{ "cells": [ { "cell_type": "markdown", "id": "4af04318-6cd5-49f3-bd41-ca7f0a1b1fd7", "metadata": {}, "source": [ "# `SurfTrack`\n", "SurfTrack operates on 3-D data `(time, lat, lon)` and uses:\n", "1. Morphological close→open to clean the binary field\n", "2. Area filtering to remove small noise objects\n", "3. 3-D connected-component labelling across time and space\n", "4. Date-line wrapping for global datasets\n", "\n", "For subsurface (4-D) tracking see the **DeepTrack** tutorial." ] }, { "cell_type": "markdown", "id": "a1728024-eaf0-4354-b61f-7b63a4f03036", "metadata": {}, "source": [ "### 1. Imports" ] }, { "cell_type": "code", "execution_count": 1, "id": "cb679949-1db2-4871-94d7-7ed22f28dab0", "metadata": {}, "outputs": [], "source": [ "import sys\n", "import os\n", "\n", "# Go up from notebooks/ to repo root\n", "repo_root = os.path.abspath(os.path.join(os.getcwd(), '..'))\n", "sys.path.insert(0, repo_root)" ] }, { "cell_type": "code", "execution_count": 2, "id": "b076159d-829c-4a07-8fe7-cbf2c1c2d990", "metadata": {}, "outputs": [], "source": [ "from ocetrac.SurfTrack import SurfTracker\n", "from ocetrac.preprocessing.cesm2_lens_utils import get_ds_var\n", "from ocetrac.preprocessing.preprocessing import calculate_anomalies_trend_features" ] }, { "cell_type": "code", "execution_count": 9, "id": "453bab10-23de-4029-bbe1-c2ad03fcda72", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import xarray as xr\n", "\n", "import cmocean\n", "import cartopy\n", "import cartopy.crs as ccrs\n", "import cartopy.feature as cfeature\n", "from cartopy.mpl.ticker import LongitudeFormatter,LatitudeFormatter\n", "from cartopy.util import add_cyclic_point\n", "import matplotlib.pyplot as plt\n", "import matplotlib.patches as mpatches\n", "from matplotlib.patches import Rectangle\n", "import matplotlib.dates as mdates\n", "\n", "import warnings\n", "\n", "warnings.filterwarnings(\"ignore\", message=\".*decode the variable.*\")\n", "warnings.filterwarnings(\"ignore\", message=\".*default value for data_vars.*\")" ] }, { "cell_type": "markdown", "id": "bf5ea225-9d19-4e20-b848-2a7df53b62fa", "metadata": {}, "source": [ "### 2. Data loading\n", "\n", "This section loads CESM2 Large Ensemble (CESM2-LENS) SST data for a single ensemble member. The CESM2-LE provides 100 ensemble members spanning 1850-2100.\n", "- Component: `atm` (atmosphere model component)\n", "- Temporal resolution: Monthly means" ] }, { "cell_type": "code", "execution_count": 16, "id": "d2a50747-5cac-4a6c-883f-84d124ef0c4c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Loaded: ('time', 'lat', 'lon') (433, 138, 288)\n", "CPU times: user 708 ms, sys: 52.4 ms, total: 760 ms\n", "Wall time: 940 ms\n" ] } ], "source": [ "%%time\n", "\n", "ens_memb_index = 0\n", "var, comp = 'SST', 'atm'\n", "directory = f'/glade/campaign/cgd/cesm/CESM2-LE/{comp}/proc/tseries/month_1/{var}/'\n", "\n", "ds_hist, _ = get_ds_var(directory, var, comp, ens_memb_index)\n", "\n", "nlat_low, nlat_high = 26, 328\n", "da_sst = ds_hist[var].sel(\n", " lat=slice(-65, 65),\n", " time=slice('1979-01', '2015-01')).compute()\n", "\n", "print(f\"Loaded: {da_sst.dims} {da_sst.shape}\")" ] }, { "cell_type": "code", "execution_count": 29, "id": "0ff3eeaf-f10f-437f-bb6b-f23f5a10b9ca", "metadata": {}, "outputs": [], "source": [ "# Replace 0s with NaN (land masking)\n", "da_sst_noland = da_sst.where(da_sst != 0, np.nan)" ] }, { "cell_type": "markdown", "id": "3c8b0791-7e10-490e-a1e8-17bd06609407", "metadata": {}, "source": [ "### 3. Anomaly computation\n", "\n", "This preprocessing step is separate from the Ocetrac tracking algorithm. It prepares the temperature field by the trend and seasonality.