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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SCWieCN1c_oP"
      },
      "source": [
        "# ML accelerated CFD data analysis\n",
        "\n",
        "This notebook reproduces key figures in our [PNAS paper](https://www.pnas.org/content/118/21/e2101784118) based on saved datasets. The data is stored in netCDF files in Google Cloud Storage, and the analysis uses xarray and JAX-CFD.\n",
        "\n",
        "> Indented block\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 12165,
          "status": "ok",
          "timestamp": 1635551082356,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
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          },
          "user_tz": 420
        },
        "id": "dq5Hou4QzH0Q",
        "outputId": "74a35f28-bc46-4678-bef4-a696f79bb482"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/home/modelzoo/jax/jax-cfd\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/site-packages/IPython/core/magics/osm.py:417: UserWarning: This is now an optional IPython functionality, setting dhist requires you to install the `pickleshare` library.\n",
            "  self.shell.db['dhist'] = compress_dhist(dhist)[-100:]\n"
          ]
        }
      ],
      "source": [
        "%cd /home/modelzoo/jax/jax-cfd/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Looking in indexes: https://mirrors.ustc.edu.cn/pypi/web/simple\n",
            "Requirement already satisfied: xarray in /usr/local/lib/python3.10/site-packages (2024.5.0)\n",
            "^C\n"
          ]
        }
      ],
      "source": [
        "! pip install -U xarray jax-cfd[data]==0.1.0"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X852u7zJiRXq"
      },
      "source": [
        "## Figure 1\n",
        "\n",
        "Replication of the Figure 1 from the PNAS paper, except with a [bootstrap](https://en.wikipedia.org/wiki/Bootstrapping_(statistics)) based estimation of uncertainty, given the sample size of 16 trajectories."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "cellView": "form",
        "id": "9NMXlZX0iX3o"
      },
      "outputs": [],
      "source": [
        "# @title Utility functions\n",
        "import xarray\n",
        "import seaborn\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import jax_cfd.data.xarray_utils as xru\n",
        "from jax_cfd.data import evaluation\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "def correlation(x, y):\n",
        "  state_dims = ['x', 'y']\n",
        "  p  = xru.normalize(x, state_dims) * xru.normalize(y, state_dims)\n",
        "  return p.sum(state_dims)\n",
        "\n",
        "def calculate_time_until(vorticity_corr):\n",
        "  threshold = 0.95\n",
        "  return (vorticity_corr.mean('sample') >= threshold).idxmin('time').rename('time_until')\n",
        "\n",
        "def calculate_time_until_bootstrap(vorticity_corr, bootstrap_samples=10000):\n",
        "  rs = np.random.RandomState(0)\n",
        "  indices = rs.choice(16, size=(10000, 16), replace=True)\n",
        "  boot_vorticity_corr = vorticity_corr.isel(\n",
        "      sample=(('boot', 'sample2'), indices)).rename({'sample2': 'sample'})\n",
        "  return calculate_time_until(boot_vorticity_corr)\n",
        "\n",
        "def calculate_upscaling(time_until):\n",
        "  slope = ((np.log(16) - np.log(8))\n",
        "          / (time_until.sel(model='baseline_1024')\n",
        "              - time_until.sel(model='baseline_512')))\n",
        "  x = time_until.sel(model='learned_interp_64')\n",
        "  x0 = time_until.sel(model='baseline_512')\n",
        "  intercept = np.log(8)\n",
        "  factor = np.exp(slope * (x - x0) + intercept)\n",
        "  return factor\n",
        "\n",
        "def calculate_speedup(time_until):\n",
        "  runtime_baseline_8x = 44.053293\n",
        "  runtime_baseline_16x = 412.725656\n",
        "  runtime_learned = 1.155115\n",
        "  slope = ((np.log(runtime_baseline_16x) - np.log(runtime_baseline_8x))\n",
        "          / (time_until.sel(model='baseline_1024')\n",
        "              - time_until.sel(model='baseline_512')))\n",
        "  x = time_until.sel(model='learned_interp_64')\n",
        "  x0 = time_until.sel(model='baseline_512')\n",
        "  intercept = np.log(runtime_baseline_8x)\n",
        "  speedups = np.exp(slope * (x - x0) + intercept) / runtime_learned\n",
        "  return speedups"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nfxj9dxTKAUF"
      },
      "source": [
        "### Load data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 55729,
          "status": "ok",
          "timestamp": 1635551143667,
          "user": {
            "displayName": "Stephan Hoyer",
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            "userId": "01386112912994523038"
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          "user_tz": 420
        },
        "id": "UNivrWIsh3tL",
        "outputId": "8b5cb028-6413-444a-fdec-ad54b6e3b209"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/bin/bash: gsutil: command not found\n",
            "CPU times: user 4.12 ms, sys: 16 ms, total: 20.1 ms\n",
            "Wall time: 300 ms\n"
          ]
        }
      ],
      "source": [
        "%time ! gsutil -m cp -r gs://gresearch/jax-cfd/public_eval_datasets/kolmogorov_re_1000_fig1 ../content"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 10,
          "status": "ok",
          "timestamp": 1635551394768,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
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          "user_tz": 420
        },
        "id": "y2hNMbdniSdV",
        "outputId": "5ddd98a5-5f5b-4a69-917f-efd58ee26deb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/home/modelzoo/jax/jax-cfd\n",
            "baseline_1024x1024.nc  baseline_32x32.nc    learned_32x32.nc\n",
            "baseline_128x128.nc    baseline_512x512.nc  learned_64x64.nc\n",
            "baseline_2048x2048.nc  baseline_64x64.nc    tpu-speed-measurements.csv\n",
            "baseline_256x256.nc    learned_128x128.nc\n"
          ]
        }
      ],
      "source": [
        "! pwd\n",
        "! ls ./content/kolmogorov_re_1000_fig1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "JZOgcLcniX3p"
      },
      "outputs": [],
      "source": [
        "baseline_filenames = {\n",
        "    f'baseline_{r}': f'baseline_{r}x{r}.nc'\n",
        "    for r in [64, 128, 256, 512, 1024, 2048]\n",
        "}\n",
        "learned_filenames = {\n",
        "    f'learned_interp_{r}': f'learned_{r}x{r}.nc'\n",
        "    for r in [32, 64, 128]\n",
        "}\n",
        "\n",
        "models = {}\n",
        "for k, v in baseline_filenames.items():\n",
        "  models[k] = xarray.open_dataset(f'./content/kolmogorov_re_1000_fig1/{v}', chunks={'time': '100MB'})\n",
        "for k, v in learned_filenames.items():\n",
        "  ds = xarray.open_dataset(f'./content/kolmogorov_re_1000_fig1/{v}', chunks={'time': '100MB'})\n",
        "  models[k] = ds.reindex_like(models['baseline_64'], method='nearest')\n",
        "\n",
        "combined_fig1 = xarray.concat(list(models.values()), dim='model')\n",
        "combined_fig1.coords['model'] = list(models.keys())\n",
        "combined_fig1['vorticity'] = xru.vorticity_2d(combined_fig1)"
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    {
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      "execution_count": 12,
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              "  background-color: var(--xr-background-color) !important;\n",
              "  padding-bottom: 5px !important;\n",
              "}\n",
              "\n",
              ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
              ".xr-var-data-in:checked ~ .xr-var-data,\n",
              ".xr-index-data-in:checked ~ .xr-index-data {\n",
              "  display: block;\n",
              "}\n",
              "\n",
              ".xr-var-data > table {\n",
              "  float: right;\n",
              "}\n",
              "\n",
              ".xr-var-name span,\n",
              ".xr-var-data,\n",
              ".xr-index-name div,\n",
              ".xr-index-data,\n",
              ".xr-attrs {\n",
              "  padding-left: 25px !important;\n",
              "}\n",
              "\n",
              ".xr-attrs,\n",
              ".xr-var-attrs,\n",
              ".xr-var-data,\n",
              ".xr-index-data {\n",
              "  grid-column: 1 / -1;\n",
              "}\n",
              "\n",
              "dl.xr-attrs {\n",
              "  padding: 0;\n",
              "  margin: 0;\n",
              "  display: grid;\n",
              "  grid-template-columns: 125px auto;\n",
              "}\n",
              "\n",
              ".xr-attrs dt,\n",
              ".xr-attrs dd {\n",
              "  padding: 0;\n",
              "  margin: 0;\n",
              "  float: left;\n",
              "  padding-right: 10px;\n",
              "  width: auto;\n",
              "}\n",
              "\n",
              ".xr-attrs dt {\n",
              "  font-weight: normal;\n",
              "  grid-column: 1;\n",
              "}\n",
              "\n",
              ".xr-attrs dt:hover span {\n",
              "  display: inline-block;\n",
              "  background: var(--xr-background-color);\n",
              "  padding-right: 10px;\n",
              "}\n",
              "\n",
              ".xr-attrs dd {\n",
              "  grid-column: 2;\n",
              "  white-space: pre-wrap;\n",
              "  word-break: break-all;\n",
              "}\n",
              "\n",
              ".xr-icon-database,\n",
              ".xr-icon-file-text2,\n",
              ".xr-no-icon {\n",
              "  display: inline-block;\n",
              "  vertical-align: middle;\n",
              "  width: 1em;\n",
              "  height: 1.5em !important;\n",
              "  stroke-width: 0;\n",
              "  stroke: currentColor;\n",
              "  fill: currentColor;\n",
              "}\n",
              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 6GB\n",
              "Dimensions:    (model: 9, sample: 16, time: 2441, x: 32, y: 32)\n",
              "Coordinates:\n",
              "  * time       (time) float64 20kB 0.0 0.01402 0.02805 ... 34.19 34.21 34.22\n",
              "  * x          (x) float64 256B 0.09817 0.2945 0.4909 ... 5.792 5.989 6.185\n",
              "  * y          (y) float64 256B 0.09817 0.2945 0.4909 ... 5.792 5.989 6.185\n",
              "  * sample     (sample) int32 64B 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15\n",
              "  * model      (model) &lt;U18 648B &#x27;baseline_64&#x27; ... &#x27;learned_interp_128&#x27;\n",
              "Data variables:\n",
              "    u          (model, sample, time, x, y) float32 1GB dask.array&lt;chunksize=(1, 16, 1525, 32, 32), meta=np.ndarray&gt;\n",
              "    v          (model, sample, time, x, y) float32 1GB dask.array&lt;chunksize=(1, 16, 1525, 32, 32), meta=np.ndarray&gt;\n",
              "    vorticity  (model, sample, time, x, y) float64 3GB dask.array&lt;chunksize=(1, 16, 1525, 32, 32), meta=np.ndarray&gt;\n",
              "Attributes: (12/25)\n",
              "    domain_size:                   6.283185307179586\n",
              "    domain_size_multiple:          1\n",
              "    full_config_str:               import google3.research.simulation.whirl.m...\n",
              "    init_cfl_safety_factor:        0.5\n",
              "    init_peak_wavenumber:          4.0\n",
              "    maximum_velocity:              7.0\n",
              "    ...                            ...\n",
              "    time_subsample_factor:         1\n",
              "    tracing_max_duration_in_msec:  100.0\n",
              "    warmup_grid_size:              2048\n",
              "    warmup_time:                   40.0\n",
              "    xm_experiment_id:              18497215\n",
              "    xm_work_unit_id:               6</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-17909048-b7f2-40a9-9282-ebaeac77edd5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-17909048-b7f2-40a9-9282-ebaeac77edd5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>model</span>: 9</li><li><span class='xr-has-index'>sample</span>: 16</li><li><span class='xr-has-index'>time</span>: 2441</li><li><span class='xr-has-index'>x</span>: 32</li><li><span class='xr-has-index'>y</span>: 32</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-abb2dc97-df33-4b9f-901e-0db634e3c920' class='xr-section-summary-in' type='checkbox'  checked><label for='section-abb2dc97-df33-4b9f-901e-0db634e3c920' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.01402 0.02805 ... 34.21 34.22</div><input id='attrs-7e5225cf-e7e5-40f4-b694-879ad972163b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7e5225cf-e7e5-40f4-b694-879ad972163b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29eec37e-0b88-46c2-9f80-2e117e3e5e7d' class='xr-var-data-in' type='checkbox'><label for='data-29eec37e-0b88-46c2-9f80-2e117e3e5e7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 1.402497e-02, 2.804993e-02, ..., 3.419287e+01,\n",
              "       3.420690e+01, 3.422092e+01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.09817 0.2945 ... 5.989 6.185</div><input id='attrs-f65012f1-a6bc-4f2a-9eec-67205e5d62ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f65012f1-a6bc-4f2a-9eec-67205e5d62ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80bdb25c-d5c0-448c-8c18-409cf7780bc6' class='xr-var-data-in' type='checkbox'><label for='data-80bdb25c-d5c0-448c-8c18-409cf7780bc6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.098175, 0.294524, 0.490874, 0.687223, 0.883573, 1.079923, 1.276272,\n",
              "       1.472622, 1.668971, 1.865321, 2.06167 , 2.25802 , 2.454369, 2.650719,\n",
              "       2.847068, 3.043418, 3.239768, 3.436117, 3.632467, 3.828816, 4.025166,\n",
              "       4.221515, 4.417865, 4.614214, 4.810564, 5.006914, 5.203263, 5.399612,\n",
              "       5.595962, 5.792312, 5.988661, 6.185011])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.09817 0.2945 ... 5.989 6.185</div><input id='attrs-424cf3f1-9eab-4a29-ae8f-0a14ffeab044' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-424cf3f1-9eab-4a29-ae8f-0a14ffeab044' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-322c5284-68ab-4eb4-8aac-d50a6a9ce0d0' class='xr-var-data-in' type='checkbox'><label for='data-322c5284-68ab-4eb4-8aac-d50a6a9ce0d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.098175, 0.294524, 0.490874, 0.687223, 0.883573, 1.079923, 1.276272,\n",
              "       1.472622, 1.668971, 1.865321, 2.06167 , 2.25802 , 2.454369, 2.650719,\n",
              "       2.847068, 3.043418, 3.239768, 3.436117, 3.632467, 3.828816, 4.025166,\n",
              "       4.221515, 4.417865, 4.614214, 4.810564, 5.006914, 5.203263, 5.399612,\n",
              "       5.595962, 5.792312, 5.988661, 6.185011])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sample</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 10 11 12 13 14 15</div><input id='attrs-2c86e9ca-3a0a-480d-b4aa-a307734dfca5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c86e9ca-3a0a-480d-b4aa-a307734dfca5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88e9e1b6-cb63-4203-bc52-751ab131f8e4' class='xr-var-data-in' type='checkbox'><label for='data-88e9e1b6-cb63-4203-bc52-751ab131f8e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15],\n",
              "      dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>model</span></div><div class='xr-var-dims'>(model)</div><div class='xr-var-dtype'>&lt;U18</div><div class='xr-var-preview xr-preview'>&#x27;baseline_64&#x27; ... &#x27;learned_inter...</div><input id='attrs-dde76f12-2bd9-4785-8eea-67f5fa7e50f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dde76f12-2bd9-4785-8eea-67f5fa7e50f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3a2fbd5-711a-42a1-99c1-9136ac8246dc' class='xr-var-data-in' type='checkbox'><label for='data-a3a2fbd5-711a-42a1-99c1-9136ac8246dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;baseline_64&#x27;, &#x27;baseline_128&#x27;, &#x27;baseline_256&#x27;, &#x27;baseline_512&#x27;,\n",
              "       &#x27;baseline_1024&#x27;, &#x27;baseline_2048&#x27;, &#x27;learned_interp_32&#x27;,\n",
              "       &#x27;learned_interp_64&#x27;, &#x27;learned_interp_128&#x27;], dtype=&#x27;&lt;U18&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-64384d6e-b2b0-41a7-bc1d-70c9a885b842' class='xr-section-summary-in' type='checkbox'  checked><label for='section-64384d6e-b2b0-41a7-bc1d-70c9a885b842' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(model, sample, time, x, y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 16, 1525, 32, 32), meta=np.ndarray&gt;</div><input id='attrs-1961d11f-406c-4ee7-8799-682a0c06534a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1961d11f-406c-4ee7-8799-682a0c06534a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a47ee63e-2b68-4017-aa76-e903d9a88e71' class='xr-var-data-in' type='checkbox'><label for='data-a47ee63e-2b68-4017-aa76-e903d9a88e71' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>offset :</span></dt><dd>[1.  0.5]</dd></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 1.34 GiB </td>\n",
              "                        <td> 95.31 MiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (9, 16, 2441, 32, 32) </td>\n",
              "                        <td> (1, 16, 1525, 32, 32) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 18 chunks in 28 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
              "                    </tr>\n",
              "                </tbody>\n",
              "            </table>\n",
              "        </td>\n",
              "        <td>\n",
              "        <svg width=\"337\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
              "\n",
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              "    </tr>\n",
              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(model, sample, time, x, y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 16, 1525, 32, 32), meta=np.ndarray&gt;</div><input id='attrs-6e9b0664-9aa6-4343-8821-66ef19dd4d35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e9b0664-9aa6-4343-8821-66ef19dd4d35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9c546eb-4830-44a9-8a01-8ea93c02857f' class='xr-var-data-in' type='checkbox'><label for='data-a9c546eb-4830-44a9-8a01-8ea93c02857f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>offset :</span></dt><dd>[0.5 1. ]</dd></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 1.34 GiB </td>\n",
              "                        <td> 95.31 MiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (9, 16, 2441, 32, 32) </td>\n",
              "                        <td> (1, 16, 1525, 32, 32) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 18 chunks in 28 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
              "                    </tr>\n",
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              "    </tr>\n",
              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vorticity</span></div><div class='xr-var-dims'>(model, sample, time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 16, 1525, 32, 32), meta=np.ndarray&gt;</div><input id='attrs-64041490-eee1-4f34-af64-d5afef112733' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-64041490-eee1-4f34-af64-d5afef112733' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a69fb070-3379-45c8-877b-2ff941335edc' class='xr-var-data-in' type='checkbox'><label for='data-a69fb070-3379-45c8-877b-2ff941335edc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 2.68 GiB </td>\n",
              "                        <td> 190.62 MiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (9, 16, 2441, 32, 32) </td>\n",
              "                        <td> (1, 16, 1525, 32, 32) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 18 chunks in 70 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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              "\n",
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              "  <text x=\"120.294118\" y=\"82.049681\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,120.294118,82.049681)\">2441</text>\n",
              "</svg>\n",
              "        </td>\n",
              "    </tr>\n",
              "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-5c2ed3e1-9683-4790-9097-7bc7bd0b6a26' class='xr-section-summary-in' type='checkbox'  ><label for='section-5c2ed3e1-9683-4790-9097-7bc7bd0b6a26' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-95dd28cd-1a56-47c4-ba28-b3bb00389246' class='xr-index-data-in' type='checkbox'/><label for='index-95dd28cd-1a56-47c4-ba28-b3bb00389246' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([                 0.0, 0.014024967203525862, 0.028049934407051724,\n",
              "       0.042074901610577586,  0.05609986881410345,  0.07012483601762931,\n",
              "        0.08414980322115517,  0.09817477042468103,   0.1121997376282069,\n",
              "        0.12622470483173276,\n",
              "       ...\n",
              "          34.09469527177137,     34.1087202389749,    34.12274520617842,\n",
              "          34.13677017338195,    34.15079514058547,      34.164820107789,\n",
              "          34.17884507499252,    34.19287004219605,    34.20689500939958,\n",
              "         34.220919976603106],\n",
              "      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;, length=2441))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-10a605aa-6c77-4961-8e3e-eb0628755585' class='xr-index-data-in' type='checkbox'/><label for='index-10a605aa-6c77-4961-8e3e-eb0628755585' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.09817477315664291, 0.29452431201934814, 0.49087387323379517,\n",
              "        0.6872234344482422,  0.8835729360580444,  1.0799225568771362,\n",
              "        1.2762720584869385,  1.4726215600967407,  1.6689711809158325,\n",
              "        1.8653206825256348,  2.0616703033447266,  2.2580196857452393,\n",
              "         2.454369306564331,   2.650718927383423,  2.8470683097839355,\n",
              "        3.0434179306030273,   3.239767551422119,   3.436117172241211,\n",
              "        3.6324665546417236,  3.8288161754608154,   4.025165557861328,\n",
              "          4.22151517868042,   4.417864799499512,  4.6142144203186035,\n",
              "         4.810564041137695,   5.006913661956787,   5.203262805938721,\n",
              "        5.3996124267578125,   5.595962047576904,   5.792311668395996,\n",
              "         5.988661289215088,    6.18501091003418],\n",
              "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e0a55583-0567-4eca-bb9f-c326d5a22d7f' class='xr-index-data-in' type='checkbox'/><label for='index-e0a55583-0567-4eca-bb9f-c326d5a22d7f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.09817477315664291, 0.29452431201934814, 0.49087387323379517,\n",
              "        0.6872234344482422,  0.8835729360580444,  1.0799225568771362,\n",
              "        1.2762720584869385,  1.4726215600967407,  1.6689711809158325,\n",
              "        1.8653206825256348,  2.0616703033447266,  2.2580196857452393,\n",
              "         2.454369306564331,   2.650718927383423,  2.8470683097839355,\n",
              "        3.0434179306030273,   3.239767551422119,   3.436117172241211,\n",
              "        3.6324665546417236,  3.8288161754608154,   4.025165557861328,\n",
              "          4.22151517868042,   4.417864799499512,  4.6142144203186035,\n",
              "         4.810564041137695,   5.006913661956787,   5.203262805938721,\n",
              "        5.3996124267578125,   5.595962047576904,   5.792311668395996,\n",
              "         5.988661289215088,    6.18501091003418],\n",
              "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>sample</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0b25153c-c3e3-42ef-acc2-b62b076fe9ed' class='xr-index-data-in' type='checkbox'/><label for='index-0b25153c-c3e3-42ef-acc2-b62b076fe9ed' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], dtype=&#x27;int32&#x27;, name=&#x27;sample&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>model</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7e9f9037-5f28-40b0-a571-7bba16135694' class='xr-index-data-in' type='checkbox'/><label for='index-7e9f9037-5f28-40b0-a571-7bba16135694' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;baseline_64&#x27;, &#x27;baseline_128&#x27;, &#x27;baseline_256&#x27;, &#x27;baseline_512&#x27;,\n",
