645 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_9\">\n", " <path d=\"M 71.446273 188.638125 \n", "L 73.427807 188.638125 \n", "L 73.427807 187.559329 \n", "L 71.446273 187.559329 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_10\">\n", " <path d=\"M 73.427807 188.638125 \n", "L 75.40934 188.638125 \n", "L 75.40934 187.283485 \n", "L 73.427807 187.283485 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_11\">\n", " <path d=\"M 75.40934 188.638125 \n", "L 77.390873 188.638125 \n", "L 77.390873 186.914783 \n", "L 75.40934 186.914783 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_12\">\n", " <path d=\"M 77.390873 188.638125 \n", "L 79.372406 188.638125 \n", "L 79.372406 186.221076 \n", "L 77.390873 186.221076 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_13\">\n", " <path d=\"M 79.372406 188.638125 \n", "L 81.353939 188.638125 \n", "L 81.353939 185.467285 \n", "L 79.372406 185.467285 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_14\">\n", " <path d=\"M 81.353939 188.638125 \n", "L 83.335493 188.638125 \n", "L 83.335493 184.626137 \n", "L 81.353939 184.626137 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_15\">\n", " <path d=\"M 83.335493 188.638125 \n", "L 85.317026 188.638125 \n", "L 85.317026 183.402551 \n", "L 83.335493 183.402551 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_16\">\n", " <path d=\"M 85.317026 188.638125 \n", "L 87.298559 188.638125 \n", "L 87.298559 181.791185 \n", "L 85.317026 181.791185 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_17\">\n", " <path d=\"M 87.298559 188.638125 \n", "L 89.280092 188.638125 \n", "L 89.280092 179.398717 \n", "L 87.298559 179.398717 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_18\">\n", " <path d=\"M 89.280092 188.638125 \n", "L 91.261626 188.638125 \n", "L 91.261626 177.019904 \n", "L 89.280092 177.019904 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_19\">\n", " <path d=\"M 91.261626 188.638125 \n", "L 93.243159 188.638125 \n", "L 93.243159 174.59193 \n", "L 91.261626 174.59193 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_20\">\n", " <path d=\"M 93.243159 188.638125 \n", "L 95.224692 188.638125 \n", "L 95.224692 170.907638 \n", "L 93.243159 170.907638 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_21\">\n", " <path d=\"M 95.224692 188.638125 \n", "L 97.206225 188.638125 \n", "L 97.206225 166.005262 \n", "L 95.224692 166.005262 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_22\">\n", " <path d=\"M 97.206225 188.638125 \n", "L 99.187758 188.638125 \n", "L 99.187758 161.162971 \n", "L 97.206225 161.162971 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_23\">\n", " <path d=\"M 99.187758 188.638125 \n", "L 101.169292 188.638125 \n", "L 101.169292 155.441256 \n", "L 99.187758 155.441256 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_24\">\n", " <path d=\"M 101.169292 188.638125 \n", "L 103.150825 188.638125 \n", "L 103.150825 148.449567 \n", "L 101.169292 148.449567 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_25\">\n", " <path d=\"M 103.150825 188.638125 \n", "L 105.132358 188.638125 \n", "L 105.132358 140.600303 \n", "L 103.150825 140.600303 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_26\">\n", " <path d=\"M 105.132358 188.638125 \n", "L 107.113891 188.638125 \n", "L 107.113891 132.008172 \n", "L 105.132358 132.008172 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_27\">\n", " <path d=\"M 107.113891 188.638125 \n", "L 109.095425 188.638125 \n", "L 109.095425 122.946287 \n", "L 107.113891 122.946287 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_28\">\n", " <path d=\"M 109.095425 188.638125 \n", "L 111.076958 188.638125 \n", "L 111.076958 114.012766 \n", "L 109.095425 114.012766 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_29\">\n", " <path d=\"M 111.076958 188.638125 \n", "L 113.058491 188.638125 \n", "L 113.058491 103.224807 \n", "L 111.076958 103.224807 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_30\">\n", " <path d=\"M 113.058491 188.638125 \n", "L 115.040024 188.638125 \n", "L 115.040024 91.680326 \n", "L 113.058491 91.680326 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_31\">\n", " <path d=\"M 115.040024 188.638125 \n", "L 117.021558 188.638125 \n", "L 117.021558 82.506465 \n", "L 115.040024 82.506465 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_32\">\n", " <path d=\"M 117.021558 188.638125 \n", "L 119.003091 188.638125 \n", "L 119.003091 70.148108 \n", "L 117.021558 70.148108 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_33\">\n", " <path d=\"M 119.003091 188.638125 \n", "L 120.984624 188.638125 \n", "L 120.984624 61.976571 \n", "L 119.003091 61.976571 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_34\">\n", " <path d=\"M 120.984624 188.638125 \n", "L 122.966157 188.638125 \n", "L 122.966157 52.677078 \n", "L 120.984624 52.677078 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_35\">\n", " <path d=\"M 122.966157 188.638125 \n", "L 124.947691 188.638125 \n", "L 124.947691 44.508272 \n", "L 122.966157 44.508272 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_36\">\n", " <path d=\"M 124.947691 188.638125 \n", "L 126.929224 188.638125 \n", "L 126.929224 37.04956 \n", "L 124.947691 37.04956 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_37\">\n", " <path d=\"M 126.929224 188.638125 \n", "L 128.910777 188.638125 \n", "L 128.910777 33.970404 \n", "L 126.929224 33.970404 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_38\">\n", " <path d=\"M 128.910777 188.638125 \n", "L 130.89231 188.638125 \n", "L 130.89231 30.486658 \n", "L 128.910777 30.486658 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_39\">\n", " <path d=\"M 130.89231 188.638125 \n", "L 132.873843 188.638125 \n", "L 132.873843 30.814393 \n", "L 130.89231 30.814393 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_40\">\n", " <path d=\"M 132.873843 188.638125 \n", "L 134.855377 188.638125 \n", "L 134.855377 30.238125 \n", "L 132.873843 30.238125 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_41\">\n", " <path d=\"M 134.855377 188.638125 \n", "L 136.83691 188.638125 \n", "L 136.83691 33.843215 \n", "L 134.855377 33.843215 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_42\">\n", " <path d=\"M 136.83691 188.638125 \n", "L 138.818443 188.638125 \n", "L 138.818443 38.680044 \n", "L 136.83691 38.680044 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_43\">\n", " <path d=\"M 138.818443 188.638125 \n", "L 140.799976 188.638125 \n", "L 140.799976 47.274906 \n", "L 138.818443 47.274906 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_44\">\n", " <path d=\"M 140.799976 188.638125 \n", "L 142.78151 188.638125 \n", "L 142.78151 53.761336 \n", "L 140.799976 53.761336 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_45\">\n", " <path d=\"M 142.78151 188.638125 \n", "L 144.763043 188.638125 \n", "L 144.763043 64.434587 \n", "L 142.78151 64.434587 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_46\">\n", " <path d=\"M 144.763043 188.638125 \n", "L 146.744576 188.638125 \n", "L 146.744576 75.583054 \n", "L 144.763043 75.583054 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_47\">\n", " <path d=\"M 146.744576 188.638125 \n", "L 148.726109 188.638125 \n", "L 148.726109 85.690961 \n", "L 146.744576 85.690961 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_48\">\n", " <path d=\"M 148.726109 188.638125 \n", "L 150.707643 188.638125 \n", "L 150.707643 98.860464 \n", "L 148.726109 98.860464 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_49\">\n", " <path d=\"M 150.707643 188.638125 \n", "L 152.689176 188.638125 \n", "L 152.689176 108.919211 \n", "L 150.707643 108.919211 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_50\">\n", " <path d=\"M 152.689176 188.638125 \n", "L 154.670709 188.638125 \n", "L 154.670709 120.026711 \n", "L 152.689176 120.026711 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_51\">\n", " <path d=\"M 154.670709 188.638125 \n", "L 156.652242 188.638125 \n", "L 156.652242 128.749936 \n", "L 154.670709 128.749936 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_52\">\n", " <path d=\"M 156.652242 188.638125 \n", "L 158.633775 188.638125 \n", "L 158.633775 138.442711 \n", "L 156.652242 138.442711 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_53\">\n", " <path d=\"M 158.633775 188.638125 \n", "L 160.615309 188.638125 \n", "L 160.615309 147.168667 \n", "L 158.633775 147.168667 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_54\">\n", " <path d=\"M 160.615309 188.638125 \n", "L 162.596842 188.638125 \n", "L 162.596842 153.24816 \n", "L 160.615309 153.24816 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_55\">\n", " <path d=\"M 162.596842 188.638125 \n", "L 164.578385 188.638125 \n", "L 164.578385 160.070663 \n", "L 162.596842 160.070663 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_56\">\n", " <path d=\"M 164.578385 