\n", "\n", "This example notebook uses `preprocessing.calculate_anomalies_trend_features`, which fits a 6-coefficient harmonic model per grid cell and returns the residual as well as provides the features. " ] }, { "cell_type": "code", "execution_count": 23, "id": "7534ba70-a63a-44c5-8fc8-14acf12cdf7f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "features shape: (433, 138, 288) (0.14 GB)\n", "CPU times: user 1.35 s, sys: 72 ms, total: 1.42 s\n", "Wall time: 1.52 s\n" ] } ], "source": [ "%%time\n", "\n", "mean, trend, seas, features, anom = calculate_anomalies_trend_features(\n", " da_sst, \n", " 0.9)\n", "\n", "print(f\"features shape: {features.shape} ({features.nbytes/1e9:.2f} GB)\")" ] }, { "cell_type": "code", "execution_count": 24, "id": "b4dadf3a-2ba4-422a-9dd7-182db59bedf8", "metadata": {}, "outputs": [], "source": [ "# Subset first 40 timesteps (months) for tutorial\n", "features = features.isel(time=slice(40))" ] }, { "cell_type": "code", "execution_count": null, "id": "1fd22d80-b320-4d53-9f8c-755cd25b564b", "metadata": {}, "outputs": [], "source": [ "da_sst_noland = da_sst.where(da_sst != 0, np.nan)" ] }, { "cell_type": "code", "execution_count": 28, "id": "f11f11f4-c263-4cde-ba34-d1051cde7a4d", "metadata": { "jupyter": { "source_hidden": true } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "## -------------- Figure of anom temperature and features\n", "\n", "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4))\n", "\n", "im1 = anom[30, :, :].plot.contourf(\n", " ax=ax1,\n", " levels=21, \n", " vmin=-2, \n", " vmax=2, \n", " cmap='RdBu_r',\n", " add_colorbar=False\n", ")\n", "ax1.set_title('Anom Temp at t=0', fontsize=12)\n", "ax1.set_xlabel('Longitude')\n", "ax1.set_ylabel('Latitude')\n", "\n", "im2 = features[30, :, :].plot.contourf(\n", " ax=ax2,\n", " levels=21, \n", " vmin=-2, \n", " vmax=2, \n", " cmap='RdBu_r',\n", " add_colorbar=False\n", ")\n", "ax2.set_title('Features at t=0', fontsize=12)\n", "ax2.set_xlabel('Longitude')\n", "ax2.set_ylabel('Latitude')\n", "\n", "cbar = plt.colorbar(im1, ax=[ax1, ax2], orientation='vertical', pad=0.05)\n", "cbar.set_label('Temperature anomaly (°C)', fontsize=10)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "641f6fe4-ce4f-409c-8865-c3287774795d", "metadata": {}, "source": [ "### 4. Build the ocean mask" ] }, { "cell_type": "code", "execution_count": 35, "id": "36a53156-a124-4615-9b9f-a27e7fb4e87b", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mask = xr.where(da_sst[0,:,:] == 0., 0., 1.)\n", "\n", "fig, ax = plt.subplots(figsize=(6, 4))\n", "mask.plot(ax=ax, cmap='Blues', add_colorbar=False)\n", "ax.set_title('Ocean mask (1 = ocean, 0 = land)')\n", "plt.tight_layout(); plt.show(); plt.close()" ] }, { "cell_type": "markdown", "id": "6650dceb-d0d0-42e0-bf6e-c981153e2cbe", "metadata": {}, "source": [ "### 5. Initialise and run the tracker\n", "\n", "| Parameter | Description |\n", "|---|---|\n", "| `radius` | Structuring element radius for morphological close→open. Larger fills wider gaps but risks bridging nearby separate events. |\n", "| `min_size_quartile` | Drop blobs below this percentile of the area distribution. Combined with `min_area_cells` via `max()`. |\n", "| `min_area_cells` | Absolute minimum blob size in grid cells. Always applied regardless of the percentile. |\n", "| `positive` | `True` → track