              "       &#x27;baseline_1024&#x27;, &#x27;baseline_2048&#x27;, &#x27;learned_interp_32&#x27;,\n",
              "       &#x27;learned_interp_64&#x27;, &#x27;learned_interp_128&#x27;],\n",
              "      dtype=&#x27;object&#x27;, name=&#x27;model&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-292615e1-d930-40d8-98d2-5b3e3af81be6' class='xr-section-summary-in' type='checkbox'  ><label for='section-292615e1-d930-40d8-98d2-5b3e3af81be6' class='xr-section-summary' >Attributes: <span>(25)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>domain_size :</span></dt><dd>6.283185307179586</dd><dt><span>domain_size_multiple :</span></dt><dd>1</dd><dt><span>full_config_str :</span></dt><dd>import google3.research.simulation.whirl.models.advection_modules\n",
              "import google3.research.simulation.whirl.models.decoder_modules\n",
              "import google3.research.simulation.whirl.models.diffusion_modules\n",
              "import google3.research.simulation.whirl.models.encoder_modules\n",
              "import google3.research.simulation.whirl.models.equation_modules\n",
              "import google3.research.simulation.whirl.models.forcing_modules\n",
              "import google3.research.simulation.whirl.models.interpolation_modules\n",
              "import google3.research.simulation.whirl.models.model_builder\n",
              "import google3.research.simulation.whirl.models.model_utils\n",
              "import google3.research.simulation.whirl.models.optimizer_modules\n",
              "import google3.research.simulation.whirl.models.physics_specs_modules\n",
              "import google3.research.simulation.whirl.models.pressure_modules\n",
              "import google3.research.simulation.whirl.models.towers\n",
              "import google3.research.simulation.whirl.models.viscosity_modules\n",
              "\n",
              "# Macros:\n",
              "# ==============================================================================\n",
              "C_INTERPOLATION_MODULE = @interpolation_modules.transformed\n",
              "CONVECTION_MODULE = @advection_modules.self_advection\n",
              "DENSITY = 1.0\n",
              "DIFFUSION_MODULE = @diffusion_modules.solve_fast_diag\n",
              "FORCING_MODULE = @forcing_modules.kolmogorov_forcing\n",
              "NS_MODULE = @equation_modules.modular_navier_stokes_model\n",
              "PRESSURE_MODULE = @pressure_modules.fast_diagonalization\n",
              "U_INTERPOLATION_MODULE = @interpolation_modules.linear\n",
              "VISCOSITY = 0.001\n",
              "\n",
              "# Parameters for get_model:\n",
              "# ==============================================================================\n",
              "get_model.model_cls = @Model\n",
              "\n",
              "# Parameters for get_physics_specs:\n",
              "# ==============================================================================\n",
              "get_physics_specs.physics_specs_cls = @NavierStokesPhysicsSpecs\n",
              "\n",
              "# Parameters for implicit_diffusion_navier_stokes:\n",
              "# ==============================================================================\n",
              "implicit_diffusion_navier_stokes.diffusion_module = %DIFFUSION_MODULE\n",
              "\n",
              "# Parameters for kolmogorov_forcing:\n",
              "# ==============================================================================\n",
              "kolmogorov_forcing.linear_coefficient = -0.1\n",
              "kolmogorov_forcing.scale = 1.0\n",
              "kolmogorov_forcing.wavenumber = 4\n",
              "\n",
              "# Parameters for Model:\n",
              "# ==============================================================================\n",
              "Model.decoder_module = @decoder_modules.aligned_array_decoder\n",
              "Model.encoder_module = @encoder_modules.aligned_array_encoder\n",
              "Model.step_module = %NS_MODULE\n",
              "Model.trajectory_module = @model_builder.get_trajectory_from_step_fn\n",
              "\n",
              "# Parameters for modular_advection:\n",
              "# ==============================================================================\n",
              "modular_advection.c_interpolation_module = %C_INTERPOLATION_MODULE\n",
              "modular_advection.u_interpolation_module = %U_INTERPOLATION_MODULE\n",
              "\n",
              "# Parameters for modular_navier_stokes_model:\n",
              "# ==============================================================================\n",
              "modular_navier_stokes_model.convection_module = %CONVECTION_MODULE\n",
              "modular_navier_stokes_model.equation_solver = \\\n",
              "    @equation_modules.implicit_diffusion_navier_stokes\n",
              "modular_navier_stokes_model.pressure_module = %PRESSURE_MODULE\n",
              "\n",
              "# Parameters for NavierStokesPhysicsSpecs:\n",
              "# ==============================================================================\n",
              "NavierStokesPhysicsSpecs.density = %DENSITY\n",
              "NavierStokesPhysicsSpecs.forcing_module = %FORCING_MODULE\n",
              "NavierStokesPhysicsSpecs.viscosity = 0.001\n",
              "\n",
              "# Parameters for self_advection:\n",
              "# ==============================================================================\n",
              "self_advection.advection_module = @advection_modules.modular_advection\n",
              "\n",
              "# Parameters for transformed:\n",
              "# ==============================================================================\n",
              "transformed.base_interpolation_module = @interpolation_modules.lax_wendroff\n",
              "transformed.transformation = @interpolation_modules.tvd_limiter_transformation\n",
              "</dd><dt><span>init_cfl_safety_factor :</span></dt><dd>0.5</dd><dt><span>init_peak_wavenumber :</span></dt><dd>4.0</dd><dt><span>maximum_velocity :</span></dt><dd>7.0</dd><dt><span>msec_per_overall_step :</span></dt><dd>nan</dd><dt><span>msec_per_sim_step :</span></dt><dd>nan</dd><dt><span>msec_per_transfer_step :</span></dt><dd>nan</dd><dt><span>msec_per_write_step :</span></dt><dd>nan</dd><dt><span>ndim :</span></dt><dd>2</dd><dt><span>num_samples :</span></dt><dd>0</dd><dt><span>output_dir :</span></dt><dd>/namespace/turbulence/primary/datasets/forced_turbulence_2d/kolmogorov_1000_32x32/</dd><dt><span>physics_config_str :</span></dt><dd>import google3.research.simulation.whirl.models.advection_modules\n",
              "import google3.research.simulation.whirl.models.decoder_modules\n",
              "import google3.research.simulation.whirl.models.diffusion_modules\n",
              "import google3.research.simulation.whirl.models.encoder_modules\n",
              "import google3.research.simulation.whirl.models.equation_modules\n",
              "import google3.research.simulation.whirl.models.forcing_modules\n",
              "import google3.research.simulation.whirl.models.interpolation_modules\n",
              "import google3.research.simulation.whirl.models.model_builder\n",
              "import google3.research.simulation.whirl.models.model_utils\n",
              "import google3.research.simulation.whirl.models.optimizer_modules\n",
              "import google3.research.simulation.whirl.models.physics_specs_modules\n",
              "import google3.research.simulation.whirl.models.pressure_modules\n",
              "import google3.research.simulation.whirl.models.towers\n",
              "import google3.research.simulation.whirl.models.viscosity_modules\n",
              "\n",
              "# Macros:\n",
              "# ==============================================================================\n",
              "DENSITY = 1.0\n",
              "FORCING_MODULE = @forcing_modules.kolmogorov_forcing\n",
              "\n",
              "# Parameters for get_physics_specs:\n",
              "# ==============================================================================\n",
              "get_physics_specs.physics_specs_cls = @NavierStokesPhysicsSpecs\n",
              "\n",
              "# Parameters for kolmogorov_forcing:\n",
              "# ==============================================================================\n",
              "kolmogorov_forcing.linear_coefficient = -0.1\n",
              "kolmogorov_forcing.scale = 1.0\n",
              "kolmogorov_forcing.swap_xy = False\n",
              "kolmogorov_forcing.wavenumber = 4\n",
              "\n",
              "# Parameters for NavierStokesPhysicsSpecs:\n",
              "# ==============================================================================\n",
              "NavierStokesPhysicsSpecs.density = %DENSITY\n",
              "NavierStokesPhysicsSpecs.forcing_module = %FORCING_MODULE\n",
              "NavierStokesPhysicsSpecs.viscosity = 0.001\n",
              "</dd><dt><span>save_grid_size :</span></dt><dd>32</dd><dt><span>seed :</span></dt><dd>1</dd><dt><span>simulation_grid_size :</span></dt><dd>64</dd><dt><span>simulation_time :</span></dt><dd>30.0</dd><dt><span>stable_time_step :</span></dt><dd>0.014024967203525862</dd><dt><span>time_subsample_factor :</span></dt><dd>1</dd><dt><span>tracing_max_duration_in_msec :</span></dt><dd>100.0</dd><dt><span>warmup_grid_size :</span></dt><dd>2048</dd><dt><span>warmup_time :</span></dt><dd>40.0</dd><dt><span>xm_experiment_id :</span></dt><dd>18497215</dd><dt><span>xm_work_unit_id :</span></dt><dd>6</dd></dl></div></li></ul></div></div>"
            ],
            "text/plain": [
              "<xarray.Dataset> Size: 6GB\n",
              "Dimensions:    (model: 9, sample: 16, time: 2441, x: 32, y: 32)\n",
              "Coordinates:\n",
              "  * time       (time) float64 20kB 0.0 0.01402 0.02805 ... 34.19 34.21 34.22\n",
              "  * x          (x) float64 256B 0.09817 0.2945 0.4909 ... 5.792 5.989 6.185\n",
              "  * y          (y) float64 256B 0.09817 0.2945 0.4909 ... 5.792 5.989 6.185\n",
              "  * sample     (sample) int32 64B 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15\n",
              "  * model      (model) <U18 648B 'baseline_64' ... 'learned_interp_128'\n",
              "Data variables:\n",
              "    u          (model, sample, time, x, y) float32 1GB dask.array<chunksize=(1, 16, 1525, 32, 32), meta=np.ndarray>\n",
              "    v          (model, sample, time, x, y) float32 1GB dask.array<chunksize=(1, 16, 1525, 32, 32), meta=np.ndarray>\n",
              "    vorticity  (model, sample, time, x, y) float64 3GB dask.array<chunksize=(1, 16, 1525, 32, 32), meta=np.ndarray>\n",
              "Attributes: (12/25)\n",
              "    domain_size:                   6.283185307179586\n",
              "    domain_size_multiple:          1\n",
              "    full_config_str:               import google3.research.simulation.whirl.m...\n",
              "    init_cfl_safety_factor:        0.5\n",
              "    init_peak_wavenumber:          4.0\n",
              "    maximum_velocity:              7.0\n",
              "    ...                            ...\n",
              "    time_subsample_factor:         1\n",
              "    tracing_max_duration_in_msec:  100.0\n",
              "    warmup_grid_size:              2048\n",
              "    warmup_time:                   40.0\n",
              "    xm_experiment_id:              18497215\n",
              "    xm_work_unit_id:               6"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Notice that the data in Figure 1 was resampled to 32x32 for validation, the\n",
        "# coarsest resolution of any of the constitutive models.\n",
        "combined_fig1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "ZBvPD6Vs8_HD"
      },
      "outputs": [],
      "source": [
        "df_raw = pd.read_csv('./content/kolmogorov_re_1000_fig1/tpu-speed-measurements.csv').reset_index(drop=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "executionInfo": {
          "elapsed": 11,
          "status": "ok",
          "timestamp": 1635551395425,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "HpPpq0ZayGh5",
        "outputId": "6d36e653-5744-49ef-9a31-2a63fb3976f4"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>model</th>\n",
              "      <th>resolution</th>\n",
              "      <th>msec_per_sim_step</th>\n",
              "      <th>model_name</th>\n",
              "      <th>msec_per_dt</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>DS</td>\n",
              "      <td>512</td>\n",
              "      <td>0.183315</td>\n",
              "      <td>baseline_64</td>\n",
              "      <td>0.366630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>DS</td>\n",
              "      <td>1024</td>\n",
              "      <td>0.862311</td>\n",
              "      <td>baseline_128</td>\n",
              "      <td>3.449244</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>DS</td>\n",
              "      <td>2048</td>\n",
              "      <td>3.484289</td>\n",
              "      <td>baseline_256</td>\n",
              "      <td>27.874312</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>DS</td>\n",
              "      <td>4096</td>\n",
              "      <td>19.306356</td>\n",
              "      <td>baseline_512</td>\n",
              "      <td>308.901689</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>DS</td>\n",
              "      <td>8192</td>\n",
              "      <td>90.438509</td>\n",
              "      <td>baseline_1024</td>\n",
              "      <td>2894.032298</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>LI</td>\n",
              "      <td>256</td>\n",
              "      <td>1.111596</td>\n",
              "      <td>learned_interp_32</td>\n",
              "      <td>1.111596</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>LI</td>\n",
              "      <td>512</td>\n",
              "      <td>4.049835</td>\n",
              "      <td>learned_interp_64</td>\n",
              "      <td>8.099669</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>LI</td>\n",
              "      <td>1024</td>\n",
              "      <td>16.043913</td>\n",
              "      <td>learned_interp_128</td>\n",
              "      <td>64.175654</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  model  resolution  msec_per_sim_step          model_name  msec_per_dt\n",
              "0    DS         512           0.183315         baseline_64     0.366630\n",
              "1    DS        1024           0.862311        baseline_128     3.449244\n",
              "2    DS        2048           3.484289        baseline_256    27.874312\n",
              "3    DS        4096          19.306356        baseline_512   308.901689\n",
              "4    DS        8192          90.438509       baseline_1024  2894.032298\n",
              "5    LI         256           1.111596   learned_interp_32     1.111596\n",
              "6    LI         512           4.049835   learned_interp_64     8.099669\n",
              "7    LI        1024          16.043913  learned_interp_128    64.175654"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# raw timing data\n",
        "df_raw"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sVFo5vWvKE5v"
      },
      "source": [
        "### Calculate headline result\n",
        "\n",
        "Note: the 85.46 vs \"86x\" number reported in the paper is because we didn't use `.thin(time=2)` for the paper (but public Colab doesn't have enough memory to avoid thinning)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 47663,
          "status": "ok",
          "timestamp": 1635551443079,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "MPfnVpKgjXe1",
        "outputId": "539fcd6b-75ce-428e-ba95-c1260f5f0bb7"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "speedup estimate: 85.46656221133746\n",
            "speedup bootstrap mean: 94.29360420066911\n",
            "speedup bootstrap stddev: 24.845175687919696\n",
            "speedup bootstrap median: 89.10921167768669\n",
            "speedup bootstrap range: [64.1076522609316, 143.0637237053277]\n",
            "upscaling estimate: 10.272075011298739\n",
            "upscaling bootstrap mean: 10.51902877871216\n",
            "upscaling bootstrap stddev: 0.8101766343321275\n",
            "upscaling bootstrap median: 10.405759362848043\n",
            "upscaling bootstrap range: [9.396541913646118, 12.049564425364894]\n",
            "CPU times: user 6.78 s, sys: 4.29 s, total: 11.1 s\n",
            "Wall time: 5.32 s\n"
          ]
        }
      ],
      "source": [
        "%%time\n",
        "v = combined_fig1.vorticity.thin(time=2).sel(time=slice(10))\n",
        "vorticity_correlation = correlation(v, v.sel(model='baseline_2048')).compute()\n",
        "\n",
        "times = calculate_time_until(vorticity_correlation)\n",
        "times_boot = calculate_time_until_bootstrap(vorticity_correlation)\n",
        "\n",
        "speedup = calculate_speedup(times)\n",
        "print('speedup estimate:', float(speedup))\n",
        "\n",
        "speedups = calculate_speedup(times_boot)\n",
        "print('speedup bootstrap mean:', float(speedups.mean('boot')))\n",
        "print('speedup bootstrap stddev:', float(speedups.std('boot')))\n",
        "print('speedup bootstrap median:', float(speedups.median('boot')))\n",
        "print('speedup bootstrap range:', speedups.quantile(dim='boot', q=[0.05, 0.95]).values.tolist())\n",
        "\n",
        "upscaling = calculate_upscaling(times)\n",
        "print('upscaling estimate:', float(upscaling))\n",
        "\n",
        "upscalings = calculate_upscaling(times_boot)\n",
        "print('upscaling bootstrap mean:', float(upscalings.mean('boot')))\n",
        "print('upscaling bootstrap stddev:', float(upscalings.std('boot')))\n",
        "print('upscaling bootstrap median:', float(upscalings.median('boot')))\n",
        "print('upscaling bootstrap range:', upscalings.quantile(dim='boot', q=[0.05, 0.95]).values.tolist())\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-wcbvGfbKZIZ"
      },
      "source": [
        "The reported 86x speed-up thus should be associated with a 95% bootstrap CI of [64, 140]:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "executionInfo": {
          "elapsed": 766,
          "status": "ok",
          "timestamp": 1635551443829,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "x-Tv25eN0V-_",
        "outputId": "870e1a48-ac59-4b4f-eb40-8cce37172b9f"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "speedups.rename('speedup factor').plot.hist(bins=50);"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9oSr3_41J2fo"
      },
      "source": [
        "### Pareto frontier plots"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "cellView": "form",
        "id": "MGOL83MQKyhV"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/tmp/ipykernel_1332464/299280752.py:12: DeprecationWarning: dropping variables using `drop` is deprecated; use drop_vars.\n",
            "  .drop('quantile')\n",
            "/tmp/ipykernel_1332464/299280752.py:20: DeprecationWarning: dropping variables using `drop` is deprecated; use drop_vars.\n",
            "  .drop('quantile')\n"
          ]
        }
      ],
      "source": [
        "#@title Prepare dataframe\n",
        "df = (\n",
        "    df_raw\n",
        "    .drop(['model', 'resolution', 'msec_per_sim_step'], axis=1)\n",
        "    .set_index('model_name')\n",
        "    .join(\n",
        "        times.rename({'model': 'model_name'}).to_dataframe()\n",
        "    )\n",
        "    .join(\n",
        "        times_boot\n",
        "        .quantile(q=0.975, dim='boot')\n",
        "        .drop('quantile')\n",
        "        .rename('time_until_upper')\n",
        "        .rename({'model': 'model_name'})\n",
        "        .to_dataframe()\n",
        "    )\n",
        "    .join(\n",
        "        times_boot\n",
        "        .quantile(q=0.025, dim='boot')\n",
        "        .drop('quantile')\n",
        "        .rename('time_until_lower')\n",
        "        .rename({'model': 'model_name'})\n",
        "        .to_dataframe()\n",
        "    )\n",
        "    .reset_index()\n",
        ")\n",
        "df[['model', 'resolution']] = df.model_name.str.rsplit('_', n=1, expand=True)\n",
        "\n",
        "df['resolution'] = df['resolution'].astype(int)\n",
        "# switch units from \"msec per time step at 64x64\" to\n",
        "# \"sec per simulation time step\"\n",
        "df['sec_per_sim_time'] = df['msec_per_dt'] / 0.007012 * 1e-3\n",
        "df = df.sort_values(['resolution', 'model'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 340
        },
        "executionInfo": {
          "elapsed": 586,
          "status": "ok",
          "timestamp": 1635551444411,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "MqowuhH6CNY4",
        "outputId": "49c3ee4f-fa87-488f-8549-4f17c857517a"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 500x500 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title Pareto frontier with uncertainty\n",
        "\n",
        "plt.figure(figsize=(5, 5))\n",
        "\n",
        "df_baseline = df.query('model==\"baseline\"')\n",
        "plt.errorbar(df_baseline.time_until,\n",
        "             df_baseline.sec_per_sim_time,\n",
        "             xerr=(df_baseline.time_until - df_baseline.time_until_lower,\n",
        "                   df_baseline.time_until_upper - df_baseline.time_until),\n",
        "             marker='s',\n",
        "             label='baseline')\n",
        "\n",
        "df_baseline = df.query('model==\"learned_interp\"')\n",
        "plt.errorbar(df_baseline.time_until,\n",
        "             df_baseline.sec_per_sim_time,\n",
        "             xerr=(df_baseline.time_until - df_baseline.time_until_lower,\n",
        "                   df_baseline.time_until_upper - df_baseline.time_until),\n",
        "             marker='s',\n",
        "             label='learned')\n",
        "\n",
        "plt.xlim(0, 8.1)\n",
        "plt.ylim(1.5e-2, 1e3)\n",
        "plt.xlabel('Time until correlation < 0.95')\n",
        "plt.ylabel('Runtime per time unit (s)')\n",
        "plt.yscale('log')\n",
        "plt.legend()\n",
        "seaborn.despine()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 338
        },
        "executionInfo": {
          "elapsed": 592,
          "status": "ok",
          "timestamp": 1635551444999,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "o4d1MUSpEuW0",
        "outputId": "3a82fb9c-3a60-433d-bd5e-7311f4324aff"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 500x500 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title Pareto frontier (transposed) with uncertainty\n",
        "plt.figure(figsize=(5, 5))\n",
        "\n",
        "df_baseline = df.query('model==\"baseline\"')\n",
        "plt.errorbar(df_baseline.sec_per_sim_time,\n",
        "             df_baseline.time_until,\n",
        "             yerr=(df_baseline.time_until - df_baseline.time_until_lower,\n",
        "                   df_baseline.time_until_upper - df_baseline.time_until),\n",
        "             marker='s',\n",
        "             label='baseline')\n",
        "\n",
        "df_baseline = df.query('model==\"learned_interp\"')\n",
        "plt.errorbar(df_baseline.sec_per_sim_time,\n",
        "             df_baseline.time_until,\n",
        "             yerr=(df_baseline.time_until - df_baseline.time_until_lower,\n",
        "                   df_baseline.time_until_upper - df_baseline.time_until),\n",
        "             marker='s',\n",
        "             label='learned')\n",
        "\n",
        "plt.ylim(0, 8.1)\n",
        "plt.xlim(1.5e-2, 1e3)\n",
        "plt.ylabel('Time until correlation < 0.95')\n",
        "plt.xlabel('Runtime per time unit (s)')\n",
        "plt.xscale('log')\n",
        "plt.legend()\n",
        "seaborn.despine()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Dv4zYWK59GcS"
      },
      "source": [
        "## Figure 2\n",
        "\n",
        "Here we reproduce the key parts of Figure 2, from scratch.\n",
        "\n",
        "Note that Figure 2 (and Figure 5) inadvertently used a different evaluation dataset than Figure 1 (different random initial velocity fields), saved at 64x64 resolution."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "23M_zG6O6w_j"
      },
      "source": [
        "### Copy data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 41717,
          "status": "ok",
          "timestamp": 1635551185377,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "6bJ-PkDw1tmd",