188.638125 \n", "L 166.559918 188.638125 \n", "L 166.559918 164.800834 \n", "L 164.578385 164.800834 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_57\">\n", " <path d=\"M 166.559918 188.638125 \n", "L 168.541452 188.638125 \n", "L 168.541452 169.088706 \n", "L 166.559918 169.088706 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_58\">\n", " <path d=\"M 168.541452 188.638125 \n", "L 170.522985 188.638125 \n", "L 170.522985 172.600938 \n", "L 168.541452 172.600938 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_59\">\n", " <path d=\"M 170.522985 188.638125 \n", "L 172.504518 188.638125 \n", "L 172.504518 175.493203 \n", "L 170.522985 175.493203 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_60\">\n", " <path d=\"M 172.504518 188.638125 \n", "L 174.486051 188.638125 \n", "L 174.486051 177.937563 \n", "L 172.504518 177.937563 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_61\">\n", " <path d=\"M 174.486051 188.638125 \n", "L 176.467585 188.638125 \n", "L 176.467585 179.912169 \n", "L 174.486051 179.912169 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_62\">\n", " <path d=\"M 176.467585 188.638125 \n", "L 178.449118 188.638125 \n", "L 178.449118 181.482568 \n", "L 176.467585 181.482568 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_63\">\n", " <path d=\"M 178.449118 188.638125 \n", "L 180.430651 188.638125 \n", "L 180.430651 182.5996 \n", "L 178.449118 182.5996 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_64\">\n", " <path d=\"M 180.430651 188.638125 \n", "L 182.412184 188.638125 \n", "L 182.412184 183.773985 \n", "L 180.430651 183.773985 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_65\">\n", " <path d=\"M 182.412184 188.638125 \n", "L 184.393717 188.638125 \n", "L 184.393717 184.402144 \n", "L 182.412184 184.402144 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_66\">\n", " <path d=\"M 184.393717 188.638125 \n", "L 186.375261 188.638125 \n", "L 186.375261 184.983893 \n", "L 184.393717 184.983893 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_67\">\n", " <path d=\"M 186.375261 188.638125 \n", "L 188.356794 188.638125 \n", "L 188.356794 185.538294 \n", "L 186.375261 185.538294 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_68\">\n", " <path d=\"M 188.356794 188.638125 \n", "L 190.338327 188.638125 \n", "L 190.338327 186.032628 \n", "L 188.356794 186.032628 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_69\">\n", " <path d=\"M 190.338327 188.638125 \n", "L 192.31986 188.638125 \n", "L 192.31986 186.551543 \n", "L 190.338327 186.551543 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_70\">\n", " <path d=\"M 192.31986 188.638125 \n", "L 194.301394 188.638125 \n", "L 194.301394 186.64167 \n", "L 192.31986 186.64167 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_71\">\n", " <path d=\"M 194.301394 188.638125 \n", "L 196.282927 188.638125 \n", "L 196.282927 186.947556 \n", "L 194.301394 186.947556 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_72\">\n", " <path d=\"M 196.282927 188.638125 \n", "L 198.26446 188.638125 \n", "L 198.26446 187.36815 \n", "L 196.282927 187.36815 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_73\">\n", " <path d=\"M 198.26446 188.638125 \n", "L 200.245993 188.638125 \n", "L 200.245993 188.146522 \n", "L 198.26446 188.146522 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_74\">\n", " <path d=\"M 200.245993 188.638125 \n", "L 202.227527 188.638125 \n", "L 202.227527 188.419635 \n", "L 200.245993 188.419635 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_75\">\n", " <path d=\"M 202.227527 188.638125 \n", "L 204.20906 188.638125 \n", "L 204.20906 188.449677 \n", "L 202.227527 188.449677 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_76\">\n", " <path d=\"M 204.20906 188.638125 \n", "L 206.190593 188.638125 \n", "L 206.190593 188.425097 \n", "L 204.20906 188.425097 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_77\">\n", " <path d=\"M 206.190593 188.638125 \n", "L 208.172126 188.638125 \n", "L 208.172126 188.40871 \n", "L 206.190593 188.40871 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_78\">\n", " <path d=\"M 208.172126 188.638125 \n", "L 210.153669 188.638125 \n", "L 210.153669 188.40598 \n", "L 208.172126 188.40598 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_79\">\n", " <path d=\"M 210.153669 188.638125 \n", "L 212.135203 188.638125 \n", "L 212.135203 188.419635 \n", "L 210.153669 188.419635 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_80\">\n", " <path d=\"M 212.135203 188.638125 \n", "L 214.116736 188.638125 \n", "L 214.116736 188.283078 \n", "L 212.135203 188.283078 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_81\">\n", " <path d=\"M 214.116736 188.638125 \n", "L 216.098269 188.638125 \n", "L 216.098269 187.911645 \n", "L 214.116736 187.911645 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_82\">\n", " <path d=\"M 216.098269 188.638125 \n", "L 218.079802 188.638125 \n", "L 218.079802 187.897989 \n", "L 216.098269 187.897989 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_83\">\n", " <path d=\"M 218.079802 188.638125 \n", "L 220.061336 188.638125 \n", "L 220.061336 187.870678 \n", "L 218.079802 187.870678 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_84\">\n", " <path d=\"M 220.061336 188.638125 \n", "L 222.042869 188.638125 \n", "L 222.042869 187.701348 \n", "L 220.061336 187.701348 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_85\">\n", " <path d=\"M 222.042869 188.638125 \n", "L 224.024402 188.638125 \n", "L 224.024402 187.82698 \n", "L 222.042869 187.82698 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_86\">\n", " <path d=\"M 224.024402 188.638125 \n", "L 226.005935 188.638125 \n", "L 226.005935 187.720466 \n", "L 224.024402 187.720466 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_87\">\n", " <path d=\"M 226.005935 188.638125 \n", "L 227.987469 188.638125 \n", "L 227.987469 187.622145 \n", "L 226.005935 187.622145 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_88\">\n", " <path d=\"M 227.987469 188.638125 \n", "L 229.969002 188.638125 \n", "L 229.969002 187.340839 \n", "L 227.987469 187.340839 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_89\">\n", " <path d=\"M 229.969002 188.638125 \n", "L 231.95054 188.638125 \n", "L 231.95054 187.171513 \n", "L 229.969002 187.171513 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_90\">\n", " <path d=\"M 231.95054 188.638125 \n", "L 233.932073 188.638125 \n", "L 233.932073 187.204282 \n", "L 231.95054 187.204282 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_91\">\n", " <path d=\"M 233.932073 188.638125 \n", "L 235.913606 188.638125 \n", "L 235.913606 187.171509 \n", "L 233.932073 187.171509 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_92\">\n", " <path d=\"M 235.913606 188.638125 \n", "L 237.89514 188.638125 \n", "L 237.89514 186.595241 \n", "L 235.913606 186.595241 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_93\">\n", " <path d=\"M 237.89514 188.638125 \n", "L 239.876678 188.638125 \n", "L 239.876678 186.196502 \n", "L 237.89514 186.196502 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_94\">\n", " <path d=\"M 239.876678 188.638125 \n", "L 241.858211 188.638125 \n", "L 241.858211 186.425911 \n", "L 239.876678 186.425911 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_95\">\n", " <path d=\"M 241.858211 188.638125 \n", "L 243.839744 188.638125 \n", "L 243.839744 186.286623 \n", "L 241.858211 186.286623 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_96\">\n", " <path d=\"M 243.839744 188.638125 \n", "L 245.821278 188.638125 \n", "L 245.821278 186.076326 \n", "L 243.839744 186.076326 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_97\">\n", " <path d=\"M 245.821278 188.638125 \n", "L 247.802811 188.638125 \n", "L 247.802811 185.049422 \n", "L 245.821278 185.049422 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_98\">\n", " <path d=\"M 247.802811 188.638125 \n", "L 249.784344 188.638125 \n", "L 249.784344 185.205096 \n", "L 247.802811 185.205096 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_99\">\n", " <path d=\"M 249.784344 188.638125 \n", "L 251.765882 188.638125 \n", "L 251.765882 184.921068 \n", "L 249.784344 184.921068 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_100\">\n", " <path d=\"M 251.765882 188.638125 \n", "L 253.747416 188.638125 \n", "L 253.747416 185.439973 \n", "L 251.765882 185.439973 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_101\">\n", " <path d=\"M 253.747416 188.638125 \n", "L 255.728949 188.638125 \n", "L 255.728949 184.503196 \n", "L 253.747416 184.503196 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_102\">\n", " <path d=\"M 255.728949 188.638125 \n", "L 257.710482 188.638125 \n", "L 257.710482 185.041229 \n", "L 255.728949 185.041229 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_103\">\n", " <path d=\"M 257.710482 