warm anomalies; `False` → cold. |" ] }, { "cell_type": "code", "execution_count": 38, "id": "475da70f-51e0-47cf-afea-75c261a8684e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Step 1 · morphological cleaning …\n", " fraction flagged = 0.1022 (OK)\n", "Step 2 · area filtering …\n", "area threshold : 100 cells (floor=100, percentile=22.0)\n", "Step 3 · 3-D connected-component labelling …\n", " initial objects : 791\n", " final objects : 60\n", "Step 4 · wrapping result …\n", " final events: 60\n", "=======================================================\n", "SurfTracker — Result Summary\n", "=======================================================\n", " Input shape : (40, 138, 288)\n", " Tracked events : 60\n", " Duration min/median/max : 1 / 1 / 22\n", " >= 1 ts : 60\n", " >= 3 ts : 20\n", " >= 6 ts : 11\n", " >= 12 ts : 5\n", "\n", " Parameters:\n", " radius = 2\n", " min_area_cells = 100\n", " min_size_quartile = 0.25\n", " positive = True\n", "=======================================================\n", "CPU times: user 1.01 s, sys: 27.2 ms, total: 1.04 s\n", "Wall time: 1.18 s\n" ] } ], "source": [ "%%time\n", "tracker = SurfTracker(\n", " features,\n", " mask,\n", " radius = 2,\n", " min_size_quartile = 0.25,\n", " min_area_cells = 100,\n", " timedim = 'time',\n", " xdim = 'lon',\n", " ydim = 'lat',\n", " positive = True,\n", ")\n", "result = tracker.run()\n", "tracker.summary()" ] }, { "cell_type": "markdown", "id": "04c09b0a-b09d-461e-a226-23743950ca76", "metadata": {}, "source": [ "### 6. Attributes" ] }, { "cell_type": "code", "execution_count": 39, "id": "0b9e6749-171f-4883-a932-0a4fb97a8f84", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Attributes:\n", " initial objects identified 791\n", " final objects tracked 60\n", " radius 2\n", " size quantile threshold 0.25\n", " min area cells 100\n", " min area (effective) 100.0\n", " percent area reject 0.10522655374881522\n", " percent area accept 0.8947734462511848\n" ] } ], "source": [ "print(\"Attributes:\")\n", "for k, v in result.attrs.items():\n", " print(f\" {k:<30} {v}\")" ] }, { "cell_type": "markdown", "id": "b2b8ca4c-17a5-46c6-ab82-adfe7b10ec02", "metadata": {}, "source": [ "# Run steps separately" ] }, { "cell_type": "code", "execution_count": 40, "id": "706312e0-07c0-4371-9764-d25174fc7e59", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Step 1 · morphological cleaning …\n", " fraction flagged = 0.1022 (OK)\n", "Step 1 done — fraction flagged warm: 0.1022\n", "Step 2 · area filtering …\n", "area threshold : 100 cells (floor=100, percentile=22.0)\n", "Step 2 done — effective area threshold: 100 cells\n", " initial objects: 791\n", "Step 3 · 3-D connected-component labelling …\n", " initial objects : 791\n", " final objects : 60\n", "Step 4 · wrapping result …\n", " final events: 60\n", "Step 4 done — final events: 60\n" ] } ], "source": [ "tracker2 = SurfTracker(\n", " features, mask,\n", " radius=2, min_size_quartile=0.25, min_area_cells=100,\n", " timedim='time', xdim='lon', ydim='lat',\n", ")\n", "\n", "# Step 1 — morphological cleaning + masking\n", "tracker2.clean()\n", "frac = float(tracker2.binary_clean.values.mean())\n", "print(f\"Step 1 done — fraction flagged warm: {frac:.4f}\")\n", "\n", "# Step 2 — area filtering\n", "tracker2.filter()\n", "print(f\"Step 2 done — effective area threshold: {tracker2.min_area:.0f} cells\")\n", "print(f\" initial objects: {tracker2.N_initial}\")\n", "\n", "# Step 3 — 3-D connected-component