        "outputId": "74344e2e-cbad-4617-ee20-b3b7890e80e3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Copying gs://gresearch/jax-cfd/public_eval_datasets/kolmogorov_re_1000/learned_interpolation_long_eval_64x64_64x64.nc...\n",
            "\\ [1/1 files][  1.7 GiB/  1.7 GiB] 100% Done  56.8 MiB/s ETA 00:00:00           \n",
            "Operation completed over 1 objects/1.7 GiB.                                      \n",
            "CPU times: user 426 ms, sys: 72.6 ms, total: 499 ms\n",
            "Wall time: 41.7 s\n"
          ]
        }
      ],
      "source": [
        "%time ! gsutil -m cp gs://gresearch/jax-cfd/public_eval_datasets/kolmogorov_re_1000/learned*.nc /content"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 209396,
          "status": "ok",
          "timestamp": 1635551394767,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "kUtRFyDgzyN9",
        "outputId": "2a4df49a-3c19-4440-beee-a428017065a8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Copying gs://gresearch/jax-cfd/public_eval_datasets/kolmogorov_re_1000/long_eval_64x64_64x64.nc...\n",
            "/ [0/6 files][    0.0 B/ 10.2 GiB]   0% Done                                    \rCopying gs://gresearch/jax-cfd/public_eval_datasets/kolmogorov_re_1000/long_eval_1024x1024_64x64.nc...\n",
            "/ [0/6 files][    0.0 B/ 10.2 GiB]   0% Done                                    \rCopying gs://gresearch/jax-cfd/public_eval_datasets/kolmogorov_re_1000/long_eval_256x256_64x64.nc...\n",
            "/ [0/6 files][    0.0 B/ 10.2 GiB]   0% Done                                    \rCopying gs://gresearch/jax-cfd/public_eval_datasets/kolmogorov_re_1000/long_eval_2048x2048_64x64.nc...\n",
            "/ [0/6 files][    0.0 B/ 10.2 GiB]   0% Done                                    \rCopying gs://gresearch/jax-cfd/public_eval_datasets/kolmogorov_re_1000/long_eval_128x128_64x64.nc...\n",
            "Copying gs://gresearch/jax-cfd/public_eval_datasets/kolmogorov_re_1000/long_eval_512x512_64x64.nc...\n",
            "| [6/6 files][ 10.2 GiB/ 10.2 GiB] 100% Done  54.1 MiB/s ETA 00:00:00           \n",
            "Operation completed over 6 objects/10.2 GiB.                                     \n",
            "CPU times: user 1.88 s, sys: 347 ms, total: 2.22 s\n",
            "Wall time: 3min 29s\n"
          ]
        }
      ],
      "source": [
        "gsutil -m cp gs://gresearch/jax-cfd/public_eval_datasets/kolmogorov_re_1000/long_eval*.nc /content%time ! "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wTfEmQPZ1YiT"
      },
      "source": [
        "### Load data at 64x64 and 32x32 resolutions"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "MVbarBes3tAJ"
      },
      "outputs": [],
      "source": [
        "import xarray\n",
        "import seaborn\n",
        "import jax_cfd.data.xarray_utils as xru\n",
        "from jax_cfd.data import evaluation\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "baseline_palette = seaborn.color_palette('YlGnBu', n_colors=7)[1:]\n",
        "models_color = seaborn.xkcd_palette(['burnt orange'])\n",
        "palette = baseline_palette + models_color\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "9oirn2QI2REz"
      },
      "outputs": [],
      "source": [
        "filenames = {\n",
        "    f'baseline_{r}': f'long_eval_{r}x{r}_64x64.nc'\n",
        "    for r in [64, 128, 256, 512, 1024, 2048]\n",
        "}\n",
        "filenames['learned_interp_64'] = 'learned_interpolation_long_eval_64x64_64x64.nc'\n",
        "\n",
        "models = {}\n",
        "for k, v in filenames.items():\n",
        "  models[k] = xarray.open_dataset(f'./content/{v}', chunks={'time': '100MB'})\n",
        "\n",
        "combined = xarray.concat(list(models.values()), dim='model')\n",
        "combined.coords['model'] = list(models.keys())\n",
        "combined['vorticity'] = xru.vorticity_2d(combined)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "id": "ExfQo-OEJJI4"
      },
      "outputs": [],
      "source": [
        "from jax_cfd.base import resize\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "def resize_64_to_32(ds):\n",
        "  coarse = xarray.Dataset({\n",
        "      'u': ds.u.isel(x=slice(1, None, 2)).coarsen(y=2, coord_func='max').mean(),\n",
        "      'v': ds.v.isel(y=slice(1, None, 2)).coarsen(x=2, coord_func='max').mean(),\n",
        "  })\n",
        "  coarse.attrs = ds.attrs\n",
        "  return coarse\n",
        "\n",
        "combined_32 = resize_64_to_32(combined)\n",
        "combined_32['vorticity'] = xru.vorticity_2d(combined_32)\n",
        "\n",
        "models_32 = {k: resize_64_to_32(v) for k, v in models.items()}"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XNXcB-Bw6-zK"
      },
      "source": [
        "### Plot solutions: Fig 2(a)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 327
        },
        "executionInfo": {
          "elapsed": 7,
          "status": "ok",
          "timestamp": 1635551445632,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "tFMn09mfkGQX",
        "outputId": "9a9ce456-318f-4dea-9f04-7ecb35c475f1"
      },
      "outputs": [
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              "\n",
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              "\n",
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              "  font-weight: normal;\n",
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              "\n",
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              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 6GB\n",
              "Dimensions:    (time: 3477, x: 32, y: 32, sample: 16, model: 7)\n",
              "Coordinates:\n",
              "  * time       (time) float64 28kB 0.0 0.07012 0.1402 ... 243.6 243.7 243.8\n",
              "  * x          (x) float64 256B 0.1473 0.3436 0.54 0.7363 ... 5.841 6.038 6.234\n",
              "  * y          (y) float64 256B 0.1473 0.3436 0.54 0.7363 ... 5.841 6.038 6.234\n",
              "  * sample     (sample) int32 64B 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15\n",
              "  * model      (model) &lt;U17 476B &#x27;baseline_64&#x27; ... &#x27;learned_interp_64&#x27;\n",
              "Data variables:\n",
              "    u          (model, sample, time, x, y) float32 2GB dask.array&lt;chunksize=(1, 16, 381, 32, 32), meta=np.ndarray&gt;\n",
              "    v          (model, sample, time, x, y) float32 2GB dask.array&lt;chunksize=(1, 16, 381, 32, 32), meta=np.ndarray&gt;\n",
              "    vorticity  (model, sample, time, x, y) float64 3GB dask.array&lt;chunksize=(1, 16, 381, 32, 32), meta=np.ndarray&gt;\n",
              "Attributes: (12/17)\n",
              "    domain_size:                   [0.         6.28318531]\n",
              "    domain_size_multiple:          1\n",
              "    full_config_str:               \\n# Macros:\\n# ===========================...\n",
              "    init_cfl_safety_factor:        0.5\n",
              "    init_peak_wavenumber:          4.0\n",
              "    maximum_velocity:              7.0\n",
              "    ...                            ...\n",
              "    simulation_time:               240.0\n",
              "    stable_time_step:              0.007012483601762931\n",
              "    time_subsample_factor:         1\n",
              "    tracing_max_duration_in_msec:  100.0\n",
              "    warmup_grid_size:              2048\n",
              "    warmup_time:                   40.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e96ebafc-56da-450a-b54e-416ce5933304' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e96ebafc-56da-450a-b54e-416ce5933304' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 3477</li><li><span class='xr-has-index'>x</span>: 32</li><li><span class='xr-has-index'>y</span>: 32</li><li><span class='xr-has-index'>sample</span>: 16</li><li><span class='xr-has-index'>model</span>: 7</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1218b070-e4a8-44d1-9073-1047b58df070' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1218b070-e4a8-44d1-9073-1047b58df070' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.07012 0.1402 ... 243.7 243.8</div><input id='attrs-55945049-db4c-47c9-844b-1ac75b0c49ff' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-55945049-db4c-47c9-844b-1ac75b0c49ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b592df54-872f-46d8-a606-6fe90aff048a' class='xr-var-data-in' type='checkbox'><label for='data-b592df54-872f-46d8-a606-6fe90aff048a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 7.012484e-02, 1.402497e-01, ..., 2.436137e+02,\n",
              "       2.436838e+02, 2.437539e+02])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1473 0.3436 0.54 ... 6.038 6.234</div><input id='attrs-40839a4c-64a3-40c5-aa4b-945221e1011b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-40839a4c-64a3-40c5-aa4b-945221e1011b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9767847d-1c8a-4d46-b8cc-3aae23764b81' class='xr-var-data-in' type='checkbox'><label for='data-9767847d-1c8a-4d46-b8cc-3aae23764b81' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.147262, 0.343612, 0.539961, 0.736311, 0.93266 , 1.12901 , 1.325359,\n",
              "       1.521709, 1.718059, 1.914408, 2.110758, 2.307107, 2.503457, 2.699806,\n",
              "       2.896156, 3.092505, 3.288855, 3.485204, 3.681554, 3.877903, 4.074253,\n",
              "       4.270603, 4.466952, 4.663302, 4.859651, 5.056001, 5.25235 , 5.4487  ,\n",
              "       5.64505 , 5.841399, 6.037748, 6.234098])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1473 0.3436 0.54 ... 6.038 6.234</div><input id='attrs-d09c9fca-0d6f-44e6-a944-aa7c74d955cf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d09c9fca-0d6f-44e6-a944-aa7c74d955cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4782040d-5e59-4ccf-a499-c65201111ca2' class='xr-var-data-in' type='checkbox'><label for='data-4782040d-5e59-4ccf-a499-c65201111ca2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.147262, 0.343612, 0.539961, 0.736311, 0.93266 , 1.12901 , 1.325359,\n",
              "       1.521709, 1.718059, 1.914408, 2.110758, 2.307107, 2.503457, 2.699806,\n",
              "       2.896156, 3.092505, 3.288855, 3.485204, 3.681554, 3.877903, 4.074253,\n",
              "       4.270603, 4.466952, 4.663302, 4.859651, 5.056001, 5.25235 , 5.4487  ,\n",
              "       5.64505 , 5.841399, 6.037748, 6.234098])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sample</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 10 11 12 13 14 15</div><input id='attrs-76450681-e518-4f3a-81fd-44fdecce77d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-76450681-e518-4f3a-81fd-44fdecce77d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1644ca0-8e5b-4122-89ea-a4e0e1407d7b' class='xr-var-data-in' type='checkbox'><label for='data-a1644ca0-8e5b-4122-89ea-a4e0e1407d7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15],\n",
              "      dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>model</span></div><div class='xr-var-dims'>(model)</div><div class='xr-var-dtype'>&lt;U17</div><div class='xr-var-preview xr-preview'>&#x27;baseline_64&#x27; ... &#x27;learned_inter...</div><input id='attrs-a9b22ad2-3fee-4089-962c-a3aab3cf8023' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a9b22ad2-3fee-4089-962c-a3aab3cf8023' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d855548-65e6-42f2-844f-0d0e82eceb9d' class='xr-var-data-in' type='checkbox'><label for='data-2d855548-65e6-42f2-844f-0d0e82eceb9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;baseline_64&#x27;, &#x27;baseline_128&#x27;, &#x27;baseline_256&#x27;, &#x27;baseline_512&#x27;,\n",
              "       &#x27;baseline_1024&#x27;, &#x27;baseline_2048&#x27;, &#x27;learned_interp_64&#x27;], dtype=&#x27;&lt;U17&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a60277c7-2e5f-40ae-90d6-7a290a8f8883' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a60277c7-2e5f-40ae-90d6-7a290a8f8883' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(model, sample, time, x, y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 16, 381, 32, 32), meta=np.ndarray&gt;</div><input id='attrs-1b8102f5-3f61-49a0-a9b3-f3717b955cb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b8102f5-3f61-49a0-a9b3-f3717b955cb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4674d286-e6aa-441b-910f-ebd37fb8cb81' class='xr-var-data-in' type='checkbox'><label for='data-4674d286-e6aa-441b-910f-ebd37fb8cb81' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>offset :</span></dt><dd>[1.  0.5]</dd></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 1.49 GiB </td>\n",
              "                        <td> 23.81 MiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (7, 16, 3477, 32, 32) </td>\n",
              "                        <td> (1, 16, 381, 32, 32) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 70 chunks in 26 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(model, sample, time, x, y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 16, 381, 32, 32), meta=np.ndarray&gt;</div><input id='attrs-acbb7062-e3e6-4fa9-a13b-52f5a613d497' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acbb7062-e3e6-4fa9-a13b-52f5a613d497' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0186c7af-f005-4ecc-aac1-329c24b730a2' class='xr-var-data-in' type='checkbox'><label for='data-0186c7af-f005-4ecc-aac1-329c24b730a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>offset :</span></dt><dd>[0.5 1. ]</dd></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 1.49 GiB </td>\n",
              "                        <td> 23.81 MiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (7, 16, 3477, 32, 32) </td>\n",
              "                        <td> (1, 16, 381, 32, 32) </td>\n",
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              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 70 chunks in 26 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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              "    </tr>\n",
              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vorticity</span></div><div class='xr-var-dims'>(model, sample, time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 16, 381, 32, 32), meta=np.ndarray&gt;</div><input id='attrs-801b079e-e05b-476b-b148-5f5d0dee82d8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-801b079e-e05b-476b-b148-5f5d0dee82d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-975f89b1-69ce-48ed-800d-b8d0f1f9ac9a' class='xr-var-data-in' type='checkbox'><label for='data-975f89b1-69ce-48ed-800d-b8d0f1f9ac9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 2.97 GiB </td>\n",
              "                        <td> 47.62 MiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (7, 16, 3477, 32, 32) </td>\n",
              "                        <td> (1, 16, 381, 32, 32) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 70 chunks in 66 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
              "                    </tr>\n",
              "                </tbody>\n",
              "            </table>\n",
              "        </td>\n",
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              "  <text x=\"120.294118\" y=\"80.706734\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,120.294118,80.706734)\">3477</text>\n",
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              "    </tr>\n",
              "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-98cc30e2-dad1-4c69-818c-c5ec6acf6d38' class='xr-section-summary-in' type='checkbox'  ><label for='section-98cc30e2-dad1-4c69-818c-c5ec6acf6d38' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c4966ff5-b734-40ed-a2f6-460e6a3e1802' class='xr-index-data-in' type='checkbox'/><label for='index-c4966ff5-b734-40ed-a2f6-460e6a3e1802' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([                0.0, 0.07012483601762931, 0.14024967203525862,\n",
              "       0.21037450805288793, 0.28049934407051724, 0.35062418008814655,\n",
              "       0.42074901610577586,  0.4908738521234052,  0.5609986881410345,\n",
              "        0.6311235241586638,\n",
              "       ...\n",
              "        243.12280647312082,  243.19293130913846,  243.26305614515607,\n",
              "         243.3331809811737,  243.40330581719132,  243.47343065320896,\n",
              "         243.5435554892266,  243.61368032524422,  243.68380516126186,\n",
              "        243.75392999727947],\n",
              "      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;, length=3477))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0979f3e8-35a4-45b2-8e7d-6d9fe26e8e6c' class='xr-index-data-in' type='checkbox'/><label for='index-0979f3e8-35a4-45b2-8e7d-6d9fe26e8e6c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.14726215600967407,  0.3436117172241211,  0.5399612784385681,\n",
              "        0.7363107800483704,  0.9326603412628174,  1.1290098428726196,\n",
              "        1.3253594636917114,  1.5217089653015137,  1.7180585861206055,\n",
              "        1.9144080877304077,    2.11075758934021,  2.3071072101593018,\n",
              "        2.5034568309783936,  2.6998062133789062,   2.896155834197998,\n",
              "          3.09250545501709,  3.2888548374176025,  3.4852044582366943,\n",
              "         3.681554079055786,   3.877903461456299,   4.074253082275391,\n",
              "         4.270602703094482,   4.466952323913574,   4.663301944732666,\n",
              "           4.8596510887146,   5.056000709533691,   5.252350330352783,\n",
              "         5.448699951171875,   5.645049571990967,   5.841399192810059,\n",
              "         6.037748336791992,   6.234097957611084],\n",
              "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8f7c3bd8-5ee8-43d0-ac1d-b43bd37cac4c' class='xr-index-data-in' type='checkbox'/><label for='index-8f7c3bd8-5ee8-43d0-ac1d-b43bd37cac4c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.14726215600967407,  0.3436117172241211,  0.5399612784385681,\n",
              "        0.7363107800483704,  0.9326603412628174,  1.1290098428726196,\n",
              "        1.3253594636917114,  1.5217089653015137,  1.7180585861206055,\n",
              "        1.9144080877304077,    2.11075758934021,  2.3071072101593018,\n",
              "        2.5034568309783936,  2.6998062133789062,   2.896155834197998,\n",
              "          3.09250545501709,  3.2888548374176025,  3.4852044582366943,\n",
              "         3.681554079055786,   3.877903461456299,   4.074253082275391,\n",
              "         4.270602703094482,   4.466952323913574,   4.663301944732666,\n",
              "           4.8596510887146,   5.056000709533691,   5.252350330352783,\n",
              "         5.448699951171875,   5.645049571990967,   5.841399192810059,\n",
              "         6.037748336791992,   6.234097957611084],\n",
              "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>sample</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-63c7ea22-2076-4572-870b-f518f6e6fd2d' class='xr-index-data-in' type='checkbox'/><label for='index-63c7ea22-2076-4572-870b-f518f6e6fd2d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], dtype=&#x27;int32&#x27;, name=&#x27;sample&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>model</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8d0bedba-2b56-4e89-8aa5-091f18c590a8' class='xr-index-data-in' type='checkbox'/><label for='index-8d0bedba-2b56-4e89-8aa5-091f18c590a8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;baseline_64&#x27;, &#x27;baseline_128&#x27;, &#x27;baseline_256&#x27;, &#x27;baseline_512&#x27;,\n",
              "       &#x27;baseline_1024&#x27;, &#x27;baseline_2048&#x27;, &#x27;learned_interp_64&#x27;],\n",
              "      dtype=&#x27;object&#x27;, name=&#x27;model&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-924e20a7-3d95-4f50-a451-5b73007f9217' class='xr-section-summary-in' type='checkbox'  ><label for='section-924e20a7-3d95-4f50-a451-5b73007f9217' class='xr-section-summary' >Attributes: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>domain_size :</span></dt><dd>[0.         6.28318531]</dd><dt><span>domain_size_multiple :</span></dt><dd>1</dd><dt><span>full_config_str :</span></dt><dd>\n",
              "# Macros:\n",
              "# ==============================================================================\n",
              "C_INTERPOLATION_MODULE = @interpolations.transformed\n",
              "CONVECTION_MODULE = @advections.self_advection\n",
              "DENSITY = 1.0\n",
              "DIFFUSION_MODULE = @diffusions.solve_fast_diag\n",
              "FORCING_MODULE = @forcings.kolmogorov_forcing\n",
              "NS_MODULE = @equations.modular_navier_stokes_model\n",
              "PRESSURE_MODULE = @pressures.fast_diagonalization\n",
              "U_INTERPOLATION_MODULE = @interpolations.linear\n",
              "VISCOSITY = 0.0003\n",
              "\n",
              "# Parameters for get_model_cls:\n",
              "# ==============================================================================\n",
              "get_model_cls.model_cls = @ModularStepModel\n",
              "\n",
              "# Parameters for get_physics_specs:\n",
              "# ==============================================================================\n",
              "get_physics_specs.physics_specs_cls = @NavierStokesPhysicsSpecs\n",
              "\n",
              "# Parameters for implicit_diffusion_navier_stokes:\n",
              "# ==============================================================================\n",
              "implicit_diffusion_navier_stokes.diffusion_module = %DIFFUSION_MODULE\n",
              "\n",
              "# Parameters for kolmogorov_forcing:\n",
              "# ==============================================================================\n",
              "kolmogorov_forcing.linear_coefficient = -0.1\n",
              "kolmogorov_forcing.scale = 1.0\n",
              "kolmogorov_forcing.wavenumber = 4\n",
              "\n",
              "# Parameters for modular_advection:\n",
              "# ==============================================================================\n",
              "modular_advection.c_interpolation_module = %C_INTERPOLATION_MODULE\n",
              "modular_advection.u_interpolation_module = %U_INTERPOLATION_MODULE\n",
              "\n",
              "# Parameters for modular_navier_stokes_model:\n",
              "# ==============================================================================\n",
              "modular_navier_stokes_model.convection_module = %CONVECTION_MODULE\n",
              "modular_navier_stokes_model.equation_solver = \\\n",
              "    @equations.implicit_diffusion_navier_stokes\n",
              "modular_navier_stokes_model.pressure_module = %PRESSURE_MODULE\n",
              "\n",
              "# Parameters for ModularStepModel:\n",
              "# ==============================================================================\n",
              "ModularStepModel.advance_module = %NS_MODULE\n",
              "ModularStepModel.decoder_module = @decoders.aligned_array_decoder\n",
              "ModularStepModel.encoder_module = @encoders.aligned_array_encoder\n",
              "\n",
              "# Parameters for NavierStokesPhysicsSpecs:\n",
              "# ==============================================================================\n",
              "NavierStokesPhysicsSpecs.density = %DENSITY\n",
              "NavierStokesPhysicsSpecs.forcing_module = %FORCING_MODULE\n",
              "NavierStokesPhysicsSpecs.viscosity = 0.001\n",
              "\n",
              "# Parameters for self_advection:\n",
              "# ==============================================================================\n",
              "self_advection.advection_module = @advections.modular_advection\n",
              "\n",
              "# Parameters for transformed:\n",
              "# ==============================================================================\n",
              "transformed.base_interpolation_module = @interpolations.lax_wendroff\n",
              "transformed.transformation = @interpolations.tvd_limiter_transformation</dd><dt><span>init_cfl_safety_factor :</span></dt><dd>0.5</dd><dt><span>init_peak_wavenumber :</span></dt><dd>4.0</dd><dt><span>maximum_velocity :</span></dt><dd>7.0</dd><dt><span>ndim :</span></dt><dd>2</dd><dt><span>physics_config_str :</span></dt><dd>\n",
              "# Macros:\n",
              "# ==============================================================================\n",
              "DENSITY = 1.0\n",
              "FORCING_MODULE = @forcings.kolmogorov_forcing\n",