188.638125 \n", "L 259.692015 188.638125 \n", "L 259.692015 184.956564 \n", "L 257.710482 184.956564 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_104\">\n", " <path d=\"M 259.692015 188.638125 \n", "L 261.673553 188.638125 \n", "L 261.673553 184.41308 \n", "L 259.692015 184.41308 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_105\">\n", " <path d=\"M 261.673553 188.638125 \n", "L 263.655087 188.638125 \n", "L 263.655087 183.659277 \n", "L 261.673553 183.659277 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_106\">\n", " <path d=\"M 263.655087 188.638125 \n", "L 265.63662 188.638125 \n", "L 265.63662 182.703382 \n", "L 263.655087 182.703382 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_107\">\n", " <path d=\"M 265.63662 188.638125 \n", "L 267.618153 188.638125 \n", "L 267.618153 184.014324 \n", "L 265.63662 184.014324 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_108\">\n", " <path d=\"M 267.618153 188.638125 \n", "L 269.599686 188.638125 \n", "L 269.599686 183.662009 \n", "L 267.618153 183.662009 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_109\">\n", " <path d=\"M 269.599686 188.638125 \n", "L 271.58122 188.638125 \n", "L 271.58122 183.779447 \n", "L 269.599686 183.779447 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_110\">\n", " <path d=\"M 271.58122 188.638125 \n", "L 273.562755 188.638125 \n", "L 273.562755 181.031941 \n", "L 271.58122 181.031941 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_111\">\n", " <path d=\"M 273.562755 188.638125 \n", "L 275.544289 188.638125 \n", "L 275.544289 182.618717 \n", "L 273.562755 182.618717 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_112\">\n", " <path d=\"M 275.544289 188.638125 \n", "L 277.525824 188.638125 \n", "L 277.525824 182.919149 \n", "L 275.544289 182.919149 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_113\">\n", " <path d=\"M 277.525824 188.638125 \n", "L 279.507358 188.638125 \n", "L 279.507358 181.747487 \n", "L 277.525824 181.747487 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_114\">\n", " <path d=\"M 279.507358 188.638125 \n", "L 281.488891 188.638125 \n", "L 281.488891 181.171219 \n", "L 279.507358 181.171219 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_115\">\n", " <path d=\"M 281.488891 188.638125 \n", "L 283.470427 188.638125 \n", "L 283.470427 182.596876 \n", "L 281.488891 182.596876 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_116\">\n", " <path d=\"M 283.470427 188.638125 \n", "L 285.45196 188.638125 \n", "L 285.45196 181.600006 \n", "L 283.470427 181.600006 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_117\">\n", " <path d=\"M 285.45196 188.638125 \n", "L 287.433495 188.638125 \n", "L 287.433495 181.234045 \n", "L 285.45196 181.234045 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_118\">\n", " <path d=\"M 287.433495 188.638125 \n", "L 289.415029 188.638125 \n", "L 289.415029 180.513017 \n", "L 287.433495 180.513017 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_119\">\n", " <path d=\"M 289.415029 188.638125 \n", "L 291.396562 188.638125 \n", "L 291.396562 182.036987 \n", "L 289.415029 182.036987 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_120\">\n", " <path d=\"M 291.396562 188.638125 \n", "L 293.378098 188.638125 \n", "L 293.378098 177.331267 \n", "L 291.396562 177.331267 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_121\">\n", " <path d=\"M 293.378098 188.638125 \n", "L 295.359631 188.638125 \n", "L 295.359631 180.726045 \n", "L 293.378098 180.726045 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_122\">\n", " <path d=\"M 295.359631 188.638125 \n", "L 297.341164 188.638125 \n", "L 297.341164 179.852084 \n", "L 295.359631 179.852084 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_123\">\n", " <path d=\"M 297.341164 188.638125 \n", "L 299.322699 188.638125 \n", "L 299.322699 179.868476 \n", "L 297.341164 179.868476 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_124\">\n", " <path d=\"M 299.322699 188.638125 \n", "L 301.304233 188.638125 \n", "L 301.304233 177.194703 \n", "L 299.322699 177.194703 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_125\">\n", " <path d=\"M 301.304233 188.638125 \n", "L 303.285768 188.638125 \n", "L 303.285768 180.575838 \n", "L 301.304233 180.575838 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_126\">\n", " <path d=\"M 303.285768 188.638125 \n", "L 305.267301 188.638125 \n", "L 305.267301 179.480651 \n", "L 303.285768 179.480651 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_127\">\n", " <path d=\"M 305.267301 188.638125 \n", "L 307.248835 188.638125 \n", "L 307.248835 179.898519 \n", "L 305.267301 179.898519 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_128\">\n", " <path d=\"M 307.248835 188.638125 \n", "L 309.230369 188.638125 \n", "L 309.230369 179.139263 \n", "L 307.248835 179.139263 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_129\">\n", " <path d=\"M 309.230369 188.638125 \n", "L 311.211903 188.638125 \n", "L 311.211903 178.237992 \n", "L 309.230369 178.237992 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_130\">\n", " <path d=\"M 311.211903 188.638125 \n", "L 313.193438 188.638125 \n", "L 313.193438 179.002708 \n", "L 311.211903 179.002708 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_131\">\n", " <path d=\"M 313.193438 188.638125 \n", "L 315.174972 188.638125 \n", "L 315.174972 173.816297 \n", "L 313.193438 173.816297 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_132\">\n", " <path d=\"M 315.174972 188.638125 \n", "L 317.156506 188.638125 \n", "L 317.156506 178.702284 \n", "L 315.174972 178.702284 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_133\">\n", " <path d=\"M 317.156506 188.638125 \n", "L 319.13804 188.638125 \n", "L 319.13804 178.205218 \n", "L 317.156506 178.205218 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_134\">\n", " <path d=\"M 319.13804 188.638125 \n", "L 321.119574 188.638125 \n", "L 321.119574 178.926238 \n", "L 319.13804 178.926238 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_135\">\n", " <path d=\"M 321.119574 188.638125 \n", "L 323.101108 188.638125 \n", "L 323.101108 178.475598 \n", "L 321.119574 178.475598 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_136\">\n", " <path d=\"M 323.101108 188.638125 \n", "L 325.082642 188.638125 \n", "L 325.082642 179.800195 \n", "L 323.101108 179.800195 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_137\">\n", " <path d=\"M 325.082642 188.638125 \n", "L 327.064176 188.638125 \n", "L 327.064176 179.568052 \n", "L 325.082642 179.568052 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_138\">\n", " <path d=\"M 327.064176 188.638125 \n", "L 329.045711 188.638125 \n", "L 329.045711 179.021827 \n", "L 327.064176 179.021827 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_139\">\n", " <path d=\"M 329.045711 188.638125 \n", "L 331.027244 188.638125 \n", "L 331.027244 178.117817 \n", "L 329.045711 178.117817 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_140\">\n", " <path d=\"M 331.027244 188.638125 \n", "L 333.008779 188.638125 \n", "L 333.008779 179.505237 \n", "L 331.027244 179.505237 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_141\">\n", " <path d=\"M 333.008779 188.638125 \n", "L 334.990313 188.638125 \n", "L 334.990313 180.551258 \n", "L 333.008779 180.551258 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_142\">\n", " <path d=\"M 334.990313 188.638125 \n", "L 336.971846 188.638125 \n", "L 336.971846 180.966385 \n", "L 334.990313 180.966385 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_143\">\n", " <path d=\"M 336.971846 188.638125 \n", "L 338.95338 188.638125 \n", "L 338.95338 176.927045 \n", "L 336.971846 176.927045 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_144\">\n", " <path d=\"M 338.95338 188.638125 \n", "L 340.934915 188.638125 \n", "L 340.934915 179.292214 \n", "L 338.95338 179.292214 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_145\">\n", " <path d=\"M 340.934915 188.638125 \n", "L 342.916448 188.638125 \n", "L 342.916448 181.77753 \n", "L 340.934915 181.77753 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_146\">\n", " <path d=\"M 342.916448 188.638125 \n", "L 344.897984 188.638125 \n", "L 344.897984 182.050651 \n", "L 342.916448 182.050651 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_147\">\n", " <path d=\"M 344.897984 188.638125 \n", "L 346.879517 188.638125 \n", "L 346.879517 181.63278 \n", "L 344.897984 181.63278 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_148\">\n", " <path d=\"M 346.879517 188.638125 \n", "L 348.861051 188.638125 \n", "L 348.861051 181.179413 \n", "L 346.879517 181.179413 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_149\">\n", " <path d=\"M 348.861051 188.638125 \n", "L 350.842586 188.638125 \n", "L 350.842586 180.881729 \n", "L 348.861051 180.881729 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_150\">\n", " <path