labelling + date-line wrap\n", "tracker2.track()\n", "\n", "# Step 4 — package result\n", "tracker2.postprocess()\n", "print(f\"Step 4 done — final events: {tracker2.n_events()}\")" ] }, { "cell_type": "markdown", "id": "91acdf0e-db9e-45f1-be22-5d21136e3ab7", "metadata": {}, "source": [ "### 8. Plotting and Inspection" ] }, { "cell_type": "code", "execution_count": 41, "id": "f752258c-d2e0-4aab-81b1-0b99c21cf518", "metadata": {}, "outputs": [ { "data": { "image/png": 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PXkMnqdWJRFu6FNwl3gBQHcO2lHs9OZ8D5YY3NQxq9Vegn3766VFXVxejRo1qWFYqleKEE06IIUOGRO/evWOzzTaLl156qaLtBAD+RXYDQLHIbgAoaAX6U089FZdffnmsscYaTZafddZZMWbMmLj66qvjK1/5Spxyyimx1VZbxWuvvRb9+vXLZ/WaCnWg2rR24s6umgCl8fuYVLRicpvd7SG76YKJPItcod6e6jUVal3MJGTUWnYDXVZ1ToW15Tuv78fVW4H+8ccfx1577RVXXHFFDBw4sEn1+fnnnx8/+9nPYtddd43hw4fHb37zm/j000/j2muvrWibAaCWyW4AKBbZDQAF7kA/5JBDYvvtt49vfOMbTZaPGzcuJk6cGFtvvXXDsl69esWmm24ajz32WLOvN2PGjJg2bVqTW0WrzwFqRTrbXe6Md/3ycjcKKbfZ3R6ymy6sUG/uVs1VbKrgIB+qKruBZsndgvOducsUagiX6667Lp599tnsUrI5pRBPllhiiSbL0/233nqrxTHdTjzxxE5oLQAguwGgWGQ3ABS0A/3tt9+Oww8/PO65555YcMEFm10vTSzaWBraZc5ljR177LFxxBFHNNxPZ8KHDh3auVVoqtcA/k1ledXKZXa3l+wmR1pThd6ZY6h3drWa8dBzlssdOV56ei25n2tVld1AbirP0/sdUFqlS9+zapTLYVna5QrTgf7MM8/EpEmTYp111mlYNmvWrHjooYfiF7/4RTZhSX0l+uDBgxvWSc+Zsyq9sXS5WboBALIbAGqZ790AUOAO9C233DJeeOGFJst+8IMfxCqrrBLHHHNMLL/88rHkkkvGvffeGyNGjMgenzlzZjz44INx5plnRi5NLaloA6BqFSq7W5vJspuC6Oix0o2RWmVUrlEN2Q20i0yHKu5A79evXwwfPrzJsoUWWigWXXTRhuWjRo2K0047LVZaaaXsln7u06dP7LnnnhVqNQDULtkNAMUiuwGgwB3orTF69Oj47LPP4uCDD44pU6bEyJEjs7Hb0ocAACB/ZDcAFIvsBqDW1JXSbB80mcxkwIABMXXq1Ojfv3/lJhRLl4iXe4/65QC1aH4mMivA5eptyiA6b7+1N99lN1Wo0pd5m3AsBzpyEtGC5XJryG77DYqg0nmeyPQOzOAqydAiZXe3Tm8VAAAAAAAUUFUN4dLlOnMiseZeV0U6UMvqz7TPqxrOGXkqQXZTZfJQrVbfBlVrVVZ9Xv/a8hrIad5VS+7kIctpB5XnuaMCHQAAAAAAylCBPr+aG+8UqvRM9bzOxLd0hrtazuKTQyrYAKq6Ui21y+eIKqg6b+695DiQ4zwsWv7kMcuLtg9hTirQAQAAAACgvRXoa6+9drRFXV1d3HrrrbHUUktF1VN5TkG196z0/JzN7ooz4c5s1wiVavMku4EiV6pR5ZXnlCW7IZ+Z15bn+D5KbnN4ztf3nbrjO9Cff/75OPLII6Nv377zXLdUKsUZZ5wRM2bMaFtLAIAOI7sBoFhkNwAUfAz0o48+OhZffPFWrXvuuefOT5sAgA4guwGgWGQ3ABS0A33cuHGx2GKLtfpFX3755RgyZMj8tAvoRNV8qbZJxuBfZDcwr7ykhhmuJZdkN3SOWsq8vG2rIW1yMAxLc5mflhvGpWM70IcNG9b6V4yIoUOHtml9AKBjyW4AKBbZDQAFH8KlsY8++iiefPLJmDRpUsyePbvJY9///vejpkwt/Xsy0cY/d+V7Q4HPSANdQ3bnhOymgnwGIHdUvrVIdkP7sy5VPlci9xq/f6XeOy9Un3eB+ury5vJ0Xleczev5tL8D/c9//nPstdde8cknn0S/fv2iru7fByP9XHMd6ACQc7IbAIpFdgNAgTvQjzzyyNhvv/3itNNOiz59+nROq4peUdb453LV6PN6HGrgbDTQdWR3B5DdFJzPAeSOarcWyW6Yv6yrpdyrpW2tuVzsqjlL5vU+66lQ79bWffruu+/GYYcdpvMcAApCdgNAschuAChwBfo222wTTz/9dCy//PKd06JqkyrWWqoyNxYqnagWz0QbZw3mJrvbSHZDbsj1KqSKrVVkN7ROLX7nzTvZnQMdXbn+ZJnXq7E8b1UH+q233trw8/bbbx9HH310vPzyy7H66qtHjx49mqy70047dXwrAYA2kd0AUCyyGwDyqa5UKs3zlEG3bq0b6SVNIjpr1qwosmnTpsWAAQNi6tSp0b9//0o3B9qtFs/EO9NN0XVkBsluoKifCeR5F+iqMVVroFpNdld+v1G78pxvXZVledkHsrvK8rrKM31aOzKoVRXos2fPnt+2AQBdSHYDQLHIbgCokklEr7nmmpgxY8Zcy2fOnJk9BgDki+wGgGKR3QBQsCFcGuvevXtMmDAhFl988SbLJ0+enC0zhAtUTl4u3+pqLhejWnTW5cyyG2pHUT8LyPIauCS8wJd6t0R252u/UVvylnldmWV52nYZXmNDt1RBrrcng9pcgZ7629NY53N65513sjcHAPJFdgNAschuAMiPVo2BnowYMSLrOE+3LbfcMhZY4N9PTVXn48aNi2233baz2gkU5OxzV3O2G5onu6G2FPHzgByv8oq2AlenVYrshuLp6izLQ97L7xq1Xu3meqs70HfZZZfs3+effz622Wab6Nu3b8NjPXv2jGWXXTa+/e1vd04rAYA2k90AUCyyGwAK3IF+/PHHZ5Xmw4YNyzrQBw8e3LktA3JxZjmPnO2G1pHdUBuK9nlBjhdADVeYVZrshmLlXFdlWh72gfyuUT4TtH0M9DQJ2YEHHhiff/55W54GAFSI7AaAYpHdAFDQCvR6q6++eowdOzaWW265zmkRkJszzB3NGWuoDNkN1aWInxF8BigQlWa5ILshv1SdU3Vkf8dWoCennnpqHHXUUXHbbbfFhAkTYtq0aU1uAEC+yG4AKBbZDQAFrkDfdttts3932mmnqKv79yzupVIpu5/GSQcA8