              "\n",
              "# Parameters for get_physics_specs:\n",
              "# ==============================================================================\n",
              "get_physics_specs.physics_specs_cls = @NavierStokesPhysicsSpecs\n",
              "\n",
              "# Parameters for kolmogorov_forcing:\n",
              "# ==============================================================================\n",
              "kolmogorov_forcing.linear_coefficient = -0.1\n",
              "kolmogorov_forcing.scale = 1.0\n",
              "kolmogorov_forcing.swap_xy = False\n",
              "kolmogorov_forcing.wavenumber = 4\n",
              "\n",
              "# Parameters for NavierStokesPhysicsSpecs:\n",
              "# ==============================================================================\n",
              "NavierStokesPhysicsSpecs.density = %DENSITY\n",
              "NavierStokesPhysicsSpecs.forcing_module = %FORCING_MODULE\n",
              "NavierStokesPhysicsSpecs.viscosity = 0.001</dd><dt><span>save_grid_size :</span></dt><dd>64</dd><dt><span>seed :</span></dt><dd>2</dd><dt><span>simulation_grid_size :</span></dt><dd>64</dd><dt><span>simulation_time :</span></dt><dd>240.0</dd><dt><span>stable_time_step :</span></dt><dd>0.007012483601762931</dd><dt><span>time_subsample_factor :</span></dt><dd>1</dd><dt><span>tracing_max_duration_in_msec :</span></dt><dd>100.0</dd><dt><span>warmup_grid_size :</span></dt><dd>2048</dd><dt><span>warmup_time :</span></dt><dd>40.0</dd></dl></div></li></ul></div></div>"
            ],
            "text/plain": [
              "<xarray.Dataset> Size: 6GB\n",
              "Dimensions:    (time: 3477, x: 32, y: 32, sample: 16, model: 7)\n",
              "Coordinates:\n",
              "  * time       (time) float64 28kB 0.0 0.07012 0.1402 ... 243.6 243.7 243.8\n",
              "  * x          (x) float64 256B 0.1473 0.3436 0.54 0.7363 ... 5.841 6.038 6.234\n",
              "  * y          (y) float64 256B 0.1473 0.3436 0.54 0.7363 ... 5.841 6.038 6.234\n",
              "  * sample     (sample) int32 64B 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15\n",
              "  * model      (model) <U17 476B 'baseline_64' ... 'learned_interp_64'\n",
              "Data variables:\n",
              "    u          (model, sample, time, x, y) float32 2GB dask.array<chunksize=(1, 16, 381, 32, 32), meta=np.ndarray>\n",
              "    v          (model, sample, time, x, y) float32 2GB dask.array<chunksize=(1, 16, 381, 32, 32), meta=np.ndarray>\n",
              "    vorticity  (model, sample, time, x, y) float64 3GB dask.array<chunksize=(1, 16, 381, 32, 32), meta=np.ndarray>\n",
              "Attributes: (12/17)\n",
              "    domain_size:                   [0.         6.28318531]\n",
              "    domain_size_multiple:          1\n",
              "    full_config_str:               \\n# Macros:\\n# ===========================...\n",
              "    init_cfl_safety_factor:        0.5\n",
              "    init_peak_wavenumber:          4.0\n",
              "    maximum_velocity:              7.0\n",
              "    ...                            ...\n",
              "    simulation_time:               240.0\n",
              "    stable_time_step:              0.007012483601762931\n",
              "    time_subsample_factor:         1\n",
              "    tracing_max_duration_in_msec:  100.0\n",
              "    warmup_grid_size:              2048\n",
              "    warmup_time:                   40.0"
            ]
          },
          "execution_count": 24,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "combined_32"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "executionInfo": {
          "elapsed": 61916,
          "status": "ok",
          "timestamp": 1635551507543,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "zFinZ9ARiqqU",
        "outputId": "5d31afee-d929-44de-ee3f-1df4c284c0d9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<xarray.plot.facetgrid.FacetGrid at 0x7fefcc050760>"
            ]
          },
          "execution_count": 25,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1135x1610 with 35 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "combined.vorticity.isel(sample=0).thin(time=50).head(time=5).plot.imshow(\n",
        "    row='model', col='time', x='x', y='y', robust=True, size=2.3, aspect=0.9,\n",
        "    add_colorbar=False, cmap=seaborn.cm.icefire, vmin=-10, vmax=10)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W_U-Fj4A7BvH"
      },
      "source": [
        "### Calculate speed-up\n",
        "\n",
        "We can calculate speed-up based upon vorticity correlation either at a resolution of 32x32 or 64x64. The numbers are similar.\n",
        "\n",
        "Note that our ML models are slightly more effective than the FVM method on these dataset (138x vs 86x speedup), but still within the range of uncertainty."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 9344,
          "status": "ok",
          "timestamp": 1635551516869,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "78pQ0PjD5QNL",
        "outputId": "fffa4b8d-af6a-45dc-9b31-6986fb996615"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "speedup estimate: 138.65628228906488\n",
            "speedup bootstrap mean: 150.1622373446224\n",
            "speedup bootstrap stddev: 56.715622519976975\n",
            "speedup bootstrap median: 140.65924736688626\n",
            "speedup bootstrap range: [78.28523529762678, 256.4975332101573]\n",
            "upscaling estimate: 11.933315923931211\n",
            "upscaling bootstrap mean: 12.065674792877463\n",
            "upscaling bootstrap stddev: 1.334714789124013\n",
            "upscaling bootstrap median: 11.986456615013452\n",
            "upscaling bootstrap range: [9.996538166582015, 14.438528892811396]\n",
            "CPU times: user 8.22 s, sys: 2.61 s, total: 10.8 s\n",
            "Wall time: 3.27 s\n"
          ]
        }
      ],
      "source": [
        "%%time\n",
        "v = combined_32.vorticity.sel(time=slice(20))\n",
        "vorticity_correlation = correlation(v, v.sel(model='baseline_2048')).compute()\n",
        "\n",
        "times = calculate_time_until(vorticity_correlation)\n",
        "times_boot = calculate_time_until_bootstrap(vorticity_correlation)\n",
        "\n",
        "speedup = calculate_speedup(times)\n",
        "print('speedup estimate:', float(speedup))\n",
        "\n",
        "speedups = calculate_speedup(times_boot)\n",
        "print('speedup bootstrap mean:', float(speedups.mean('boot')))\n",
        "print('speedup bootstrap stddev:', float(speedups.std('boot')))\n",
        "print('speedup bootstrap median:', float(speedups.median('boot')))\n",
        "print('speedup bootstrap range:', speedups.quantile(dim='boot', q=[0.05, 0.95]).values.tolist())\n",
        "\n",
        "upscaling = calculate_upscaling(times)\n",
        "print('upscaling estimate:', float(upscaling))\n",
        "\n",
        "upscalings = calculate_upscaling(times_boot)\n",
        "print('upscaling bootstrap mean:', float(upscalings.mean('boot')))\n",
        "print('upscaling bootstrap stddev:', float(upscalings.std('boot')))\n",
        "print('upscaling bootstrap median:', float(upscalings.median('boot')))\n",
        "print('upscaling bootstrap range:', upscalings.quantile(dim='boot', q=[0.05, 0.95]).values.tolist())\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 8636,
          "status": "ok",
          "timestamp": 1635551525494,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "nStmzvTn5vt0",
        "outputId": "02072209-ac60-4df2-c7d8-4c9af7b82696"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "speedup estimate: 146.00341279323766\n",
            "speedup bootstrap mean: 159.08210350631379\n",
            "speedup bootstrap stddev: 51.99629206702296\n",
            "speedup bootstrap median: 151.11653189502027\n",
            "speedup bootstrap range: [91.53284716965098, 256.4975332101573]\n",
            "upscaling estimate: 12.125732532083184\n",
            "upscaling bootstrap mean: 12.321154928480457\n",
            "upscaling bootstrap stddev: 1.2015687231188001\n",
            "upscaling bootstrap median: 12.255730858687793\n",
            "upscaling bootstrap range: [10.492629382668657, 14.438528892811396]\n",
            "CPU times: user 5.9 s, sys: 3.27 s, total: 9.17 s\n",
            "Wall time: 3.13 s\n"
          ]
        }
      ],
      "source": [
        "%%time\n",
        "v = combined.vorticity.sel(time=slice(20))\n",
        "vorticity_correlation = correlation(v, v.sel(model='baseline_2048')).compute()\n",
        "\n",
        "times = calculate_time_until(vorticity_correlation)\n",
        "times_boot = calculate_time_until_bootstrap(vorticity_correlation)\n",
        "\n",
        "speedup = calculate_speedup(times)\n",
        "print('speedup estimate:', float(speedup))\n",
        "\n",
        "speedups = calculate_speedup(times_boot)\n",
        "print('speedup bootstrap mean:', float(speedups.mean('boot')))\n",
        "print('speedup bootstrap stddev:', float(speedups.std('boot')))\n",
        "print('speedup bootstrap median:', float(speedups.median('boot')))\n",
        "print('speedup bootstrap range:', speedups.quantile(dim='boot', q=[0.05, 0.95]).values.tolist())\n",
        "\n",
        "upscaling = calculate_upscaling(times)\n",
        "print('upscaling estimate:', float(upscaling))\n",
        "\n",
        "upscalings = calculate_upscaling(times_boot)\n",
        "print('upscaling bootstrap mean:', float(upscalings.mean('boot')))\n",
        "print('upscaling bootstrap stddev:', float(upscalings.std('boot')))\n",
        "print('upscaling bootstrap median:', float(upscalings.median('boot')))\n",
        "print('upscaling bootstrap range:', upscalings.quantile(dim='boot', q=[0.05, 0.95]).values.tolist())\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "executionInfo": {
          "elapsed": 215,
          "status": "ok",
          "timestamp": 1635551525706,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "PqaVAd3I7kOA",
        "outputId": "f1dfcaab-112d-4c6b-d6a8-780d6418cd4b"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "speedups.rename('speedup factor').plot.hist(bins=50);"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mJmmcyMw7AhI"
      },
      "source": [
        "### Calculate metrics"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 52831,
          "status": "ok",
          "timestamp": 1635551578534,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "LDKCKaKm3-43",
        "outputId": "3afabcce-cf09-46d5-d2a9-f3824069f56f"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n",
            "/home/modelzoo/jax/jax-cfd/jax_cfd/data/xarray_utils.py:196: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
            "  result = xarray.apply_ufunc(\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 53.8 s, sys: 20 s, total: 1min 13s\n",
            "Wall time: 24.7 s\n"
          ]
        }
      ],
      "source": [
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "%%time\n",
        "summary = xarray.concat([\n",
        "    evaluation.compute_summary_dataset(ds, models['baseline_2048'])\n",
        "    for ds in models.values()\n",
        "], dim='model')\n",
        "summary.coords['model'] = list(models.keys())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 222
        },
        "executionInfo": {
          "elapsed": 238,
          "status": "ok",
          "timestamp": 1635551578759,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
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          "user_tz": 420
        },
        "id": "Bdm2XuPl5M1J",
        "outputId": "f9635572-ad01-4aac-e1e9-19bab975988e"
      },
      "outputs": [
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              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 17MB\n",
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              "  * model                         (model) &lt;U17 476B &#x27;baseline_64&#x27; ... &#x27;learne...\n",
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              "    ...                            ...\n",
              "    energy_spectrum_within_q=1.0  (model, k, time) bool 730kB dask.array&lt;chunksize=(1, 30, 381), meta=np.ndarray&gt;\n",
              "    enstrophy_within_q=1.0        (model, time) float64 195kB dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;\n",
              "    vorticity_within_q=1.0        (model, time) float64 195kB dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;\n",
              "    u_correlation                 (model, time) float32 97kB dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;\n",
              "    v_correlation                 (model, time) float32 97kB dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;\n",
              "    vorticity_correlation         (model, time) float64 195kB dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0b6cc028-5731-42e8-8ab9-44b82ca2e537' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0b6cc028-5731-42e8-8ab9-44b82ca2e537' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>model</span>: 7</li><li><span class='xr-has-index'>time</span>: 3477</li><li><span class='xr-has-index'>k</span>: 30</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-219564c6-eb44-494c-9dd0-2c9108fdee36' class='xr-section-summary-in' type='checkbox'  checked><label for='section-219564c6-eb44-494c-9dd0-2c9108fdee36' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.07012 0.1402 ... 243.7 243.8</div><input id='attrs-b7394633-d46a-4359-8063-bf2adfb4a676' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7394633-d46a-4359-8063-bf2adfb4a676' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8ba31d4-2446-4451-8a40-76854316f162' class='xr-var-data-in' type='checkbox'><label for='data-f8ba31d4-2446-4451-8a40-76854316f162' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 7.012484e-02, 1.402497e-01, ..., 2.436137e+02,\n",
              "       2.436838e+02, 2.437539e+02])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>k</span></div><div class='xr-var-dims'>(k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... 28.0 29.0 30.0</div><input id='attrs-87b0c8a5-ff69-4ba2-9eee-f4e59ad752e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-87b0c8a5-ff69-4ba2-9eee-f4e59ad752e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64442a1f-f2f4-4f56-895d-ccace13292df' class='xr-var-data-in' type='checkbox'><label for='data-64442a1f-f2f4-4f56-895d-ccace13292df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13., 14.,\n",
              "       15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,\n",
              "       29., 30.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>model</span></div><div class='xr-var-dims'>(model)</div><div class='xr-var-dtype'>&lt;U17</div><div class='xr-var-preview xr-preview'>&#x27;baseline_64&#x27; ... &#x27;learned_inter...</div><input id='attrs-de21900b-8f3c-4085-8379-6d2874955e36' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-de21900b-8f3c-4085-8379-6d2874955e36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8b889a0-e158-46e9-bbc9-31c06eef44fb' class='xr-var-data-in' type='checkbox'><label for='data-a8b889a0-e158-46e9-bbc9-31c06eef44fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;baseline_64&#x27;, &#x27;baseline_128&#x27;, &#x27;baseline_256&#x27;, &#x27;baseline_512&#x27;,\n",
              "       &#x27;baseline_1024&#x27;, &#x27;baseline_2048&#x27;, &#x27;learned_interp_64&#x27;], dtype=&#x27;&lt;U17&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-15c0e43d-66d9-42dd-9e79-5ae2adb8277f' class='xr-section-summary-in' type='checkbox'  ><label for='section-15c0e43d-66d9-42dd-9e79-5ae2adb8277f' class='xr-section-summary' >Data variables: <span>(31)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u_mean</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-bd888a58-88a7-4cf7-b014-75717153faff' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd888a58-88a7-4cf7-b014-75717153faff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2293049-83af-46a4-b6ef-ef43aac575d2' class='xr-var-data-in' type='checkbox'><label for='data-b2293049-83af-46a4-b6ef-ef43aac575d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 95.07 kiB </td>\n",
              "                        <td> 1.49 kiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (7, 3477) </td>\n",
              "                        <td> (1, 381) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 70 chunks in 57 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_mean</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-3da6d9dc-b52e-4678-a90f-ccd3fd39501f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3da6d9dc-b52e-4678-a90f-ccd3fd39501f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f120c7f9-ab51-4012-97d9-d8d139924dc4' class='xr-var-data-in' type='checkbox'><label for='data-f120c7f9-ab51-4012-97d9-d8d139924dc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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              "                        <th> Array </th>\n",
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              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 95.07 kiB </td>\n",
              "                        <td> 1.49 kiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (7, 3477) </td>\n",
              "                        <td> (1, 381) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 70 chunks in 57 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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              "    </tr>\n",
              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>kinetic_energy_mean</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-d8e2cf46-4b68-4ccd-80ad-1800403ddb3e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d8e2cf46-4b68-4ccd-80ad-1800403ddb3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a06cce90-48a6-46ac-80c9-ae21f1615a41' class='xr-var-data-in' type='checkbox'><label for='data-a06cce90-48a6-46ac-80c9-ae21f1615a41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 95.07 kiB </td>\n",
              "                        <td> 1.49 kiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (7, 3477) </td>\n",
              "                        <td> (1, 381) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
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              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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              "        </td>\n",
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              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>speed_mean</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-01a26da4-5489-420e-9c89-9ad20639b51a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-01a26da4-5489-420e-9c89-9ad20639b51a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b09e10c9-1043-4abe-980f-468eec559132' class='xr-var-data-in' type='checkbox'><label for='data-b09e10c9-1043-4abe-980f-468eec559132' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
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              "                <thead>\n",
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              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
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              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
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              "            <table style=\"border-collapse: collapse;\">\n",
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              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 95.07 kiB </td>\n",
              "                        <td> 1.49 kiB </td>\n",
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              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (7, 3477) </td>\n",
              "                        <td> (1, 381) </td>\n",
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              "                    <tr>\n",
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              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_error</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-988e9310-a6be-4cff-af0c-8cfd6ab6bb6b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-988e9310-a6be-4cff-af0c-8cfd6ab6bb6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f50d7c7a-e7cb-41d4-a32c-8c3b27ecd920' class='xr-var-data-in' type='checkbox'><label for='data-f50d7c7a-e7cb-41d4-a32c-8c3b27ecd920' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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              "                        <th> Chunk </th>\n",
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              "                <tbody>\n",
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              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 95.07 kiB </td>\n",
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              "                    <tr>\n",
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              "                        <th> Data type </th>\n",
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              "    </tr>\n",
              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>kinetic_energy_error</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-6300bee9-35cf-4896-80d2-69445d60449b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6300bee9-35cf-4896-80d2-69445d60449b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db45ed1e-706e-48cd-8598-0cac57fc90d8' class='xr-var-data-in' type='checkbox'><label for='data-db45ed1e-706e-48cd-8598-0cac57fc90d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
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              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 95.07 kiB </td>\n",
              "                        <td> 1.49 kiB </td>\n",
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              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
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              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
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              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>speed_error</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-b7fed2d9-eb12-4436-884d-b94637c31609' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7fed2d9-eb12-4436-884d-b94637c31609' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b23aaa1c-5d63-4fb6-a2d3-61f4cf62c28f' class='xr-var-data-in' type='checkbox'><label for='data-b23aaa1c-5d63-4fb6-a2d3-61f4cf62c28f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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              "                <thead>\n",
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              "                        <th> Array </th>\n",
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              "                    <tr>\n",
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              "                        <td> 95.07 kiB </td>\n",
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              "                        <th> Shape </th>\n",
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              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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              "                    <tr>\n",
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              "                        <td> 5.57 MiB </td>\n",
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              "                <tbody>\n",
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              "                    <tr>\n",
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              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u_within_q=1.0</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-2e1a806d-4172-449b-ac47-83ece6eaaaff' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2e1a806d-4172-449b-ac47-83ece6eaaaff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72601300-e121-4eac-8f52-1395bae3384f' class='xr-var-data-in' type='checkbox'><label for='data-72601300-e121-4eac-8f52-1395bae3384f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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              "                <tbody>\n",
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              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 190.15 kiB </td>\n",
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              "                    <tr>\n",