d=\"M 350.842586 188.638125 \n", "L 352.82412 188.638125 \n", "L 352.82412 182.829014 \n", "L 350.842586 182.829014 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_151\">\n", " <path d=\"M 352.82412 188.638125 \n", "L 354.805653 188.638125 \n", "L 354.805653 181.976902 \n", "L 352.82412 181.976902 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_152\">\n", " <path d=\"M 354.805653 188.638125 \n", "L 356.787189 188.638125 \n", "L 356.787189 182.687003 \n", "L 354.805653 182.687003 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_153\">\n", " <path d=\"M 356.787189 188.638125 \n", "L 358.768722 188.638125 \n", "L 358.768722 181.701058 \n", "L 356.787189 181.701058 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_154\">\n", " <path d=\"M 358.768722 188.638125 \n", "L 360.750255 188.638125 \n", "L 360.750255 183.49541 \n", "L 358.768722 183.49541 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_155\">\n", " <path d=\"M 360.750255 188.638125 \n", "L 362.731788 188.638125 \n", "L 362.731788 183.15675 \n", "L 360.750255 183.15675 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_156\">\n", " <path d=\"M 362.731788 188.638125 \n", "L 364.713322 188.638125 \n", "L 364.713322 182.64876 \n", "L 362.731788 182.64876 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_157\">\n", " <path d=\"M 364.713322 188.638125 \n", "L 366.69486 188.638125 \n", "L 366.69486 184.077152 \n", "L 364.713322 184.077152 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_158\">\n", " <path d=\"M 366.69486 188.638125 \n", "L 368.676393 188.638125 \n", "L 368.676393 183.279651 \n", "L 366.69486 183.279651 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_159\">\n", " <path d=\"M 368.676393 188.638125 \n", "L 370.657926 188.638125 \n", "L 370.657926 184.836394 \n", "L 368.676393 184.836394 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_160\">\n", " <path d=\"M 370.657926 188.638125 \n", "L 372.639459 188.638125 \n", "L 372.639459 184.768116 \n", "L 370.657926 184.768116 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_161\">\n", " <path d=\"M 372.639459 188.638125 \n", "L 374.620993 188.638125 \n", "L 374.620993 184.434918 \n", "L 372.639459 184.434918 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_162\">\n", " <path d=\"M 374.620993 188.638125 \n", "L 376.602531 188.638125 \n", "L 376.602531 184.871908 \n", "L 374.620993 184.871908 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_163\">\n", " <path d=\"M 376.602531 188.638125 \n", "L 378.584064 188.638125 \n", "L 378.584064 185.341653 \n", "L 376.602531 185.341653 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_164\">\n", " <path d=\"M 378.584064 188.638125 \n", "L 380.565597 188.638125 \n", "L 380.565597 185.240601 \n", "L 378.584064 185.240601 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_165\">\n", " <path d=\"M 380.565597 188.638125 \n", "L 382.547131 188.638125 \n", "L 382.547131 185.688506 \n", "L 380.565597 185.688506 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_166\">\n", " <path d=\"M 382.547131 188.638125 \n", "L 384.528664 188.638125 \n", "L 384.528664 186.218345 \n", "L 382.547131 186.218345 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_167\">\n", " <path d=\"M 384.528664 188.638125 \n", "L 386.510197 188.638125 \n", "L 386.510197 185.784096 \n", "L 384.528664 185.784096 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_168\">\n", " <path d=\"M 386.510197 188.638125 \n", "L 388.491735 188.638125 \n", "L 388.491735 186.442303 \n", "L 386.510197 186.442303 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_169\">\n", " <path d=\"M 388.491735 188.638125 \n", "L 390.473269 188.638125 \n", "L 390.473269 186.417717 \n", "L 388.491735 186.417717 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_170\">\n", " <path d=\"M 390.473269 188.638125 \n", "L 392.454802 188.638125 \n", "L 392.454802 186.412255 \n", "L 390.473269 186.412255 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_171\">\n", " <path d=\"M 392.454802 188.638125 \n", "L 394.436335 188.638125 \n", "L 394.436335 186.903858 \n", "L 392.454802 186.903858 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_172\">\n", " <path d=\"M 394.436335 188.638125 \n", "L 396.417868 188.638125 \n", "L 396.417868 186.66625 \n", "L 394.436335 186.66625 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_173\">\n", " <path d=\"M 396.417868 188.638125 \n", "L 398.399401 188.638125 \n", "L 398.399401 185.128625 \n", "L 396.417868 185.128625 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_174\">\n", " <path d=\"M 398.399401 188.638125 \n", "L 400.38094 188.638125 \n", "L 400.38094 183.672946 \n", "L 398.399401 183.672946 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_175\">\n", " <path d=\"M 400.38094 188.638125 \n", "L 402.362473 188.638125 \n", "L 402.362473 179.16384 \n", "L 400.38094 179.16384 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_176\">\n", " <path d=\"M 402.362473 188.638125 \n", "L 404.344006 188.638125 \n", "L 404.344006 161.722852 \n", "L 402.362473 161.722852 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_177\">\n", " <path d=\"M 404.344006 188.638125 \n", "L 406.325539 188.638125 \n", "L 406.325539 161.624531 \n", "L 404.344006 161.624531 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_178\">\n", " <path d=\"M 406.325539 188.638125 \n", "L 408.307073 188.638125 \n", "L 408.307073 172.248622 \n", "L 406.325539 172.248622 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_179\">\n", " <path d=\"M 408.307073 188.638125 \n", "L 410.288606 188.638125 \n", "L 410.288606 158.825125 \n", "L 408.307073 158.825125 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_180\">\n", " <path d=\"M 410.288606 188.638125 \n", "L 412.270139 188.638125 \n", "L 412.270139 152.955929 \n", "L 410.288606 152.955929 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_181\">\n", " <path d=\"M 412.270139 188.638125 \n", "L 414.251672 188.638125 \n", "L 414.251672 159.125549 \n", "L 412.270139 159.125549 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_182\">\n", " <path d=\"M 414.251672 188.638125 \n", "L 416.233206 188.638125 \n", "L 416.233206 172.682871 \n", "L 414.251672 172.682871 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_183\">\n", " <path d=\"M 416.233206 188.638125 \n", "L 418.214749 188.638125 \n", "L 418.214749 177.598959 \n", "L 416.233206 177.598959 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_184\">\n", " <path d=\"M 418.214749 188.638125 \n", "L 420.196282 188.638125 \n", "L 420.196282 173.625111 \n", "L 418.214749 173.625111 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_185\">\n", " <path d=\"M 420.196282 188.638125 \n", "L 422.177815 188.638125 \n", "L 422.177815 172.472574 \n", "L 420.196282 172.472574 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_186\">\n", " <path d=\"M 422.177815 188.638125 \n", "L 424.159348 188.638125 \n", "L 424.159348 173.545908 \n", "L 422.177815 173.545908 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_187\">\n", " <path d=\"M 424.159348 188.638125 \n", "L 426.140882 188.638125 \n", "L 426.140882 176.225145 \n", "L 424.159348 176.225145 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_188\">\n", " <path d=\"M 426.140882 188.638125 \n", "L 428.122415 188.638125 \n", "L 428.122415 179.723721 \n", "L 426.140882 179.723721 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_189\">\n", " <path d=\"M 428.122415 188.638125 \n", "L 430.103948 188.638125 \n", "L 430.103948 182.602331 \n", "L 428.122415 182.602331 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_190\">\n", " <path d=\"M 430.103948 188.638125 \n", "L 432.085481 188.638125 \n", "L 432.085481 186.794613 \n", "L 430.103948 186.794613 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_191\">\n", " <path d=\"M 432.085481 188.638125 \n", "L 434.067015 188.638125 \n", "L 434.067015 187.013103 \n", "L 432.085481 187.013103 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_192\">\n", " <path d=\"M 434.067015 188.638125 \n", "L 436.048548 188.638125 \n", "L 436.048548 186.76184 \n", "L 434.067015 186.76184 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_193\">\n", " <path d=\"M 436.048548 188.638125 \n", "L 438.030081 188.638125 \n", "L 438.030081 186.540618 \n", "L 436.048548 186.540618 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_194\">\n", " <path d=\"M 438.030081 188.638125 \n", "L 440.011614 188.638125 \n", "L 440.011614 186.668981 \n", "L 438.030081 186.668981 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_195\">\n", " <path d=\"M 440.011614 188.638125 \n", "L 441.993158 188.638125 \n", "L 441.993158 186.559747 \n", "L 440.011614 186.559747 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_196\">\n", " <path d=\"M 441.993158 188.638125 \n", "L 443.974691 188.638125 \n", "L 443.974691 186.611628 \n", "L 441.993158 