kN2A0CxyG4AKHAH+v333985LQEKe1l2OS7VhvyQ3VBMRf9M4LNADrlEuzBkN+QvBzs71/KwvbI7Z3n9ZF3HvyZd04G+6aabtu+dAICKkN0AUCyyGwAK3IGefPTRR3HllVfGK6+8kg3bsuqqq8Z+++0XAwYM6PgWQg3JwxnntnKGGopBdkMxFPGzQGM+F0DHkd3UojzmYDVXnsvtnFM1XtxJRJ9++ulYYYUV4rzzzosPP/wwPvjggxgzZky27Nlnn+2cVgIA7Sa7AaBYZDcA5EddKc3+2QYbb7xxrLjiinHFFVfEAgv8q4D9yy+/jB/+8IcxduzYeOihh6LIpk2bllXST506Nfr371/p5lAD8niGfU7OSkOxM0h2Q74V4bNAS3xOoJbJ7nztN4otb3nYFflWqW2W3dSyae3IoAXacya8ced59iILLBCjR4+Oddddt60vBwB0MtkNAMUiuwEgP9rcgZ565sePHx+rrNL0TNzbb78d/fr168i2QdXL2xn2xpyRhuohuyF/8vwZoC18XoDOIbuhsqo536p52yA3Y6Dvvvvusf/++8f111+fdZq/8847cd1112VDuHz3u9/tnFYCAO0muwGgWGQ3ABS4Av2cc86Jurq6+P73v5+NfZ706NEjDjrooDjjjDOis5x++ulx4403xquvvhq9e/eODTbYIM4888xYeeWVG9ZJw7mfeOKJcfnll8eUKVNi5MiR8ctf/jJWW221TmsXVEPFmTPQUN1kN1RGHjO/I/jcAJ1PdsO8s6cjcrZSmVaJzwjyG7qwAr1nz55xwQUXZB3Uzz//fDz33HPx4YcfxnnnnRe9evWKzvLggw/GIYccEk888UTce++9Wef91ltvHZ988knDOmeddVaMGTMmfvGLX8RTTz0VSy65ZGy11VYxffr0TmsXAOSd7AaAYpHdAJAfdaVUtl1A77//fiy++OJZx/omm2ySVZ8PGTIkRo0aFcccc0y2zowZM2KJJZbIKtV//OMft+p1zQZOLVajORMN+VDtGSS7qTV5zPyO4HMD/Jvs9r2brslNFejzT35D+7O7zUO4pIrvNFTLX//615g0aVLMnj27yeNjx46NrpA2MllkkUWyf8eNGxcTJ07MqtLrpYr4TTfdNB577LFmO9BTJ3u6Nd6JUO1fnAUn1BbZTa1qTQ53dCbmNfvbw+cFqBzZDfMmp+wj6Cpt7kBPk4Wmqu+99947Bg8enI2H3tVStfkRRxwRG220UQwfPjxbljrPk1Rx3li6/9Zbb7U4tnoaNx0AqpXsBoBikd0AUOAO9DvvvDNuv/322HDDDaNSDj300Pjb3/4WjzzyyFyPzdmhnzrbW+rkP/bYY7PO+MYV6EOHDu3gFlOLKlWB5iw8MCfZTS2ppgrwruBzA+ST7AbaQ65DTjrQBw4c2DBsSiX85Cc/iVtvvTUeeuihWHrppRuWpwlD6yvRU2V8vTTMzJxV6Y2lYV46c/JTAKg02Q0AxSK7AaDAHegnn3xyHHfccfGb3/wm+vTpE10lVZKnzvObbropHnjggVhuueWaPJ7up070e++9N0aMGJEtmzlzZjbcTJpEFDqbinMgr2Q3dGx+F6W6qyjtBOYmu6lFKbeay+X65dWSbfXbUc2fQ6CmO9DPPffc+Mc//pFVdS+77LLRo0ePJo8/++yz0RkOOeSQuPbaa+OWW26Jfv36NYx5nmZN7d27dzZMy6hRo+K0006LlVZaKbuln1Mn/5577tkpbQKAIpDdAFAsshsACtyBvssuu0QlXHLJJdm/m222WZPlV111Vey7777Zz6NHj47PPvssDj744JgyZUqMHDky7rnnnqzDHYpede4sM9BeshuicHk952cMnwOgtshuatX8VGYXkXyHYqgrpbFROsHvf//72GmnnWKhhRaKIkmTiKaq9qlTp0b//v0r3RxyTgc6UE0ZJLupBl2RzV3xZVcHOhSD7C7mfqO4ea7DGahEBnWLTvLjH/84/vnPf3bWywMAHUx2A0CxyG4AyOEQLq3VSYXtUFOV586uA11JdkN++AwAtIbsphYnFAXoap1WgQ4AAAAAAEXWaRXoUK2aG5N0fs+OqzQDgK4xP9ktrwGga8hcIC9UoAMAAAAAQBkq0KGVmqtSm5/Kc2fUAaDjtDaTW7uenAYAADqtAn3YsGHRo0cPexgACkJ2A0CxyG4AyGEF+ttvvx11dXWx9NJLZ/effPLJuPbaa2PVVVeNH/3oRw3rvfjiix3bUqigjpz9WzUb0NVkN7Wgo7JaTgN5ILsBoMAV6HvuuWfcf//92c8TJ06MrbbaKutE/6//+q846aSTOqONAMB8kN0AUCyyGwAK3IGeKsvXW2+97Oc//OEPMXz48HjssceyKvSrr766M9oIVSFVtKlqAypBdlPtlecdeaUYQB7IbgAocAf6F198Eb169cp+/stf/hI77bRT9vMqq6wSEyZM6PgWAgDzRXYDQLHIbgAocAf6aqutFpdeemk8/PDDce+998a2226bLX/vvfdi0UUX7Yw2AgDzQXYDQLHIbgAocAf6mWeeGZdddllsttlm8d3vfjfWXHPNbPmtt97aMLQLVAuXhQPVQHYDQLHIbgDIjwXa+oTUcf7BBx/EtGnTYuDAgQ3Lf/SjH0WfPn06un0AwHyS3QBQLLIbAApcgZ6USqV45plnskr06dOnZ8t69uypAx0Ackp2A0CxyG4AKGgF+ltvvZWNez5+/PiYMWNGbLXVVtGvX78466yz4vPPP8/GRwcA8kN2A0CxyG4AKHAF+uGHHx7rrrtuTJkyJXr37t2w/Fvf+lb89a9/7ej2AQDzSXZD6xxQWsWuAnJBdgNAgSvQH3nkkXj00UezIVsaGzZsWLz77rsd2TYAoAPIbgAoFtkNAAWuQJ89e3bMmjVrruXvvPNONpQLAJAvshsAikV2A0CBO9DTmOfnn39+w/26urr4+OOP4/jjj49vfvObHd0+AGA+yW4AKBbZDQD5UVdKU3u3wXvvvRebb755dO/ePV5//fVsPPT076BBg+Khhx6KxRdfPIps2rRpMWDAgJg6dWr079+/0s0hJ66oe7XNY6g2fo4xVYFKZpDspha0NavnJKuB9pDd7eN7NwBFyqA2j4E+ZMiQeP755+P3v/99PPvss9mlZfvvv3/stddeTSYVBQDyQXYDQLHIbgDIjzZ3oCepo3y//fbLbgBA/sluACgW2Q0ABR0DPfntb38bG220UXZW/K233sqWnXfeeXHLLbd0dPugJi8jB+hoshvmnd3yG8gT2Q0ABe1Av+SSS+KII46I7bbbLqZMmRKzZs3Klg8cOLDJ5KIAQD7IbgAoFtkNAAXuQL/oooviiiuuiJ/97GexwAL/HgEmTSb6wgsvdHT7AID5JLsBoFhkNwAUuAN93LhxMWLEiLmW9+rVKz755JOOahcA0EFkNwAUi+wGgAJPIrrccsvF888/H8OGDWuy/M4774xVV121I9sGuXJAaZWGn9s6Rmpav/HzAbqS