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              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_within_q=1.0</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-36afd6df-db35-48f7-9611-b2d72752ddc0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-36afd6df-db35-48f7-9611-b2d72752ddc0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eef05cfc-efae-4374-9a12-cd60ff390b60' class='xr-var-data-in' type='checkbox'><label for='data-eef05cfc-efae-4374-9a12-cd60ff390b60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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              "                <tbody>\n",
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              "                    <tr>\n",
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              "                    <tr>\n",
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              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>kinetic_energy_within_q=1.0</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-bfeaf3a4-9d0d-4b22-b5a9-9f09611f9fce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bfeaf3a4-9d0d-4b22-b5a9-9f09611f9fce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1209c1aa-047d-415e-b1ad-da80d0c0338a' class='xr-var-data-in' type='checkbox'><label for='data-1209c1aa-047d-415e-b1ad-da80d0c0338a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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              "                    <tr>\n",
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              "</svg>\n",
              "        </td>\n",
              "    </tr>\n",
              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u_correlation</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-831ea186-88b4-491f-8a2d-1ce4e71a5d7f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-831ea186-88b4-491f-8a2d-1ce4e71a5d7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-712d55a0-fe26-49a8-82a8-3553b719fb11' class='xr-var-data-in' type='checkbox'><label for='data-712d55a0-fe26-49a8-82a8-3553b719fb11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 95.07 kiB </td>\n",
              "                        <td> 1.49 kiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (7, 3477) </td>\n",
              "                        <td> (1, 381) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 70 chunks in 226 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
              "                    </tr>\n",
              "                </tbody>\n",
              "            </table>\n",
              "        </td>\n",
              "        <td>\n",
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              "\n",
              "  <!-- Text -->\n",
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              "</svg>\n",
              "        </td>\n",
              "    </tr>\n",
              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_correlation</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-53ade848-6681-4faf-85f9-7687248b26fb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53ade848-6681-4faf-85f9-7687248b26fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0247a7c-7bef-4a0a-9d87-0941c7f10765' class='xr-var-data-in' type='checkbox'><label for='data-e0247a7c-7bef-4a0a-9d87-0941c7f10765' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 95.07 kiB </td>\n",
              "                        <td> 1.49 kiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (7, 3477) </td>\n",
              "                        <td> (1, 381) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 70 chunks in 226 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
              "                    </tr>\n",
              "                </tbody>\n",
              "            </table>\n",
              "        </td>\n",
              "        <td>\n",
              "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
              "\n",
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              "\n",
              "  <!-- Vertical lines -->\n",
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              "  <line x1=\"26\" y1=\"0\" x2=\"26\" y2=\"25\" />\n",
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              "  <line x1=\"92\" y1=\"0\" x2=\"92\" y2=\"25\" />\n",
              "  <line x1=\"105\" y1=\"0\" x2=\"105\" y2=\"25\" />\n",
              "  <line x1=\"118\" y1=\"0\" x2=\"118\" y2=\"25\" />\n",
              "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
              "\n",
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              "\n",
              "  <!-- Text -->\n",
              "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3477</text>\n",
              "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">7</text>\n",
              "</svg>\n",
              "        </td>\n",
              "    </tr>\n",
              "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vorticity_correlation</span></div><div class='xr-var-dims'>(model, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 381), meta=np.ndarray&gt;</div><input id='attrs-64af9c2e-ec8a-427c-b1a2-c6c0d7055ca6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-64af9c2e-ec8a-427c-b1a2-c6c0d7055ca6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26bdbad4-cb3e-4423-8d88-0235c8b19eb4' class='xr-var-data-in' type='checkbox'><label for='data-26bdbad4-cb3e-4423-8d88-0235c8b19eb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
              "    <tr>\n",
              "        <td>\n",
              "            <table style=\"border-collapse: collapse;\">\n",
              "                <thead>\n",
              "                    <tr>\n",
              "                        <td> </td>\n",
              "                        <th> Array </th>\n",
              "                        <th> Chunk </th>\n",
              "                    </tr>\n",
              "                </thead>\n",
              "                <tbody>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Bytes </th>\n",
              "                        <td> 190.15 kiB </td>\n",
              "                        <td> 2.98 kiB </td>\n",
              "                    </tr>\n",
              "                    \n",
              "                    <tr>\n",
              "                        <th> Shape </th>\n",
              "                        <td> (7, 3477) </td>\n",
              "                        <td> (1, 381) </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Dask graph </th>\n",
              "                        <td colspan=\"2\"> 70 chunks in 346 graph layers </td>\n",
              "                    </tr>\n",
              "                    <tr>\n",
              "                        <th> Data type </th>\n",
              "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
              "                    </tr>\n",
              "                </tbody>\n",
              "            </table>\n",
              "        </td>\n",
              "        <td>\n",
              "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
              "\n",
              "  <!-- Horizontal lines -->\n",
              "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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              "\n",
              "  <!-- Vertical lines -->\n",
              "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
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              "  <line x1=\"26\" y1=\"0\" x2=\"26\" y2=\"25\" />\n",
              "  <line x1=\"39\" y1=\"0\" x2=\"39\" y2=\"25\" />\n",
              "  <line x1=\"52\" y1=\"0\" x2=\"52\" y2=\"25\" />\n",
              "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"25\" />\n",
              "  <line x1=\"78\" y1=\"0\" x2=\"78\" y2=\"25\" />\n",
              "  <line x1=\"92\" y1=\"0\" x2=\"92\" y2=\"25\" />\n",
              "  <line x1=\"105\" y1=\"0\" x2=\"105\" y2=\"25\" />\n",
              "  <line x1=\"118\" y1=\"0\" x2=\"118\" y2=\"25\" />\n",
              "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
              "\n",
              "  <!-- Colored Rectangle -->\n",
              "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
              "\n",
              "  <!-- Text -->\n",
              "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3477</text>\n",
              "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">7</text>\n",
              "</svg>\n",
              "        </td>\n",
              "    </tr>\n",
              "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-9306495a-1aa8-4b4e-8969-14ba97642e1e' class='xr-section-summary-in' type='checkbox'  ><label for='section-9306495a-1aa8-4b4e-8969-14ba97642e1e' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4a257599-9a71-4376-8ba5-67cd556e38f3' class='xr-index-data-in' type='checkbox'/><label for='index-4a257599-9a71-4376-8ba5-67cd556e38f3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([                0.0, 0.07012483601762931, 0.14024967203525862,\n",
              "       0.21037450805288793, 0.28049934407051724, 0.35062418008814655,\n",
              "       0.42074901610577586,  0.4908738521234052,  0.5609986881410345,\n",
              "        0.6311235241586638,\n",
              "       ...\n",
              "        243.12280647312082,  243.19293130913846,  243.26305614515607,\n",
              "         243.3331809811737,  243.40330581719132,  243.47343065320896,\n",
              "         243.5435554892266,  243.61368032524422,  243.68380516126186,\n",
              "        243.75392999727947],\n",
              "      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;, length=3477))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>k</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f8a3b75b-b552-46a1-8716-84c40b63b03a' class='xr-index-data-in' type='checkbox'/><label for='index-f8a3b75b-b552-46a1-8716-84c40b63b03a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1.0000000101179651, 2.0000000202359303, 3.0000000303538954,\n",
              "       4.0000000404718605,  5.000000050589826,  6.000000060707791,\n",
              "        7.000000070825756,  8.000000080943721,  9.000000091061686,\n",
              "       10.000000101179651, 11.000000111297616, 12.000000121415582,\n",
              "       13.000000131533547, 14.000000141651512, 15.000000151769477,\n",
              "       16.000000161887442, 17.000000172005407, 18.000000182123372,\n",
              "       19.000000192241338, 20.000000202359303, 21.000000212477268,\n",
              "       22.000000222595233, 23.000000232713198, 24.000000242831163,\n",
              "        25.00000025294913, 26.000000263067093,  27.00000027318506,\n",
              "       28.000000283303024,  29.00000029342099, 30.000000303538954],\n",
              "      dtype=&#x27;float64&#x27;, name=&#x27;k&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>model</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-658c663b-9236-475f-870a-8d5b10a342cd' class='xr-index-data-in' type='checkbox'/><label for='index-658c663b-9236-475f-870a-8d5b10a342cd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;baseline_64&#x27;, &#x27;baseline_128&#x27;, &#x27;baseline_256&#x27;, &#x27;baseline_512&#x27;,\n",
              "       &#x27;baseline_1024&#x27;, &#x27;baseline_2048&#x27;, &#x27;learned_interp_64&#x27;],\n",
              "      dtype=&#x27;object&#x27;, name=&#x27;model&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-04bce3f8-9f33-4495-8d7e-944f7831f663' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-04bce3f8-9f33-4495-8d7e-944f7831f663' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
            ],
            "text/plain": [
              "<xarray.Dataset> Size: 17MB\n",
              "Dimensions:                       (model: 7, time: 3477, k: 30)\n",
              "Coordinates:\n",
              "  * time                          (time) float64 28kB 0.0 0.07012 ... 243.8\n",
              "  * k                             (k) float64 240B 1.0 2.0 3.0 ... 29.0 30.0\n",
              "  * model                         (model) <U17 476B 'baseline_64' ... 'learne...\n",
              "Data variables: (12/31)\n",
              "    u_mean                        (model, time) float32 97kB dask.array<chunksize=(1, 381), meta=np.ndarray>\n",
              "    v_mean                        (model, time) float32 97kB dask.array<chunksize=(1, 381), meta=np.ndarray>\n",
              "    kinetic_energy_mean           (model, time) float32 97kB dask.array<chunksize=(1, 381), meta=np.ndarray>\n",
              "    speed_mean                    (model, time) float32 97kB dask.array<chunksize=(1, 381), meta=np.ndarray>\n",
              "    energy_spectrum_mean          (model, k, time) float64 6MB dask.array<chunksize=(1, 30, 381), meta=np.ndarray>\n",
              "    enstrophy_mean                (model, time) float64 195kB dask.array<chunksize=(1, 381), meta=np.ndarray>\n",
              "    ...                            ...\n",
              "    energy_spectrum_within_q=1.0  (model, k, time) bool 730kB dask.array<chunksize=(1, 30, 381), meta=np.ndarray>\n",
              "    enstrophy_within_q=1.0        (model, time) float64 195kB dask.array<chunksize=(1, 381), meta=np.ndarray>\n",
              "    vorticity_within_q=1.0        (model, time) float64 195kB dask.array<chunksize=(1, 381), meta=np.ndarray>\n",
              "    u_correlation                 (model, time) float32 97kB dask.array<chunksize=(1, 381), meta=np.ndarray>\n",
              "    v_correlation                 (model, time) float32 97kB dask.array<chunksize=(1, 381), meta=np.ndarray>\n",
              "    vorticity_correlation         (model, time) float64 195kB dask.array<chunksize=(1, 381), meta=np.ndarray>"
            ]
          },
          "execution_count": 30,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "summary"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 9415,
          "status": "ok",
          "timestamp": 1635551588170,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "BAeYoRKN6S0p",
        "outputId": "c1385683-c042-4707-e822-2f47e3d3d871"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 11.7 s, sys: 8.01 s, total: 19.7 s\n",
            "Wall time: 2.04 s\n"
          ]
        }
      ],
      "source": [
        "%time correlation = summary.vorticity_correlation.sel(time=slice(20)).compute()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "executionInfo": {
          "elapsed": 180133,
          "status": "ok",
          "timestamp": 1635551768289,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "O69M1xI96_ZU",
        "outputId": "4e22e587-0133-4371-b36d-01dafb1d38ce"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 4min 35s, sys: 4min 24s, total: 8min 59s\n",
            "Wall time: 22.5 s\n"
          ]
        }
      ],
      "source": [
        "%time spectrum = summary.energy_spectrum_mean.tail(time=2000).mean('time').compute()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MI7EsVRXcIyI"
      },
      "source": [
        "### Plot correlation over time: Fig 2(b)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 405
        },
        "executionInfo": {
          "elapsed": 548,
          "status": "ok",
          "timestamp": 1635551768828,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "QN1EySqC3a1h",
        "outputId": "f09fb92d-c7f3-4837-b18f-778332daa8f9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(0.0, 15.0)"
            ]
          },
          "execution_count": 33,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 700x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure(figsize=(7, 6))\n",
        "for color, model in zip(palette, summary['model'].data):\n",
        "  style = '-' if 'baseline' in model else '--'\n",
        "  correlation.sel(model=model).plot.line(\n",
        "      color=color, linestyle=style, label=model, linewidth=3);\n",
        "plt.axhline(y=0.95, xmin=0, xmax=20, color='gray')\n",
        "plt.legend();\n",
        "plt.title('')\n",
        "plt.xlim(0, 15)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oA6j1EcecMTZ"
      },
      "source": [
        "### Plot spectrum: Fig 2(c)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 409
        },
        "executionInfo": {
          "elapsed": 792,
          "status": "ok",
          "timestamp": 1635551769614,
          "user": {
            "displayName": "Stephan Hoyer",
            "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gh3-wMvU44jUaVFR9jlCY_2pss4FrdtAZbLsUaV=s64",
            "userId": "01386112912994523038"
          },
          "user_tz": 420
        },
        "id": "CNN1GuKc9S6L",
        "outputId": "e8404efd-06e3-4d44-8e0e-ba3c6e338895"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(1000000000.0, 5696212345.813846)"
            ]
          },
          "execution_count": 34,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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xMRGTyUR2djaJiYmkpqba9pk+fTqff/45X3zxBXq9nry8PPLy8qiurgaga9eudOrUiUcffZQ9e/Zw8uRJ5s6dy4YNGxotbCyEEEIIIW48EqpuEBMnTqS6upp+/foxffp0nnzySaZOnYqPjw+fffYZK1euJDo6mtmzZzNnzpxGx2q1Wl544QV69OjBrbfeikqlss03cnZ2ZuvWrYSGhjJhwgSioqJ45JFHMBqN7dardLHnyMnJISYmhpiYGHJzc5kzZw4xMTH85S9/se2zaNEiysrKGDJkCAEBAbavFStWAPXDE9esWYOPjw933HEHPXr04L///S9LlixhzJgx7fI6hRBCCCHEtUlhtVqtV7oRV5Py8nLc3NwoKytr8oHdaDSSlpZGeHg4jo6OV6iFQrSevHeFEEIIIVrvfNngXNJTJYQQQgghhBAXQUKVuOadLbPe3Ne2bduudPOEEEIIIcR1Tqr/iWteYmJii48FBQVdvoYIIYQQQogbkoQqcc3r1KnTlW6CEEIIIYS4gcnwPyGEEEIIIYS4CBKqhBBCCCGEEOIiSKgSQgghhBBCiIsgoUoIIYQQQgghLoKEKiGEEEIIIYS4CBKqbgBDhgzhqaeeumLnnzx5MuPHj79q2iOEEEIIIUR7klAlLrtVq1Yxa9asy3a+f//738TFxeHh4YGHhwcjRoxgz549jfaZPHkyCoWi0deoUaOaPNePP/5I//79cXJywsPDo1FYFEIIIYQQNyZZp6qNLFYr5aa6K9oGV60apUJxRdvQFp6enpf1fAkJCdx///0MGjQIR0dH3nnnHUaOHMmRI0caLQ48atQoFi9ebLvv4ODQ6Hm+/vprpkyZwttvv82wYcOoq6vj8OHDl+11CCGEEEKIq5OEqjYqN9Vx56Y9F97xEvpmeD/cHTR27VtXV8eMGTNYunQpGo2GadOm8cYbb6BQKFi6dCkLFiwgJSUFFxcXhg0bxvz58/H19QWgpKSEGTNmsH79egwGA8HBwbz44os89NBDAGRlZfH000+zfv16lEolcXFxLFiwgLCwsGbbMmTIEHr16sX8+fMBCAsLY+rUqaSmprJy5Uo8PDx4+eWXmTp1qu2Y1p7jXMuWLWt0/5NPPuHrr79m06ZNTJw40bbdwcEBf3//Fn9+Tz75JO+99x6PPPKIbXt0dPQFzy+EEEIIIa5vMvzvBrFkyRLUajV79uxhwYIFvP/++3zyyScA1NbWMmvWLA4dOsTq1atJT09n8uTJtmNfeeUVkpOTWbt2LUePHmXRokV4e3vbjo2Pj0ev17Nt2za2b9+OTqdj1KhRmEwmu9s3d+5c+vTpw8GDB3n88ceZNm0aKSkp7XqOs6qqqqitrW3SY5aQkICvry+RkZFMmzaNoqIi22MHDhwgOzsbpVJJTEwMAQEBjB49WnqqhBBCCCGE9FTdKEJCQpg3bx4KhYLIyEiSkpKYN28eU6ZM4eGHH7btFxERwQcffEDfvn0xGAzodDoyMzOJiYmhT58+AI16h1asWIHFYuGTTz5B0TAUcfHixbi7u5OQkMDIkSPtat+YMWN4/PHHAXjuueeYN28eW7ZsITIyst3OcdZzzz1HYGAgI0aMsG0bNWoUEyZMIDw8nJMnT/Liiy8yevRodu7ciUql4tSpUwC8/vrrvP/++4SFhTF37lyGDBnC8ePHL/uQRiGEEEIIcfWQUHWDGDBggC2QAAwcOJC5c+diNptJTEzk9ddf59ChQ5SUlGCxWADIzMwkOjqaadOmcdddd3HgwAFGjhzJ+PHjGTRoEACHDh0iNTUVvV7f6HxGo5GTJ0/a3b4ePXrYvlcoFPj7+1NQUNCu5wCYPXs2y5cvJyEhAUdHR9v2++67z/b9TTfdRI8ePejYsSMJCQkMHz7c9jN56aWXuOuuu4D6YBccHMzKlSt59NFHW9UOIYQQQghx/ZBQ1UauWjXfDO93xdtwsYxGI/Hx8cTHx7Ns2TJ8fHzIzMwkPj7eNrRu9OjRZGRksGbNGjZs2MDw4cOZPn06c+bMwWAwEBsb22TeEoCPj4/d7dBoGs8NUygUtiDTXueYM2cOs2fPZuPGjY1CXHMiIiLw9vYmNTWV4cOHExAQADSeQ+Xg4EBERASZmZl2t0EIIYQQQlx/JFS1kVKhsLtIxNVg9+7dje7v2rWLzp07c+zYMYqKipg9ezYhISEA7Nu3r8nxPj4+TJo0iUmTJhEXF8czzzzDnDlz6N27NytWrMDX1xdXV9dL0vb2OMe7777LW2+9xU8//WQbxng+p0+fpqioyBamYmNjcXBwICUlhVtuuQWon+uVnp5Ohw4d2tQmIYQQQghxfZBCFTeIzMxMZs6cSUpKCv/73/9YuHAhTz75JKGhoWi1WhYuXMipU6f47rvvmqwh9eqrr/Ltt9+SmprKkSNH+OGHH4iKigLggQcewNvbm3HjxrFt2zbS0tJISEjgiSee4PTp0+3S9os9xzvvvMMrr7zCp59+SlhYGHl5eeTl5WEwGID6nrBnnnmGXbt2kZ6ezqZNmxg3bhydOnUiPj4eAFdXVx577DFee+011q9fT0pKCtOmTQPgnnvuaZfXKYQQQgghrk0Sqm4QEydOpLq6mn79+jF9+nSefPJJpk6dio+PD5999hkrV64kOjqa2bNnM2fOnEbHarVaXnjhBXr06MGtt96KSqVi+fLlADg7O7N161ZCQ0OZMGECUVFRPPLIIxiNxnbrubrYcyxatAiTycTdd99NQECA7evs61SpVPz666/84Q9/oEuXLjzyyCPExsaybdu2RmtVvffee9x33338+c9/pm/fvmRkZLB582Y8PDza5XUKIYQQQohrk8JqtVqvdCOuJuXl5bi5uVFWVtbkA7vRaCQtLY3w8PBGRQ6EuNrJe1cIIYQQovXOlw3OJT1VQgghhBBCCHERJFSJa55Op2vxa9u2bVe6eUIIIYQQ4jon1f/ENS8xMbHFx4KCgi5fQ4QQQgghxA1JQpW45nXq1OlKN0EIIYQQQtzAZPifEEIIIYQQQlwECVVCCCGEEEIIcREkVAkhhBBCCCHERZBQJYQQQgghhBAXQUKVEEIIIYQQQlwECVU3gCFDhvDUU09dsfNPnjyZ8ePHXzXtEUIIIYQQoj1JqBKX3apVq5g1a9ZlO99nn32GQqFo9OXo6NikTSNHjsTLywuFQtFk7avi4mL++te/EhkZiZOTE6GhoTzxxBOUlZVdttchhBBCCCGuTrJOVRtZrFZKqmuvaBs8nDQoFYor2oa28PT0vOzndHV1JSUlxXZf8bufW2VlJbfccgt//OMfmTJlSpPjc3JyyMnJYc6cOURHR5ORkcFjjz1GTk4OX3311SVvvxBCCCGEuHpJqGqjkupaYv6984q24eCUgXg5a+3at66ujhkzZrB06VI0Gg3Tpk3jjTfeQKFQsHTpUhYsWEBKSgouLi4MGzaM+fPn4+vrC0BJSQkzZsxg/fr1GAwGgoODefHFF3nooYcAyMrK4umnn2b9+vUolUri4uJYsGABYWFhzbZlyJAh9OrVi/nz5wMQFhbG1KlTSU1NZeXKlXh4ePDyyy8zdepU2zGtPcfvKRQK/P39W3z8z3/+MwDp6enNPt69e3e+/vpr2/2OHTvy1ltv8eCDD1JXV4daLb9KQgghhBA3Khn+d4NYsmQJarWaPXv2sGDBAt5//30++eQTAGpra5k1axaHDh1i9erVpKenM3nyZNuxr7zyCsnJyaxdu5ajR4+yaNEivL29bcfGx8ej1+vZtm0b27dvR6fTMWrUKEwmk93tmzt3Ln369OHgwYM8/vjjTJs2zdaz1B7nMBgMdOjQgZCQEMaNG8eRI0fsbltLysrKcHV1lUAlhBBCCHGDk0+DN4iQkBDmzZuHQqEgMjKSpKQk5s2bx5QpU3j44Ydt+0VERPDBBx/Qt29fDAYDOp2OzMxMYmJi6NOnD0Cj3qEVK1ZgsVj45JNPbEPqFi9ejLu7OwkJCYwcOdKu9o0ZM4bHH38cgOeee4558+axZcsWIiMjL/ockZGRfPrpp/To0YOysjLmzJnDoEGDOHLkCMHBwXb/DM9VWFjIrFmzGvWmCSGEEEKIG5P0VN0gBgwY0Gge0cCBAzlx4gRms5n9+/dzxx13EBoail6vZ/DgwQBkZmYCMG3aNJYvX06vXr149tln2bFjh+15Dh06RGpqKnq9Hp1Oh06nw9PTE6PRyMmTJ+1uX48ePWzfnx2qV1BQ0C7nGDhwIBMnTqRXr14MHjyYVatW4ePjw8cff2x3+85VXl7O2LFjiY6O5vXXX2/TcwghhBBCiOuH9FS1kYeThoNTBl7xNlwso9FIfHw88fHxLFu2DB8fHzIzM4mPj7cNrRs9ejQZGRmsWbOGDRs2MHz4cKZPn86cOXMwGAzExsaybNmyJs/t4+Njdzs0msavRaFQYLFYANrtHOeeKyYmhtTU1FYfW1FRwahRo9Dr9XzzzTdN2i2EEEIIIW48EqraSKlQ2F0k4mqwe/fuRvd37dpF586dOXbsGEVFRcyePZuQkBAA9u3b1+R4Hx8fJk2axKRJk4iLi+OZZ55hzpw59O7dmxUrVuDr64urq+slaXt7n8NsNpOUlMSYMWNadVx5eTnx8fE4ODjw3XffNSnLLoQQQgghbkwy/O8GkZmZycyZM0lJSeF///sfCxcu5MknnyQ0NBStVsvChQs5deoU3333XZM1pF599VW+/fZbUlNTOXLkCD/88ANRUVEAPPDAA3h7ezNu3Di2bdtGWloaCQkJPPHEE5w+fbpd2n6x53jjjTdYv349p06d4sCBAzz44INkZGTwl7/8xbZPcXExiYmJJCcnA5CSkkJiYiJ5eXlAfaAaOXIklZWV/Oc//6G8vJy8vDzy8vIwm83t8jqFEEIIIcS1SULVDWLixIlUV1fTr18/pk+fzpNPPsnUqVPx8fHhs88+Y+XKlURHRzN79mzmzJnT6FitVssLL7xAjx49uPXWW1GpVCxfvhwAZ2dntm7dSmhoKBMmTCAqKopHHnkEo9HYbj1XF3uOkpISpkyZQlRUFGPGjKG8vJwdO3YQHR1t2+e7774jJiaGsWPHAnDfffcRExPDRx99BMCBAwfYvXs3SUlJdOrUiYCAANtXVlZWu7xOIYQQQghxbVJYrVbrlW7E1aS8vBw3NzdbuexzGY1G0tLSCA8Pl6Ff4poi710hhBBCiNY7XzY413XdUzVnzhy6detG9+7d+fzzz690c4QQQgghhBDXoeu2UEVSUhJffPEF+/fvx2q1MnToUG6//Xbc3d2vdNNEO9PpdC0+tnbtWuLi4i5ja4QQQgghxI3mug1VR48eZeDAgbahTj179mTdunXcd999V7hlor0lJia2+FhQUNDla4gQQgghhLghXdTwv9mzZ6NQKHjqqafaqTn1tm7dyh133EFgYCAKhYLVq1c3u9+HH35IWFgYjo6O9O/fnz179tge6969OwkJCZSWllJSUkJCQgLZ2dnt2k5xdejUqVOLX05OTle6eUIIIYQQ4jrX5lC1d+9ePv74Y3r06HHe/bZv305tbW2T7cnJyeTn5zd7TGVlJT179uTDDz9s8XlXrFjBzJkzee211zhw4AA9e/YkPj6egoICAKKjo3niiScYNmwYEyZMYMCAAahUqla8QiGEEEIIIYS4sDaFKoPBwAMPPMC///1vPDw8WtzPYrEwffp0/vSnPzVayyclJYVhw4axZMmSZo8bPXo0b775JnfeeWeLz/3+++8zZcoUHnroIaKjo/noo49wdnbm008/te3z6KOPcuDAAbZs2YJGo6Fz584tPt+HH35IdHQ0ffv2Pd9LF0IIIYQQQohG2hSqpk+fztixYxkxYsT5n1ypZM2aNRw8eJCJEydisVg4efIkw4YNY/z48Tz77LNtarTJZGL//v2Nzq9UKhkxYgQ7d+60bTvba5WSksKePXuIj48/72tKTk5m7969bWqTEEIIIYQQ4sbU6kIVy5cv58CBA3aHj8DAQDZv3kxcXBx/+tOf2LlzJyNGjGDRokWtbuxZhYWFmM1m/Pz8Gm338/Pj2LFjtvvjxo2jrKwMFxcXFi9ejFp93dblEEIIIYQQQlwhrUoZWVlZPPnkk2zYsKFVC4iGhoaydOlSBg8eTEREBP/5z39QKBStbmxrndtrJYQQQgghhBCXQquG/+3fv5+CggJ69+6NWq1GrVbz888/88EHH6BWqxvNmzpXfn4+U6dO5Y477qCqqoq//e1vF9Vob29vVCpVk0IX+fn5+Pv7X9RzX4+GDBnS7hUaW2Py5MmMHz/+qmmPEEIIIYQQ7alVoWr48OEkJSWRmJho++rTpw8PPPAAiYmJzVbXKywsZPjw4URFRbFq1So2bdrEihUr+Pvf/97mRmu1WmJjY9m0aZNtm8ViYdOmTQwcOLDNzysuj1WrVjFr1qzLdr4jR45w1113ERYWhkKhYP78+c3ud74S/cXFxfz1r38lMjISJycnQkNDeeKJJygrK2v2uYqKiggODkahUFBaWnoJXpUQQgghhLhatGr4n16vp3v37o22ubi44OXl1WQ71Aed0aNH06FDB1asWIFarSY6OpoNGzYwbNgwgoKCmu21MhgMpKam2u6npaWRmJiIp6cnoaGhAMycOZNJkybRp08f+vXrx/z586msrOShhx5qzUtqM4vFSomh5rKcqyUeOgeUyks/jLK9eXp6XtbzVVVVERERwT333NNiL+nZEv0fffQR/fv3Z/78+cTHx5OSkoKvry85OTnk5OQwZ84coqOjycjI4LHHHiMnJ4evvvqqyfM98sgj9OjRQ9ZGE0IIIYS4AVzSyg1KpZK3336buLg4tFqtbXvPnj3ZuHEjPj4+zR63b98+hg4dars/c+ZMACZNmsRnn30GwL333suZM2d49dVXycvLo1evXqxbt65J8YpLpcRQQ78Z316Wc7Vkz7/G4eVq39y2uro6ZsyYwdKlS9FoNEybNo033ngDhULB0qVLWbBgASkpKbi4uDBs2DDmz5+Pr68vACUlJcyYMYP169djMBgIDg7mxRdftAXYrKwsnn76adavX49SqSQuLo4FCxYQFhbWbFuGDBlCr169bD1GYWFhTJ06ldTUVFauXImHhwcvv/wyU6dOtR3T2nOcq2/fvrZS+c8//3yz+5xboh/go48+4scff+TTTz/l+eefp3v37nz99de2/Tt27Mhbb73Fgw8+SF1dXaMiKIsWLaK0tJRXX32VtWvXXrB9QgghhBDi2tbmxX/PSkhIaHE4FcBtt93WbFGLmJgYgoODmz1myJAhWK3WJl9nA9VZM2bMICMjg5qaGnbv3k3//v0v5qVc15YsWYJarWbPnj0sWLCA999/n08++QSA2tpaZs2axaFDh1i9ejXp6elMnjzZduwrr7xCcnIya9eu5ejRoyxatAhvb2/bsfHx8ej1erZt28b27dvR6XSMGjUKk8lkd/vmzp1Lnz59OHjwII8//jjTpk0jJSWlXc/REntL9P9eWVkZrq6ujQJVcnIyb7zxBv/9739RKi/610sIIYQQQlwDpMb4DSIkJIR58+ahUCiIjIwkKSmJefPmMWXKFB5++GHbfhEREXzwwQf07dsXg8GATqcjMzOTmJgY+vTpA9Cod2jFihVYLBY++eQTW0XHxYsX4+7uTkJCAiNHjrSrfWPGjOHxxx8H4LnnnmPevHls2bKFyMjIdjtHS+wt0f/7Y2bNmtWoN62mpob777+f9957j9DQUE6dOnVR7RJCCCGEENcGuZR+gxgwYECjMvYDBw7kxIkTmM1m9u/fzx133EFoaCh6vZ7BgwcDkJmZCcC0adNYvnw5vXr14tlnn2XHjh225zl06BCpqano9Xp0Oh06nQ5PT0+MRiMnT560u309evSwfa9QKPD397ct3txe52gv5eXljB07lujoaF5//XXb9hdeeIGoqCgefPDBy94mIYQQQghx5UhPVRt56BzY869xV7wNF8toNBIfH098fDzLli3Dx8eHzMxM4uPjbUPrRo8eTUZGBmvWrGHDhg0MHz6c6dOnM2fOHAwGA7GxsSxbtqzJc7c0Z645Go2m0X2FQoHFYgFot3O0pDUl+isqKhg1ahR6vZ5vvvmmUbs3b95MUlKSrXCF1Wq1Pf9LL73EP/7xj4tuqxBCCNEWppI8Cnd/i1LrhMrBCYXGEZXWCaWDE0qNI0qtE0pt/a2q4XuFxuGyrCsqxPVAQlUbKZUKu4tEXA12797d6P6uXbvo3Lkzx44do6ioiNmzZxMSEgLUFwr5PR8fHyZNmsSkSZOIi4vjmWeeYc6cOfTu3ZsVK1bg6+uLq6vrJWn7pT7HuSX6z66ndbZE/4wZM2z7lZeXEx8fj4ODA999912TuYJff/011dXVtvt79+7l4YcfZtu2bXTs2LHd2y2EEOLGZa6ppjrnOFWnj1GVfYyq0ylY62rp9vzKZvevOn2ME4umte4kCkV94HJwpsdra9F37tO0HdUG8rd+gUbngdrFA7XunC9nNxQyv1jcICRU3SAyMzOZOXMmjz76KAcOHGDhwoXMnTuX0NBQtFotCxcu5LHHHuPw4cNN1pB69dVXiY2NpVu3btTU1PDDDz8QFRUFwAMPPMB7773HuHHjeOONNwgODiYjI4NVq1bx7LPPtliMpDUu9hwmk4nk5GTb99nZ2SQmJqLT6ejUqRNw4RL95eXljBw5kqqqKj7//HPKy8spLy8H6gOnSqVqEpwKCwsBiIqKwt3d/aJ/DkIIIW4sVquV2vLC+uB0+ihVp49RnZ1C1eljGAvSoWFEhG1/pZoFi34hO7+a3DwD2bnlGI116HVaujkcpdXja6xWLKZqLKZqlA5Oze5SU3SaE//3WPPHKxSond1Q6zzQegTg4BWMg09w/a13CA5ewTiHRKN21re2ZUJcdSRU3SAmTpxIdXU1/fr1Q6VS8eSTTzJ16lQUCgWfffYZL774Ih988AG9e/dmzpw5/OEPf7Adq9VqeeGFF0hPT8fJyYm4uDiWL18OgLOzM1u3buW5555jwoQJVFRUEBQUxPDhw9utV+liz5GTk0NMTIzt/pw5c5gzZw6DBw8mISEBuHCJ/gMHDth6+84GsbPS0tLsKu0uhBBCXEjFqYNkf/8B1TknqMo+Rl1Fsd3HKix1fPnZTxSYfRttP1NUhZtjAXi1vV33/3UD1aoDKJUK1ColKpUCtVpJoDWVe1o6yGqlrrKUuspSjPlpze7S/eXv8eo7tumh5joKd3+Lg1cwjn7haN19mzlaiKuHwmr93WWOG1x5eTlubm62ctnnMhqNpKWlER4e3myZeCGuVvLeFUKIy89Sa6KmOJuawixqzmRSU5iF8UwmNYWniX72S0xWNbl5BnLzK8grqCQ3vwLT8a3Epjzb5nMuLJrCIWP3Jtu7ao8z3nUNGkWt7UurqEWjqEOjMKFRmM/7vNOy36MWbZPt3R2Secr74za395+lL1Ln2QVfHxd8vV3w83HB18cFP8cK9Et/W7PUpcNNeMaOwjN2DK5dB6FUa87zrEK0n/Nlg3NJT5UQQgghRBvVlhdiSE+iKvMw1flp1BSepuZMJsbCLGpL85oM0Tvr9rFzSS11a7LdV1VGrH8zB7SgqM6D3Do/8up8yavzI6s2sNn9jpm6MLuwS4vPo8DSELBq0VAfuNQNwctBYWo2UAHUWjWcMnXAWVGNs7IKZ2UVaoXF7vbnVemorCwjI6us0fYIbRovnlOLqjIjicqMJLJWvYfK2RWPXiPxih2NR+9ROHgG2H0+IS4VCVXimqfT6Vp8bO3atcTFxV3G1gghhLgRFCdu4Oj7f6aurKBNx6ur8oGmoarE7N5kW61VTX6dD7m1fuTV+ZHbEKDy6nwxWesrAbvqHQgM0tPLT09QgJ4A//pbvU6LodJEhcFEeUUNFQYTFRU1VBhqKK8wUVFZ03C//nFDpamlHNisFFNn3j4z85wtVhwUJpyVVbgoqnBWVqNTVuKuKsNDVYqnqgQPVRkeqhKcldVUWp2bfV5PVWmL5zRXlVO44ysKd9RX29VFxOAZOxrP2NG4dumPQiUfb8XlJ+86cc1LTExs8bGgoKDL1xAhhBDXPKu5jurcVCozDlOZkUTQ+KcpN6o5caqY1FPFpKbV31amH+Ipx7YFKgBPdQmYmm6vRcvaiuFUWHS2EFVk8cTHR09QiCsB/jp6BegJ9NcTGKAnyN+VAP/68NQeLBYrlVXnhrAaqqpqqTNbsVgs1NVZMZst9V8WK+Y6C3Vm6+/un/O42UJNjZmikmryz1SSdKaSgsJKSguNgBVovmS7Aitn6rzwUJWivsDQRMOpgxhOHSRz5duodR54xMTTacoCtG4Xv+yKEPaSUCWueb8vHCGEEEJciNVqxVScYwtPhowkyk7+Sk32UTD/lnaeWVxDYknTC3Rq3DAHKlHZMdTNaNFSYvagyOxBidmdIrMHWbW/Paer3oEAPx3+fjoC/PT4+w4gwF9HUENw8vPVodWo2ueFX4BSqUCvc0CvcyDQ/9JV5aupqaOgsJKChpCVf6bhe9t9D946M4CqymrCtZnc5JDMTY7JdNCePu/z1hlKyNv5A4rb59LV1SrrbInLRkKVEEIIIW4ItRXFFO9fS/7Obyk5tAmqSy54jGtNBtA0VNWhoaDOhwBNPrVWNTm1/uTW+VFs9qDY7F5/W+eB0dEXdx9fAvz1DcFJT6Svjrv8dAT46/D31eHi3D69TNcSBwc1IUFuhAQ1HQJ5LkOliT0HstmyLZ3/90saxtwcujse5SbHo0Q7HMNZaWxyzMGKTjz64FcE+usZGhfG0FvCGNAnGAcHNcUHfqKmMAuPmHgcfUIu1csTNyAJVUIIIYS4btVVlZO34T/k7ViNIWUHCuv5h5L9XpAmp8XHFpfej0npgi6oCx27+xAW6k6svx5/X50tQLXXsLyW1JktFJYZKSitJq+kmoKShtvSavJLqjHVWnDTaXF30eLmosVdd/bWof72nG0ujuqrrmdH56JlWFw4w+LCsVqHkJxSyJZf0tiyLZ1/H8khQptGD8f6XqxgTS4AScb6tTRz8ipYtjKJZSuTcHJUc3P/EO6seR+HrAQAnEOi8YgZiWfvUbhFx6FqYS0uIewhoUoIIYQQ16WMrFI2bfyVsNXPosLcwuyd5pWZ9WTXBpBbV1+Kz8FBRccwTzpFeNIp3KPh1pOQIDfUamW7t91qtVJeVUteSRUFJUbyS6psoSm/pJr8htBUWFaDpZ1Wx9GolM0GsLNfrs6ahlstri6/fe/mosFRe+k/UioUCrp19aFbVx9m/KUfZworSdiewZZtaby7OwsHUwHdHY7yq7Fbk2OrjXVs+fkE4wN2QMM/V1VWMlVZyWR/Nx+l1hG37kPwjBmJR0w8zsFdr7qAKa5uEqqEEEIIcU0z11Rhrq5A4+bL4aMFbEg4xcaEU5w4Vb9w7lNenenueKzZY40WLdl1AWTXBpJdG0ChMgSHoGiCOobRMdyT+zt68kq4J0EBelSqiwtPVquViqpaCsuNFJYZKSyvobDMSFG5sWFbDUVl9d+fKTNiNLWuV+1i1Tb0ehWWNR1SdyFajbI+YDlrcD0nbJ0NXqG+LnQMdKVToCv6dhru6OPtwj3jorlnXDQ1NXW2YYKntqVRkVvRZP9O2jQclc1UBwEsJiMlB9ZRcmAdAA4+oXgPnIDvrfej79RHApa4IFn893dk8V9xPZL3rhDiemMqzado7w+c2f0dJQc3kOs5jA9z7iIv39Bk36Eu23jAvb78tsmqIdkYSZLpJszBA/Dv3JVOHb3oFF7fCxXgp0epbN0HaLPFQmZ+JTnFVRTZQlJNQ3Ay2m6Ly2sw1dm/htP1yt/DqT5gBdWHrE6BrnQKcsNT79Auz2+1WjlxspjN2+qHCR5MysVqhQ6aTOJ1m+nmmIKLssru53MK6IRP3L0E3PYXHH07tEsbxbVDFv8VNkOGDKFXr17Mnz//ipx/8uTJlJaWsnr16quiPUIIIa49VquVqqyjFO35joJd32E4sRsFv10XdsndSn7+bdjGdp0j0did0MrTHLP2wif2NoYMjWbyzR1wc239RabqmjqOny4jObOU5IwSjmaUciyrlOrL3Kv0e2qVAl93J/zcnfDzdMLX3Ql/DycctSrKq2opNdRQWmmizGCqv600UWqovzVbLu/19byGeV/bj+Q32u6pd2gIWI3Dlq+7Y6t6ihQKBV06edGlkxePPdSHopJqtm5PZ8sv6Szb2ZGqkhrCNJl0dzxKN4djRGgzUCpa/hlU56aS+eVbuEbdLKFKtEhClbjsVq1ahUajuWzn+/e//81///tfDh8+DEBsbCxvv/02/fr1s+1jtVp57bXX+Pe//01paSk333wzixYtonPnzk2er6amhv79+3Po0CEOHjxIr169bI/99NNPvPbaaxw5cgRHR0duvfVW5s6dS1hY2KV+mUIIcd2xms2UHf2Foj3fkb/zW2oLTtke+/1HbFeVgXBtBqdM4Y22e3k6MWJwN24ZPJFn+tZXgLNXcUUNRzNKfgtQmaWczKlotzlM9vLUO+Dv4YSvhxN+Hg3BqeF734YQ5alzaHUPG9T//2cw1tWHLkPjsFUfwhrCWGUtFVX128sqaymvMlFprGvX11lcUcOelDPsSTnTaLu7i5Zbe/gzPCaIwT0D0Du17jOEl4cTd94exZ23R2GqNbPvYA6bt6WxeWsPvs8ux0VRSVeH4/Uhy/EYnqqyJs9RbtZx7z9yGTH0F4YPDqd3j4CLHg4qri8SqtrIYrFS0oYxx+3Jw82xTX9ArzRPT8/Ler6EhATuv/9+Bg0ahKOjI++88w4jR47kyJEjtsWB3333XT744AOWLFlCeHg4r7zyCvHx8SQnJzcZLvfss88SGBjIoUOHGm1PS0tj3LhxzJw5k2XLllFWVsbf/vY3JkyYwIEDBy7b6xVCiGuZxWSk5NdNFO5cRcGu77AYiuw7zqogRJ3NKVM4YaHu3DYkghGDI+jZ3e+CH36tVitZZyo5mlHKkYbwlJxZQl5xdXu8pGbpnDR4uzrg5eqIt5sj3q4O9bdujrZt/h5O+Lg7olVfujWqFAoFeicNeicNIa1cK7fObKG8qpaySlND4Kr/vrzKRHllLWUNIayovIZTueVk5Bva1CtWWmniu52ZfLczE41KyYAoX0b0DmRYTBCBXs6tei6tRsWgfiEM6hfCSzPjOJVRwuat6Wz5pTOfH+qNudRCsDqHWKdE+jvvx1dd//7bV92LjDID//n8IP/5/CCeHk4MvSWMEYMj6GreSfHWpfjeeh/eA+5E7XL+MvHi+iRzqn7H3jlVldVWBtz2yRVqZb1dG/6Cl8eFy38OGTKE7t27A7B06VI0Gg3Tpk3jjTfeQKFQsHTpUhYsWEBKSgouLi4MGzaM+fPn4+vrC0BJSQkzZsxg/fr1GAwGgoODefHFF3nooYcAyMrK4umnn2b9+vUolUri4uJYsGCBrXfmQsP/wsLCmDp1KqmpqaxcuRIPDw9efvllpk6dansNFzpHa5jNZjw8PPjXv/7FxIkTsVqtBAYG8vTTT/P3v/8dgLKyMvz8/Pjss8+47777bMeuXbuWmTNn8vXXX9OtW7dGPVVfffUV999/PzU1NSiV9f+Bf//994wbN46amprL2jv3ezKnSghxLSg/sZfEl4ZjrWk6L6o5RosDh2uiSKzujiVsMHHDejJiSAQdwzzOO1wst7iK7UfybcP3kjNLMVTXXnT73Vy0+Lg54nVOSPJyPScwuZ4NTQ6XpVre1cZUZyY9z0BqTjknc8o5kV1Gak45abkVbZ5r1i3Mg9t6BzE8JpCoUPeLKihRWmZk684MNm9NY+uODCoMNYRrMunnvJ89VbGk1TY/9O8pn/9Hd+0RABQaR3xuvpuA2x7BrdutUuDiOiBzqkQjS5Ys4ZFHHmHPnj3s27ePqVOnEhoaypQpU6itrWXWrFlERkZSUFDAzJkzmTx5MmvWrAHglVdeITk5mbVr1+Lt7U1qairV1fVX72pra4mPj2fgwIFs27YNtVrNm2++yahRo/j111/Rau2r8DN37lxmzZrFiy++yFdffcW0adMYPHgwkZGR7XaOs6qqqqitrbX1mKWlpZGXl8eIESNs+7i5udG/f3927txpC1X5+flMmTKF1atX4+zc9MpYbGwsSqWSxYsXM3nyZAwGA0uXLmXEiBFXNFAJIcTVLi2jhLUbU9mw8QjTqk04nKdjqbjOnURjdw7X9sCjxxCGDYnkwcHh+PnoWjzGarWSklXGhgPZbDyQzeH0Cy/6ez4KBYT764nu4EF0qDtRoe5Ed/DA200uWp2PVq2iS7AbXYIb9+TUmS1knakkNbshbOWU2b6/0Fy1I+klHEkvYf6qwwR5OzM8JogRvYPoF+mDppWl7t3dHPnDqEj+MCoSU62ZPfuz2fTzKTZu7UZeWfNBX6c00FVz1HbfWmukIOFzChI+xzGgMwG3PYz/sEloPfxb1RZx7ZFQdYMICQlh3rx5KBQKIiMjSUpKYt68eUyZMoWHH37Ytl9ERAQffPABffv2xWAwoNPpyMzMJCYmhj59+gA06h1asWIFFouFTz75xHY1ZvHixbi7u5OQkMDIkSPtat+YMWN4/PHHAXjuueeYN28eW7ZsITIyst3OcdZzzz1HYGCgLUTl5eUB4Ofn12g/Pz8/22NWq5XJkyfz2GOP0adPH9LT05s8b3h4OOvXr+ePf/wjjz76KGazmYEDB9rCqRBC3OiMZ7Io3PUNuvCeFLrcxLpNqazbmEpK6m9D/A57diXW6ddGx2Wagkg03sQxRQyd+93CiKEd+fvNHdDrWq4WV2e2sO94IRsbglTWmco2tdlBoyIyxI3oDu5Eh3oQFepO11B3nFsxN0ucn1qlJNxfT7i/nttig2zbLRYrpwsr+eVwHhsOZLMrueC8PVrZhVX8d8MJ/rvhBHpnDUN6BDCidxBDegaga+U8LK1GxS0DQrllQCivPjuYI8fOsPHnU2z6+RTHTvz2fu3teAi1ovk2GXNPkPbfF0j7/GW8+t5BwMhH8IyJR6GS9871SP5VbxADBgxo1AU9cOBA5s6di9lsJjExkddff51Dhw5RUlKCxVL/xyEzM5Po6GimTZvGXXfdxYEDBxg5ciTjx49n0KBBABw6dIjU1FT0en2j8xmNRk6ePGl3+3r06GH7XqFQ4O/vT0FBQbueA2D27NksX76chISEVg2DW7hwIRUVFbzwwgst7pOXl8eUKVOYNGkS999/PxUVFbz66qvcfffdbNiwQYYACCFuSFWnj1G46xvO7PwGQ+o+AI4oBzIv675m9z9Q3ZMYxyRSTeEcNPbgpKYvfYf0Z9zQjrzdJxgHbcvziyqNtWxLqv8AnpCYS2ll82sStcTdRVvf+9TBveHLg3B/PWopSHBFKJUKQn11/GlYJ/40rBOG6vp/340HstlyKJey8/z7VlTV8v2uTL7flYlWoySuuz/xfYIZHhOI+3nCeHMUCgXdo3zpHuXLU48NICu7jI0/p7Hp51PsSexLdbET/Zz2c5PjUdSKZnrWLGaKdq+maPdqNB6BBNz2EP4jHsbJL7zpvuKaJaGqjTzcHNm14S9XvA0Xy2g0Eh8fT3x8PMuWLcPHx4fMzEzi4+Mxmer/WI0ePZqMjAzWrFnDhg0bGD58ONOnT2fOnDkYDAZiY2NZtmxZk+f28bF/xuvvh8cpFApbuGuvc8yZM4fZs2ezcePGRiHO37++Sz4/P5+AgADb9vz8fNt8qc2bN7Nz504cHBr/Ie7Tpw8PPPAAS5Ys4cMPP8TNzY13333X9vjnn39OSEgIu3fvZsCAAXa3VQghrlVWqxXDyQMU7lxF4a7VVJ0+2mSfiLoDqLmbumY+hhw03sTbNe8xaGhv/jy8I31jglCfZxjXmdJqNh7MYeOBbHYk52OqtW9ujquzhv5RvnSzhSgP/D2c5ALYVUznpGF0vxBG9wuhts7CvuNn2NTwb3++nkhTrYVNB3PYdDAHtUrBgChf4vsEMzI2uE1DNkOC3HjoT7146E+9KCmtJuGXdDb+nMaKnYeJUe8iznkngZr8Zo+tLckh88u3yPzyLdx7DKfr3/6Lg2dAs/uKa4uEqjZSKhV2FYm4WuzevbvR/V27dtG5c2eOHTtGUVERs2fPJiQkBIB9+/Y1Od7Hx4dJkyYxadIk4uLieOaZZ5gzZw69e/dmxYoV+Pr6nnfy3sVoj3O8++67vPXWW/z000+2YYxnhYeH4+/vz6ZNm2whqry8nN27dzNt2jQAPvjgA958803bMTk5OcTHx7NixQr69+8P1M/VOlug4iyVqv6K6tmAKIQQ16Ozpc8Ld31D4a7V1JzJPO/+TsoaohxSSKrpZtvm4+VM/LCOjBrRmT69Wi5XbbVaOZlTYRvWd/CkfdUBAYK8nRnRu37OTd8urZ9zI64eGrWSgdF+DIz246U/9eL46fo5c5sO5vDrqeIWj6szW/nlcD6/HM7n1SX76dPFh/g+wcT3CW51JUEAD/ffyrVXGEawduMJvv42mbKUncQ576Sv00EclM33qGUe2semZancNd6JDiHurT63uLpIqLpBZGZmMnPmTB599FEOHDjAwoULmTt3LqGhoWi1WhYuXMhjjz3G4cOHmTVrVqNjX331VWJjY+nWrRs1NTX88MMPREVFAfDAAw/w3nvvMW7cON544w2Cg4PJyMhg1apVPPvsswQHB1902y/2HO+88w6vvvoqX3zxBWFhYbZ5UjqdDp1Oh0Kh4KmnnuLNN9+kc+fOtpLqgYGBjB8/HoDQ0NBGz6nT1U+I7tixo+38Y8eOZd68ebzxxhu24X8vvvgiHTp0ICYm5qJ/DkIIcTWxWq1UHN9N/s/LOPPLSmrLCuw6rtLizCFjN8osrvj5uBA/vBOjhnc877o/ZouFgyeKbIUm0vPtqw4I0K2Duy1IXWx1uCvNarVSWWumvKaOMmMd5aY6ymrqKG/4KjP+9n25qf4+gLezFl+Xc76ctfi5OODrosXdUX1N/0ygfnRLZIg7kSHuzBjXjbziKjYn5rB+f/08rFpz8xc2rVbYm3KGvSlneHPZQXpGeBLftz5ghfnpmz3mfPQ6LX8c340/ju/GqfQRrPrhKO/8eJCwyl+Ic9lJuLbxxYZthn58sySRRUsSGdAnmPsmdOO2oR3Rai5dCX1x6UioukFMnDiR6upq+vXrh0ql4sknn2Tq1KkoFAo+++wzXnzxRT744AN69+7NnDlz+MMf/mA7VqvV8sILL5Ceno6TkxNxcXEsX74cAGdnZ7Zu3cpzzz3HhAkTqKioICgoiOHDh7dbz9XFnmPRokWYTCbuvvvuRttfe+01Xn/9daB+7anKykqmTp1KaWkpt9xyC+vWrWvVvKthw4bxxRdf8O677/Luu+/i7OzMwIEDWbduHU5O106vphBC2KN4/xoOz7rDrn1Lza4cqO7BQWMPytx7MnJUV94b0YleN/m3uN6i0VTH9iP5bNhf3/tQXFFj17nUKgX9u/rWB6mYQAK9Xex+TZdKnaU+DFWa6jCYzFTWmjGYzFQ13Faa6jDUmqlseKzSZKbcdE5AqqkPTxU1dZjbeSEcjVKBz+9Dl4sWXxcHfBu2++nqg9i1Er78PZ1t87DKK01sSszhp32n2fprHjW1LVcTPHSqmEOninl3xa90DXFjTP9QxvYPaVPAigjz4O8zBvHUYwPYvnssX39/lGXbtzJQu5MBzntxUVbzS+Vv0wJ27TvNrn2n8fRw4u4/RDHSeT2BUT3w7j8ehUpC1rVA1qn6HXvXqZK1fsS1RN67Qoj2UlhUxQ/rj/PjmsM8VPooLsrmF8gtqPPmQHUPDlT3xOTdjfjhXYgf3ome3fxaDFJllSa2NPQwbP0194LltM/SOaoZ3LOh0luPAFxdWrfURmuZLVZyDTVklRvJKjOSWV5NVrmR0uo6DLV1VJrMtpBkMJmpaaGn5FriqFYS6uZImJsTHdyc6ODmSJi7E6FuTgS7OqJu4d/0alJprOXnX/NYtzeLhEO5VDb05F1ItzAPxvYPYWy/UIJ92h7SS0qr+eGn46z+9hB1GbtJruna7H5uyjLe8X8dtcKCxTWYiAlPEjTyL7Ko8BVi7zpVEqp+R0KVuB7Je1cI0Vp1lWUU7lyFY0AntBED2PjzKb5bk8IvuzMxN3SXTHRfzq0uO23HZNUG2oKUwi+SUcM6M3pEJ26K9m2xlyOnqIqNB7LZsD+b3ccKMFvs+1ji7+FkG9bXP8oHrbr9ruZbrVZKjHVklVWTWW4ks8xIVrmRzLL68JRTUUOtne28EaiVCoL0DnRwcyLMvT5wdXBzokPD947t+G/TXmpMZn45kse6vafZdDDnvJUEz9Wroydj+4cyul8IAZ6tn4N11tHjZ/j6+6N8tyaFkjJjo8fudP2BsfoNjbaZVc543jqRyHufximgY5vPK1pPQlUbSai69pyd39SctWvXEhcXdxlbc3WS964Qwh6W2hqK968l/+cvKNr7PdbaGnLdBvHPtAepqq5tsn+k9gR/9ljB7qpYdlfF4hhQH6JGDe9Et64+zQYpq9XKiexyNhzIZsP+0ySl2b8Qb2SIGyMaFne9KdzjooajVdea63uabKGp2haessqNGOzsJbtSFIDeQY2bgxrXc27rv1S4OWhwdVBjsVo5U2WioPKcryoTxc38e14qfi5auni5EO3tQrSPjmhvHREeTmiuklL1tXUWdh0t4Kd9p1m//zRF5fYNNe3Txbs+YPUNxse9bcP8a2rq+GnLSZavOszeAzloFSbe8Xsdvar5aoZWFFg7juCmPz+DV89hKJRXx8/weiahqo0kVF17UlNTW3wsKChI5jMh710hRMusFgtlydso+HkZZ7Z/RV1laaPHa60qns59kyprc1flrXh7OXNHfCR/GB3ZYpCyWKwcPFnEhv3ZrN9/mgw7C00oFQr6RnrbeqRCfVu+iHY+VquVrHIj+3LL2Ztdxr7cco4XVXKlPgA5qpXoNCpctCpcGm51GnX9rVaFs0aFXvtbMHJ1UOPmeG5oUqPXqlBeRKg0mS0UnhO28s8JXAWVNbbthVWmdp/HBeCgUtDZy4Vu3jqifFyI9tYR5aPD7Qovqmy21C8avWZ3Fmv3ZtkVsJQKBf26+jC2fwij+obgqW/dOlhnpaYV8+VXh0hbv4yb1RsI12add3+j1gfn2LvocfdU3Dr1atM5xYVJqGojCVXieiTvXSHEuaxWK5Xpv9ZX7tu6nJqi0+fdf0nJfWyrGmi77+SoZuTQjowb25WBfYKbXUeqptbMjuTfCk0U/m6IU0scNCriuvtxW2wQQ3sF4uXa+r9ZtWYLyWcM7M0tZ19OfYgqaOVCwPZw1igJcXUi1M2REFdHfF206LVqnDX14cjl7K0tPKlx0aiuiflHZ5ktVgoqTWSUVTd8GUkvbfi+tJrydu7RC9Y7EO2jI8pbRzef+sAV6up4RYpk1Jkt7D52hh93Z/LT3tN2LSatUSm5LTaI+4Z2ZGCUb4vzB8/HaKxj7YbjJHy5itD8r+nt+CtKxfk/rlc4heM64F563/8oOr8OrT6naJmEqjaSUCWuR/LeFUIAGAsyKNj6Bfk/f0FV5pEL7l9nVZFkjGKjYQgn6rpwy4AQ/jC6KyMGh+Pi3LQYREWViS2HctmwP5uff7W/EICbi5ahvQIYGRtM3E3+OLeyt6K8po4DueXsyy1jb04ZiXkVVNddfHEIlQIC9fWBKdTNkVBXR0LdnAhpCFFeTpprpiLepWC1Wik11jUNW2XVpJcaOVPVPkHWzUHN6E7e3B3lT99A1yvyM6+ts7AjOZ8fd2eyfn82FVUXHj7ZwU/HvUMiuCsuHO82XBwASEktZPWyjVTv+A/9tdtxVp7/4sRq4z04DJrC6BGdGNgvRMqztwMJVW0koUpcj+S9K8SNraY4l+T37qU8+Re79j9e05FdVbHsN/YiPDKcP4yO5PaRnfFppjx5TlEVWxJz2LA/m11HW14T6PcCPJ25LTaI22JbtxDvuUP59uWUsS+nnJSLGMrn7aSxhaRQNydbgApxdSRQf21UtbtaVdWaySyr5mRJNUcLDRw5Y+DomUpyDPbNWWpOBzdH7o7y564oP4LbGFQuVk2tmV8O5/Hj7iw2Hsi+4MWDs71X9w+r771qSyisqq5lzY+JJH/1f4SXbSRUm91kH7NVyTN5/6DcUv/5Va/TMmJwBPHDO3FzvxAcHWUlpbaQUNVGEqrE9Ujeu0LcuKxWK/sPnqb47d441Ba1uN/p2oD6ghPVsTj5duAPo+vnSXUK92y0n8Vi5dCpIjYn5rIlMYejmaV2t6VLsBu39a4PUt3D7Cs0UWu2kFxYaRvGty+njPw2DuXzcFTTJ9CNPgGu9Al0I9pbh4tWruRfbqXGWpLPGEgurCT5jIGjhZUcL6psdUXFQcHu3B3tx5hOPjhfoR4Zo6mOnw/l8cPuTDYdzDnvOlgAYX467hvakQm3hLVpaCtAemYpCd+so/CX/9Gxahue6lIAkoxRLCh6rNljbnXZyWD3g1S4dUMdEotX90GERXUmIswDTzuLbNTVWcg/YyAnr4KcPAO5eRXk5JaSk19FxzAPXvjb9VkYTEJVG0moEtcjee8KcWOwmutQqOqvRp8prOTr74/y5eojZGWX80e3bxipS2i0f1GdO3uqY9lV1YcKp3BGj+jEuDGRxPYMbDQXpKK6lu2H89icmMOWxFy7F+JVKKB3J29bj5S9i6gWVJrYkl7E5rRitmWVtLkSX0cPJ/oEuNEnsD5ERbg73dDD9a5mJrOFk8VVHCms781KLjSQfMZAiR1DSF00KsZ08uaeaH/6BbldVAGPi1FeaeKb7en8b8tJTmSXn3dfrVrJyD7B3D+0I/1bKPBij4zMErat/IqyXSvYmtuBA8Zeze43xWMJ/Z0PNNp2ps6Lk6Yw8lSdqPPthWvHXoRH+BAUoKe41EhObjk5uRX14SnfQP6ZSiznBN/uDsn0ckri89J76RHty9f/vbdNr+FqJ6GqjSRUieuRvHeFuH5ZTEYKd60md+OnKB1cKBk6n+XfHGbL1nTqzhmK10GTxSu+c6i0OLOvuhe7qmLJsHZiyC0dGTcmksE3h+FwTq9NRr6hIUTlsOfYGbuH9WnVSgZ182NkbBDDY4Lwdrvw3xyL1cqv+RVsSitmc3oRSQX2VQdsdF6Vgpt89fQJdKVvgBuxAa54NTPvS1w7rFYrpytq+P54AV8l55NaUnXBY0JcHbkryo+7ovzo4HZlqv9arVYOpBbxv80nWbMn64K9VxEBeh6K78KEW8Jw1LZ9iF52bjk/bTrJus2pHPw1r9Fj//T7Bz7q4vMeb7JqSDeFkFUbhF5pwFddiK+6kNfyn6fE4t5k/wB1Hve7fc37RdPx9nJm50+PtLntVzMJVW10PYaqIUOG0KtXL+bPn3+lm9ImCoWCb775hvHjx593v/T0dMLDwzl48CC9evW6LG27Vlyr710hRMsMpxLJ2/gp+T8vo85Qv9aT2ark2bzXKbO4NXOElW4Ox0ip6UyvmFDGjY5k1PBOuDeEnjqzhf0nCtl8sD5IncytsLstbi5aBvfw57bYYG69yR+dk+aCx5TV1LE1o5gt6cUkpBdT2Mp1k34/lO8mXz2Ods7LEtceq9VKYn4FXyXn8+3xAsprLtyD1T/IjXui/Bnb2eeKDfMsa+i9Wm5H75WXqwOTRnbhweGdcHO5uAsCufkG1m85ybpNqZz49Rhz/V9p83O9d2YGKabOTbarqWWW3z95If9VAA5vn4bDFS6JfynYG6quv1cublghISHk5ubi7e1t9zGvv/46q1evJjEx8dI1rJWOHj3Kc889x88//0xdXR3R0dF8/fXXhIaGNtrParUyZswY1q1bZ1foFEJc++oMpeRv/YK8jZ9iOHmgyeMqhYWBzntZZxjR5LGIDh6MHPMQ/xodSXBg/QeDUkMN3+3IYHNiDj//mku5HRXNzuoc5MrQXoEM6xVITCcv1BdYyNVqtXKiuIrN6cVsTitiX245da2YQxPh7tQoRHX0kKF8NxKFQkGMvysx/q68cmtHNpwq5Ouj+SRkFNPS22h3dhm7s8t47edU7ujiw33dAojx11/W942bi5bJI7sw6bbO7D9eyP8S6nuvTLVNe36Lymt4/6skPv7hKPcNiWByfCSBXs2tD3dhAX46Jt3Xk0n39aS8pIwTW8Io/PUXTBn7cCpJRmOttvu5fNWFjUKVo4OawAA9gf56dPkanpoSQ2CQFzd6N42EqnZgKjvT5mNVjjpUDs13T9eWF9JcR6LWzafN57sUTCYTWu2VH2KhUqnw9/e/Iudur5/ByZMnueWWW3jkkUf4xz/+gaurK0eOHGm2d2n+/PnygUKIG4DVYqH08M/kbfyUwp1fYzGdv6Ryb6dfbaHKyVHNmNs6c++E7vTq7gdAak45H/94lC2Juew/XojFzk9CGpWSAVG+DO0VwNBegXYtxGusM7PzdCmb04rZnF5MVrl9a1UB6LQq4kI9GB7mxZAwT3wv8sq9uH44qpXc0cWXO7r4kl9ZwzfHCliZnMeJ4uaHB1bWmll+JI/lR/Lo4uXMfdEBTIjyw9OOHtX2olAo6BPpQ59IH155IIZvfqmfe9Vcj3ClsY7/rDvOkg0n+MPADkwZ05Uuwc31PtvH1cON2AkPwIQHALCazVRmHaE0eQf5iduoOLEbRfGpFo8fN8iJ+0eNIdBfT4C/Hg+339YNM57pTbxXEAql9BLL8L/facvwv5/Htf2N1GnqQoLGTm/2sR1/9qW2vLDJ9sHftm7tjXOH/9XU1PDSSy/xv//9j9LSUrp3784777zDkCFDACgqKmLGjBls3bqVkpISOnbsyIsvvsj999/f6Pm6d++OWq3m888/56abbuK1115j6NChbNy4keeee47k5GR69erF4sWLiYyMtB377bff8o9//IPk5GQCAwOZNGkSL730Emp1fb4/ceIEjzzyCHv27CEiIoIFCxYwcuTINg3/S0hIOG+bPvvsMx566KFGz7F48WImT55MaWkpf//73/n222+pqamhT58+zJs3j549ewK/9XDNmDGDt956i4yMDCwWi+1nA7B06VI0Gg3Tpk3jjTfesCsA3XfffWg0GpYuXXre/RITE7n99tvZt28fAQEBF/z5yPA/Ia49NYWnydv8GXmbPsOY1/IHnrOOGjuzrWoAB6t70KlLIPdO6M4fRnVB66Bmb8oZNjUM68s6U2l3G7xcHRjas7436ubufnYN68suN9b3RqUXsT2rFGMr1ovq6OHEsDAvhoV70jfQDe0Fer+EOMtqtfJrgYGvkvP49ngBpRcqc65UMLKjN/d18+eWEA9UV6B0vtVqZUdyAf/+8RjbDuedd99hvQJ5dGxXYrt4X5ILqrUVxZQf3035sZ0Y89PQuvviFNAJx4BOuIR2x8EzoN3Pea2Q4X+iWTNmzCA5OZnly5cTGBjIN998w6hRo0hKSqJz584YjUZiY2N57rnncHV15ccff+TPf/4zHTt2pF+/frbnWbJkCdOmTWP79u0A5ObmAvDSSy8xd+5cfHx8eOyxx3j44Ydt+2zbto2JEyfywQcfEBcXx8mTJ5k6dSoAr732GhaLhQkTJuDn58fu3bspKyvjqaeeuujX3FKb7r33Xg4fPsy6devYuHEjAG5u9VeC7rnnHpycnFi7di1ubm58/PHHDB8+nOPHj+PpWV9eODU1la+//ppVq1ahUv02VnvJkiW2YLhv3z6mTp1KaGgoU6ZMOW87LRYLP/74I88++yzx8fEcPHiQ8PBwXnjhhUaBqaqqij/96U98+OGHV6xnTghxaaUsfIS8zUvAcv5AUlznzvaqfmyv6k+VNoA7RnXh+Tu70bWLN7uOnmHW/xL5aV82hlbMV+rWwd02rO+mcM9GVQCbU2exsj+3jM1p9fOjjhXZH9q0KgUDgtwZFu7JsDAvwuws7SzE7ykUCnr66enpp+fluI5sSiviy+S8FocH1lqs/HjiDD+eOEOQ3oF7ov35Y7T/ZV37SqFQcHM3P27u5seR9BL+35pjrNmd1Wzv8ebEHDYn5hDTyYtHx0YxPCbwgr+braHRe+IVOxqv2NHt9pw3GglVN5DMzEwWL15MZmYmgYGBAPz9739n3bp1LF68mLfffpugoCD+/ve/247561//yk8//cSXX37ZKFR17tyZd99913b/bKh66623GDx4MADPP/88Y8eOxWg04ujoyD/+8Q+ef/55Jk2aBEBERASzZs3i2Wef5bXXXmPjxo0cO3aMn376yda+t99+m9GjL+4XvKU2OTk5odPpUKvVjcLJL7/8wp49eygoKMDBwQGAOXPmsHr1ar766itbEDSZTPz3v//Fx6fxcMyQkBDmzZuHQqEgMjKSpKQk5s2bd8FQVVBQgMFgYPbs2bz55pu88847rFu3jgkTJrBlyxbba/jb3/7GoEGDGDdu3EX9XIQQV6faOjNZpVo0LQSqOquKRONN/FLZnyM1Xeke7c9Td3ZjzG2dOZ5bwdc7M1jzfzspKrev7LmjVsXN3fwY2iuQIT0DCPC88ByO4upaEjLq50b9nFFCmR1FA87y12ltvVG3hHhcsfWFxPXLQa1kTGcfxnT2Ic9Qw8rkPFYk55FZ1vzw0+yKGubvzmDB7gziQj24t5s/IyO8cbiMhU+6hXmw4PGBPH33TXy6LoUvf05rtmrgwdQiHlvwC6G+OibcEsaEW8IIamZRbnH5Sai6gSQlJWE2m+nSpUuj7TU1NXh5eQFgNpt5++23+fLLL8nOzsZkMlFTU4Ozc+P/ZGNjY5s9R48ePWzfBwTUdxUXFBQQGhrKoUOH2L59O2+99ZZtH7PZjNFopKqqiqNHjxISEmILVAADBw68uBd9gTY159ChQxgMBtvP5Kzq6mpOnjxpu9+hQ4cmgQpgwIABjbrmBw4cyNy5czGbzY16tH7P0vABaty4cfztb38DoFevXuzYsYOPPvqIwYMH891337F582YOHjx4oZcthLjKWUxGlNrfropnnC5j5eojfP39UZSlPrz9u47o7Fp/fqkcwM7qvlidPPjD7ZHMGh+NykXL9zszGfvqerILL1xyGsDf04lhvQIZFhPIwCjfC5ZxtlqtJBdWsjmtiM3pxRzILcfeuQNKBcT4uzI8zJNh4V5EebvIfFBx2fjrHPhrvw5M7xvKrtOlLD+Sx9rUM9SYm76DrcDWzBK2Zpbg4ajmvm4BTO4ZRIDe4bK1N9RXx+sTY/nr+G4s3ZjK0g0nKG1msevMAgPzVx1m/qrD9I/yZcItYYzuG4yL4+WbJyYak1DVDgb+N7/Nx6ocW57o2/fD5GYLVbSVwWBApVKxf//+Jh/udbr6drz33nssWLCA+fPnc9NNN+Hi4sJTTz2FydT4F9rFpfmrIhrNb7/MZ//TPBsWDAYD//jHP5gwYUKT4y7lPJ/ztak5BoOBgIAAEhISmjzm7u5u+76ln0FbeXt7o1ariY6ObrQ9KiqKX375BYDNmzdz8uTJRu0AuOuuu4iLi2u2zUKIq4fVYqEseRt5mz6jcOcqer6fyLYjdaz45jA79pw+Z08fUmo6EarJYk91b36pHEBabQd6dvfnxTu7072XPxsP5vL0kgOk5py/TDPUL8LbK8KLoTGBDOsVQNcQ9wsGm0qTme1ZJWxKL2ZLehF5hqYf7Fri5qBmSAdPhoV7MqSDJx6XsSCAEM1RKhQMCvFgUIgHpcZOrE4pYPnhXJILmx+uWmKsY9H+LP598DRjO/nwl97B9LRz8er24OXqyFMTujNlTCRf/pzGp+tSyClq/qLJ7qMF7D5awOtL9hPfN5gJt4QzMMq3XYcHiguTUNUOLlU1Po2r/aXB7RETE4PZbKagoIC4uLhm99m+fTvjxo3jwQcfBOrDx/Hjx5t80G+L3r17k5KSQqdOnZp9PCoqiqysLHJzc209Srt27bro856PVqvFbG7cvd67d2/y8vJQq9WEhYW1+jl3797d6P6uXbvo3LnzeXupzralb9++pKSkNNp+/PhxOnToANQPX/zLX/7S6PGbbrqJefPmcccdd7S6rUKIy6M6P438Lf8lf/N/Mean2bbPfuRvfHlmeLPHfFZyP2UWPQ4uesbf2ZXXhnck5Uwly3ZmkPR1kl3nvSncgzsGdGBs/xD87RjWl15azaaG3qjd2aWYmrma35IobxeGNfRGxfi7opYPdOIq5e6oYXLPICb1CCSpwMCKI3msTsmnwtR0uF2dxcq3xwv49ngBfQNd+UtMMCMjvC9bYQsXRw0PxdevXfXj7kz+35pjpGSVNbtvtcnM6u0ZrN6eQYCnM+Nv7sCEW8KICGi5uIJoPxKqbiBdunThgQceYOLEicydO5eYmBjOnDnDpk2b6NGjB2PHjqVz58589dVX7NixAw8PD95//33y8/PbJVS9+uqr3H777YSGhnL33XejVCo5dOgQhw8f5s0332TEiBF06dKFSZMm8d5771FeXs5LL73UDq+8ZWFhYaSlpZGYmEhwcDB6vZ4RI0YwcOBAxo8fz7vvvkuXLl3Iycnhxx9/5M4776RPnz7nfc7MzExmzpzJo48+yoEDB1i4cCFz5861qz3PPPMM9957L7feeitDhw5l3bp1fP/997YeKH9//2aLU4SGhhIeHt7q1y+EuHTM1QbO7PyavE1LKDuc0Ow+McpfWMlQrDSduxHa/SZuHx2JWe/ATwey+e8H2+1aB6ZjgJ47Bnbg9gGhhPuf/8q6yWxhT3YZm9OL2JxWzKlS+9eucVIruTnEo6HIhCeBeqksKq4tCoWCHn56evjpeTkugjWphaw4ksuu7OZDy96ccvbmJBPi6sjDvYK4t5s/ugsMnW0vGrWS8TeHMW5QBw6mFvHN9nR+2JXZ4tpyucVVLPr+KIu+P0qvjp7E9wmhWwd3uoa643UZi3HcSCRU3WAWL17Mm2++ydNPP012djbe3t4MGDCA22+/HYCXX36ZU6dOER8fj7OzM1OnTmX8+PGUlTX/B6Y14uPj+eGHH3jjjTd455130Gg0dO3a1dbzolQq+eabb3jkkUfo168fYWFhfPDBB4waNeqiz92Su+66i1WrVjF06FBKS0ttJdXXrFnDSy+9xEMPPcSZM2fw9/fn1ltvxc/P74LPOXHiRKqrq+nXrx8qlYonn3zSVtziQu68804++ugj/vnPf/LEE08QGRnJ119/zS233HKxL1UIcRlYrdb64X0bP+PMjpVYjOevhOepKiVYk0NWbTAAbq4O3D6qCwEdvdibXsKsH49SZ0dvUaCXM7cPCOWOAaFEhZ5/aF9BpYktDSFqW1YJhmauzrckxNWR4Q2V+gYEu+N4GSfyC3EpOWlU3BXlx11RfpwsqeLTg9msPJrX7JIAWeVG/rH1JO/vSue+bgE81CvoslUNVCgU9O7sTe/O3rz8pxg2JeawalsaW5PyMLewCnLiyWISTxbb7vu6OxIZ4k5UqDtRIe5EhroR4e+Kxs7fZ7PFQlllLWUGEyWGGkoNJrQaJbd0v7ErEss6Vb/TlnWqhDjr3DXBriby3hXi0jLmp5O35b/kb/mvXWtKZdf6s72qP7urYimzuNEnJpDuMYHk1JpJSMrDaEfQ8dQ7MLZ/CLcPCKV3J+8W509YrFZ+za9gU1r92lFJBQa7X5daqaBfoJut5HlHDycpMiFuGCXVtSw7nMuSQ9nkN1Ms4iylAkZ38uEvMUHEBrR9kd6LUVhm5LudGaz6JZ2jmaWtPl6rVtI5yJXIEHc6BbliqrVQYqhpCE4mSg01lFaaKDWYKK8yNek17x7mwbdvjGyfF3OVkXWqhBBCiMsgP+Fzjs2beMH9Ki3O7K6KZXtVPzJqQ/D10THwliDMbo7sPFnEnl2ZF3wOnZOGkbFB3DEglEHd/FC3sDhuda2ZbVklbDxVxMZTRRS2Yp0qbycNQxvmRsWFeuDqIB8VxI3Jw0nDjL6hTO0dzI8nzvDJwdPNXpSwWLGtedXbX8/jfUO5Ldzrsl6A8HZz5OFRkTw8KpKjmSWs2pbOtzsz7F5awVRn4UhGKUcyStt0/tJWFLK5XslfSnHNePvtt3n77bebfSwuLo61a9de5ha1zrZt28675pbBYP/VYyHElZeTV8HajSf4+ScDD1kVKBVNB35YrAoO10SxvbIfh4zd8fByI3ZYMJF6B/aeLmWNHVeUHTQqhvUK4I4BHRjSMwAHbfNFbwqrTGxKK2L9qSK2ZZY0O2ypJT189QwL92R4mCc3+elRSm+UEDZalZI7u/oxPtKXPTllfHLwNOtPFjW7rMCBvAr+8v0RorxdmN43lLGdfC5bUYuzokI9eOkBD569tye/HM5j/f5sjmWVkpJV1uzaV+2h1GBfeLueyfC/35Hhf1ev4uJiiouLm33MycmJoKCgy9yi1qmuriY7O7vFx1uqitge5L0rxMUxFmSgUGsprtWzblMqazacIDEpz/b4U16L6O54zHY/p9aP7VX92VXVB7W7P337BqN0d2J/dhm5xRcuBqFSKriluz93DAxlRO8g9C2UJE8trmL9qUI2nCpq1dpReq2KuFAPhod7MbiDJ74uWjuPFEJAfaXMxYey+fJIHpXnCSoR7k5M7xvK+EhfNC30LF8uZouF9DwDx7JKOZpZyrHMUo5llZFbbN/6ds1x0qpw02nx1Dmw+o3bUCmvv3mW9g7/k1D1OxKqxPVI3rtCtJ65porCnavIXPsfqo79zEGnP/BhavPlz/s6HeBB9y/ZU9WbHVX9KXXpwoD+HdB6OXEgp5yMgvMXrLA9T6QPdwwIZVTf4GYrdJktVvbllrHxVBEbThW1qlpfJw9nW6W+PoFuaK/wBzwhrgdlNXUsP5zLZ4eyya5oubcmxNWRx2JDuCfa/6or8FJqqOFYVhnHsuqD1unCSlwc1LjrHHDXafHQOeCm0+Kh0+Kuc8BDp8XNpX57Sz3n1xMJVW1kT6gKCwvDycnpCrVQiNarrq4mPT1dQpUQF2C1Wik/up30NZ9QvPNrlHW/haFSsyvP5r2OhaYfIlTU4enmQN8BHXH0ceHX/AqOZ194UV6AbmEe3DEglLH9Qwn0arqWVFWtma0ZJaw/Vcjm9GKK7ZwfpVRAv0A3bovw4rYIb8Lc5f8tIS6VOouV748XsHBvJqnn6fnxc9HyaGwIf+oegLPm+g8k1wMpVHEJnF281WQySagS15Sqqvo/8BpN80OIhLjRGc9kkrbmU7I3fIamor5gxO+vJburyunmcIykmm62bW6uDtw8sAM6fx1HzlTyQ3oJZJVe8Hxn15Ia2z+k2YU58ytr2JRWzPqThWzPKqHGzkV4XTQqBnfw4LYIb4aFeeLRwrBBIUT7UisV3NnVj3GRvqxLLeRfezM5fKbpXOn8ShNvbD3Jv/Zm8peYYCb1CEQvxWCuC9JT9TvnS6NWq5XMzExqa2sJDAxEeR2OGxXXF6vVSlVVFQUFBbi7uxMQEHClmyTEVaO2opj0jctJW/dftHl7UVxgRlKVxYmVZeNIVA7m1pvDcA3Uc7SoigOpRXadL8THhdsHhHJ7/1AiQ9waVQazWq0cL65iw8lCNqQVcTCvwu7X4eei5bYIL0ZGeMvaUUJcJaxWK1vSi1m4N5P9uS33Wrs6qHmoZyCPxATj7igXQa5GMvyvjS70gzOZTKSlpWGx2F9VSYgrzd3dHX9/f1lfRtzwLCYjJ9Z9wam1S3DI2YGK81fCslgVHKnpygHzINz63I5HB1+Ol1SzO6UQix3/ffp5ODG2X/1aUj0iPBv9DtZZrOzNKWPDqULWnyois8xo9+uI8nZhZIQXIyK86eGrk99tIa5SVquVnadL+WBPJjtOl7a4n6uDmmmxITzUK0iGBV5lJFS1kT0/OIvFgskk9fjFtUGj0diGrgpxo8rIKmXdppNs2ZTEI2WPolWcf15Sbq0v+2oHoup5F26dO5FaXsOO5AJqzRe+oOapd2B032BuHxBKny4+jRblLTXW8nNGCZvTiticXkxZTZ1d7VcrFfQP+m1+VEgzRSxE65jMFixYUSkUKBUKlCDhVFxS+3LK+NfeTDanN1/JGMDHWcsT/UK5v3uAFJO5SkioaiN7f3BCCCGuXlarlRMni/lpy0nWb07l2Infhug95rmYPk6JTY6psjhxwBRLbdc7ceo2kPTKWn4+nG/Xui56Zw3xsfVBamC0r21RXqvVyvGiKjalF7E5rZj9uWXYOT0KvVbFkDBPRkZ4M7iDhwwNaiWL1UqR0UROtZGcSiO51UZyqozkVtWQW2WkxNQ0WCsVoFIobF9K2y2N7qsUnPP9b9td1Cp8HLX4Ojng4+hg+97X0QEntVzcEvWSCir4195M1qYWtrhPiKsjMweEMT7S97KvcyUak1DVRhKqhBDi2mQxmzm07gdS1yzhVLaRT043v9h2b8dDPO71KQC1VjVHam/CGD4Kdc94MmtVbPk1j0rjhXuQnB3UjOgdyNj+ocTd5I9Dw5AdY52ZHVmlbE4vZnNaEafPU2b59wJ1Dg29UV4MCHaXK9UXUF1nJrfKSE61kdyGwJRTVR+e8qqN1Fquno84OrUKH0eHhsCltd36ONaHLh8nLY4yquCGcryokvm7M/jhxJkW94n0cuGZgWHcFuElPalXiISqNpJQJYQQ1w6z2cL+dT+RumYJuqwNuClKAKiyODIz903qaNq7o8HENN9lmDuOQBNzOxm1WjYm5lJWeeFh3VqNkqE9A7l9QChDewbg1FC1K6fCyKa0YjanF7E9qxRjnf3zbrv76rgt3IuRHb2J9naRD07nsFqtFNfUkl1VTU5VDTlV1baeppwWepuuZa4adUPwqg9bng4aPBy0eDpo8Dx7q9VK2L7OJBVU8N6ONBIySlrcp7e/nmcHhTMoxOMytkyAhKo2k1AlhBBXt7o6C7t/2lIfpDLX460saHa/D4se5qCxp+2+l6cTIwZHENLJi/QKIxsO5FBiuHCQUqsU3NLdn9sHhDKidxB6Jw1mi5WDeeVsapgbdbTQvsV9ARxUSm4OcWd4uBfDwz0J1Mv8KLPFSk6VkYzKKrIM1WQYqsmsrCLTUE1l3YWHX95odGrVbyHrnNvfBzA3rQaVhPRrxu7sUmZvTztvtcC4UA+eHRROTz/9ZWzZjU1CFTBnzhwWL16MQqHg+eef58EHH7zgMRKqhBDi6lNjMrNz/XZO/LgEfdZ6AlTZFzxmb1UvvtP+lduGRhAc4UVqaTXr92dTbMdwPIUCBkT5cnv/UOL7BOOhd6DUWMvWjBI2pRWRkFFMiR1DBM8K0jswLMyLYeGeDAp2x+kGre5VXWcms7KaTEN9YDobnrIrjdRdoo8jDkolAc6OBDo7EODs2PC9IwFOjjiolJitVixWK2arFbOV391v+N4CFqyYLVbMDbcWaLitv19ntVJuqqPAWMMZYw0F1SbOGGsor7X/fdLelICPowOx3m4M9PMk1std5nZd5axWK5vSinlvZ9p5L9aM6ujN9D4h9PSXz6qX2g0fqpKSkpg0aRI7duzAarUydOhQ1q1bh7u7+3mPk1AlhBBXh2pjLVvX7+bEms9xzVpPB3W6XcflE0xNxGgc+k3giMmLdfuyKbSzXHnvzl7c3j+U0f1C8HFz5HhxFZvTitjUyiITSgXEBrgyLKy+NyrS68YZ1me1Wikx1TaEpqqGEFUfpAqMl6ZyrpeDxhaWAhuCU4BT/feeDpor+rM3ms2cqTY1hC1TQ+Bq/L3hMvXGaZVKenvVB6yBvh74ODpclvOK1rNYrXyXUsCcXennXW5hYLAbj8WGMKSD5w3zN+Zyu+FD1ZdffsnPP//Mhx9+CMCjjz7K0KFDue+++857nIQqIYS4cioMJrb8ksZPm07yy45TvO35PDpl1QWPK8GXmo6jceh3N4kmf37ad5qCUvuCVI8IT8b0C2FMvxC83J3YebqEzWnFbGplkQk3BzVDOngyPNyTwR088XC6vqv1nQ1PJ8srOVVRRXpD71OmoardQ4JWqSTA2aFJYAp0dsTf2eGaL/BQXWeuD1228FVDkdFEsamW4hoTxTX1t+1deKOLqwuD/DwZ5OtJJ9cbJ/hfS2rNFpYfyWPBngwKzjPvs6uXC4/GhvCHLj5oZM5du7pkoWrRokUsWrSI9PR0ALp168arr77K6NHNV1lqi61bt/Lee++xf/9+cnNz+eabbxg/fnyT/T788EPee+898vLy6NmzJwsXLqRfv34AJCcnc88997B9+3asVisDBgxg6tSpPP300+c9t4QqIYS4vIpKqtmyLY2fNp9k++5Mamt/K/Iwyf0L4lx2N3tchcITU8QoHPvfzYHaUNbuPU1eSbVd5+we5sGY/vVBSuWobqjUV8wvWSWtKjIR6eXC8HBPhoV50TvAFfV1WvrYZLaQbqjiVEUlJ8vrb09VVFHazoUi3LUaQl2cCNXVf3XQORPq4oSvkwPKG/wDv9VqpbLO3ChktXRbaqqltfHLx1HLQN/6HqzeXlJ58mpTXWvms0PZ/N++rPOubxeoc+AvMcHc190fnVZ9GVt4/bpkoer7779HpVLRuXNnrFYrS5Ys4b333uPgwYN069atyf7bt2+nX79+aDSNr9glJyfj5eWFn59fk2PWrl3L9u3biY2NZcKECc2GqhUrVjBx4kQ++ugj+vfvz/z581m5ciUpKSn4+voC8PHHH/Pxxx/j5uZGaGgoMTExPPXUU+d9fRKqhBDi0rJYrBw5VsCunxLI272WusI0vii9u9l9oxxSeNr7/2z3qxV6TBEjcep/D3vrOrJmbw65xRfuyQKIDnVnTP8QhsUEkVNXx88ZJWzNKCG1xL7j4bciE8PCPBkW7kXwdbYIr9Vq5YzRxMnySk42BKdTFZVkVVbTXp0kCiDA2ZEQFyc6NISnUBdnQnVOuGmv7969y8VssVJWW8sZo4lDRWXsLCjm15Jyu/8NHVVK+ni7M