186.611628 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_197\">\n", " <path d=\"M 443.974691 188.638125 \n", "L 445.956224 188.638125 \n", "L 445.956224 186.66625 \n", "L 443.974691 186.66625 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_198\">\n", " <path d=\"M 445.956224 188.638125 \n", "L 447.937757 188.638125 \n", "L 447.937757 186.879278 \n", "L 445.956224 186.879278 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_199\">\n", " <path d=\"M 447.937757 188.638125 \n", "L 449.91929 188.638125 \n", "L 449.91929 187.013103 \n", "L 447.937757 187.013103 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_200\">\n", " <path d=\"M 449.91929 188.638125 \n", "L 451.900824 188.638125 \n", "L 451.900824 187.190627 \n", "L 449.91929 187.190627 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_201\">\n", " <path d=\"M 451.900824 188.638125 \n", "L 453.882357 188.638125 \n", "L 453.882357 187.39273 \n", "L 451.900824 187.39273 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_202\">\n", " <path d=\"M 453.882357 188.638125 \n", "L 455.86389 188.638125 \n", "L 455.86389 187.384537 \n", "L 453.882357 187.384537 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_203\">\n", " <path d=\"M 455.86389 188.638125 \n", "L 457.845423 188.638125 \n", "L 457.845423 187.53748 \n", "L 455.86389 187.53748 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_204\">\n", " <path d=\"M 457.845423 188.638125 \n", "L 459.826957 188.638125 \n", "L 459.826957 187.777819 \n", "L 457.845423 187.777819 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_205\">\n", " <path d=\"M 459.826957 188.638125 \n", "L 461.80849 188.638125 \n", "L 461.80849 187.82698 \n", "L 459.826957 187.82698 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_206\">\n", " <path d=\"M 461.80849 188.638125 \n", "L 463.790033 188.638125 \n", "L 463.790033 187.93896 \n", "L 461.80849 187.93896 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_207\">\n", " <path d=\"M 463.790033 188.638125 \n", "L 465.771566 188.638125 \n", "L 465.771566 187.966267 \n", "L 463.790033 187.966267 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_208\">\n", " <path d=\"M 465.771566 188.638125 \n", "L 467.7531 188.638125 \n", "L 467.7531 188.143791 \n", "L 465.771566 188.143791 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_209\">\n", " <path d=\"M 467.7531 188.638125 \n", "L 469.734633 188.638125 \n", "L 469.734633 188.119211 \n", "L 467.7531 188.119211 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_210\">\n", " <path d=\"M 469.734633 188.638125 \n", "L 471.716166 188.638125 \n", "L 471.716166 188.225725 \n", "L 469.734633 188.225725 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_211\">\n", " <path d=\"M 471.716166 188.638125 \n", "L 473.697699 188.638125 \n", "L 473.697699 188.318583 \n", "L 471.716166 188.318583 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_212\">\n", " <path d=\"M 473.697699 188.638125 \n", "L 475.679232 188.638125 \n", "L 475.679232 188.294003 \n", "L 473.697699 188.294003 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_213\">\n", " <path d=\"M 475.679232 188.638125 \n", "L 477.660766 188.638125 \n", "L 477.660766 188.365012 \n", "L 475.679232 188.365012 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_214\">\n", " <path d=\"M 477.660766 188.638125 \n", "L 479.642299 188.638125 \n", "L 479.642299 188.400517 \n", "L 477.660766 188.400517 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_215\">\n", " <path d=\"M 479.642299 188.638125 \n", "L 481.623832 188.638125 \n", "L 481.623832 188.40871 \n", "L 479.642299 188.40871 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_216\">\n", " <path d=\"M 481.623832 188.638125 \n", "L 483.605365 188.638125 \n", "L 483.605365 188.422366 \n", "L 481.623832 188.422366 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_217\">\n", " <path d=\"M 483.605365 188.638125 \n", "L 485.586899 188.638125 \n", "L 485.586899 188.471526 \n", "L 483.605365 188.471526 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_218\">\n", " <path d=\"M 485.586899 188.638125 \n", "L 487.568432 188.638125 \n", "L 487.568432 188.531611 \n", "L 485.586899 188.531611 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_219\">\n", " <path d=\"M 487.568432 188.638125 \n", "L 489.549965 188.638125 \n", "L 489.549965 188.507031 \n", "L 487.568432 188.507031 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_220\">\n", " <path d=\"M 489.549965 188.638125 \n", "L 491.531498 188.638125 \n", "L 491.531498 188.507031 \n", "L 489.549965 188.507031 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_221\">\n", " <path d=\"M 491.531498 188.638125 \n", "L 493.513032 188.638125 \n", "L 493.513032 188.526149 \n", "L 491.531498 188.526149 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_222\">\n", " <path d=\"M 493.513032 188.638125 \n", "L 495.494565 188.638125 \n", "L 495.494565 188.55346 \n", "L 493.513032 188.55346 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_223\">\n", " <path d=\"M 495.494565 188.638125 \n", "L 497.476098 188.638125 \n", "L 497.476098 188.569847 \n", "L 495.494565 188.569847 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_224\">\n", " <path d=\"M 497.476098 188.638125 \n", "L 499.457651 188.638125 \n", "L 499.457651 188.52615 \n", "L 497.476098 188.52615 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_225\">\n", " <path d=\"M 499.457651 188.638125 \n", "L 501.439184 188.638125 \n", "L 501.439184 188.580771 \n", "L 499.457651 188.580771 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_226\">\n", " <path d=\"M 501.439184 188.638125 \n", "L 503.420718 188.638125 \n", "L 503.420718 188.572578 \n", "L 501.439184 188.572578 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_227\">\n", " <path d=\"M 503.420718 188.638125 \n", "L 505.402251 188.638125 \n", "L 505.402251 188.597158 \n", "L 503.420718 188.597158 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_228\">\n", " <path d=\"M 505.402251 188.638125 \n", "L 507.383784 188.638125 \n", "L 507.383784 188.580771 \n", "L 505.402251 188.580771 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_229\">\n", " <path d=\"M 507.383784 188.638125 \n", "L 509.365317 188.638125 \n", "L 509.365317 188.583502 \n", "L 507.383784 188.583502 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_230\">\n", " <path d=\"M 509.365317 188.638125 \n", "L 511.346851 188.638125 \n", "L 511.346851 188.597158 \n", "L 509.365317 188.597158 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_231\">\n", " <path d=\"M 511.346851 188.638125 \n", "L 513.328384 188.638125 \n", "L 513.328384 188.594427 \n", "L 511.346851 188.594427 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_232\">\n", " <path d=\"M 513.328384 188.638125 \n", "L 515.309917 188.638125 \n", "L 515.309917 188.594427 \n", "L 513.328384 188.594427 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_233\">\n", " <path d=\"M 515.309917 188.638125 \n", "L 517.29145 188.638125 \n", "L 517.29145 188.580771 \n", "L 515.309917 188.580771 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_234\">\n", " <path d=\"M 517.29145 188.638125 \n", "L 519.272984 188.638125 \n", "L 519.272984 188.619007 \n", "L 517.29145 188.619007 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_235\">\n", " <path d=\"M 519.272984 188.638125 \n", "L 521.254517 188.638125 \n", "L 521.254517 188.613545 \n", "L 519.272984 188.613545 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_236\">\n", " <path d=\"M 521.254517 188.638125 \n", "L 523.23605 188.638125 \n", "L 523.23605 188.616276 \n", "L 521.254517 188.616276 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_237\">\n", " <path d=\"M 523.23605 188.638125 \n", "L 525.217583 188.638125 \n", "L 525.217583 188.610814 \n", "L 523.23605 188.610814 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_238\">\n", " <path d=\"M 525.217583 188.638125 \n", "L 527.199117 188.638125 \n", "L 527.199117 188.608083 \n", "L 525.217583 188.608083 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_239\">\n", " <path d=\"M 527.199117 188.638125 \n", "L 529.18065 188.638125 \n", "L 529.18065 188.624469 \n", "L 527.199117 188.624469 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_240\">\n", " <path d=\"M 529.18065 188.638125 \n", "L 531.162183 188.638125 \n", "L 531.162183 188.6272 \n", "L 529.18065 188.6272 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_241\">\n", " <path d=\"M 531.162183 188.638125 \n", "L 533.143716 188.638125 \n", "L 533.143716 188.6272 \n", "L 531.162183 188.6272 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_242\">\n", " <path d=\"M 533.143716 188.638125 \n", "L 535.125249 188.638125 \n", "L 535.125249 188.632663 \n", "L 533.143716 188.632663 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_243\">\n", " <path d=\"M 535.125249 188.638125 \n", "L 537.106783 188.638125 \n", "L 537.106783 188.6272 \n", "L 535.125249 188.6272 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_244\">\n", " <path d=\"M 537.106783 188.638125 \n", "L 539.088316 188.638125 \n", "L 539.088316 188.632663 \n", "L 537.106783 188.632663 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_245\">\n", " <path d=\"M 539.088316 188.638125 \n", "L 541.069849 188.638125 \n", "L 541.069849 188.621738 \n", "L 539.088316 188.621738 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_246\">\n", " <path d=\"M 541.069849 188.638125 \n", "L 543.051382 188.638125 \n", "L 543.051382 188.635394 \n", "L 541.069849 188.635394 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_247\">\n", " <path d=\"M 543.051382 188.638125 \n", "L 545.032936 188.638125 \n", "L 545.032936 188.638125 \n", "L 543.051382 188.638125 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_248\">\n", " <path d=\"M 545.032936 188.638125 \n", "L 547.014469 188.638125 \n", "L 547.014469 188.635394 \n", "L 545.032936 188.635394 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_249\">\n", " <path d=\"M 547.014469 188.638125 \n", "L 548.996002 188.638125 \n", "L 548.996002 188.635394 \n", "L 547.014469 188.635394 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_250\">\n", " <path d=\"M 548.996002 188.638125 \n", "L 550.977535 188.638125 \n", "L 550.977535 188.632663 \n", "L 548.996002 188.632663 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_251\">\n", " <path d=\"M 550.977535 188.638125 \n", "L 552.959068 188.638125 \n", "L 552.959068 188.632663 \n", "L 550.977535 188.632663 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_252\">\n", " <path d=\"M 552.959068 188.638125 \n", "L 554.940602 188.638125 \n", "L 554.940602 188.632663 \n", "L 552.959068 188.632663 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_253\">\n", " <path d=\"M 554.940602 188.638125 \n", "L 556.922135 188.638125 \n", "L 556.922135 188.635394 \n", "L 554.940602 188.635394 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_254\">\n", " <path d=\"M 556.922135 188.638125 \n", "L 558.903668 188.638125 \n", "L 558.903668 188.629932 \n", "L 556.922135 188.629932 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_255\">\n", " <path d=\"M 558.903668 188.638125 \n", "L 560.885201 188.638125 \n", "L 560.885201 188.635394 \n", "L 558.903668 188.635394 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_256\">\n", " <path d=\"M 560.885201 188.638125 \n", "L 562.866735 188.638125 \n", "L 562.866735 188.638125 \n", "L 560.885201 188.638125 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_257\">\n", " <path d=\"M 562.866735 188.638125 \n", "L 564.848268 188.638125 \n", "L 564.848268 188.635394 \n", "L 562.866735 188.635394 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_258\">\n", " <path d=\"M 564.848268 188.638125 \n", "L 566.829801 188.638125 \n", "L 566.829801 188.635394 \n", "L 564.848268 188.635394 \n", "z\n", "\" clip-path=\"url(#pc11b9d35d5)\" style=\"fill: #4c72b0; fill-opacity: 0.5; stroke: #4c72b0; stroke-linejoin: miter\"/>\n", " </g>\n", " <g id=\"patch_259\">\n", " <path d=\"M 34.193438 188.638125 \n", "L 34.193438 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_260\">\n", " <path d=\"M 592.193437 188.638125 \n", "L 592.193437 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_261\">\n", " <path d=\"M 34.193438 188.638125 \n", "L 592.193438 188.638125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"patch_262\">\n", " <path d=\"M 34.193438 22.318125 \n", "L 592.193438 22.318125 \n", "\" style=\"fill: none; stroke: #ffffff; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square\"/>\n", " </g>\n", " <g id=\"text_11\">\n", " <!-- Variational dequantization -->\n", " <g style=\"fill: #262626\" transform=\"translate(234.39375 16.318125) scale(0.12 -0.12)\">\n", " <defs>\n", " <path id=\"DejaVuSans-56\" d=\"M 1831 0 \n", "L 50 4666 \n", "L 709 4666 \n", "L 2188 738 \n", "L 3669 4666 \n", "L 4325 4666 \n", "L 2547 0 \n", "L 1831 0 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-61\" d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-72\" d=\"M 2631 2963 \n", "Q 2534 3019 2420 3045 \n", "Q 2306 3072 2169 3072 \n", "Q 1681 3072 1420 2755 \n", "Q 1159 2438 1159 1844 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1341 3275 1631 3429 \n", "Q 1922 3584 2338 3584 \n", "Q 2397 3584 2469 3576 \n", "Q 2541 3569 2628 3553 \n", "L 2631 2963 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-69\" d=\"M 603 3500 \n", "L 1178 3500 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 3500 \n", "z\n", "M 603 4863 \n", "L 1178 4863 \n", "L 1178 4134 \n", "L 603 4134 \n", "L 603 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-74\" d=\"M 1172 4494 \n", "L 1172 3500 \n", "L 2356 3500 \n", "L 2356 3053 \n", "L 1172 3053 \n", "L 1172 1153 \n", "Q 1172 725 1289 603 \n", "Q 1406 481 1766 481 \n", "L 2356 481 \n", "L 2356 0 \n", "L 1766 0 \n", "Q 1100 0 847 248 \n", "Q 594 497 594 1153 \n", "L 594 3053 \n", "L 172 3053 \n", "L 172 3500 \n", "L 594 3500 \n", "L 594 4494 \n", "L 1172 4494 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6f\" d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6e\" d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-6c\" d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-64\" d=\"M 2906 2969 \n", "L 2906 4863 \n", "L 3481 4863 \n", "L 3481 0 \n", "L 2906 0 \n", "L 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "z\n", "M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-65\" d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-71\" d=\"M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "M 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "L 2906 3500 \n", "L 3481 3500 \n", "L 3481 -1331 \n", "L 2906 -1331 \n", "L 2906 525 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-75\" d=\"M 544 1381 \n", "L 544 3500 \n", "L 1119 3500 \n", "L 1119 1403 \n", "Q 1119 906 1312 657 \n", "Q 1506 409 1894 409 \n", "Q 2359 409 2629 706 \n", "Q 2900 1003 2900 1516 \n", "L 2900 3500 \n", "L 3475 3500 \n", "L 3475 0 \n", "L 2900 0 \n", "L 2900 538 \n", "Q 2691 219 2414 64 \n", "Q 2138 -91 1772 -91 \n", "Q 1169 -91 856 284 \n", "Q 544 659 544 1381 \n", "z\n", "M 1991 3584 \n", "L 1991 3584 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " <path id=\"DejaVuSans-7a\" d=\"M 353 3500 \n", "L 3084 3500 \n", "L 3084 2975 \n", "L 922 459 \n", "L 3084 459 \n", "L 3084 0 \n", "L 275 0 \n", "L 275 525 \n", "L 2438 3041 \n", "L 353 3041 \n", "L 353 3500 \n", "z\n", "\" transform=\"scale(0.015625)\"/>\n", " </defs>\n", " <use xlink:href=\"#DejaVuSans-56\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"60.658203\"/>\n", " <use xlink:href=\"#DejaVuSans-72\" x=\"121.9375\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"163.050781\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"190.833984\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"252.113281\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"291.322266\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"319.105469\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"380.287109\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"443.666016\"/>\n", " <use xlink:href=\"#DejaVuSans-6c\" x=\"504.945312\"/>\n", " <use xlink:href=\"#DejaVuSans-20\" x=\"532.728516\"/>\n", " <use xlink:href=\"#DejaVuSans-64\" x=\"564.515625\"/>\n", " <use xlink:href=\"#DejaVuSans-65\" x=\"627.992188\"/>\n", " <use xlink:href=\"#DejaVuSans-71\" x=\"689.515625\"/>\n", " <use xlink:href=\"#DejaVuSans-75\" x=\"752.992188\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"816.371094\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"877.650391\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"941.029297\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"980.238281\"/>\n", " <use xlink:href=\"#DejaVuSans-7a\" x=\"1008.021484\"/>\n", " <use xlink:href=\"#DejaVuSans-61\" x=\"1060.511719\"/>\n", " <use xlink:href=\"#DejaVuSans-74\" x=\"1121.791016\"/>\n", " <use xlink:href=\"#DejaVuSans-69\" x=\"1161\"/>\n", " <use xlink:href=\"#DejaVuSans-6f\" x=\"1188.783203\"/>\n", " <use xlink:href=\"#DejaVuSans-6e\" x=\"1249.964844\"/>\n", " </g>\n", " </g>\n", " </g>\n", " </g>\n", " <defs>\n", " <clipPath id=\"pc11b9d35d5\">\n", " <rect x=\"34.193438\" y=\"22.318125\" width=\"558\" height=\"166.32\"/>\n", " </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 1000x300 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["visualize_dequant_distribution(flow_dict[\"vardeq\"][\"model\"], sample_imgs, title=\"Variational dequantization\")"]}, {"cell_type": "markdown", "id": "1c94ee1f", "metadata": {"papermill": {"duration": 0.026779, "end_time": "2023-03-14T16:09:03.188381", "exception": false, "start_time": "2023-03-14T16:09:03.161602", "status": "completed"}, "tags": []}, "source": ["The dequantization distribution in the first plot shows that the MNIST images have a strong bias towards 0 (black),\n", "and the distribution of them have a sharp border as mentioned before.\n", "The variational dequantization module has indeed learned a much smoother distribution with a Gaussian-like curve which can be modeled much better.\n", "For the other values, we would need to visualize the distribution $q(u|x)$ on a deeper level, depending on $x$.\n", "However, as all $u$'s interact and depend on each other, we would need\n", "to visualize a distribution in 784 dimensions, which is not that\n", "intuitive anymore."]}, {"cell_type": "markdown", "id": "ae3bae45", "metadata": {"papermill": {"duration": 0.026724, "end_time": "2023-03-14T16:09:03.241886", "exception": false, "start_time": "2023-03-14T16:09:03.215162", "status": "completed"}, "tags": []}, "source": ["## Conclusion\n", "\n", "In conclusion, we have seen how to implement our own normalizing flow, and what difficulties arise if we want to apply them on images.\n", "Dequantization is a crucial step in mapping the discrete images into continuous space to prevent underisable delta-peak solutions.\n", "While dequantization creates hypercubes with hard border, variational dequantization allows us to fit a flow much better on the data.\n", "This allows us to obtain a lower bits per dimension score, while not affecting the sampling speed.\n", "The most common flow element, the coupling layer, is simple to implement, and yet effective.\n", "Furthermore, multi-scale architectures help to capture the global image context while allowing us to efficiently scale up the flow.\n", "Normalizing flows are an interesting alternative to VAEs as they allow an exact likelihood estimate in continuous space,\n", "and we have the guarantee that every possible input $x$ has a corresponding latent vector $z$.\n", "However, even beyond continuous inputs and images, flows can be applied and allow us to exploit\n", "the data structure in latent space, as e.g. on graphs for the task of molecule generation [6].\n", "Recent advances in [Neural ODEs](https://arxiv.org/pdf/1806.07366.pdf) allow a flow with infinite number of layers,\n", "called Continuous Normalizing Flows, whose potential is yet to fully explore.\n", "Overall, normalizing flows are an exciting research area which will continue over the next couple of years."]}, {"cell_type": "markdown", "id": "ab8843c8", "metadata": {"papermill": {"duration": 0.026911, "end_time": "2023-03-14T16:09:03.295703", "exception": false, "start_time": "2023-03-14T16:09:03.268792", "status": "completed"}, "tags": []}, "source": ["## References\n", "\n", "[1] Dinh, L., Sohl-Dickstein, J., and Bengio, S. (2017).\n", "\u201cDensity estimation using Real NVP,\u201d In: 5th International Conference on Learning Representations, ICLR 2017.\n", "[Link](https://arxiv.org/abs/1605.08803)\n", "\n", "[2] Kingma, D. P., and Dhariwal, P. (2018).\n", "\u201cGlow: Generative Flow with Invertible 1x1 Convolutions,\u201d In: Advances in Neural Information Processing Systems, vol.\n", "31, pp.\n", "10215--10224.\n", "[Link](http://papers.nips.cc/paper/8224-glow-generative-flow-with-invertible-1x1-convolutions.pdf)\n", "\n", "[3] Ho, J., Chen, X., Srinivas, A., Duan, Y., and Abbeel, P. (2019).\n", "\u201cFlow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design,\u201d\n", "in Proceedings of the 36th International Conference on Machine Learning, vol.\n", "97, pp.\n", "2722\u20132730.\n", "[Link](https://arxiv.org/abs/1902.00275)\n", "\n", "[4] Durkan, C., Bekasov, A., Murray, I., and Papamakarios, G. (2019).\n", "\u201cNeural Spline Flows,\u201d In: Advances in Neural Information Processing Systems, pp.\n", "7509\u20137520.\n", "[Link](http://papers.neurips.cc/paper/8969-neural-spline-flows.pdf)\n", "\n", "[5] Hoogeboom, E., Cohen, T. S., and Tomczak, J. M. (2020).\n", "\u201cLearning Discrete Distributions by Dequantization,\u201d arXiv preprint arXiv2001.11235v1.\n", "[Link](https://arxiv.org/abs/2001.11235)\n", "\n", "[6] Lippe, P., and Gavves, E. (2021).\n", "\u201cCategorical Normalizing Flows via Continuous Transformations,\u201d\n", "In: International Conference on Learning Representations, ICLR 2021.\n", "[Link](https://openreview.net/pdf?id=-GLNZeVDuik)"]}, {"cell_type": "markdown", "id": "24215753", "metadata": {"papermill": {"duration": 0.026354, "end_time": "2023-03-14T16:09:03.348421", "exception": false, "start_time": "2023-03-14T16:09:03.322067", "status": "completed"}, "tags": []}, "source": ["## Congratulations - Time to Join the Community!\n", "\n", "Congratulations on completing this notebook tutorial! If you enjoyed this and would like to join the Lightning\n", "movement, you can do so in the following ways!\n", "\n", "### Star [Lightning](https://github.com/Lightning-AI/lightning) on GitHub\n", "The easiest way to help our community is just by starring the GitHub repos! This helps raise awareness of the cool\n", "tools we're building.\n", "\n", "### Join our [Slack](https://www.pytorchlightning.ai/community)!\n", "The best way to keep up to date on the latest advancements is to join our community! Make sure to introduce yourself\n", "and share your interests in `#general` channel\n", "\n", "\n", "### Contributions !\n", "The best way to contribute to our community is to become a code contributor! At any time you can go to\n", "[Lightning](https://github.com/Lightning-AI/lightning) or [Bolt](https://github.com/Lightning-AI/lightning-bolts)\n", "GitHub Issues page and filter for \"good first issue\".\n", "\n", "* [Lightning good first issue](https://github.com/Lightning-AI/lightning/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22)\n", "* [Bolt good first issue](https://github.com/Lightning-AI/lightning-bolts/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22)\n", "* You can also contribute your own notebooks with useful examples !\n", "\n", "### Great thanks from the entire Pytorch Lightning Team for your interest !\n", "\n", "[{height=\"60px\" width=\"240px\"}](https://pytorchlightning.ai)"]}, {"cell_type": "raw", "metadata": {"raw_mimetype": "text/restructuredtext"}, "source": [".. customcarditem::\n", " :header: Tutorial 9: Normalizing Flows for Image Modeling\n", " :card_description: In this tutorial, we will take a closer look at complex, deep normalizing flows. The most popular, current application of deep normalizing flows is to model datasets of...\n", " :tags: Image,GPU/TPU,UvA-DL-Course\n", " :image: _static/images/course_UvA-DL/09-normalizing-flows.jpg"]}], "metadata": {"jupytext": {"cell_metadata_filter": "id,colab_type,colab,-all", "formats": "ipynb,py:percent", "main_language": "python"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.16"}, "papermill": {"default_parameters": {}, "duration": 23.837617, "end_time": "2023-03-14T16:09:04.999019", "environment_variables": {}, "exception": null, "input_path": "course_UvA-DL/09-normalizing-flows/NF_image_modeling.ipynb", "output_path": ".notebooks/course_UvA-DL/09-normalizing-flows.ipynb", "parameters": {}, "start_time": "2023-03-14T16:08:41.161402", "version": "2.4.0"}, "widgets": {"application/vnd.jupyter.widget-state+json": {"state": {"022d5e4feba64ae0928ed7f3872066d4": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "03403854507e4c1d82b2987d56a49a06": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_10dd727b74354aedafd5edc7db9549c8", "placeholder": "\u200b", "style": "IPY_MODEL_72e2bef6f95849f3b2a0157e2ae7d38f", "tabbable": null, "tooltip": null, "value": " 4542/4542 [00:00<00:00, 302461.36it/s]"}}, "04427c133ec74f93997b1bb09c212b93": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "07c5caa1cdc1422c953a73791e4deb9e": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "0aeadef176b2496588e4f17a7b736316": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_93e00f14a44948dcbd5b7b278de95bf1", "max": 1648877.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_35c8abf4b2d44eb1a9e990d070993da4", "tabbable": null, "tooltip": null, "value": 1648877.0}}, "0dfc77c724fe4dda8fa5ed6733af68d9": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_bb1e7ecd74f646189cde10378bfed99a", "placeholder": "\u200b", "style": "IPY_MODEL_758c5cc85a124fd6b1a1e5fc08e4578b", "tabbable": null, "tooltip": null, "value": " 0/8 [00:00<?, ?it/s]"}}, "0eb9bbfb6b8b423e90e7466594745546": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "10dd727b74354aedafd5edc7db9549c8": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "16f7dfe27ae0431f882ae8a7521045b1": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "1995f3296f964c10b7b2c669529f7ae2": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "1d86d0fabf6a402bb5546127da7d9bfd": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "1db7ae52a4e14296ad74930df9a97e79": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "21b86501888548e285936fadbc245102": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_c2ebe72c3bd64974b4786470efc97363", "placeholder": "\u200b", "style": "IPY_MODEL_1995f3296f964c10b7b2c669529f7ae2", "tabbable": null, "tooltip": null, "value": " 1648877/1648877 [00:00<00:00, 15388647.04it/s]"}}, "25676a4efd8540fb93d4cf022d30d53f": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_ced0fd121fc2474ba4c1abb075e13f5d", "placeholder": "\u200b", "style": "IPY_MODEL_e69479b2f0cf41f2b1b48ebb2ebf58d4", "tabbable": null, "tooltip": null, "value": " 0%"}}, "25d20e49e81241cebfe05a6a212c597c": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "29068e73798d4582a1e52fb849969cf1": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "29f6933ebb224f55bdab78facfbd0916": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "2c5126982c5e4f6698e08f10d0afc360": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_758427a471744b47ab6192598eefc69b", "max": 8.