9DXkwG+Hng6aC9tg4XdymvqWJaUw38Ss8/bc+XqoGZSj0Am9wzCx0X+/S7GZR3+5+npyXvvvccjjzzSaLvFYqF379507tyZ5cuXo2ronk9JSWHw4MHMnDmTZ5999rzPrVAomg1V/fv3p2/fvvzrX/+ynSskJIS//vWvPP/8802e5y9/+Qt33nknY8eObfY8H374IR9++CFms5njx49LqBJCiHZUYahh+5ZDpGz8lrrUrUQoDuOpKrM9PjN3FuWWpn9zNSoLs4PeRd2hDy4D7mGXuSs/7sslu9C+INQ1xI0x/ULo2tmL1Opafs4oZm9OGTX2To6i/srvsIbeqJtDrp8iE9V1ZtIMVZxqGL53sqKSU+WV7TZ0T6tUEuJytsfJqSFEORPs4ojDNT5c71pUUVvH7oISdhYUs/tMid1VFRVAlLuegb4e3OznSZjOWYYJXgVq6iysTsnn4/2nz3thyEGl4O4of/7SO5iOHs6XsYXXj8sSqsxmMytXrmTSpEkcPHiQ6OjoJvvk5ORw66230r9/f5YuXUpaWhq33nord9xxBx999NEFz9FcqDKZTDg7O/PVV1812j5p0iRKS0v59ttvASgoKMDX15eUlBTuueceDhw4gFp9/q5Q6akSQoiLZ7VaSU3NY89331G4fz0epfvooMlqcf9/F/+Z3dV9ANColQzqH0L8sI4EhXvwS3I+a/Zmk3XGvrLlnYNcGdo7CI9APccqa9iaWXLeK7q/p1RAb39XhoV7MTzMk67X+NpRFquV3Cqjrdfp7PC9nCpjq4eINcdRpSRc70y4zrl+uF7DsD1fJwcp532VqrNY+LW4nJ0FxewoKCGnyr75hwABTg4MbJiH1cPTFY1ShgleSRarlY1pRXy0L4t95ynFDvVr4o3t5MPYzj6EuTtdphZe++zNBm0abJmUlMTAgQMxGo3odDq++eabZgMVQGBgIJs3byYuLo4//elP7Ny5kxEjRrBo0aK2nBqAwsJCzGZzk6GDfn5+HDt2zHZ/3LhxlJWV4eLiwuLFiy8YqIQQQrRddXVt/fpRW76FtF8ItaYQrDQRDDSzBm8jPVxO4DbgXuKHRRAY5kHC4XwW/ZJOxteH7Tp3RICeXtG+qL2cSKqo4f9ySrDmtLyQ5u+5OagZ3MGD4eFeDLnGi0yYLVZSKyo5VFTGoeJykkrKqWinst6Bzo501DsToXchwtWFjnpnApwdb/j5TtcatVJJb293enu783iUlQxDdUPAKia5pILzzSrMra5hVXouq9JzcVGr6OfjwUBfD/r7eOAqwzcvO6VCwcgIb0ZGeLM3p4yP92ex/lRRs/seLjBwuMDAOzvSJGBdAm1KGZGRkSQmJlJWVsZXX33FpEmT+Pnnn1sMVqGhoSxdupTBgwcTERHBf/7zn8ty1W/nzp2X/BxCCHEjO51TTsIv6WzblsLotEfxUJXSGerHDNnxZ75G64Nj16GM6DeOhJoQPthyirS8CrvOHezrQkSEJ9WuWg6VV5NSWgml9vVmqRQQ4+/K4A6e3NrBgx6+elTXaJGJOouFlDIDh4rL+bUhRFVd5BA+F7WKjnoXIlzrA1RHvQtheiec5eLkdUehUBCmdyZM78z9HYMprall15n6YYJ7z5RQbW45YlXWmdmSW8iW3EKUCrjJw5VBvp4M8vMk2EU+qF9ufQPd6BvoxoniSv594DRfH81vsWJko4Dlo2NMZx9ul4B1UdplTtWIESPo2LEjH3/8cbOP5+fnM3jwYLp06cLevXu5++67WbhwoX0NvIjhf20hw/+EEKJltXVm9ifmkrA9nYRf0jmZ9ltv0Ks+7xKqPf+ivLUKR2oD+uDUfQQFfv3Zka9n74lC8ortq9rn4+mET7ArZxxU5JjN9av02ilY78CtHTwZ3MGDQSEeuDlcmwHBZLZwtKyCQ0XlHCouI7m0AuN5PviejxIIdnEiwtW5PkTpXejo6oKvo/aaHvIo2ofJbCGxuL7Qxc78EvKN9i8xEOrixEA/T2729STaQy9DQa+APEMNnyZm82VyHsXV9lXq7OajY0wnb3xdtNRZflvY2myxNrlvtmLb5uqg5sn+HS7xK7oyLunwv9+zWCzU1DT/i1ZYWMjw4cOJiopi5cqVHD9+nCFDhuDg4MCcOXPadD6tVktsbCybNm2yhSqLxcKmTZuYMWNGW1+GEEKI37FarZw+tI9f13xNxeFNJBX58GVR80toHKnp2iRUWawKKnSdMYfFUR56M7urO7DnRCklu01AacPX+bm5OuDk60KeVkmOo4ochQIslgsGKie1koHB7gxuCFLh7k7XZFCorjOTXFrBoeL64XxHSyvatF6Rq0ZNx4Yhe2eH74XpnKRohGiRVqWkn48H/Xw8eCLaysmKKnbkF7OzoJhjZYbzHptZWU3mqWxWnMrGVaMmzt+LO0L8iHTXX6bWC3+dAy/eEsGzg8LZdbqUH0+cYe3JwvMGrCNnDBw5c/5/2+YE6x2u21Blr1aHqhdeeIHRo0cTGhpKRUUFX3zxBQkJCfz0009N9rVYLIwePZoOHTqwYsUK1Go10dHRbNiwgWHDhhEUFMTf/va3JscZDAZSU1Nt99PS0khMTMTT05PQ0FAAZs6cyaRJk+jTpw/9+vVj/vz5VFZW8tBDD7X2JQkhhDhHdVEuSWu/4fSONTjk7EBnLUUH6ACLyh9oKVRFMlq/iQqlF+Xe/SkJGsghdXd2ZdZReboOTgMU2NUGJxcNZndHKvVaCp3VdvdIdfPRcWuoB7d28KBPgBsO6mtvEn1lbR2HS+pD1K/F5RwrM2Buw6CSEBdHeni60dPTlR6ebtL7JC6KQqGgk6sLnVxdmNg5hEJjDbsKSthRUMz+wjJMlpZ7S8tr6/gxK58fs/Lp4urCHzr4MyzABye1BPrLQa1UcEuoB7eEejBraGdbwFp3spAiO3uwLqTu4ge+XfNaPfzvkUceYdOmTeTm5uLm5kaPHj147rnnuO2225rdf8OGDcTFxeHo2Hgtj4MHD+Lj40NwcHCTYxISEhg6dGiT7ZMmTeKzzz6z3f/Xv/5lW/y3V69efPDBB/Tv3781L6cJGf4nhLjRWExGsvdu5uiG1RiPbsHNePK8+z+d+wZlFjfbfQ93R7pG+6HzVFNTlcuOM3pMrShZfpbaUU2NmxarhyNWZ41dQcrLSdMQojyJC/XA9xpcj6XcVEtSSTmHiss5VFRGannleQsFtCRM50xPT1d6ernRw8MVL8dr72chrk1Gs5n9haXsLChhR34xJXYsCu2iVnFbkA93hPgT4epyGVopfq/OYmV3dkMPVurFBSwfZw37pwxqx9ZdPS7rOlXXEwlVQojrnaW2BkPaIU5s/Ym83WtxLNiPGvv/M/205AFO+4zE3V9PuUpBeqmxTSFA46Sm1klNnU6LVacFR9UFg5RGqaBPoCu3htYP6Yv20V1zlefOGGs4XFJBUnH9nKi0iqpWlzZXAJ1cXWy9UD08XWXhXHFVsFitpJQZ2JFfX03wVMWF15Tr5qHnD6H+DPH3Rqu69nqXrwdnA9aaE4UcPlOB1QoqpQK1UoFKUX+rVipQNdxXKRWoz94qFei1Kl4b3OlKv4xLQkJVG0moEkJcj4pLq0k6ks+vR/LJPrCN0bnnX3i9yfFmD9K0PTmm7cFORTeqNK3/++io02J0UlPnoqkPUQ72Df0Jd3eyDekbGOyOTnvtFJgwW62kVVSSVFzBkdJyDpdUkF9t/2T/s5QK6OKqo6dX/XC+mzxc0WmunZ+DuHHlVRnZkHOGHzLzKDCef704V42a+GBf7gjxJ0QnVejE1UFCVRtJqBJCXKtqK4oxnDpIccpecg/tJi3oQfZnuXAoOZ/T2b8tCqnBxL8Cn0OlaLl/yWhx4ISlK8fUN3FAdRP5zsHQikU+FQpwdnOk2lGFyVmDVacBjX0hSqdVcXOIu603KtTt2vlwVVVXx9FSA4dL6gNUcmlFm8qba5QKurrpG3qiXOnu4SrzT8Q1zWy1sudMCd9n5rGroOSCvbMxXm78IdSfm/08ZYFhcUVd1up/QgghLq+a4lwMpw5QnnqA/KTdVKUloqrMabTPpm3ObK8a0OTYWrTk1vkRrMm1bbNYFaTXhnKU7vyq6s4plyjMDg52t0elUqDzcKLSQYnRqT5EmewcxqNSQE8/PTeH1PdG9fZ3RXONDAHKr65pCFD1IepUG+dDaZVKunnUh6ienm5EueukKp+4rqgUCgb6ejLQ15O8aiNrGgpXFNc0P/T4YFEZB4vK8NBqGB3ix11hAXg6yDxBcfWSUCWEEFcxq9VKTUEGFacOUHHyAIXJe6lMS0RZdabRfs19/O6gOc32Fp43wxSCGjMpdZ05ouxOsmMPqrw86seZ2UGjUeLq5UyFVkmVo5paFw1GO49VAN19dQwKdmdgsDv9gtyuiSF9ZouVkxWVtgB1uKScMxcYztQSF7WK7h6udPfQ09PTjUg3ncwlETcMfydHHu7SgYmdQtieX8wPWfnsKyxtdt8SUy1fnDzNqvQc/tQxmHvCA3GUCw7iKiTD/35Hhv8JIa4WRcVVJP0tGkVpZpuOT60JY3bhb8tWKFQKrA5qrI5qcFJhdXIAjdKuKnvOTmr0Xs6UaZQYHFRYW1HmHKCrlwsDQ9y5uSFEuTte/UUVDLV1JJdW2ELU0YtYZDfQ2ZFuHnq6e7hyk4eeDjrna67AhhCXUnZlNd9n5bM2K5/y2roW9/Nx1DIlsgPDA33kd0hcFjKnqo0kVAkhLgdLXS1VWckYTh5A6x2MQ5fBHDl2hqTk+mISvx4p4HROOU97/YsoxxN2P2+tVc3p2kAyaoNJoxO/cDNWJw04aeoLQ9j5IcRVr0Xv5Uy5RkmxRgGOrQtRHT2cGBjszqAQDwYGueHlfHUP27FareRX15B0Ti9UW6ryAagVCjq7uTT0RNX3RsmwJSHsYzJb2JpXxPdZefxaXN7ifpFuOqZFhdHT063FfYRoDxKq2khClRCivZlrqqlM/xXDqYP186BOHqAy/TCY64eOHVP14/3TD2KxNP1zfLfrt4zSb272eY0WBzJrg8msDSKbME4pOpDjEIzZyREcNXYP5QPw8XTCxcuZUrWCMypAa38AAwhxdeTmkPrhfAOD3fHX2T8f60owmS0cLzeQXFLBkdIKkksqKKxp21A+V42abh56urm70t1TT1c3mQ8lRHtIr6jiy7Rs1p0uaPECR5yfJ492DSPI5dopaCOuLVKoQgghrgCr1Up1zgnKjmyl7Oh2KlL3U3X6KFhargDnWXOq2UAFkFlbv0C6weJMpimYjNoQcqyhZKjCydb4Y3XW1gcotf3zcVRKBUF+OhzdHSnWKMjFSo6dlfnO8tdpGRTsUT8vKsSdEFfHCx90hZzthUou/S1ApZZXUtfGa4rBzo71PVCe9cP5QlycZBiSEJdAmN6ZZ3t0ZkJYIIuOpnGgqKzJPtvyi9lZUML4DgFM7ByCXpYaEFeI9FT9jvRUCSHaonDXavJ//oLSI1upKyto9fF/zZlNtbXplVYXTQ1uejM5Ci8sjg3D+OycB3WWq06Lp48LFmc1eQqo1Chb1YsF4O2kYWCIO4OC67/C3J1QXKVBwmg2c7zMwJGGeVBHSitarDB2IRqlgi5uOtswvm7uejxkKJ8Ql53VamXXmRI+OppOZmV1s/u4atT8uVMI4zr4Sxl20W6kp0oIIS6x2jozKSeKSEzKo3rj13TJ/6rVz3GmzouM2mAclUaMFmdc3B0xqZUY1Upw0lDhoKKiFeFFqVTg7e2MSu9AqVpBuUZJkVZJUSsDkJuD2tYLNSjYnc6ezldliLJareRW13CkpJyjpQaOlJRzsqIKcxuvF7pp1XT3cKWbe30vlFTlE+LqoGgoyd7X250fsvL57EQmZabGBS3Ka+v48Gga32bk8mhUGDf7el6Vf7fE9Ul6qn5HeqqEEOeqq6qg/NgOSpO3UXLyCPmD3uXQ4TwOHc7n8LECamrqh/VFOaTwtPf/tfg8FquC/DpfMmqDyawNJsMUQrFTBEZndyqs1vpeKEd1q3uQnJ01OHs4UqlVUaFVYnVu3Vyqs3RaFf2D3Op7okI8iPJ2uSqHtFXXmUkpM9QP5WvoiSoxta0XSkn98KJod71tTlSwi6N8CBPiGmCorePzhlLrtS0Mn+7p6crjUeF0cdNd5taJ64kUqmgjCVVC3NhMZWcoS95G4aGfOZOYgCX3CIpzlnN9Nu81is2eTY5zUNTwQcDzqBT1+5aaXTlR05FUUzjptaEUaUJRunlQqYBqlaLV86CgvhdK5+5IrZO6PkC5aFpdUOIsLycNPf309GsIUt199ajbEMYuJavVSnaV0Ragkv9/e/cdHulZn4v/fuv0ol5WZVdaaftq1+v14oYLTogTCKadUGMMOQmJIQH/TiE5J4e0k3ASIBzAwTkBTDU4FNNDM7bBeN22d23RFq26NL2+5fn9MaORRm3VVqNyf65LlzTvO/PqmS3S3PN8n+8TjuFCLIFpXj9dk19TCwFqa9CHzUEv3CoLNohWst5kGv/vzEU83Ts85XkJwL0N1fjPm9Yj6Fj+WznQ8sNQNU8MVURrS3rgEsLHf4krL/wc0VPPQo10zXj/z468A8+n9k557jW+HyNkBXHeaoNZ3gzLoSFk2rBdai5AzTH8OJwqJJ+OhK5AeLV5z0IFHCp21viws9qLjho/dtZ4Ued1LLsZmaRp4nQ4XhSiZtqvZiayBLT6PNgyLkStc3MWimi1Oh6K4l9OdeFUOD7leZ+m4j3tTXhNUy0U/hygOWComieGKqLVzUoncOGHn0f3S7+A2fU89HT/nB7/TOIWfDn8e0XHAuUu6D4HIkIgrchz3tMJyN1d8zmQdiiwvdq8Z6G8uoId1V7srPZhR40PHTU+NPmXX5iwbIGueBKnwzGcjsRxKhzDxVgS89taFwjqWtEs1KaAFy6Vbc2J1hIhBJ7qHcL/O3MJ/anMlPdp83vwgW2t2FrmW+LR0UrFUDVPDFVEq0sma+FU5yAOH8utgzpx/BL+u3gQqjR9i/OJTKHgYrYJZ7MtOC12YCDQgYyqIGzbuW5882hkoOgKTLcK26NBePRciJrjLJRTlbG9ypubhcoHqA3B5dfeWwiBnmQaZyJxnArHcToSw9lIAhl7fhFKkSS0+tzYVubHlqAX28r8qHMtv5k3IiqNrGXjmxd78JVzV5Cypv45c29DNf6QJYE0C+z+R0RrjplO4vxzT+Hicz9DZ6oJz1xtwMkzgzCM4l+ql6oa0apfnPY6aVvH+ewGnDNa0efahsvOTRhUVJgBZX5rmCQAbg2WW8uV8Xk0GHO8jq5I2FLpRUeNDzurfdhZ48XGcs+yWwcFACOZLM6E4zgdyQWo0+H4vMv4AKDcoWFb0Fco5WsPeOHk5rpENA1dkfG21gb85roqfObURfyid2jSff6jewC/6hvGu9ub8bvNLAmkhWOoIqIVK9Tfj+M//w/0H3wauPICytLnoEoWnAAiiVfgSPitUz6uM9NaFKpilgdnsy24LG3CVfc2dCrNiDmUXDOJ+YQWTS6agZrrLJQiAZsrvdhRnQ9RNT5sqvAsy9beSdNEZyRRCE+nI/Fpy25mQ5UkbPR7sDW/J9TWMh9qnJyFIqK5q3Q68Je7N+G1TbX4xInzuBQv3t8qblr45MkL+I/ufvzZthZsK2OFEs0fQxURrQiWZePUoZM498ufIHryV3ANHUKl3Q1ZEqgavdO4191tjvPTXut4egsqtAiuOrbinLYFZ6Qa2D4d0OYx+yFLsN1qcYDSZ38dCUBbhTs/+5Qr4dtS6YFzGa4HMmwbF2Jj66BOh+O4FE9iITXk9W4nNge82Bz0YnPAh/aABw7OQhHRItpVEcBnb9uFb1/sxRfPXUHSLC7/PhtN4H37j+G31lXjDzc3c4NvmheuqZqAa6qIlodMxsShn/wHrv7yW0hdOQFv8gLK5NCcrvFQ798iavshSUCw3A3VpyNsC2RUBXDMrxW5cCr58KTD9miAa25NKVqCrnwnPh921HixvcoHzxxC2FKxhUB3IlW0DupcNDHtfjCzEdS1QoDakm8mEdC5noGIls5QOoNHTl/Ekz2TSwIBwKMqeE97M363qRbKMiyvpqXHRhXzxFBFtHSEEDDjIWi+csQTWRw62ouXDvbgpcM9OHqiH3foP8fvBb4zp2vaQkK31YjL6mb8XP1tXBZlueAzj9I5oUhjM1CjLc3nsLdUo99ZVMK3vdqHgGN5FggMpTOF8r3RmaiEOftmHhM5FRmbAt58iMrtCcUyPiJaLg4PR/B/T1zAxXhyyvOtPg8e2s4ugcRGFUS0zFiZFJJXTiJx8SjiF48ifP4I4l1HYWeS+JTnczjZOQx7wixIt1R/zesaQsUVtKBL2Yyjoh1nnZuQ1j1znoUSAMTEMr45zGY1+BzYUePDjurcflA7qn0ocy2/WRjTttGbzKA7mcKFaDK3FioSx1A6O+9rKpKEFp8bW4K+wkxUk9fNhd9EtGztqgjg327rwBOXevGFs5NLAs/HEnj//qN484Z6PNDexLJkuiaGKiJaVMK2kR68hMTFo0hcOobExWOIXzyKVM9ZQBR34ZMAKAAGzp6CbVdNutZVo27SsZRw4rLcjjNSO45Lm3HR1QZTmXv9u9DlogA1l411670O7Kzx5faDygep8mUUoGwhMJDO4GoijSuJFK4mUriSSKM7kUJvKo0FVPABABo9TmwK5GaftgR8aPW7+YKDiFYcVZbx5g3rcHddFf719EX8rGew6LwN4PGuHjw3EMKHdrZx1opmxFBFRAuW6j2HK098FIlLx5G4dAxWKjanxzdoPRiwJoeqqPDjoLkXI2oVzqMB3a4N6NGaIKS5lfIJWYIY185ceLRZN6Wo9eq59U/5NuY7qn2odJd+EbMQAqGsge58YLqaSKE7kUJ3Io2ryTSy89wDaqJyhzY2AxXwYVPQC5/GXx1EtHpUOHX8xa52/E5TDf7v8QvomlASeCWRys1atazDu9ualmUnVio9rqmagGuqiCYTlolkz1k4q9dDcbgmnY92HcehD+yc9/W/E70XP4j9FiRZgsPvQFqVYbs0wD33jXUFADhVCI+Wb2s++2YS1R69sAfUjnyQqvaUNkDFDDMflnKBqfB1Mj2pXGWh3KqCTQEvtgS82BT0YUvAi0qnznVQRLRmWLbAv3ddxaNnL0/ZmKfJ48J/72jD1iBnrdYKNqqYJ4YqWuuy4YHcuqdLR5G4eCxXwnf5BISRQcf/fgrB7XcgkzFx9GQ/XjrYg5cP9+Dw0W78Y+AD0KSZX+TbQsKgVYFuox7dRj2uWuvQrTah31EH4XYArrnvCyVUeayEbzREzSKIVbm1/OxTroxvR7UPtV7HnL73YkmZFq4m08XhKZn7OpKd/6a5M/FrKho9LrQFPNicL+Vr9LggM0AREeFiLIn/c/QsTkfik87JAH6vZR3exVmrNYGNKohoRnY2jcSVk/l1T0cRv5j7bEQGpn3M97/8PfxoZAhHjvfBMIrLy3rdtWjSrxZuJ2w3rhj1uJoPUN1GPa6KOmScXgiPDgQ0wDm3duRCQq6Mb3yA0q/dTKLCpY3NQOXbmdd4lnYGxrBt9CZH1zjlP+dvL6RJxExciowGjyv/4USjx4V1Hhca3E742cqciGha631ufPrmnXi86yq+MGHWygbwtQtX8dzACD60sw2bOWtF4EzVJJypotVMWCZOffydSFw8imRPJ2DPrXzsmcTN+HL4LVOee6X713DLaXQbdeg26hG2AxCqArjzTSDc+py66QkAcKmFEGW782V815jJKndphe57o7NQdd6la+Vt2QKX4kmcjSZwLhrH5fzMU18yjcVZ5VRMkyWsc+dC08QAVaZrLN0jIlqgrlgSHznSic5oYtI5GcBbWtbhfs5arVqcqSJao4QQgG1DmqIbm6SoiJ5+DpmhK/O6dlCJTHvul8lbIfR8iKrIhyhNnn2IcihFnfhm040v6FTzTSTGuvCt8y1dgMpaNi7EEuiMJnAuEsfZaAIXYslFaxIxSpaAOpezEJgaPC40uF1o8DpR5XSwdTkR0XW0wefGv9zSga9d6MYXz16BKYpnrR67cBW/5qzVmsdQRbQK2KaByMlnMfzidzH84vex/m1/jZo73zHlfT3rd1wzVGVsDT1mXaFsr9uoR7dZj4TtKdxntCHE2EyUBqiz66gndGUsPHlys1HXWgcVcKiFtU8785vpNixhgEqaJs5FE+iMJHAumsDZaBwX48kFtycfr9qpY53HhcbR8OTOzTzVuh3QZL4DSkRUKoos4R0bG3FrTTk+cuTspFmrS/EUHtx/FG9tacD9bY38mb0GMVQRrVBmMoqRgz/G8Avfw8iBH8FMhAvnhl/8fiFUmaaNU52DePlQD1463IPK4zZeNa6h3YBZmQ9OYyFq0KqEQPEvhFw5nlYcomZR6iA0eWwdVP4z1JkfF3Sq+e573sLnRr9zyQJUJGvgbCQXnM5GEzgbiaM7mV6Ua5fpGtaNn23Kl+rVe5xwcq8nIqJlbYPPg4dv2YmvXbiKL02ctRLAV89346XBEP7X7k1Y55ncLZdWL66pmoBrqmg5Sw9ewfCL38Pwi99H+PhTEKYx5f0khwfnX/Nz/OqlPhw80otEcux+zdplNGnduGrU46pZh4yYuuOdkCTArUK49VyAmkVnPqFIReFJuPONJGZQ7tKKwtNSlvAJITCUzuaCUzSen4WKY2ARGkfUOB1oC3jQ4vOg0eNCo8eJdR4XvNzjiYhoVTgfTeD/HD2Ls1OstXKrCh7a3opX1U/eg5FWFrZUnyeGKlpOhBCIdx3OBakXvof4hUOzfuzHhv4EpzKbZv+9FCk/C5UPUdfozCfkiQFKvWYnvoqiAJULUfVLFKBsIdCbTBfWP3VGc2V84ezUwXS2JAANHhfa/B60BTxo83ux0e9BgN31iIhWPdO28dj5q/jSuSuwpnhJ/dsN1Xjf1ha4ZlkeT8sPG1UQrXBDz38H5/7tz+bUVOJStgGH0jtwJL0dV4x1M95XqPKsO/MVtTIfLeG7Rie/0X2gxoeoWu/StDG3bIHLiWRh5qkzmsD5aAKJBW6Wq0gS1nvdRQGq1e+GW+WPUiKitUiVZfx+WyNuqSnD3x7qxOVEquj8j7oHcCIcw4d3b8IGn2eaq9BqwFcCRMuU5q+8ZqAyhYLTmTYcTu/AkdR2hOzgtPctdOZzz9yZT0iAGNfKXIy2Mp8hDFV7dOyo9mJ7lQ87arxLug9U1rLRle/Ad3YRO/DpsoxWvxttfm8+RHmxwetmy1wiIppko9+LR27twCdPXMCPrxbv93gpnsJ7f30U79u6Aa9prOFWF6sUQ9UKZthZdMWOI2nGUeVch3r3BkgSX/CtFOn+ixh68XuouvXNcJTXTTrv33QzFF8lrNhQ0fGE7cbR9FYcTm3HicwWpIVzyusLVQa8OoRXn7Yz32gHv6IyvmvsBVXj0YtnoGq8qPFMvS5rsY124Ms1j8itg7oUT01ZcjEXHlXBRn9u5ml0BqrJ44JyjTVkREREo1yqgv/e0YYbKgP45+PnkbLG3tzL2jY+fvw8Dg6H8f9t38j1tasQ/0ZXsIsjhzHw/U9DdF9ELFiB3rqNaG65E976LXDVtpR6eDSBsG3Ezx/EUL7teeLiUQCArOqov/e9ufsIgZNnhvD0sxfxzHMXsau/Bbe6hzBgVhRmo85lW2BhmoDkUiG8DsCrT7kmqrAX1PgANcPMS53XUdREYnu1D9Uefdr7L6a4Yea670USOBOJ42w0ju5EGgtdBBrUtcLMU5vfgza/B3VuJ2S+c0hERIvgN9ZVY3PAh789fGZSE4une4dxJhzHX+7ehC3c02pVYaOKCVZKowpb2Nj/mbfA/Mk3J51T/ZW49csDUzwKsDJJyKoOSWGeXgp2No3Qsacw/MJ3MfzSD5Ad6Zl0H3/Hb2LwrodzQerXlzAwNPYDuEbthwIbPWYtci0RiglZGpuN8jqKWpULCRBeHcKnj5XxzdDKvN7rwI6a4i58le6lCVAxw0RnPjh1RhLojMRxdRFamNc4HdgY8OTDU24WqtKxNGWJRES0tmUtG/965iK+fbF30jlFkvCHm5rxpg31fFNvmWP3v3laKaEqmurHyw+0Q0nFJp0L122B+l++hVsbWhF0Fncgu/j1v8Hlf/87OGs2wFW3Ea7aVrjq2+Cs2whX3UY4q9dDVtm1bCGM6DCGX/4hhl/8PkKHfgIrHZ/5/kLFB3r/NzLTlPFNJBwK4HWMlfWN+2EsdAV2QIfwOyB8+rSzUA0+x1h4qvFhe5UXFUsUoKJZIxecovF8kEqgZxECVKPHiY359U/tAXbgIyKi5eHZ/mH849FziBnmpHP7qsrwoZ1tCDr4+2q5Yve/Va73yI+nDFQAcPKiD599368hfC/BW+1Ba2sFbthajZs2VqLq8hkIy0Sq5yxSPWcnP1hW4Kxenwtc9bmglftoywUubWleeK80qf4uDD3/BIZf+B4ip54FZtkkIWZ5cDS9DU4pM22oEhIAjw7hy5f1aUrROeHLhSg74JiyI1+Dz4EdNbnuezvzJXzlrqX54R3JGjgTGQtPnZE4+lKZBV1TloD1Xjfa/V5sDHjQzg58RES0jN1WU4G227z4u8NncDxU/NrthcEQ/uDZQ/jL3ZvQUR4o0QhpMXCmaoKVMlP1zEffAPzqO4XbEcuHkBVEtTqIn8bvxg9ir570GCEBf1H9CbSqXfP6nr6NN+KGj7045TkhxJouqbr49b/Bpa/91azu22dU43B6Ow6nt+N8dgMEJs8mCU0GfKOzUXpR4wjhUGD7HRCBfNnfhNmoCpeG2xrLcFtTELc2lqHBP7sZsIUKZbLFM1CRBPrTCwtQqiRhg8+N9oA39+HPbabLDnxERLTSWLbAF85exlfPd09aH6xIEh7csgH3Ndeu6ddTyxFnqlYx08wi9dIzcI079vP4HfiP+G8AEFAw9SyJJIBqaeq1VrPhrG2d9tzZf/kjhA7/HM66jXDXb8yXE7blZrlqNkDWl+aF/fVkZVJQHK4pz1Xue920ocoWEs5n1+NIegcOpbej36yZdB8BAB5trMnEuE10C7NRAQdsvyPXgGIctybjFeuCuK2xDLc2BrGp0nPd67NHMtnCDFRnvgvfYDq7oGtqsoQWnwft+fI9tjAnIqLVRJElvGdTM3ZVBPD3RzoxkhnbfN4SAp88eQFno3F8YFsrf/etQAxVK1DfiR/DlQ4VHTuY7sh/JU3ZGW7UXw78BaqVIVSrg6hWiz975eSM3/eJFzL43F/9DJs2lKO5MYDmxiCaGgJwuzQku88gPXAR6YGLCB/5efEDJQmOqia4ajfCVZdbw1UoK6xtXdaBKxsewPDLP8ivj/op9vzzQbgbNhXOj4RT+NVzl/D0s714pV2OcnkEAJCxNZzMbMbh9HYcTW9DzJ7c4aeo5bmneMZJOBTYAcfY2qhxM1WKBOyu9ePW/GzU7lr/df3hO5TOFJpHjM5CDY/7RTAfmiyh1ecpzEBtCnjQ7HVDk/lLhIiIVrc9lUH822278A9HzuLloXDRuf/oHsDFeBJ/fcNmVDmXZrsSWhwMVSvQ1V8Vd/zrNuowUNOCinvXIdOThNGfhjmcgRXNQiRNIGNByld5xm0v4rYXF4z1k67rkRKoVodQlQ9aNaOBSxmET0mgc8CD535wetLj/AEn/tZ3HNPuEy4EMgOXkBm4hPDRJ4vPSRJq73k3Nr3v3+bxJ7H4hBBIdp/G8Ivfw/CL30f0zH5gXIXs0IvfQyz+rkLL88PH+gqnZd9NCCoRHElvx8l0OwwUrz+bqeW5kKX82ig9vzaq+L/mpgoPbm3MzUbtWxeAz7H4/3WFEBhKZ3EmWjwDNbLAAOWQZbT6PWjPr39qD3jR7HVBZYAiIqI1qtyh4yN7t+ILnZfxlfPdRedOheN476+P4K9v2IztZct3KQoVY6haYYQQCO3/aVHp38FUBzw3lsHV5IGrqTjaCFvAiBvI9mWQ6U3CGEjDHMlCxLNAxgKyFiQ7lwoSwoMuw4Muo3nS93VJSdjTzIBlohF4vKEpz83iCUHzlU97+tTH3oHMSM+EGa42uOpaoTjc8/ueE4dgWYicfg7D+f2jpmzgkffUo/+Gv+udembte7F7J197ppbnztG1Ufm1U+Nmo+q8DtzWGMRtTWW4pTG46JvrCiEwkM7mw9PoDFQC4ezCApRTkQub6I7OQDV53NxEl4iIaAJFypUDbvR78JGjZ5Eet1nwSMbAB58/jj/d1oLXNtWWcJQ0WwxVK0yo8zm44sXrol7O7MINd6zDnvpKHBgK4UIsVTgnyRJ0vw7dr8PbPlaCJoSAlbRgRE1k+tPI9KYhhtMwo1mIlAlkLSBrQrJygSslpg8whlDxNwP/JTezVSgtzM1yBZSpOxSO98RzGYjYc2huCKCpIYCmxiBqqjyQZQmRU88iM3gZkeNPT3qcXl6fC1q1rfluhW2FkkLF5Z3xe1qpOEYO/xTDL34fwy/9AGZs+JrjBIAGqQsuKYWUmHptFTCu5blPB1za5NmogAO2Xy+ajfLrCm5pLMNtjUHc2lSGlqBr0RaqCiHQn8rk1kDlO/CdjcYRyU5u7ToXLkUu7P2UayLhRaPXBYULbImIiGbtjrpKNHpc+MuDp4u2GDGFwMePn8fZSBzv39bCEvlljqFqhbnyq68V3e43K9Fb1oL/taUZr6qvBrABMcPEkeEIftU/gEPDEQymTUzcOFaSJKgeFapHhavOCezKHRdCwM7YEBET7oSEzHAGkZ4EEsNJWEkDUtbKBy4Lkpl7R8WGgstGIy4bjZPG65TSqMqXEBbKCfNruIJKFADw1DEbZw4cKHqcw6FgQ70L/1/2yhRb3uZkR3qQHelB5Pgzk87pZXVoetOHsO417590ruvL/wNXvvtxCGN2nenSto7jmS04nNqBY5mtkwLVjC3PnWp+bZReNBulKxJurAvgtqZckNpR7Vu02ZxwxsCpcAwnwzGczs9ERafYG2Mu3KpS2P+pze/BpoAX6zwMUERERIuhxe/BZ27Zib893DlpndX3r/SjK7/OqtzBrW2WK4aqFUQIgf5nv4fxhWAHUx1w7ynDrTUVhWM+TcVttRW4rTZ3bCidxg8uX8Sv+/vRl5IRNyVMDFmjJEmC4lQAp4IsAKlFRxA+1Mgy2lwuuOISIkMZ9A4k0d0bRXQgAZEwciGrELhMwLAhAUgLJ64YDbhiNEz6Xg4pgyplCANW5aRzmYyFyJVzkGrm1/E/G+oF5KnLFTV/5TUDVcgK4Egq1/b8dKYNJor3dZqu5bmQpcK6KOF35Lr4IfenvaPaW+jQt7c+AJc2fUORWT9Py8a5WCIXokK5ELXQjXQ9qlJoX96Wn4Fa53Fyx3ciIqLryK9r+MiNW/FvnZfw+IWrReeOh2L4o18fwd/csBlbgpObX1HpMVStIMK28V399WhJ/Qo7HCfhkLN4Od2BPfesg1OZ/gV6pdOJd7Vvxu+3tePYyDG8ONiLk2Edg2kF4ayMxAwha1TGtnE8kcjdrQpw1jrwqjtasbPMh2rFgcs9CRy8EELn1Qh6BxNIR9NAPFsIWuNnuGBYkASQEQ50m+um/Z5hK4B/GX73hE6FgyhXIrP683r86QR8QwfznQoDqK/148y5ITzf2YAdU9z/ilGPw6kdOJzejktGY9GfyYwtz13qWKc+71i53/qAK9dcoqkMtzQEUbbADXeFEOhLZXAyHCvMRJ2LJmDY899qzqephRmo0SBV52aAIiIiKgVFlvDezevR7vfgH4+eQ8YeW2c1lM7iz54/hg9ua8W9jZO3Z6HSYqhaQZJ2Aj+9vAMY2QhdymKLoxOXvO34k03TB5PxZElGR0UH6j0V2BE5hqGMwNWkgu6EjJGMgkh29iErbdl4eShcmKJ2KjK2b/bjgVuqsbsigDqnEyf743j27BAOXxzB+Z4ohkMpIGUCKQNS1gaMKQJX1oSUzwgp4RrXKn6MLmVRNVVbeGUQFWq4cL9vPJPA0C9+PeX4/7q6FjXqADozG3E4vQNH0tswbFUU3Wes5bkD8GiFludCkSD8uXVR42ejKlxaoUPfrU1laFzgprtxw8SZSLwQoE6F4wtqJOHX1EJwGg1RtS4HNxkkIiJaZu6ur0KT14X/eeA0+lNj1TWGLfCPx87hbDSBP96ynuuslhFJCDH/t7lXodnumlwKTxw/hv/67mcK3foAwLGvBs/98+vh1+c2C5IwozgTOYCMlYRpA30pGVcTCkJZGYYNRLLyuJA19/+wTkXG9jI/dpUHsKvCj00BLywbODuSwLH+GF7sCuHYpRFc7o/DSGSBlAUpbUKybMC0x2a0igKXVfTcp6Ihiyp1GNXqEI6kt0Fg6rE3qFcxbJUVNeCYseW5Wx3r1OfJzUa51Pymu025ILWQTXctIXAxliyahbocT03acX22nIqMTQEvtgZ92Bz0oT3gQY2TAYqIiGgliWQN/PWhMzg0PLlKZ1uZDx/evYn7WV1ns80GDFUTLOdQ9dsffgJnfzi2l4EAcMOfd+Df3/jKeV3PtA2cix5GKDvWTTBhAj0JBT1JFSkrd2w0ZIWzCiILDFm7KwLYVR5Ae8ADVZZhC4HLkTRODMZxfCCGw5fDOHkljEg4DaTNXNBK5bsQCgFYohC4xma5ct0KRzsVzsVYy/N8kFInzEblm0xAU6BIwK5aP25bhE13h9PZcTNQubVQ41upzlWz14UtQR+2Bn3YEvRhg5dtzImIiFYDyxZ45HQXvnmxd9K5oK7hf+5qx57K4NIPbI1gqJqn5RqqLNvCltd9EaI3MXbQr+PPH/kNvLu9Zd7XFULgavIcriQ6JxwHQlkVkWw5LkRjMMTYC/7FClk7yvzYNSFkjRpMZHFyKI7jA3GcHIrjaHcEl/vjkNJmLmyl8oHLGBdELHuKwFXcqRAAhEPNBalxLc8FAOHWIAK5kr7R2aj2CnehucQr1gXnteluxrLQGUmMdeQLx9Gfnl3nwakEdLUQnrYGfdgU8MKrsZKXiIhoNftJ9wA+dvzcpLXUMoAH2pvwttYGrom+Dhiq5mm5hqoXuq/g7W/8btFsjLarEk996vWocS1s7Q4AhDODOBs9BFNMXrNToTcjagZxZLgPlxPhSecXI2S5FBk7ynPlgh0VAbT7i0MWACSyFk4NxXFyMI7jg3GcHEzgdH8URtIAUiaktFWY2ULWKl4VZotc2FLksdkodXRtVL5Tnyaj1qvnZ6JyQWqum+7mQmp6rIwvFMP5WBLWPP+bqZKEjX4Ptpb5sCXgw9YyH+q4DoqWCSFEoURVQGD0n7lA/rgY+3r0V43Inx9/LnetsetO/OctTfhKmnBi2vOF603YUmLi+fwRAQFbjI03d7v4OUy+T34rivzzz/05CNjj7j96fOK1BQBFkqHJMlRJhirLUCUl9zl/TJMVKJLE//NEBADojMTx4YOn0Zea/ObszdVl+POOdvj4RuuiYqiap+UYqrKhPnz4o/+K7/zED3Ncb5G292/Bj+6/Z9G+T9pKojNyEAlzct2uTytHu383YoaNwyO9ODLcg8g0bcnHh6yEoSIyj94KE0PWJr93ynI2w7JxIZTKh6w4TuQ/IimjuHwwbULKWLmyPp8jNyPl1uB3qLg531zitnlsuhszTJzKB6hT4VxTiYXsCVXncmDLuFmojX7PvEsMafUQQsAUNrK2BcOycp9tG4Y9+vWEz5aFbP78VPcx7Ny1TNseF4amDj9FQWliaKIlo46Gr/HBazSIyTK0KY6N3k+Tc+HMrzng153waw54NR2KxJ8tRCtRzDDxD0c6sX8gNOlcrcuBv7phMzYFvCUY2erEUDVPyzFUdX/vEzj/uYeQsh04mt6G55M34qjSgff9y134wPbNi/q9bGGhK3YCA+krk85psgPt/hvg18thC4GLsRAODffgVHigqDxwoqwNxLIKAA9CWQk9yeycx+VSZOwsD6CjPFcy2D5NyALys0WxzLgZrVzQuhrLjG26m291vr3aB3WWa49M28aFcc0kToXjuJJIzfm5jHKrCjYHvOPWQnlRxk39VjxL2EhbJlKmgZRpIDMaaKzpw83o+eIQZI+7n8UQQ4tKAuDTHEVBa+Jnn+aYVDFARMuDLQS+dv4qPt95CRNfgWmyhD/d2oLfaazhLPciYKiap+UYqp7/r7ci07m/cPvXiZvwpdr34Yf/ch9a/dfnnYj+1GV0xU5ATPivKkFCs3cLal3rC/9R05aJE6F+HB7uweXEtfeQUiUNfr0cSUNDZzSFi/HknMfnVhXsKPOjozzX/KJthpA1KmlY0GQJ2ixmfoQQGCxqJhFHZyRetF/EXMgA1vvcRbNQTV4XFP6wW7ZsIcbCkZULSMn818nCMXPSubQ1/5lKouXGq+rw6w74NefYZ81RdEybZqN1Irr+Dg6F8beHO6fccuXV66rxge0tM+5lStfGUDVPyy1UZUN9eO5d6yCNe5/6k8P/GcO/dx+efv+91/V7x40wzkQOImtPno2pdNSjxb8DilRctzucTuLwSA8OD/ciOk154Hh1Lh82+qthCRdORxI4PBxdUMjaVZErGZxNyBovZVqFPaFGZ6GGMnOfURtV7tAKzSS2BL3YFPDCrbLGuRTEaDjKh5+UZeYCkGkgWThmFGaWkvmwlLYMzg7RNeV29ZMgSWOfZeTWQBXfHj2fW8E1upjcsm2YwoZp2zBsG/YK/FfnVjX4NQcCuhMVDg8qnW5UOj2odLjhVjW+U050nQ2mM/jrQ2dwIhSbdK7F58Zf37AZDR5XCUa2OjBUzdNyC1U9//EZnH3kwcLtlO3AB4Y/grd86k781Z7JG+MuNsPO4mzkECLG0KRzLsWHTYE9cKmeSedsIdAVG8Gh4V6cCg/AnKE8EAAUSUJ7oBK7y+tR4fTjeCiGw8MRHB6J4FJ87iV2oyEr18Ldj43jQpYtBK4kUjgZGt0TKo6ueALX2AJrWrosoy3gKerIV+3U+UJikQkhkLGtKWeOxoeh1ITZpLRprsgXqtcyusZGkxXospL7rOQ+a7I8dkwePZb7evx9NEkpCgOjLRtyX477uhAKxt1HkgoNH8YeP8XXGGsUUfx1/vHSuK+BcX9Tovi2uMb50aPiGucn3HH8+fGBZ+w5SmO3x4Wj8fdZTJawYdkCpsiVgJqF0GUVwpdp2zAmHDPGhTNTWIX7jR5LWQZiRgbRbOaaP48Xk0tRUZEPWBVONyrzoavc4WZpIdEiMm0b/3r6Er55sWfSOY+q4L/vbMPttRUlGNnKx1A1T8stVB34n7+B+LEnC7dfSN6AzwXfj6/8y+9gb1XlkoxBCIEriU5cTZ6bdE6RVGz0d6DcUTvt49OWieP58sArsygP9Kg6dpbXYndFPWpcXoxksjg6El1QyPKoCraX+WEJgVPhGBKmNedrjGpwO8eV8XnR4vdwR/MZmLaNrG0iY1nIWCYy03096dy445aJ7ApcV6TJMpyKWhx8JoQcTcmFm9GwoxfuM11gyp1jkwGaDyEEkpaBaDaDqJFGNJtBJJtG1Bi7HTXSMOZZ6jxbEoAyhwsVjtysVu5z7muvyjeliObr6d4h/OPRs0hNsffl3XWV+KPN61Ht4mbBc8FQNU/LKVQZ0WH8+vdrIYmxAPCZ4Qdw8bdfh/1//tol/6UzkunHuehhWGLympF17lY0ejZdc0xD6QQOD/fiyMjsygPr3T7sKq/HjvIauFU9P44sjuRD1pF5hqzZ8qpK0TqozUEvArp23b7fcmELAcOeKtxY+eAzxdf5UJSdcHwp3xW/XlRJhkvV4FY0uFQVLlWDS9Hgzn92qcVfu/L341oTWolGS2ajRgbRbBqR/OfohM8Ze/5vTs3EISu5oOV0ozIfunIfbr6ZQDQLl+NJfPjgmSmXUzgVGW9rbcB/2lAPB9dazQpD1Twtp1DV9/NHceZT7yncztgaPjD4D7j346/Ex265sSRjSpkJnIkcQMqaXLcb0CrRFtgNTb52BztbCFyIjeDwcA9OhQdnVR64KVCFXRV12OivKPrFOj5kHR6O4PI8O/LJEtDq8xTNQjV4XCtyI72sbSFuZBA3skjnA1F6fOiZcpbIWtGzQrOhSNJYGJoQgnLH1HxwGndO1aAzHBFNkrbMQsiKZNMIZVIYyiQwlE5iJDP//fmmo0oyal1e1Ln9qHf7UO/2o8rlYdAimkLKtPDPx8/jZz2DU56vdTnwx1s24Paacs4MXwND1Twtp1B15G9eg/CBHxVuH0ztxGdcf4ZPPfwbeHVDQ8nGZQkTF6LHMJSZXLeryy5sCtwArxac9fVSpoET4X4cHu6dVXmgV9Wxs7wOuyrqUOOa3P1wJJPNz2JFZwxZVU69qJ15e8C7rDvkjJbtxI0s4kYGsXxoipmZccdyn6/XO8jLhQwpH3zUSQGpaPaoMLOkw6Wo0GWFvzyIloAtBMLZFIbSSQylExjOJAtfx835NwGaSJVk1Li8qMuHrHq3D1VOL9drESH3uuFH3f3419OXEJtmD80bKgJ439YWbPC5l3h0KwdD1Twtl1BlJqN49h3VkKyxXz7/NvJOnLzjPjz/N79b8nfOhRDoS13EpfipSduASpCxwbcNNa6mOV93KJ3AoXx5YGxW5YF+7Kqow46yWrjVqcvyRkPWmUgcqiRhUz5EVTmXR02xadtImNmxkGRkcrNM446N3l7sd36XmgTAoahwyEru8+iHrEBXVDgUBQ65+PjEr12qBgfDEdGKlbZMDKdzM1pDmWTu60wSw+nkopQLK5KEGpcP9W5fIWxVM2jRGhbJGvh852V8/3LflFUosgTc11yHd7U1waexU/FEDFXztFxCVf8zj+H0x99RuG0KBR/o/3vs+/tb8NlX3VqycU0UzY6gM3oQhj05AFU5G7DBtx2KNPcAOFoeeGi4B6fnUB64u6Ierf7ykpeDCCGQta2iUBQzxwUmYywwJa3Je0ssN5okjwtBCnQ5H4AUdVwIGg1E44NQ8f00WWYYIqIp2UIgkk3nZ7VyoWv069mswZ2JIkmodnpR7/bng5YPNS4fgxatKeeicXzqRBeOhqJTnvdrKt6zqRm/01jDfTTHYaiap+USqo5/5E0Y3v/twu1j6S34v8pD+JtP3Ym3traWbFxTyVppdEYPIWaMTDrnUf1oD+yBU5n/tHLKNHLdA0d60T2H8sDdFXWonqI8cCFsIZA0s2OhaNIMUxZxM1ead727Z82GLitw59cETR10Js8YTfxaV5SSh1QiWtsSZha9yRh6klH0JmPoTcYQyi6sSZEMCQ2eALaX12BbsAZe7drrgYlWOiEEnuodwiOnL2IwPXUp7ka/B+9pb8KNlUG+8QCGqnlbDqHKyiTxq7dXQTLGfmF8IfQWHLjxDXj2I6+FX18eZWvj2cLG5fhp9Ka6Jp1TJQ1t/t0IOqoW/H0G0wkcHu7Jlwdeuy5/Xb48cPsM5YEAYNhWUZldbNz6pPEBKmFkl8WeR25Vg091wKvp8GoO+AqfHfCqeu6zpsOhcBqfiFanpGmgNxlFTzJW+DzfoCVDQou/HDvKarA5WA0nf3bSKpcyLXztQje+fuEqjGk26vRrKl5ZW4G76irRURFYs7NXDFXztBxC1eD+b+PkR95UuG0JGQ/1/y02/4+b8fXfvbMkY5qtoXQPzseOwhaTGyU0etqxzr1xUcq/LGHjQnQEh0d6Z10euDlQhXqPHwkjmwtM5lhgSltTL+BcSookwauOC0fjAtP4AOXVdM4cERFNIWUa6E2NzWj1JKMYycwtaKmSjPZAJXaU1aAtUMmtEWhV602m8ZlTF/Gr/uEZ71ema7mAVV+JHWX+FdkZeb4YquZpOYSqkx97OwZ/+bXC7VPpNnzM/i/44P+9BX+ydVtJxjQXSTOGM5EDSFuJSefK9Gps9O+CKi/eXk+F8sDhHnQnp64TLiWHrMw4mzR6zqVoXG9ERLTIUqaBvlSsaEZrODN5/56pOGQFW4LV2FFeiw2+Mr6hRavWgaEwPn2ya8q9rSaqcGi4o64Sd9VVYmvQt+oDFkPVPC2HUPXSz7+Dn/6f/4NdzmPwykl8JfwmPLf1jfjxP92LRm9p27zPlmkbOB87ipFM36RzDsWNTYE98KiL/1wGUnEcHunF0VmWB86XBMCj6sXld/nZJN/4mSbVAX0Zt2knIlqL0paJS7EQjoX6cDoyOKs1sB5Vx7ayauwoq0WjJ8A3wWjVsWyBH17pw4+6B3AmEp/VY6qdeiFgbQ54V+X/C4aqeVoOoeodH3kKL3zzOGRYaHecwxVjHRo+eCN+8NbfKMl45ksIgZ7kBVxOnJ50ToaMFv8OVDmvz35bo+WBh4Z7cToyMOtW5KokjwUldYr1Svmg5NE0vmNJRLQKZC0LZyKDOBbqw7no8Kx+XwR1J7aX1WJHWQ1qXKvzhSStbT3JNJ7uHcJTvUM4F51ceTSVv9+zBTfXlF/nkS09hqp5Wg6hauvrvgjj6lgZm/DpeOCf9+B/7LqxJONZqEh2CJ2RQzDF5JmjGlcz1nu3Qr6OASWZLw88GxmCYVsTgtJogMoFJqei8pcjEdEalTQNnAwP4PhIHy7GQ7NqS1Tl9GBHWS12lNeg3MENVGn1uRJP4em+ITzdO4QLsanLA12KjCfuuQmOVVidw1A1T6UOVZdGEnjVvV+AZI2VIqg7KvC1j96NXRW1Sz6exZKxUuiMHETcDE8651WDaA/sgUNxLv3AiIiIphDNpnE81I/joX5cneV63Qa3H3urGrC9rJatqGlVuhhLFmawLifGmsDcU1+F/7GrvYQju34Yquap1KHq/Y/sx48/+3LRseb3bsRP3vPqFV9uZgsLF+Mn0Z+6POmcJuloC9yAgF5RgpERERFNbzidxLFQH46N9GFoFk0uvKqOvVUNuLGygftf0aokhEBXLImn+4bwVM8Q/njLBtyyCkv/AIaqeSt1qNr5n76C1IVQ4bZwqXjjxzrwf266ZcnHcr0MpLpxIXYMAhMXBkto9m5GnWsDS/CIiGjZEUKgLxXHsVAfjof6EcmmZ7y/IknYUVaLV1Q3oc7tW6JREi0tIQQEsGq7AM42G3B3u2VC2Da6nvoa7Kv9AMbe1VIavbi7vrJ0A7sOql0N8Kg+nIkcQMYev3+IwKX4KcSMEDb6OqDI/OdJRETLhyRJqHP7UOf24Z76jbiSiODYSB9OhPuRNI1J97eEwOGRXhwe6cV6bxleUd2ITYGqVfvik9YmSZLAf9GcqZqkVDNVkVO/xuEP3Q5DKDiZ2YSDqQ48l7wJ1W9vxU/e95vwrMLyAdM2cDZ6COHs4KRzLsWD9sAeuFW+s0dERMubJWycjQzh+YEr6IqHZrxvme7CvupG7K6oh1Phm4dEyx1nqlaYwee+BQDQJAsdzpOoVEbwrHELdu71rspABQCqrGFzYC+6k2fRnThbdC5lJXAs9Gts9HWgwllXohESERFdmyLJ2BysxuZgNfqSMTw/eBlHR/qmbM8eyqbw4+5O/KLnPHZX1GNfVSMqnOwaSLTSMVQtA0IIDO5/oujYgVQH5HVe3FK7Mjb7nS9JktDoaYdXDeJs9BAsYRbO2cJCZ/Qg6swWNHs2QVrhjTqIiGj1q3X7cF/zNtxT34aXh7rx0mA34ubkLUWytoUXBq/gxcEraA9U4hXVTdjgLeOaYqIViqFqGYifP4js4KWiYwdTHQjuCuLO2sYSjWpplTmqsbP8dpyJHEDSLG5d25u8gIQRRlvgBuiyo0QjJCIimj2vpuPOuhbcVrMeJ0L92D9wGb2p2KT7CQBnIkM4ExlCjdOLfdWN2FleC01effv9EK1mfOt/GRjc/62i2wNmJa6Iddh6qw/rPKurScVMnIob28tuQZWzYdK5qDGCYyPPImbMXKtORES0nKiyjI6KOvzR5pvw7vYbsTVYPe2i/v50HN+7fAofP/4snuw5h5iRWdKxEtH8caaqxIQQGHru20XHDqQ6INd4sLvKsebKABRJQatvJ3xaEF2xExDj9rPP2mmcCO3Heu9W1Lia19yfDRERrVySJKHZG0SzN4hQJoUXB7txcPgq0pY56b5J08Av+y7iuf7L2FVRh1trmlHu4LorouWMoarEkpdPINXTWXTsYKoDnn1B3F5bVaJRlZYkSahxNcOt+tEZOYisPbYPiIBAV/wEYmYYLb4dUCSWRxAR0cpS5nDh1Q1tuLNuAw6P9OKFgSsYnmJTYVPYeHnoKg4MXcX2shrcVrMetdzvimhZYqgqscH9xbNUI2YQF6xm7HllAFuDTSUa1fLg08qws/w2dEYOIWoMF50bSl9F0oxik38PnKqnRCMkIiKaP4eiYl9VI/ZWNuBcdBjPD1zG+djIpPsJAMdC/TgW6kebvwK31axHszfIig2iZYShqsSGJoSqg+mdkMpd2F4rw6k6SzSq5UOTHdgavAmXE53oSZ4vOpc0YzgaehZt/l0oc9SUaIREREQLI0sS2gOVaA9UYiAVx/6Byzgy0jtlS/az0WGcjQ6j0RPA7TXr0Rao5GbCRMsAG1WUUKr3HBIXjxYdO5DqgGtTAPuqOb0/SpJkNHs3o91/AxSp+H0AS5g4HXkZV+Kd4D7WRES00lW7vHhd81Z8YNutuKW6Cfo0XQCvJCJ47MIRfObU8zgy3AtL2Es8UiIaj6GqhEY3/B0Vtbw4m23BhleWYWfZ5A54a12Fsw47ym6FS/FOOtedPIvTkZdg2JP3AiEiIlpp/LoTr25oxwe334a761rgVrUp7zeQTuDbl07gkyeewwsDV5C1rSUeKREBDFUlNTRhw9+D6Z1A0IXNjRKqXWuzScW1uFQvdpTdigpH3aRz4ewgjo08i7gRKcHIiIiIFp9b1XBHXQs+uP02/HbDJgT0qZcGhLNp/Kj7DP75+LN4pvcCUqaxxCMlWtsYqkokPXgFsbMvFh07mOqA1urHDRUaZHa1m5Yiq2jz78Z671Zgwm4fGTuF46HnMJC6UprBERERXQe6rGBfdSP+bNsteEPzNlQ7p27SlDQN/KL3Aj5+/Fn8pLsT0Sz3uiJaCmxUUSJDzxc3qEjYbpzOtKHl9jJsK+Ms1bVIkoQ69wZ4VD86o4dg2GO/NARsnI8dRcwIY4NvKwMqERGtGoqU20x4R3ktzkaG8Kv+i7iSmFyhkbUtPDdwGS8MXsG+qkbcVdcKXeHvQ6LrhTNVJRLcdgd+If0mhs0gAOBwajssrwttrRqavZNL22hqfr0CO8tug08rm3RuIH0Zx0P7kbFSJRgZERHR9SNLEjYFq/Ce9hvx7vY9aPNXTHk/Swg8N3AZD5/aj87I0BKPkmjtkARbphWJRqMIBAKIRCLw+/3X7fsMxTN4xT2fhWRaWK9dRlbo6N+0DR/4UDX+aPM93Htijmxh41L8FPpSFyedUyUdbYHdCOqVSz8wIiKiJdKXjOHZ/os4HurHdC/utgVrcG9jO3yaY0nHRrRSzTYbcKaqRP7x8cOQTBuAhItGM3rMOtTfXIYtQT8D1TzIkowNvm3Y6N8FGcXlDabI4lT4BVxNnGPbdSIiWrVq3T68acMO/Om2W7C3sgHKFK8nToT78emT+/HyUDds/k4kWjQMVSXys58Xb2QrnCo2bnOiLVBbohGtDlXOddhefgucinvSucuJMzgdeRlD6R6kzDgDFhERrUrlDjde07QZf7LlFVjvnVwen7ZMfP/yaTzaeQCDqUQJRki0+rBRRQkksyZil8NFfeuUBg82BU2UO9ikYqE8qh87ym7DuegRhLL9RefC2QGEswMAAFlS4FH9cKt+eFQ/PGoAbtXLxhZERLQqVDo9eFfbDTg80oufdJ9Fyipus345EcZnTj+P22rW4/ba9dCm2WiYiK5tVYeqj370o3j00UchSRI+9KEP4R3veEephwQA+JcfnoKUKd6cr+rGMrT6lSlnWGjuVFnDpsAe9CTP43LizJT3sYWFmBFCzAgVjkmQ4FJ9+ZCVC1oe1Q9FXtX/VYiIaJWSJAm7K+rR5q/ET7o7cTTUV3TeEgLP9HXheKgfr23ajA2+8hKNlGhlW7WvFI8dO4bHHnsMBw4cgBACd911F17zmtcgGAyWdFzDL/8IP/7u1aJjQpOxca8b7X42UlhMkiRhnWcjPFoAZyOHYIprb4QoIJA0o0iaUQyOO+5U3IWA5Vb98GgB6DIX+RIR0crg1XS8ccN27Kqow/cvn0YoW9wZdziTxBfOHsTuijr85ro2uFW9RCMlWplWbag6deoUbr75ZjiduZ3HOzo68OMf/xhvectbSjYmMxnDiY+8Ef8jm8W5yg04mOrAs8lXIFNXhVa/jRpXdcnGtpoF9Sp0lL8SA+kriBkhJMxo0b5Ws5G2kkhbSQxnegvHNNlRNJvl0QJwyC42GiEiomWr1V+BP9n6CjzT24Xn+i/BntAn8NBwLzojQ/ithnbsKKvl7zSiWZpzo4p/+Id/wN69e+Hz+VBdXY377rsPZ85MXV41X7/85S/x2te+FvX19ZAkCd/5znemvN/DDz+M9evXw+l0Yt++fXjxxRcL57Zv346nn34a4XAYoVAITz/9NK5evTrldZbKyMs/hDAykCWBdscFvCnwPUiwEewIYoPPgl+feo8JWjhdcaLB04YtwZtwY+U92FPxKmwO7EWjZxPKHbVwzKPs0rAzCGcHcTV5Dp3Rgzg0/BReGvopToT242LsJAZT3UiYUQhhX4dnREREND+6rOA31m3EH22+CQ3uyS2iE6aBb108gS+fO4SRTLIEIyRaeeY8U/XMM8/gwQcfxN69e2GaJv7iL/4Cv/mbv4mTJ0/C4/FMuv+vf/1r3HTTTdA0rej4yZMnUVFRgZqamkmPSSQS6OjowLvf/W684Q1vmHIcjz/+OB566CE88sgj2LdvHz7xiU/g1a9+Nc6cOYPq6mps3boVf/qnf4q7774bgUAAr3jFK6CUeCfxwf3fLrp9KtOOpOzBzlv8aPaq0GROtS8VXXFCV5woc4zNDpq2gaQZRaLwEcl1CZx2t4/JLGEiaowgaowUjkmQ4S6s0wrAo+VKCBU2xCAiohKqdfvwnk178dJgN57sOYeMXbze+3xsBA+ffB531rXglpomKBKbRhNNZ8Gb/w4ODqK6uhrPPPMMXvnKVxads20bN9xwA9ra2vD1r3+9EGrOnDmDO+64Aw899BD+23/7bzMPUJLwxBNP4L777is6vm/fPuzduxef/vSnC9+rsbER73//+/GhD31o0nX+4A/+AK9//evxO7/zO1N+n4cffhgPP/wwLMtCZ2fnom/+a2WSeO6d1bDHvePzxdBb8Cv/PXjTh5vw3s3r0OzbsmjfjxaHLSwkzTgSZiQXtIwIkmYMNqxrP/gaXIo3XzY42nnQz2BNREQlEcmm8R9XzuBUZHDK8zVOL17TtBlN3uDSDoyoxGa7+e+C11RFIhEAQHn55G4xsizjRz/6EV75ylfi93//9/HlL38ZXV1duPvuu3HfffddM1BNJ5vN4sCBA/jzP//zou91zz33YP/+/YVjAwMDqK6uxpkzZ/Diiy/ikUcemfaaDz74IB588MHCH9xiCx36aVGgsoWEQ+kd8L4igFafhSBbqS9LsqTAqwXg1cb+TQghkLYS44JWblZrNo0wxktZcaSsOIYyPYVjuuwqCloe1Q9ddrKmnYiIrquA7sRbWjtwKjyAH105g6hRvPa4Px3H5zpfxp7KdbinfiPcqjbNlYjWpgWFKtu28YEPfAC33nortm/fPuV96uvr8Ytf/AK333473va2t2H//v2455578JnPfGbe33doaAiWZU0qHaypqcHp06cLt1/3utchEonA4/Hg0UcfhaqWri/HxNK/zmwrYsKLG+4IoNZtwqdN3pyPlidJkuBSvXCpXlRiHYBc0Mra6ULZYC5oRZG1U9e4WrGsnUI2myraX0uV9ElBy6l4GLSIiGjRbQlWY4OvHE/2nMNLg92TCuAPDF3F6fAAXr2uHTvL2ciCaNSCUsaDDz6I48eP49lnn53xfk1NTfjyl7+MO+64Ay0tLfjc5z63JP8Jx89alZJtZDH80veLjh1IdUAqd6GhUkKzL8gNZ1c4SZLgUFxwKC6UO8bCvmFn8+u0xoJWyorP6dqmyCJiDCFiDBWOceNiIiK6XpyKit9p3IyO8jp87/Ip9KeKf28lTAPfvnQCh0Z68JrGzah0Tl5TT7TWzDtUve9978MPfvAD/PKXv0RDQ8OM9+3v78cf/uEf4rWvfS1eeuklfPCDH8SnPvWp+X5rVFZWQlEU9Pf3Fx3v7+9HbW3tvK97vYSOPgkrESk6dii1E86dfrT6TFSw9G/V0mQdAb0SAX1sDzJLmEiasULZYMKMImnGIDD7LoGz3bjYrfqgyizRICKiuWvwBPBHm2/C8wNX8HTvBWQnNLLoioXwL6eex20163F77XpoMt/Yo7VrzqFKCIH3v//9eOKJJ/D0009jw4YNM95/aGgIr3rVq7BlyxZ84xvfQGdnJ+688044HA589KMfndegdV3Hnj178OSTTxYaWNi2jSeffBLve9/75nXN62nouW8V3T6XWY+QHcS2O8tR7TIQ0Ljp71qiSCp8WllRyactbKSsOJLGWOfBhBmFJcxZX3f6jYs98Gvl8Ovl8GsVcCiuRXw2RES0mimSjFtrmrGtrAb/ceUMTk9oZGEJgWf6unA81I/fadyEVj+3h6G1ac6h6sEHH8Rjjz2G7373u/D5fOjr6wMABAIBuFzFL9Zs28a9996L5uZmPP7441BVFVu3bsXPfvYz3H333Vi3bh0++MEPTvoe8Xgc586dK9zu6urC4cOHUV5ejqamJgDAQw89hPvvvx833ngjbrrpJnziE59AIpHAAw88MNendF0Jy8TQC98tOnYw3QEEHGiql1DnUuFWF6/LIK1MsiQXZphG5y2FEMjYKSSMSFHQmvvGxQmkrQQG0lcAAA7ZBb9eDp+WC1lOxc2aeCIimlFQd+KtrR04nW9kEZnQyGI4k8SXzh3CjrJa/FZDG7yao0QjJSqNObdUn+7F16OPPop3vetdk47/7Gc/w+233w6n01l0/NChQ6iqqpqydPDpp5/GXXfdNen4/fffjy984QuF25/+9KfxT//0T+jr68OuXbvwyU9+Evv27ZvL05lktm0TZyt09Ckc/ctXFR37UN//QmTnZrz7T8vxu01VaA/sXvD3obUja6WL9tJKmFFkrPlvzqjJjtxMllYOv14Bl+JlyCIiomllLBNP93bh+YHLsKfYy9GpqLinfiP2VK6DzN8ntMLNNhsseJ+q1WaxQ9XZf30fen70L4Xbl7IN+NvB/4rW97fhHbcCv7FuK2pcTQv+PrS2LcbGxaNUScvNYum5oOVR/ZC44SMREU3Ql4zh+1dOo3vCuvFRDZ4AXtu4GbVu3xKPjGjxLNk+VTQ9YdsY2v9E0bGDqQ4Ij4aWNh3VzjSCOptU0MKpsga/XgG/PlbLbgsLCTOGmDGCaHYEMWNkVntpmcJAKNtfaOs+ugbMr+VKBr1agF0GiYgItW4f3tN+Iw4MXcXPe84hbRWvA+5ORPCvp1/EK6obcWddCxwKX3bS6sV/3ddR9MzzyIZ6i44dSHdAbfOhzmWh0uli0wC6bmRJgU8LwqcFUe9ugRACSSuGWHYEUSP3MZv1WZYwEc4OIpzNLU6WIMOnBeHXKuDXy+HVyqAwZBERrUmyJGFvVQO2BKvwk+6zOBrqKzpvQ+C5gcs4ER7Am9ZvR5M3WJqBEl1nDFXXkaOyARe3vAfa0R9indaHq0Yt+swarLs5iHq3jaCDXf9o6UiSVGiGUYv1EEIgbSURNYYLs1mZWWxWLGAXQhmSuVbuHjWQmynTyuHTytjGnYhojfFqDrxxw3bsrqjHD66cxnCmeK1vJJvGo50HcHd9K26taeZaK1p1GKquI2dVEz7VfTciAztRq/bDL8cgHArad7hQ5cwgwNI/KiFJkuBSPXCpnsK6voyVzAWm/GxW2kpc8zoCAnEzjLgZRg/OAwA8qh9+rQK+/LosTdav63MhIqLlocVfjj/esg/P9l3Er/ovwhq3dN+GwM97zuFiPIQ3NG+DR+PvBlo9GKquo6xpIdwVggSgz6xBH2ogt3hR7bZQ7rQR0LiXAy0vDsWNKsWNKmeuK2fWzuTLBYcRNUaQNGOzus5ow4zeVBcAwKV4C/tk+bRyOBTnNa5AREQrlSYruKu+FTvKa/H9y6dwMR4uOn8uOozPnH4Bb1q/Het9ZVNfhGiFYai6jj7/s05ImeLdxyv3BFHnshHQgiyRomVPlx2ocNahwlkHADDsLGJGCFFjBLHsCOJmBJhFh8GUFUcqFUd/6jKAXHgb38bdIbvYxp2IaJWpdHpwf9sePNPXhWd6LxT9togZGXzh7AHcVdeK22vXsxyQVjyGquvoq98+UXRbaDI23+RBtSuLgM71VLTyaLKOckcNyh01AADLNgshK2qMIG6EIWBf8zoZK4lBK4nBdDcAQJed+YCV6zDIvbKIiFYHWZJwV10L1nuD+GbXccTNbOGcAPCL3vO4FA/hDeu3ccNgWtEYqq4TIQT6OoeKjsm1HlR5gSqnzVBFq4Iiqwg6qhB05NYH2sJC3AgX1mXFjBBsWNe4CpC10xjK9GAo0wMAUCW9sE+WXyuHW/UzZBERrWAbfLm1Vt++eALnYyNF587HRvCZUy/gTRu2Y4OvvEQjJFoYhqrrIHJ6P57pMoBE8Z5A/h0B1DgtuJRcq2ui1UaWlLH9sjyALWwkzEhhn6yoMQJLmNe8jimyGMn0YSSTa82b2ysrF7C8WhAe1c/yWSKiFcarOfCOjbvxq76LeKr3fFE5YNzM4otnD+LOuha8snYDywFpxWGoug7OPvInCHQdwf+qWoeD6Z34dXIfRlCOzbcFUOXKwq+Xc/NUWhNkSYZPK4NPKwPQmtsry4wVGl9EsyMwRfaa18ntlTWAcHagcMyhuOFVA/k28QF4ND80maUjRETLmSxJuKNuA5q9QXzz4nHEjLH9EgWAp3ov4GI8hDeu3w4fywFpBWGoWmSp3vNIdB0BADTpV9GkX0VnZiNCZetQFxSoZukfrWGSJMGj+eHR/KjDhvxeWYl8wMoFraydntW1MlYSGSuJ4czYBtu67CwELI8agEcNQJcdLB0kIlpm1vvK8Meb9+Hbl07gXHS46FxXLIRHTr2AN67fjhY/ywFpZWCoWmSD+79VdDtqeXE22wL3lgDKHTZ8mmCoIsrL7ZXlhUv1osbVBCEEMnYqv09WblPitJW89oXysnYa2WwaoWx/4Zgm6fBo42e0Auw2SES0DHg0HW9v3YVf91/CL3rOwx5XEBg3s/jSuYN4Ze0G3FnXwnJAWvYYqhbZ0P4nim4fSu+ELcnYdGcQVU4LuqzDrfhKNDqi5U2SJDgVN5wuN6pd+b2yrHS+u+Aw4kYESTM2qw6DowyRRTg7iHB2sHBMkdRCwPLmw5ZT8TBoEREtMVmScHvtejR7g/hG1zFEJ5QDPtPXhUvxEN64fgf8OssBafliqFpEmaFuxDpfKDp2MLUTUpkLDVVSvutfNV+4Ec2BrjhRqdSj0lkPINf8ImXGkDCjiJsRJIwIkmYU9hyCliXM/LqusZITWVLGZrPyJYRuxQtJkhf9ORERUbEmbxB/vGUfnrh4Ep3R4u7JF+Nh/L8zL+IdrbtQ6+Yb07Q8MVQtosH93y66nbBdOJ1pg77LB79mo4LrqYgWTJbkXDmfFkA1GgHktjBIWXEkzAgSRjT32YzOqtPgKFtYiBkhxIxQ4ZgEORe0xq3RcqteNpohIroO3KqOt7Z2YP/AZfz86rmicsCYkcHnO1/GW1o6uM6KliWGqkU0NCFUHUlvhwkVm+4oQ6XThiKBoYroOpAkCW7VB7fqQ5UzdyzXBCNZCFgJI4KEGYEpjJkvNo6AjbgZRtwMj30vSHCpPnhUf677oBaAW/VBkfjjlIhooWRJwq01zWjKlwNGsmPNizK2ha+cP4TXNW1FR0VdCUdJNBlfBSySbLgfkZO/Kjp2INUB+HWsb1RR7czAqXjgUFwlGiHR2pJrguGBS/WgErnSQSEEsnYaCTOCuJEPW2YEhp25xtXGCAgkzSiSZhSD6C4cdyne/KxWvnyQe2kREc1boyeA927eh69fOIJL8XDhuCUEvn3pBKJGBrfVNHNJBS0bDFWLZOiF7wJibJo6bes4md4EbZMfAd1GlYulf0SlJkkSHIoLDsWFckdt4XjWShcC1mgJYcZOzenaKSuOlBXHUKancCy3l1YQ5Y5qBPVqhiwiojlwqxreuXE3nrh4AifCA0Xnft5zDpFsGr/duImdAWlZYKhaJEPPFZf+HUtvgwEdLbeXIaDbcCpAkKGKaFnSFSd0xYkyR3XhmGFni8oGE2YUaSsxp+uO7aXVAwkyAnoFKhx1KHPUQJP1xX4aRESrjiYreNOGHfBfPYv9A5eLzr001I2okcabNuyALnOtK5UWQ9UiMOIhhI/9oujYgXQHhFtDW7uOalcWgAS/VlGaARLRnGmyjqBeWfRmiGkbSJqxwoxW3IgiZcVmdT0Be6y1ewzwaxUod9Si3FHDsmAiohnIkoTfamiHX3Pgp1fPjmtfAZyJDOGLnQfwttZd8Gh8s4pKh6FqEQy/+D0Ia6zLmCFUHEtvgdLuRdBho8ppw6sGWPpDtMKpsga/Xg6/PtZ5yhIWkmZ0XNfB0b20xAxXQqGl+8X4iXyJYC3KHbVwqZ7r/TSIiFakW2qaEdCd+NbF47DGLbnoTkbx2c6X8M6Nu1HucJdwhLSWMVQtgokb/h5Pb0ZGOLHuFWVwKwJ+TXA9FdEqpUgKfFoZfFpZ4djoXloxM4xQph+R7NCMIWu0w+DlxGm4FV8uYDlr4VZ8XIRNRDTOtrIaeFQdX7twBOlxb2iPZFL47JmX8LbWXWjwBEo4QlqrGKoWyEzGMHLoJ0XHDqY6IBwKNu1yosplQpK4nopoLRm/l1atqxmmbSCUHcBIpg/hzCBsWNM+NmnFkEzG0J08C4fiRkV+BsurBhmwiIgArPeV4T3tN+Ir5w8XtVxPmAa+cPYA3rxhBzYFqko4QlqL5FIPYOUTWP/2v8V5YwMAwBQyjqS3Q673oNIlUO20IUsKvOPexSaitUWVNVQ512FTYA9urPoNbArsQaVz3TX3tspYSfQkL+B46DkcGH4SF2LHc7Newl6ikRMRLU/VLi/+oH0val3eouOGbeNr54/g5aHuaR5JdH1wpmqBVLcfvwy8Dv8w4ECZHMZ6/RKSwo3K3UHoskCFw4Zfq4IsMb8SUa5ccHT9lC1sRLPDGMn0YSTTB0Nkp32cYWfQn7qE/tQlqJKGMkcNKhy1COiVkCV2vSKitcevO/BA+4349wtHcT42UjguAHz/8mlEshncXdfCWX5aEgxVi+Bz3zgGAAjZQYTSQQhVxpabvahwmlBkIKhzCpqIJpMlGUFHFYKOKmwQ2xEzQoWANdM+WaYwMJjuxmC6G4qkIqhXo8JRi6BeBUXmj3UiWjucioq3te7C9y6fwpGR3qJzv+zrQjSbxu82b4HCN7fpOuNv30XQfWqw6LZU40aNV6DKmSvRYZMKIroWSZIKnQWbvVuQMKP5gNWL1Az7Y1nCxHCmp7AXVlCvQrmjFmWOau6FRURrgirLeH3zVgR0B37Zd7Ho3OGRXsSMDH6vZSccCl/20vXDf10L9PPDV4F4ccmOf3sAugJUu2xosgMuxTvNo4mIJpMkCV4tAK8WQJN3E5JmrDCDlTCj0z5OwEYo249Qth+ISQiM2wtLV5xL+AyIiJaWJEl4Vf1G+DUnfnjldFG/1fOxEXzx7EG8feMueFS+2UTXB0PVAv3frxwqui1kCVvvCMCvWXAqQECrZC0vES2IW/XBrfrQ4GlD2koWAlbMCM3wKIGIMYSIMYSu+HH4tLLCWi6nwn1ciGh12lvVAL/mwDe6jsEY19TnajKKz595Ge9suwFBnW8y0eJjqJqnZPcZWNkkOo/0FB2XKlyoC4Klf0R0XTgVN+rdLah3tyBrpRHK9mM404dodnjGvbBiRggxI4RL8VNwq/5Cq3aX4uUbP0S0qmwKVuFd7Xvw1XOHkbSMwvGhTBKfO5PbJLjaxSoiWlySEGL638JrUDQaRSAQQCQSgd/vn/Z+nQ//IXp/+lkMmhU4mNqJ/cm96DbXwX17Le57Zxlurs4ioAvcUPEqOFh2Q0TXmWkbCGVyASucHYTA7NquO2Q3yhxVCOrV8OsVUNhJkIhWicFUAl8+dxARI1N03KWoeHvrLjR6g6UZGK0os80GnKmaB2FZGHrhuwCAKnUYr/Y9hajtw5XEOmy6KwiHLODXBFyKl4GKiJaEKmuocjWgytUAS5gIZwYxkulDKDsAS5jTPi5jJ9GXuoS+1CVIkBHQKxDUq1GmV8GpepbwGRARLa4qlwfv2bQXXz53CIPpsYY/KcvEF88exO+17ERbgBVFtDgYquYhcvJXMCLFHf8OpDqAoBONNTKqnCYkiaV/RFQaiqSiwlmHCmcdbGEhUtgLqx/mDHthCdgIZwcRzg7iIgCn4kGZXo2gowp+rZz7YRHRihPQnXh3+x589fwRdCciheOGsPHY+SO4r3krOirqSjhCWi0YquZhcP+3im5fzq7DkFUJR6sfHlWgysX1VES0PMiSgjJHNcoc1WgRNqLj9sLK2ukZH5u2EuhNdaE31QUZSm4Wy5GbxXKw2QURrRBuVcf9G2/Av3cdxdnocOG4DYFvXzqBhJnFLTXNJRwhrQYMVXMkbBtD+58oOnYg3QEBYOMdQSiSQIXDBiDBr5WXZIxERFORpFx5X0CvwHrvViTNGMLZAYSyg/lOgtMvsbVhIZQdQCg7gC4ALsVbCFg+rRwyN9YkomVMVxS8tbUD37l0EkdH+orO/eTqWSTMLO6p38jGPTRvDFVzFDv7IrIjxR3/DqY6AJ+ODRs0lDsNqDLg04JQZa1EoyQimpkkSfBofng0P9Z5NsK0jULpXzg7CMPOzPj4lBVHKhlHb/ICFEktrMUK6tVcS0pEy5IiyXh98zZ4VB37By4XnXu2/xISpoHXNm2GwjeJaB4YquZo8Lni0r9eowa9Zi3UZh/8mo3q0VbqGkv/iGjlUGUNlc56VDrrIYRAwozmZrEyA4ib4RkfawkTI5l+jGT6AeT21co1u6iGTwtC4gsUIlomZEnCq9e1waPq+HnPuaJzh4Z7kDSzePOGHdBkriGluWGomgMhBIb2f7vo2IFUBwCg+bYySBL3pyKilU+SJHi1ALxaAA2eNhh2NjeDlRlAODsIUxgzPj5pxpA0Y+hJnociqQjqVYUPnbNYRFRikiTh9tr18Kgavnf5VFHh85nIEL587hDe2tIBl8qKI5o9hqo5iHcdRrq/q+jYgXQHhEtF21YdPs2CS80tDPdqwdIMkohokWmyjirnOlQ510EIgbgZRjgziFB2AAkzMuNjLWFiONOL4UwvAMCjBhDUq1DmqIZXDXL9AhGVzA2V6+BWNXyj6zhMMba336V4GI+ePYB3btwNn+Yo4QhpJWGomoOhCaV/g2YFrhjroGzwoswhxpX+VXDRNhGtSpIkwaeVwaeVoRHtyNoZhDODCGdzs1gz7YkFAAkzgoQZwdXkOaiSlpvBcuRmsTSZL16IaGltDlbj99t247HzR5C2xn5+9afi+OyZl/DOjbtR6eSefXRtDFVzMLH072BqJwAJNXuDkFn6R0RrkC47UO1qQLWrAULYiBnhQkfBpBmd8bGmMDCU6cFQJtf8x6sGCx0FPWqAs1hEtCSavWV4oG0PvnzuEOLm2F5+4Wwan+t8Ge9o3YV1nkAJR0grAUPVLCWunEKy+3TRsQPpDghdwda9LuiyQEDPVeUyVBHRWiRJMvx6Ofx6OZqwGRkrXZjBimSHrjmLFTfDiJthdCc6ocmOXJmgXo2AXsluqkR0XdW6ffiDTXvxpXMHMZJJFY4nTQOPnj2A39uwE20Bvr6j6TFUzdLQhA1/Q1YAXdlmSM0eVDpzs1SSBGiyAy7FW6JREhEtHw7FiRpXE2pcTbCFjZgRKnQUTFnxGR9r2BkMprsxmO4GkCs5LNOrEXRUwa34OItFRIuuzOHCe9r34qvnD6EnGSscN2wbj50/gvuat6Kjoq6EI6TljKFqloaem1z6JyCjfFcAigxUu3Klf0G9kr/siYgmkMdtPNzs3YKMlcoHrNwslg1rhkcLxIwRxIwRXE6chi478wGrGgGtAorMX2VEtDi8mo53te3B4xeO4nxspHDchsC3L51AzMzg1upmvtajSfibaBaEEKi797348ecfQXPqKFTJxsFUB4QqY/ttPkiwUeHg/lRERLPlUFyocTWjxtUMW1iIGiOFjoJpKzHjY7N2Gv3py+hPX4YEGX6tHGWOagT1KrhUVgoQ0cI4FBVva92F71w6iWOhvqJzP7t6DnEji99c1waZwYrGYaiaBUmSUP/qP8RHPiLgjoeww3kSZ7MtkOrdqPEJVDgE1HyzP66nIiKaG1lSCvtYrcdWpMzEuLVYwxCwp32sgI2IMYSIMQQAcCruwsbDfr0cssQNPIlo7lRZxhvWb4NX07F/4HLRuf0DlxE3MriveRtUmd2eKYehapaeP90PO5ZFAh48n9oLAPBtC0CTgSpXrmzFpXi5sSUR0QK5VA9c6gbUuTfAEhai2SGEsgMIZwaRsVMzPjZtJdGXuoi+1EXIkBHQK3Mhy1EFh+JeomdARKuBLEn4rYZ2+DQHfnr1bNG5Y6F+JEwDb2nZCYfCl9PEUDVr//iFAxg/yStkCdvu8AHA2P5UnKUiIlpUiqSgzFGDMkcNhFcgZcULa7FixggExLSPtWEjlB1AKDuArnjuja9cmWA1fFoZ9xMkolm5taYZXlXHdy6dhD3uZ86F2Ai+cPYA3t66C15uErzmMVTN0smDPUW3pQoX1lVI8Go2XPk/xSBDFRHRdSNJEtyqD27Vh3p3K0zbQCQ7hHA2txbLsDMzPj5lxZFKxtGTvABFUhHQK3MNL/QqVhkQ0Yw6Kurg0XQ8fuEosvZYY52eZAyf63wZ79y4G+UOzoavZQxVs3C+NwYzlCqaqXK1++FQxmapJEjwaxWlGSAR0RqkyhoqnHWocNZBCIGkGc2VCWYHETNCMz7WEiZGMn0YyeQWoXtUf6FM0KuWsbMXEU2y0V+Bd7XdgK+eP4yEaRSOj2RS+OyZl/GOjbtQ7/aXcIRUSgxVMzBiI0hcOoa//24G0rgKEyEBm+4MAsjtTwUAXi3Itr5ERCUiSRI8WgAeLYAGTxsMO4tIdhChzCDC2QGYwpjx8QkzioQZxdXkOaiShoBehTJHrnmGJrOsh4hy1nkCeE/7Xnz53CGEsmNrPBNmFo92HsBbWnai1c832dcipoAZDO3/Fjof/iPcJ/xoDm7Hi8kbcCbbBgScWL9Ohi7bCOq5tBXQq0o8WiIiGqXJOiqd61DpXAchBOJmuNCyPWFGZnysKQwMZ3ownMmVfXvVIIKOapTpVfCoAc5iEa1xFU433rPpRnzl3CH0pcY2Ms/aFr56/jBe37wNO8prSzhCKgWGqhkM5jf89UtR3OF5Dm4piTPZNjhafHCrApVOG6O/W4M635UgIlqOJEmCTyuDTytDI9qRtdIIZwcLH5YwZ3x83AwjbobRneiEJukI5vfECupVUGVtiZ4FES0nPs2BB9pvxNcvHEFXbKzc2BIC37p4HGnLxN6qhhKOkJYaQ9U0jHgI4aNPFh07mO6AANDyyjIAY+upFEmFVw0u8QiJiGg+dMWJalcjql2NsIWNmBHKBazMAJJWbMbHGiKLwXQ3BtPdAHJhrUyvQtBRDbfi4ywW0RriVFS8o3U3nrh0AsdD/YXjAsAPrpxGyjJwe816/lxYIxiqphE6+BMIa+zdS0OoOJreCnh1tLWpkGCjMh+q/FoFJLbmJSJacWRJRkCvQECvQLN3MzJWKtdNMDOAiDEEW1gzPFogZowgZozgcuIMdNmZm8FyVCOoVXKdLdEaoMoy3rh+OzyqjhcGrxSde7LnPJKmgVeva2OwWgP4E38aQy9+r+j2ifRmZIQTarMXXlWg3CGg5nNUgKV/RESrgkNxocbVhBpXE2xhIWqEEM7k9rpKW4kZH5u10xhIX8FA+gokSPBp5fl9sargUrx8UUW0SsmShHsb2uFWNTzVe6Ho3P6By0hbBl7btAUK34Bf1RiqphE++iRc424fTHcAABpuLoMkAdWusXcvg2xSQUS06siSgqBeiaBeifXYirSZQCib6yYYyQ5DwJ72sQICUWMYUWMYl3AKDtlVaHbh1yuhSMoSPhMiut4kScKddS1wKRp+1H2m6Nyh4V6kTBNv2rAdmsz/+6sVQ9U07Gwa0HLvKppCxpHUNginiq0dDgCi0Epdl51wKp4SjpSIiJaCU/WgTvWgzr0elrAQzQ4jnB1AKDOAjJ2a8bEZO4X+1CX0py5BQq7kcLTZhVPxcBaLaJXYV90Il6riiYsnYWNsP57TkUF89fxhvLWlAw6FL79XI/6tzsKZTBsSwgO5wYugLuBVbbjzf3IBvZK/DImI1hhFUlDmqEaZoxrrvQJpK5HbeDgziKgxDDHuxdREAnah8yAA6LILQb0SgfyHJutL9TSI6DrYWV4Hh6Li3y8cgynGZrS7YiF88exBvH3jLnhU/j9fbRiqZuFAKlf6V70nCEkCqlxj/0ECemWphkVERMuAJElwqV64VC/q3S2wbBMRY6iw8XDWTs/4+KydKqzFAgCP6s8HrCr4tTLILBUkWnE2Barwzo278dj5w8jYY0tGriajeLTzAN65cTcCurOEI6TFxlB1DbaQcDi9A0JTsGNfbpXVaCt1AAhobFJBRERjFFlFuaMW5Y5aCCGQtGKFjYdjRgiYYRYLABJmFAkzip7kBUiQ4dfKEciv7XKrflZHEK0Q631leKB9D7587hASplE4PphO4HOdL+P3N+5GpZNLSFYLhqprOJttQdT2Q2pwo9IDaLJAUM/9QnQrPugK32UgIqKpSZIEj+qHR/VjnacVpm0gkh3KlQpmB2HYmRkfL2AjYgwhYgzhcgJQJb0QsAJ6JRyKa8bHE1Fp1bn9eHf7jfjSuUOIZMdmrSPZND7f+TLeuXE36tz+Eo6QFgtD1TUcTO0EAJTtDEKWgCqnjdE3CVn6R0REc6HKGiqcdahw1kEIgZQVRyQ7hHB2EFFj5Br7YgGmyGI404PhTA8AwKl48gGrCn6tHKqsLcXTIKI5qHR68J72G/GlswcxlEkWjidMA492HsDbN+5Cs7eshCOkxcBQdQ0H0x0QioSdr/QBEMWlfwxVREQ0T5Ikwa364FZ9qHNvgC1sxIwQItkhRLJDiJvha14jbSXQl0qgL3UJgASfFizMZHnVIDemJ1omAroT7950I75y7jB6ktHC8Yxt4UtnD+H3WnaiPcDXlSsZQ9UMLmSbEbLKINW6UeMXkCBQkQ9VEiT4tfISj5CIiFYLWcq1Ws9tKL+pUCqYm8kaQsZOXuMKAjEjhJgRQnfiLBRJhV+rKIQstm4nKi2PquNdbTfgaxeOoCsWKhw3hY2vXziCt7R0MFitYAxVMziY7/rn3RqAKgPlDgEt/6afVyuDIvOPj4iIro/xpYIAkLaSiGQHEc4OIZIdhiWMGR9vCROhbD9C2X4AuX0Vx6/H0mTHdX8ORFTMoah4e+sufLPrOE5HBgvHLSHw9QtH8NaWDrQxWK1ITAXT+H8jv48eeyOELGHbnbkFhFXjSv+CLP0jIqIl5FTccLqaUeNqhhACCTOSD1iDiBmhGffGAoCsncZguhuD6W4AgDvfuj2oVcKnl0Nh63aiJaHJCv5Tyw5879IpHB7pLRzPBaujeGtrBzb62V16pWGomsaxzDbIiguocKKxKlcuUe0aW0DM9VRERFQqkiTBqwXh1YJo8GyEJUxEsyOFUsGUFbvmNZJmFEkzil7kWrf7tLLCLJZHDbBUkOg6UiQZr2veCgHgyLhgZQobXzt/BG9r7UDrCghWkewQ/FoFf16AoeqaXG1+6ArgUW24839aiqTCqwZKOzAiIqI8RVJR5qhGmaMaAJC10rmAZeTWZM2mdXvUGEbUGAYSZ6BIGgJ6RS5kaZVwqtxLh2ixyZKE+5q3QkDg6Ehf4XghWG3chRbf8l2/P5S+irPRwyh31KLVt3PNdx9lqJqBALDpzlx4Gt/1L5fI2VGJiIiWJ11xosrVgCpXw4TW7UOIGsPXbN1uCQMjmT6MZHIv9ByyK78eqwp+vQKarC/F0yBa9WRJwuubt0EI4FhoLFgZwsZj5w7jHRt3Y71v+bVbT5oxnI8eAwCMZPqQNKNoD+yBR127e24xVM0k4EBrkwpAoMrF9VRERLTyTNW6PW6EC/tjxc0IcI31WBk7hYH0FQykrwAAPGqg0PTCp5VB5nosonmTJQmvX5+bsToe6i8cN4SNr5w/hHdu3L2s9rGybBNnIgdgY+zNmbSVRMKIMFTR1PQNPjhVAU0SCOpjv3C4noqIiFYqWZLh18vh18vRiHaYtoGoMVyYyUpbiWteI2FGkDAj6EmehwQZfq0cAb0Sfr0cHjUAmdUcRHOiSDLesH4bhBA4ER4oHDdsG185dxjv3LgbTd5g6QaYJ4TA+djRST8nqp2NqHY1lmhUywND1TQEgPW3BwEAlS4bcn79nS474VRYW05ERKuDKmsod9Si3FELAMhYqcL+WJHsEAyRnfHxAjYixhAixhCQAGQo8GrBXHDTynNbkHAmi+iaFEnGGzdsh+g6jpPjglXWtvDlc4fw+xt3o7HEwaovdRHDmd6iYx7Vjw2+bSUa0fLBUDUdt4atm3UAomg9VUCvZIcTIiJatRyKC9Wu3LvOQggkrVghYEWzw7Bhz/h4G9ZY0wsAEiR41EAhZPm08jW/oJ1oOook400btuPfLxwr2seqEKzabkCDpzTN0qLZEVyKnyo6pkgq2gN7WAIMhqppyQ1euFUBCQKV3J+KiIjWIEmS4FH98Kh+1LtbYAsLsfx6rEh2CHEzfM1rCAjEzTDiZhg9uAAAcKu+QsDya+XQFed1fiZEK4ciyXjzhh34966jOBMZKhzP2Ba+dPZgSYKVYWfQGT04aT+8Nv8uOBX3ko5luWKomkb9jUFIElDmENDGlYZzPRUREa1VsqQgoFcgoFcA2ATTNnIByxhCNDuClBWf1XWSZgxJM4a+1CUAuY2NcwGrAn69HA7ZxaoQWtNUWcZ/2rATj184is5ocbDKlQLegHWepWkKIYSNzsihSVszrHNvRJmjZknGsBIwVE1j665cu9iqcbNUbtUPTXaUakhERETLiiprqHDWocJZBwAw7Cxixgii2RFEjREkzCiu1VkQyHUOS1tJDKa7AeTWL4/OYvn1crgUL0MWrTmqLOP3Wnbi6xeO4Gx0uHA8bZn40rmDeMfG3WhcghmrK4nOQjnvqIBWgUZP+3X/3isJQ9U0AvktOIrWU2nLf2drIiKiUtFkvajphWWbiJkhRLMjiBkjiBlhiGusyQKArJ3GcKYHw5keAIAqafBpZfmPcni1ANdw0JowFqyO4tyEYPXFzgN404Yd2Bysum7ffyTTj6vJ80XHdNmJtsBuvtExAUPVNCQJcKsCHo2t1ImIiOZDkVUE9SoE9dyLPltYiBuR3GyWMYKYEYIlzGtexxQGQtkBhLK5jmijzS98ejn8+bDFShJarTRZwVtaduJr54/gfGykcNwQNr5+4Qh+p3Ez9lY1LPr3TVtJnIseLjomQUJ74Ab+f5sCQ9UMqp1jm5pJyO3rQURERPMjS0phj6x1yO15kzSjiOZDVjQ7AvMaLdyB4uYXo82dnYqnMJvl18rhVDx8J51WDU1W8JbWDjw+YcZKAPjBldOIZNN4VX3rov2bt4SFM5EDk970aPZugU9bPhsRLycMVTOodo2VKPi0IBSJf1xERESLRZIkeLQAPFoAddgAIQTSVqIQsGLGCDJ2albXSlsJpK1EYV3WWMlgOXxaGUsGacXTZQVva+3A9y+fwqHh4r2iftV/EVEjg9c1b4GyCJtvd8WOI2lGi45VOOpR61q/4GuvVkwJ01BlIKiPL/27fvWqRERElAtZLtULl+pFjasJQG4z4ly5YAgxIzTphd50JpcMyvBqgXFrs1gySCuPIsl4XdNW+DUnnunrKjp3ZKQXcSOD32vZCYcy/5f4/anLhTcnRrkUL1p9Ozj7OwOGqmlUOCzI42amuJ6KiIho6TkUFxzKOlQ61wEATNtA3AgjZoRyzS/MMGxhXeMqgICdf0yocCxXMhiEVy2DTwvCrfogLcK7/ETXkyRJuLu+FX7dgR9cPl3UX/N8bASf73wZ79i4Gz5t7m8aJIwIumInio7JkoL2wA1QZMaGmfBPZxqVzrF/ooqkwquWZvdqIiIiGqPKGoKOKgQduQoSIWwkzFi+u2AIUWNk0n460ymUDOIqgNyLR68agFfLhSyvVgads1m0TN1Y2QCf5sA3uo7BsMeWrPSl4vjsmZfwjo27UeX0zPp6WSuNM5EDkzp0tvp2wq36Fm3cqxVD1TQqx7dS1ys53UlERLQMSVKurM87bl1Wxk6NzWQZISTN2KyuZQur0DRjlEN25ddkBeHTyuBW/ZA5m0XLxKZAFd7VtgdfPX8YSdMoHA9n0/jcmZfxttYONHmD17xOwozidPhlZCesYax1rUels36xh70qMVRNQxv38zKgsfSPiIhoJZAkCU7FDafiRtW4ksHR0r+YEULcCMPGtUsGASBjp5DJpDCU3zNrdG2WVyuDT83NZjkU53V7PkTX0uAJ4A/a9+Ir5w9hJDMWilKWgS+ePYg3bdiOLcHqaR8fygygM3pwUhmtTytDs3fLdRv3asNQNQtcT0VERLRyqbKGMkc1yhy5F5a2sJE0o4gZYcSNEGJmGBkrOatrjV+bNdp/TZedheYXQb2K7dxpyVU43XhP+148dv4wribHmrmYwsbjF47i3oZN2FfdWPQYIQT6UhdxMX5y0vUcsgtt/hs4KzsHDFXX4JBdcCruUg+DiIiIFoksyfBqQXi1IID1AADDzoyFLCO3B9ZsGmAAQNZOYzjTi+FMLmY5ZBeCjmqU6VXw6xXckoWWhFfT8a62PfhG1zF0RocKxwWAH3WfQXcygt9u2ASXqkEIG13xk+hPXZp0HZ9Whk2BPeyOOUf8X34NXE9FRES0+mmyA+WOGpQ7agDkGmAkzTjiZi5kxYwQ0lZiVtfK2Cn0py6hP3UJEmT4tXIEHVUo06s5i0XXla4oeEvrTvzw8hkcGL5adO7oSB+6YiG8prEdNi4ikh2a9PhKRz1a/Tu5p9s8MFRdA0v/iIiI1h5JkuHR/PBoftS4mgEAhp1F3AgXWrrHzTAsYc54HQEbEWMIEWMIl3CKs1h03SmSjNc2bYZfd+Cp3gtF52JGBl+7cAwNHgubA7l9WUc1eNrR4N7I0D9P/J98DQG9otRDICIiomVAk/WitVlCCKSseGGNVTg7eM127pzFoqUgSRLurGtBhcONH1w5jbRVHP67EwqG0jJ2lBmodErY6O9gl78FYqiagUf1s56UiIiIpiRJEtyqD27VhxpXE4QQSJoxhLMDCGUH8xsNi2kfz1ksut52lNeiyRvEN7oO4UqiuHw1bUl4aUjH7ooq3FBRU6IRrh783zoDlv4RERHRbEmSVCgZXOfZCNM2EMkOIZQdmPMsFpBrDe9WfXAp3txn1QuX4uF6F5o1IQSi2cvYGhyBX5NxOqLCEsWzoYeGB3Ep/jxe37xtVnta0dQYqmbA/amIiIhovlRZQ4WzDhXOujnPYgECaSsxRXMMCS7FDde4sOVWfXAqHra/piIZK4Wu2AmEsv2QJKDRa6PCmcWxEQ2hbPG/lZFMCp/vfBk3Vzfh7vpWaDKD+1wxVE1DggyfXl7qYRAREdEqsNBZrDECKSuB1ISwJUGCU/HApXrhVnKzWgxba5MtLPQkL+Bq4hxs2EXn3Crwu0316E/58GTPeRhi7LwA8NzAZXRGhnBv4yas95ZBlflvZ7YYqqbhVYNQOL1ORERE18HCZrEmE8g1zUhZcYygr3BcggS36odPC8KrlcGrBuFU3GyIsQoJIRDK9uNi7CQydmrK+2zwbkOtez1a/EBboBLfuXQSVxKRovsMZZL48rlD0GUF671l2OivwEZ/BcodLv67mYEkhJjb/9pVLhqNIhAI4FTPQWyu213q4RAREdEaY9kmklYMKTOOpBlD0oojZcaQtdOLcn1V0gqbH3vV3GdN1hfl2lQaKTOOrvhJRLKDU55XJQ0b/bsKnStH2ULguf5L+EXveVjXiARB3YmN/gq0+irQ4i+HU1kbczOj2SASicDv9097P4aqCUb/4K4OXUJ9RVOph0NEREQEADBtAykrF7RSZrwQvBYjbDkVD7xaEL58yHKrfpYNrgCWbaI7eRa9yS6IaWY3a1zNaPS0zxicB1JxPHHpBHqSsVl9XxkS1nn8uZDlr8A6tx/yKp3FYqiap9E/uHA4jEAgUOrhEBEREc3oeoQtCTK8WqAwk8X1WcuLEAJD6au4lDg97Xo8n1aODd5t8GjTB4HxLGHjxcFuHBnuRW9qduFqlEtR8Y6Nu9HgWX2vnWcbqtbGvN08sGaUiIiIVgJV1uCTy+DTyoqOm7aBhBlBzAgjboQRN0IwRHZW1xSwC5saI788Z7QZxmh799GGGAxbSytuRHAxfiK/9m4yTXag2bsFlY76Ob2eVSQZN1c34ebqJiSMLM7HRnAuOozz0WHEzZn/3WQsC5VOz5yex2rDUEVERES0CqmyhoBeWdh3UwiBjJ3KB6ww4mYYcSMCMaFD3HTGN8PAuMkRhq3rL20lEc4OIpwZRCjbP+V9JEioc7egwb0Rirywl/geTcfO8lrsLK+FEAL9qXghZF2Oh2GK4n8zDR7/mlljNZ21/eyJiIiI1ghJym0o7FTcqHTWAwBsYSNpRhE3woiZubA1eW+smc0mbDkUNxyyE7riKnxWJY2VQdMwbQMRYxiR7CDC2SFkrOSM9w/qVVjv3QqX6l30sUiShFq3D7VuH26taUbWtnApFsK52DDOR0cwmE6g1V+x6N93pWGoIiIiIlqjZEkudAKszR8z7CwSRgQxM4S4EUbCjM5hH60xRWFrChJkOBQXdNkJh+KELrsKn3XFCYfsgiKpayJ4CWEjboYRzg4hkh1CzAhjNm31HbIb631bUaZXL9mfky4raAtUoi2QmwGNZNNQ1sDf0bUwVBERERFRgSbrCDqqEHRUFY6ZtpFrhDGhIcZ8wtYoARtpK5GbGTOmvo8sKXDILjgUV362ywWn4i7cXomzXUIIGCJbaJkfNYYQyQ7DEuasryFDxjrPRtS7WyCXeF/VgO4s6fdfLhiqiIiIiGhGqqzBr5fDj/Ki49cjbI1nC2vG2a5c6HLDqRQHL0e+zLGUM11CCGTtFJJmbvyp/OekGYclpkmRM1AlHUG9EgG9CmWOau4ttswwVBERERHRvMwmbKXMODJ2ClkrjaydXrRNjIHR0BVDypq6BbgEGYqkQJFUyPnPiqRAnvB58vmx2Z/p9n+aSEAgY6Xy4SmGlJmADWvez02CDL9WhoBehaBeCbfqX3GzcmsJQxURERERLarpwhaQa45h2BlkrBSydnrS56ydXrSZLgEbprBhzmNmqBRcig9BvRJBvQo+vRxKiUv7aPYYqoiIiIhoyciSnC/Vc017H1tYyI4GLyuFtJ1CxkrmP1LI2GnMppHDciZBzrWgV30IarnW97rC9UkrFUMVERERES0rsqQU2r9PRQgbmfzs1ljQSiKdv72YJYYLpUgqXIoXLtULl+KFO//ZobhZzreKMFQRERER0YoiSfK40DV5jyRb2MhaKZjCgCUs2MKEJSxYwoSd/zz++MRjtpjdhshAcSjSZG1cePLBpXihyQ6GpzWAoYqIiIiIVhVZkuFUPaUeBq0hcqkHQEREREREtJIxVBERERERES0AQxUREREREdECMFQREREREREtAEMVERERERHRAjBUERERERERLQBDFRERERER0QIwVBERERERES0AQxUREREREdECMFQREREREREtAEMVERERERHRAjBUERERERERLQBDFRERERER0QIwVBERERERES0AQxUREREREdECMFQREREREREtAEMVERERERHRAjBUERERERERLQBDFRERERER0QIwVBERERERES0AQxUREREREdECMFQREREREREtAEMVERERERHRAjBUERERERERLQBDFRERERER0QIwVBERERERES0AQxUREREREdECMFQREREREREtAEMVERERERHRAjBUERERERERLQBDFRERERER0QIwVBERERERES0AQxUREREREdECMFQREREREREtAEMVERERERHRAjBUERERERERLQBDFRERERER0QIwVBERERERES0AQxUREREREdECMFQREREREREtAEMVERERERHRAjBUERERERERLQBDFRERERER0QIwVBERERERES0AQxUREREREdECMFQREREREREtAEMVERERERHRAjBUERERERERLQBDFRERERER0QIwVBERERERES0AQxUREREREdECMFQREREREREtAEMVERERERHRAjBUERERERERLQBDFRERERER0QIwVBERERERES0AQxUREREREdECMFQREREREREtAEMVERERERHRAqzKUPXRj34U27Ztw/bt2/GVr3yl1MMhIiIiIqJVTC31ABbbsWPH8Nhjj+HAgQMQQuCuu+7Ca17zGgSDwVIPjYiIiIiIVqFVN1N16tQp3HzzzXA6nXC5XOjo6MCPf/zjUg+LiIiIiIhWqWUXqn75y1/ita99Lerr6yFJEr7zne9Mus/DDz+M9evXw+l0Yt++fXjxxRcL57Zv346nn34a4XAYoVAITz/9NK5evbqEz4CIiIiIiNaSZVf+l0gk0NHRgXe/+914wxveMOn8448/joceegiPPPII9u3bh0984hN49atfjTNnzqC6uhpbt27Fn/7pn+Luu+9GIBDAK17xCiiKMu33y2QyyGQyhduRSAQAEI1GF//JERERERHRijGaCYQQM99RLGMAxBNPPFF07KabbhIPPvhg4bZlWaK+vl78wz/8w5TXeM973iN+8IMfTPs9PvzhDwsA/OAHP/jBD37wgx/84Ac/+DHlx5UrV2bMLVI+vCxLkiThiSeewH333QcAyGazcLvd+OY3v1k4BgD3338/wuEwvvvd7wIABgYGUF1djTNnzuDNb34zDh48CFWdelJu4kyVbdsYGRlBRUUFJEm6bs9tMe3duxcvvfRSqYexIqzFP6vV9JxX4nNZzmNeTmOLRqNobGzElStX4Pf7Sz0cIhpnOf2soOVntf/7EEIgFouhvr4esjz9yqllV/43k6GhIViWhZqamqLjNTU1OH36dOH26173OkQiEXg8Hjz66KPTBioAcDgccDgcRcdWWqdARVH4ImSW1uKf1Wp6zivxuSznMS/Hsfn9/mU3JqK1bjn+rKDlYy38+wgEAte8z4oKVbO1f//+Ug9hST344IOlHsKKsRb/rFbTc16Jz2U5j3k5j42Ilg/+rKCZ8N9Hzqos/yMiopUlGo0iEAggEoms+nc8iYho9Vl2LdVnous69uzZgyeffLJwzLZtPPnkk7j55ptLODIiIloIh8OBD3/4w5PKsYmIiFaCZVf+F4/Hce7cucLtrq4uHD58GOXl5WhqasJDDz2E+++/HzfeeCNuuukmfOITn0AikcADDzxQwlETEdFCOBwO/NVf/VWph0FERDQvy6787+mnn8Zdd9016fj999+PL3zhCwCAT3/60/inf/on9PX1YdeuXfjkJz+Jffv2LfFIiYiIiIiIlmGoIiIiIiIiWklW1JoqIiIiIiKi5YahioiIiIiIaAEYqoiIiIiIiBaAoYqIiJa117/+9SgrK8Ob3vSmUg+FiIhoSgxVRES0rP3Zn/0ZvvSlL5V6GERERNNiqCIiomXtzjvvhM/nK/UwiIiIpsVQRURE180vf/lLvPa1r0V9fT0kScJ3vvOdSfd5+OGHsX79ejidTuzbtw8vvvji0g+UiIhoARiqiIjoukkkEujo6MDDDz885fnHH38cDz30ED784Q/j4MGD6OjowKtf/WoMDAws8UiJiIjmj6GKiIium3vvvRd/93d/h9e//vVTnv/4xz+O//yf/zMeeOABbN26FY888gjcbjc+//nPL/FIiYiI5o+hioiISiKbzeLAgQO45557CsdkWcY999yD/fv3l3BkREREc8NQRUREJTE0NATLslBTU1N0vKamBn19fYXb99xzD9785jfjRz/6ERoaGhi4iIho2VFLPQAiIqKZ/PznPy/1EIiIiGbEmSoiIiqJyspKKIqC/v7+ouP9/f2ora0t0aiIiIjmjqGKiIhKQtd17NmzB08++WThmG3bePLJJ3HzzTeXcGRERERzw/I/IiK6buLxOM6dO1e43dXVhcOHD6O8vBxNTU146KGHcP/99+PGG2/ETTfdhE984hNIJBJ44IEHSjhqIiKiuZGEEKLUgyAiotXp6aefxl133TXp+P33348vfOELAIBPf/rT+Kd/+if09fVh165d+OQnP4l9+/Yt8UiJiIjmj6GKiIiIiIhoAbimioiIiIiIaAEYqoiIiIiIiBaAoYqIiIiIiGgBGKqIiIiIiIgWgKGKiIiIiIhoARiqiIiIiIiIFoChioiIiIiIaAEYqoiIiIiIiBaAoYqIiIiIiGgBGKqIiIjy7rzzTnzgAx8o9TCIiGiFYagiIiIiIiJaAIYqIiIiIiKiBWCoIiIimsYPf/hDBAIBfPWrXy31UIiIaBlTSz0AIiKi5eixxx7De9/7Xjz22GN4zWteU+rhEBHRMsaZKiIiogkefvhh/Mmf/Am+//3vM1AREdE1caaKiIhonG9+85sYGBjAr3/9a+zdu7fUwyEiohWAM1VERETj7N69G1VVVfj85z8PIUSph0NERCsAQxUREdE4ra2teOqpp/Dd734X73//+0s9HCIiWgFY/kdERDRBe3s7nnrqKdx5551QVRWf+MQnSj0kIiJaxhiqiIiIprBp0yb84he/wJ133glFUfCxj32s1EMiIqJlShIsGCciIiIiIpo3rqkiIiIiIiJaAIYqIiIiIiKiBWCoIiIiIiIiWgCGKiIiIiIiogVgqCIiIiIiIloAhioiIiIiIqIFYKgiIiIiIiJaAIYqIiIiIiKiBWCoIiIiIiIiWgCGKiIiIiIiogVgqCIiIiIiIlqA/x/5dQQYbfQf/AAAAABJRU5ErkJggg==",
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure(figsize=(10, 6))\n",
        "for color, model in zip(palette, summary['model'].data):\n",
        "  style = '-' if 'baseline' in model else '--'\n",
        "  (spectrum.k ** 5 * spectrum).sel(model=model).plot.line(\n",
        "      color=color, linestyle=style, label=model, linewidth=3);\n",
        "plt.legend();\n",
        "plt.yscale('log')\n",
        "plt.xscale('log')\n",
        "plt.title('')\n",
        "plt.xlim(3.5, None)\n",
        "plt.ylim(1e9, None)"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "ML accelerated CFD data analysis.ipynb",
      "provenance": [
        {
          "file_id": "1qPDCx7Zctr9FZKnNeKBrPUncuODiiesh",
          "timestamp": 1635551846799
        }
      ]
    },
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.12"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}