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_1db7ae52a4e14296ad74930df9a97e79", "tabbable": null, "tooltip": null, "value": 8.0}}, "312e269520644f68abf6c03135cf0e0d": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "339023c700c64174b9a147df03787e07": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "35c8abf4b2d44eb1a9e990d070993da4": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "411e2bdd0d104a759cf2219457a9ea10": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": "hidden", "width": null}}, "558441ee629d4bd9a4fdc90089a3586c": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "60985b1c703d4f8aa3aba175811d2a69": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_8a2bd283700345c0a750d978690229cc", "IPY_MODEL_0aeadef176b2496588e4f17a7b736316", "IPY_MODEL_21b86501888548e285936fadbc245102"], "layout": "IPY_MODEL_04427c133ec74f93997b1bb09c212b93", "tabbable": null, "tooltip": null}}, "6224fdd5ab06423482c0205dc09216d1": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_d97bd4b5fe8a49499d119431d07cf0fb", "placeholder": "\u200b", "style": "IPY_MODEL_a0812f0a0f8e40a0991db82254c34e4f", "tabbable": null, "tooltip": null, "value": " 0%"}}, "66fc512f4207461b9e493495d88854e7": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "67a200eee455445bad5167f0917cb600": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_07c5caa1cdc1422c953a73791e4deb9e", "max": 4542.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_25d20e49e81241cebfe05a6a212c597c", "tabbable": null, "tooltip": null, "value": 4542.0}}, "6e93eead70d64710b21580c9dfdcab47": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_c496aa960e8f441a96ebcfb22e62e988", "IPY_MODEL_fa7f221d159f44a399abb85eb67a0201", "IPY_MODEL_e249257f48ab4642814161e5cbe3a3c4"], "layout": "IPY_MODEL_339023c700c64174b9a147df03787e07", "tabbable": null, "tooltip": null}}, "6ef3a3aa22d64d32972473557f20dc75": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": "hidden", "width": null}}, "70b1f09cd80c4b6d954c95765acf99ac": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "72e2bef6f95849f3b2a0157e2ae7d38f": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "758427a471744b47ab6192598eefc69b": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "758c5cc85a124fd6b1a1e5fc08e4578b": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "85c1da41f2e24252b1bfd646e70cdce8": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_c73775d8b0f64318b72d97215a38fdd9", "IPY_MODEL_67a200eee455445bad5167f0917cb600", "IPY_MODEL_03403854507e4c1d82b2987d56a49a06"], "layout": "IPY_MODEL_d5feb3c4282f42c4950e191fc88be2a9", "tabbable": null, "tooltip": null}}, "8a2bd283700345c0a750d978690229cc": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_ab54194ee2f84f5e83f08a888c5a305f", "placeholder": "\u200b", "style": "IPY_MODEL_ff9e6a2733e34e72bfb2541bdf073901", "tabbable": null, "tooltip": null, "value": "100%"}}, "8e868462f756444d9b1a566c8f77d457": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_d63d18e016b24e3786cada711468334a", "IPY_MODEL_a5e6be0f0d264bd68359c69613627269", "IPY_MODEL_ed5753a1b5e24a52b3de7d67a56394be"], "layout": "IPY_MODEL_1d86d0fabf6a402bb5546127da7d9bfd", "tabbable": null, "tooltip": null}}, "93b1209a50b74dabbb125bc942d22e42": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "93e00f14a44948dcbd5b7b278de95bf1": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "a0812f0a0f8e40a0991db82254c34e4f": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "a50cba50ade742a4b7490036e1e11dc5": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "a5e6be0f0d264bd68359c69613627269": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_29f6933ebb224f55bdab78facfbd0916", "max": 9912422.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_d6df66553ca0434198434c840620964a", "tabbable": null, "tooltip": null, "value": 9912422.0}}, "a9b352eea54247f68d5c4fb54771ffff": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_a50cba50ade742a4b7490036e1e11dc5", "placeholder": "\u200b", "style": "IPY_MODEL_cf866df37d1d4998924e0ec0647dc3bb", "tabbable": null, "tooltip": null, "value": " 0/8 [00:00<?, ?it/s]"}}, "ab54194ee2f84f5e83f08a888c5a305f": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "b2b8c9cb3fdd4e77bf734fc7a847d4ff": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_6224fdd5ab06423482c0205dc09216d1", "IPY_MODEL_2c5126982c5e4f6698e08f10d0afc360", "IPY_MODEL_0dfc77c724fe4dda8fa5ed6733af68d9"], "layout": "IPY_MODEL_411e2bdd0d104a759cf2219457a9ea10", "tabbable": null, "tooltip": null}}, "b86389928edd42a6a9e52ef9cd86f311": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "bb1e7ecd74f646189cde10378bfed99a": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "bbe213511b3245368a116d011cf7a97d": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_25676a4efd8540fb93d4cf022d30d53f", "IPY_MODEL_ed5fb11f3a9e47b69aad48f8bf1f7461", "IPY_MODEL_a9b352eea54247f68d5c4fb54771ffff"], "layout": "IPY_MODEL_6ef3a3aa22d64d32972473557f20dc75", "tabbable": null, "tooltip": null}}, "c2ebe72c3bd64974b4786470efc97363": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "c496aa960e8f441a96ebcfb22e62e988": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_0eb9bbfb6b8b423e90e7466594745546", "placeholder": "\u200b", "style": "IPY_MODEL_b86389928edd42a6a9e52ef9cd86f311", "tabbable": null, "tooltip": null, "value": "100%"}}, "c73775d8b0f64318b72d97215a38fdd9": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_ebe1de3fe436417e9648098be8d9b038", "placeholder": "\u200b", "style": "IPY_MODEL_558441ee629d4bd9a4fdc90089a3586c", "tabbable": null, "tooltip": null, "value": "100%"}}, "ced0fd121fc2474ba4c1abb075e13f5d": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "cf866df37d1d4998924e0ec0647dc3bb": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "d1b544192fff4a4da583c624d12890b3": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "d5feb3c4282f42c4950e191fc88be2a9": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "d63d18e016b24e3786cada711468334a": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_e21ced0da6c14114927d42a13bb051a8", "placeholder": "\u200b", "style": "IPY_MODEL_93b1209a50b74dabbb125bc942d22e42", "tabbable": null, "tooltip": null, "value": "100%"}}, "d6df66553ca0434198434c840620964a": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "d97bd4b5fe8a49499d119431d07cf0fb": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "e21ced0da6c14114927d42a13bb051a8": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "e249257f48ab4642814161e5cbe3a3c4": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_70b1f09cd80c4b6d954c95765acf99ac", "placeholder": "\u200b", "style": "IPY_MODEL_16f7dfe27ae0431f882ae8a7521045b1", "tabbable": null, "tooltip": null, "value": " 28881/28881 [00:00<00:00, 1838816.19it/s]"}}, "e69479b2f0cf41f2b1b48ebb2ebf58d4": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "ebe1de3fe436417e9648098be8d9b038": {"model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "ed5753a1b5e24a52b3de7d67a56394be": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_022d5e4feba64ae0928ed7f3872066d4", "placeholder": "\u200b", "style": "IPY_MODEL_29068e73798d4582a1e52fb849969cf1", "tabbable": null, "tooltip": null, "value": " 9912422/9912422 [00:00<00:00, 26360107.18it/s]"}}, "ed5fb11f3a9e47b69aad48f8bf1f7461": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_d1b544192fff4a4da583c624d12890b3", "max": 8.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_ff4e278d816b407d972984608281faaa", "tabbable": null, "tooltip": null, "value": 8.0}}, "fa7f221d159f44a399abb85eb67a0201": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_66fc512f4207461b9e493495d88854e7", "max": 28881.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_312e269520644f68abf6c03135cf0e0d", "tabbable": null, "tooltip": null, "value": 28881.0}}, "ff4e278d816b407d972984608281faaa": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "ff9e6a2733e34e72bfb2541bdf073901": {"model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}}, "version_major": 2, "version_minor": 0}}}, "nbformat": 4, "nbformat_minor": 5}