7KYWzZm7rc3u+vXkNlBJshsACtyBfvTRR8chhxwSn3/+eZRKpXjyySfj97//fZx++unxq1/9qnNaCQC0m+wGgGKR3QBQ4A70H/zgB/Hll1/G6NGj49NPP40999wzllpqqbjgggtijz326JxWQoGrzwEqTXZTC+ZVMS7LgSKR3QBQ0A701HH+u9/9Lnbcccc44IAD4oMPPojZs2fH4osv3nktBADaTXYDQLHIbgAo8CSiCyywQBx00EExY8aM7P6gQYN0ngNAjsluACgW2Q0ABe5AT0aOHBnPPfdc57QGCsCkYkDRyG6YO8vlOZBnshsACjwG+sEHHxxHHnlkvPPOO7HOOuvEQgst1OTxNdZYoyPbBwDMJ9kNAMUiuwEgP+pKpVKpLU/o1m3uovW6urpIL5P+nTVrVhTZtGnTYsCAATF16tTo379/pZtDTrVnIlGVbkClMkh2Q9vzXG4DrSG728f3bgCKlEFtrkAfN25ce9oGAFSI7AaAYpHdAFDgMdCHDRvW4i0PLr744lhuueViwQUXzIaZefjhhyvdJKqMsVOBIpHdUJ4qcyCvZDcA5EebK9BvvfXWssvT8C2pw3rFFVfMOq8r5frrr49Ro0ZlnegbbrhhXHbZZbHddtvFyy+/HMsss0zF2gUAlSK7AaBYZDcAFHwM9Poxz5sbB32jjTaKm2++OQYOHBiVmK187bXXjksuuaRh2Ve/+tXYZZdd4vTTT5/n843FRmeNqarKDahUBsluaPs46HIbaA3Z7Xs3ANWf3W0ewuXee++Nr33ta9m/6Y3SLf283nrrxW233RYPPfRQTJ48OY466qjoajNnzoxnnnkmtt566ybL0/3HHnus7HNmzJiR7bjGNwCoJrIbAIpFdgNAgYdwOfzww+Pyyy+PDTbYoGHZlltumQ3f8qMf/SheeumlOP/882O//faLrvbBBx/ErFmzYokllmiyPN2fOHFi2eekqvQTTzyxi1oIAF1PdkPz6ivNm6tEB6gE2Q1NtSanXT0GdJY2V6D/4x//KFvenpaNHTs2+3mllVbKOrMrJQ0j01j90DLlHHvssQ2V9On29ttvd1ErAaBryG4AKBbZDQAF7kBfZ5114uijj47333+/YVn6efTo0dnQLsnrr78eSy+9dHS1QYMGRffu3eeqNp80adJcVen1evXqlXX+N74BQDWR3QBQLLIbAAo8hMuVV14ZO++8c9ZBPnTo0Kyye/z48bH88svHLbfckq3z8ccfx89//vPoaj179sw+aKTx4r71rW81LE/3U5uhkkwsClSK7Ib5z22XhQNdSXZD24dcMzE4kJsO9JVXXjleeeWVuPvuu+Pvf/97NjzKKqusEltttVV06/avgvZddtklKuWII46IvffeO9Zdd91Yf/31s/HaUwf/gQceWLE2AUAlyW4AKBbZDQAF7kBPUtX5tttuG5tttlk2BEpz44tXwu677x6TJ0+Ok046KSZMmBDDhw+PO+64I4YNG1bppkHZM+Qq2oCuILuhZSmPTSQK5InsBoCCjoE+e/bsOPnkk2OppZaKvn37xrhx47LlaciWdJlZHhx88MHx5ptvxowZM+KZZ56JTTbZpNJNAoCKkd0AUCyyGwAK3IF+yimnxNVXXx1nnXVWNuZ4vdVXXz1+9atfdXT7oFBS5Vpbq9fa8xyAtpDdAFAssptaVP/duNyto14XoEs60K+55ppsXPG99torunfv3rB8jTXWiFdf9ccIAPJGdgNAschuACjwGOjvvvturLjiimUvMfviiy86ql1UsbpWnLYpzY6aYzx0oLPIbgAoFtlNLWlNZXhHVY/73g10SQX6aqutFg8//PBcy//4xz/GiBEj2tUIAKDzyG4AKBbZDQAFrkA//vjjY++9987OiKeq8xtvvDFee+217BKz2267rXNaCQC0m+wGgGKR3QBQ4Ar0HXfcMa6//vq44447oq6uLo477rh45ZVX4s9//nNstdVWndNKqmLYlvpbW9cvd2vve7fn+V3JpCZAZ5DdAFAsshvy8727syY3Baq4Aj3ZZpttshsAUAyyGwCKRXYDQIE70KHS8lxFPr/qz2IfUFql1euW05rnAwCyEwBqTVu+d8/rdXz3hurXqg70gQMHZsO1tMaHH344v20CAOaT7AaAYpHdAFDgDvTzzz+/4efJkyfHKaeckl1Otv7662fLHn/88bj77rvj5z//eee1FDq5gr00e/5ft/7Mc2ePhWasNWBeZDcAFIvshnzxvRuoV1cqlUrRBt/+9rdj8803j0MPPbTJ8l/84hfxl7/8JW6++eYosmnTpsWAAQNi6tSp0b9//0o3p2oUYciVjuhA78igbekysNa8vsvIoHg6K4NkNwB0Dtmdr/1GMVWyo3p+v3fP6zWA6sigNneg9+3bN55//vlYccUVmyx//fXXY8SIEfHxxx9HkQnyzqEDvX0aB3FbP1QIcSiezsog2Q0AnUN252u/kV95ruaen+/dcz4fqM4ManNd8KKLLho33XTTXMtT5Xl6DADIF9kNAMUiuwGgYGOgN3biiSfG/vvvHw888EDDGOhPPPFE3HXXXfGrX/2qM9pIQRWh6ryaz9K35bnOmEN1k90AUCyym2qS5+rzjmhf/fN9r4bq1eYO9H333Te++tWvxoUXXhg33nhjpBFgVl111Xj00Udj5MiRndNKAKDdZDcAFIvsBoACd6AnqaP8d7/7Xce3BgDoFLIbAIpFdgNAPnRr7eDqbTF9+vT2tocaUpo9962S7ahl6ZKz+htQHWQ3ABSL7IZi830aarwDfeDAgTFp0qRWv+hSSy0VY8eOnZ92AQDzQXYDQLHIbgAo8BAuaZzzNEFo3759W/WiX3zxxfy2ixrVuBK8yJOQtjR5SN7PSjdun0lQoLhkNwAUi+yG+TPn99dKfPf2fRpquAN9mWWWiSuuuKLVL7rkkktGjx495qddAMB8kN0AUCyyGwAK3IH+5ptvdn5LoJlq9CJXojd3VjzvVej1nD2H4pLdAFAssptq1dHfgYtypXTa5qK0FWhZlXVNAgAAAABAF1agQzWPi97SazZ+747U+Cy0anQAalV7cr2zshkA6Dzt+Q48v9XbRfzeDeSTCnQAAAAAAChDBzoAAAAAAJRhCBe63Pxcet3VE4uWe5+OvnS8NZeV5W3iUZOLAlApc2azIV0AoFjyOrFmZ3zv9t0ZqkO7uiEffvjh+N73vhfrr79+vPvuu9my3/72t/HII490dPsAgA4guwGgWGQ3ABS0A/2GG26IbbbZJnr37h3PPfdczJgxI1s+ffr0OO200zqjjRRUqggrd+vo165E5Vv9rVbOxM/rjHr9Dcgn2U0168xc7uzclJ1Ac2Q3VB/5D8XV5q8ap5xySlx66aVxxRVXRI8ePRqWb7DBBvHss892dPsAgPkkuwGgWGQ3ABR4DPTXXnstNtlkk7mW9+/fPz766KOOahe0WuMq9K6uPkvv11VV8K0ZK73SUruKWEUP1U52Uyu6Mpc7SnsyXdZC9ZPdUBld9b3b2OhQLG3ubhw8eHC88cYbcy1P458vv/zyHdUuAKCDyG4AKBbZDQAFrkD/8Y9/HIcffnj8+te/jrq6unjvvffi8ccfj6OOOiqOO+64zmklFKAavaMUvaqs/kx6e7fjnahr1XpLR6ldrw+1SHaT59wual5X0pwVcUX/7ADMTXZDx6rPyjxezV2uTbIdCt6BPnr06Jg6dWpsvvnm8fnnn2fDufTq1SvrQD/00EM7p5UAQLvJbgAoFtkNAPlRVyqV2lXG+emnn8bLL78cs2fPjlVXXTX69u0b1WDatGkxYMCA7CRBGted6tAV1W1dOeZqHs+at6S1Z89bW30+L6rTKarOziDZTS1ldV7HQu/MDFetBl1Pdudzv0FHVH1X+nu3XIf8ZFCbK9Dr9enTJ9Zdd932Ph0A6GKyGwCKRXYDQOW1qgN91113bfUL3njjjfPTHgCgA8huACgW2Q0A+dSqi2VTWXv9LZW2//Wvf42nn3664fFnnnkmW5Ye7wxvvvlm7L///rHccstF7969Y4UVVojjjz8+Zs6c2WS98ePHx4477hgLLbRQDBo0KA477LC51qE25fUy7lrR1Ze+paFg6m9Qq2Q3RSOrOyZv629A8chu6NrhUea85Y08h4JVoF911VUNPx9zzDHxne98Jy699NLo3r17tmzWrFlx8MEHd9rYZa+++mo21vpll10WK664Yrz44otxwAEHxCeffBLnnHNOQxu23377WGyxxeKRRx6JyZMnxz777BNpiPeLLrqoU9oFAHkluwGgWGQ3AFTJJKL1HdQrr7xyk+WvvfZabLDBBlnHdVc4++yz45JLLomxY8dm9++8887YYYcd4u23344hQ4Zky6677rrYd999Y9KkSa3u3DeZSfXrrAlFTSI6b/M6q9/ZFeMmFyXvOiuDZDe1mNV5rWjvymqyPFbTQbWR3b53U73yUAEuyyEf2d3mrydffvllvPLKK3MtT8tSlXhXSRu5yCKLNNx//PHHY/jw4Q2d58k222wTM2bMyIaYAYBaJbsBoFhkNwAUbAiXxn7wgx/EfvvtF2+88UZ8/etfz5Y98cQTccYZZ2SPdYV//OMf2bAs5557bsOyiRMnxhJLLNFkvYEDB0bPnj2zx5qTOtjTrfFZCKpbqkjryCr0SlS41Z+FzsMZ8bZorr1ddVa9uQp3lelUO9lNLWZ1en5eq9BrJXeB9pPdUHl5+N7d+L3lNxSoAz2NOb7kkkvGeeedFxMmTMiWDR48OEaPHh1HHnlkm17rhBNOiBNPPLHFdZ566qlYd911G+6/9957se2228Zuu+0WP/zhD5usW1c3d+dYGqGm3PJ6p59++jzbAABFJrsBoFhkNwAUeAz0xuqrtds7TusHH3yQ3Vqy7LLLxoILLtjQeb755pvHyJEj4+qrr45u3f5dmnTcccfFLbfcEv/7v//bsGzKlCnZMC/33Xdf9rzWVqAPHTq0w8ef7Wx979ugyf2Pt3isYm0pkvZWtxWxoi3P1erlzqR39njoraEyna7WFfNwyG6KwjjoXUdFG7Sf7K6t793Urjx8n5bXULnsbnMFemPzG3SDBg3Kbq3x7rvvZmG8zjrrZLOTN+48T9Zff/049dRTs6r4VBGf3HPPPdGrV6/sOc1Jj6cbANQC2Q0AxSK7AaBgFejLLbdci0OijB07NjpaqjzfdNNNY5lllolrrrkmunfv3vBYGk4mmTVrVqy11lrZOOhnn312fPjhh7HvvvvGLrvsko2XnqcKgs6gAr3zq9uKWHWe9zPo8zqTnocq9HJUptNZOiuDZDe1WoWe5+zOUw53dI6X2zZVc1Qr2V1b37upbZXOblkKBapAHzVqVJP7X3zxRTz33HNx1113xdFHHx2dIVWSp0lL023ppZdu8lh9/3/qVL/99tvj4IMPjg033DB69+4de+65ZzZ2HADUMtkNAMUiuwGgSsZAb+yXv/xlPP3009nwKkVW1DPhKtDbRwV6PqhAh8pkkOwm71SgF4MKdGqZ7C7GfoOOoAIdqkN7MqjDOtDT0C1pCJX6ycmKqlo60Bszoej8fznP8yXgRflA0N7LzfI6jEtzDO9CkTJIdlPNHeh5z+5KfwnPG5elU1Syuxj7DTozu5vLsI7OelkJlcug+RxZ8t/+9Kc/ZTNvAwDFILsBoFhkNwB0vTaPgT5ixIgmk4imAvaJEyfG+++/HxdffHFHt48Oqk5XhU5Hn9Fuy9n0+TlTXl/RXZRK9DnbqSKdPJDdkD/12agSvX1VfVDtZDfkTyWzWx5CwTrQd9555yYd6N26dYvFFlssNttss1hlFR9wASBvZDcAFIvsBoD86LAx0KtFNY6BnqhAn79xVvM+jmqtKEoV+ryoSqfaMqjS7Lfq156x0IuU3arQ20YVHnkig+w36Mh8l3FQJWOgd+/ePSZNmjTX8smTJ2ePAQD5IrsBoFhkNwAUeAiX5grWZ8yYET179uyINkFFpEq19lS40XWKNh56c+rbrxKdriK7Kbpqz2jjobe9ok+FHtVOdkPtXUUm26AKOtAvvPDC7N80/vmvfvWr6Nu3b8Njs2bNioceesgY6ACQI7IbAIpFdgNAgTvQzzvvvIYz4ZdeemmT4VpS5fmyyy6bLQcA8kF2A0CxyG4AKHAH+rhx47J/N99887jxxhtj4MCBndkuOmjyUKhGaeiTog/jkjS3DYZ2oaPIbgAoFtkNtcfQLVCFY6Dff//9ndMSAKBTyG4AKBbZDQAF60A/4ogj4uSTT46FFloo+7klY8aM6ai2UYFK9Y+3eMx+pxCqZULRcsptk6p02kp2U40TiSbVPJloV1W2deSEZ0DHkd0AHavu6N+WXV46e2+7mo7vQH/uuefiiy++yH5+9tlns4lEAYD8kt0AUCyyGwAK3IHe+PKxBx54oDPbQ04q1Wu1El11W/E0rsyuxmr0xtumCp22kN1Uc1a3pgo9rVOf67WopfFUGz+mGh3yQ3bXoDmLE0v//m4DdE1lump0WqPNF8Hut99+MX369LmWf/LJJ9ljAEC+yG4AKBbZDQD5UVcqte0UZ/fu3WPChAmx+OKLN1n+wQcfxJJLLhlffvllFNm0adNiwIABMXXq1Ojfv39Uy9jmbVWrFegUW2dWoLel+ruz2qECvQu1NFRZJ1YGdVYGyW6q1bwq0YtWgd7eavCWqs274v27WkdtL3QE2Z2v/ZZ77R0OV2V6rnVUfsq3rhsDvTmq0WvDtHZk0AJtefHU155uqQJ9wQUXbHhs1qxZcccdd8zVqQ4AVI7sBoBikd0AkD+t7kBfeOGFs8lD0+0rX/nKXI+n5SeeeGJHtw+gzRXaHVUBruK7BrSnCqi55+SwMkh2U+1aOx46XVP5VpQKdsgz2V2l2lt5Xu75OfzMSXVcica/KtZVoTNfHehpQpNUfb7FFlvEDTfcEIssskjDYz179oxhw4bFkCFDWvtyAEAnk90AUCyyGwAK3IG+6aabZv+OGzcuhg4dGt26KfcBgDyT3QBQLLIbAArcgV4vVZonn376aYwfPz5mzpzZ5PE11lij41oH0A7VOPRKNW5T1am/tDaHl9XKbsi3ahn6ZM5LyKtlu6ASZDctfubM4edNKqc+bw3lMrc0HEtbJxJtvL7hXGh3B/r7778fP/jBD+LOO+8s+3iaUBQAyA/ZDQDFIrsBoMAd6KNGjYopU6bEE088EZtvvnncdNNN8c9//jNOOeWUOPfcczunlTTr4y0eK7u8730bdMjrAJWl8rxKJomqcJWQ7KbaJxJNTCaaP62thGttpbrKOmqJ7KZFJhWFVquvIm9rJXr9c1Sh064O9Pvuuy9uueWW+NrXvpaNg54uLdtqq62if//+cfrpp8f2229vzwJAjshuACgW2Q0ABe5A/+STT2LxxRfPfl5kkUWyS8u+8pWvxOqrrx7PPvtsZ7SRdlBRDpDzqvQurFCX3Tn+XTCGKagshzJkN9BW6YouV2t17HjoiTHRSbq1dTesvPLK8dprr2U/r7XWWnHZZZfFu+++G5deemkMHjzYXgWAnJHdAFAsshsACj4G+oQJE7Kfjz/++Nhmm23id7/7XfTs2TOuvvrqzmgjVMbJzVSM/rzU9LF0H8hnZXdRKnzTdnRiO2V3jn9XW1OR3txzi/C7XYGx0IuocbVYa8YDV10G1U92Q3HU53Jr5/SguOqr0Y2LXnva3IG+1157Nfw8YsSIePPNN+PVV1+NZZZZJgYNGtTR7QMA5pPsBoBikd0AUOAO9Dn16dMn1l577Y5pDQDQ6WQ3ABSL7AaAnHegH3HEEa1+wTFjxsxPeyDfw7eUe6z+vqFc+D9Lx7+GVXgnWjG8CPM/REtXvEZX6OB2yu6CHtu2rmsYl5pi6BboQhUYPkt2A3Su+qFX2jOZKLWtVR3ozz33XKterK4onRQAUOVkNwAUi+wGgAJ3oN9///2d3xKo5qp11enQNk7Izreazu7WTMxZiXZ01nuoQgfo+L+tFVDT2V3NfK6FXFaiz08VenquiURrS7dKNwAAAAAAAKpyEtGaUIHx76ji6nTV6LRB43HU68dWB5oxYEBtVpr5nALQ+X9TIa+/K/Xt0D9RMVfUvVq5N6fdjIdOW6hABwAAAACAMlSg572KjcpIVeItjWk+P1SjMx/V6KrQIcfyUolWT0UaQNv/ZnbUegAUQuOxzOdnXHSqW+Eq0GfMmBFrrbVW1NXVxfPPP9/ksfHjx8eOO+4YCy20UAwaNCgOO+ywmDlzZsXaCgDIbgAoGt+7AaDAFeijR4+OIUOGxP/+7/82WT5r1qzYfvvtY7HFFotHHnkkJk+eHPvss0+USqW46KKLOqcxqfqguXHG2lOZYMyy2qlCr6caHagBucrujlaESsSWPq8AUIy/5V2sqrMbCuiA0irzHGs9rUPHVaNDYSvQ77zzzrjnnnvinHPOmeuxtPzll1+O//7v/44RI0bEN77xjTj33HPjiiuuiGnTplWkvQBQ62Q3ABSL7AaAgnag//Of/4wDDjggfvvb30afPn3mevzxxx+P4cOHZ2fJ622zzTbZpWfPPPNMF7cWAJDdAFAsshsACjqES7ocbN99940DDzww1l133XjzzTfnWmfixImxxBJLNFk2cODA6NmzZ/ZYc1IHe7rVa3O1usv9gGakCT/TxJ+0Q/1wE/7GFlaustvvkQlFq0T9pdsu0YYOIh/ym93AXHkv/6FGK9BPOOGEbDLQlm5PP/10NpZaCthjjz22xddL65f7EFBueb3TTz89BgwY0HAbOnRoh2wbAFQj2Q0AxSK7AWD+1JVSD3OFfPDBB9mtJcsuu2zsscce8ec//7lJR3iavKR79+6x1157xW9+85s47rjj4pZbbmkyycmUKVNikUUWifvuuy8233zzVp8JT53oUyOif3QxE3zlW2dPKJomLaWqzVmNnirUmYcaqwxLtVgDImLq1KnRv3+Xp1CryO6C81kj9+Y1QVg9VWiQj88Wsns+v3fn+DNPYT6nyvbCZXhL5Dt0vpRBqYi6LRlU0SFcBg0alN3m5cILL4xTTjml4f57772XjW9+/fXXx8iRI7Nl66+/fpx66qkxYcKEGDx4cMPEor169Yp11lmn2ddOj6cbACC7AaDa+N4NADUwBvoyyyzT5H7fvn2zf1dYYYVYeumls5+33nrrWHXVVWPvvfeOs88+Oz788MM46qijsolHC3FG21nj/GtcId6eanQV5jVPxXk7/zbmpbqHNqmJ7IZOUF951hFVbMD/8VmiVWQ3dFz1eHtyXPU55FdFx0DvSGk4l9tvvz0WXHDB2HDDDeM73/lO7LLLLnHOOedUumkAQBmyGwCKRXYDUIsqOgZ6rsfB6Yox0O16gNargeqxIoyjGrWe3UXns0ehtFS9pkoN8vH5QXZ33fizXfL70Zac7OrPpjK8anNdpkP+M6hqKtABAAAAAKAj6UAHAAAAAICiTiJadVx6BTB/fztrYDgXAJd0w3zyeaG2tHS8y30Hz/vvh36DqiPXobhUoAMAAAAAQBkq0OeHM8IAQBH4zALUirxXFVOZ494ZvxeyFaBmqEAHAAAAAIAyVKADAFQjlXFArVB1Tmf/LslUgJqmAh0AAAAAAMpQgQ4AUA1UxwEAAHQ4FegAAAAAAFCGCnQAgCJScQ4AANDpVKADAAAAAEAZOtABAAAAAKAMQ7gAAOSN4VkAIB9kMkDNU4EOAAAAAABlqEAHIL/q6irdAugaqtsAIF9kMwD/RwU6AAAAAACUoQIdAKAzqWADgGKR3QA0ogIdAAAAAADKUIE+L848AwDt4TMEAOQjc1s7r47sBqAMFegAAAAAAFCGDnQAAAAAAChDB3pzpk51+RZApbmMlqLyuwvQ+dKwHK0dmoPalnJZNgPQTjrQAQAAAACgDJOIApBvjauFqqHKrKXqp2nTIgYM6MrW1IbOrDgr9zupwg0A8illdHOfJ+U3AM1QgQ4AAAAAAGXoQAegeONXFm0cyyK2ucjzl3Tl70lXvx8AlVPub37KHop/HOU3AC3QgQ4AAAAAAGUYAx2A4sr7+OiqmQCg2J8DZDkA1DwV6AAAAAAAUIYKdACqQ2dUiLW3mk21GgB0LdkLAHQSFegAAAAAAFCGDnQAAAAAACjDEC4A0ByXgwMAAEBNU4EOAAAAAABl6EAHAAAAAICid6DffvvtMXLkyOjdu3cMGjQodt111yaPjx8/PnbcccdYaKGFsscPO+ywmDlzZsXaCwC1TnYDQLHIbgAo6BjoN9xwQxxwwAFx2mmnxRZbbBGlUileeOGFhsdnzZoV22+/fSy22GLxyCOPxOTJk2OfffbJ1rvooosq2nYAqEWyGwCKRXYDwNzqSqmHOee+/PLLWHbZZePEE0+M/fffv+w6d955Z+ywww7x9ttvx5AhQ7Jl1113Xey7774xadKk6N+/f6vea9q0aTFgwICYOnVqq58DAB2hmjJIdgNQC2S3790AVH92F2IIl2effTbefffd6NatW4wYMSIGDx4c2223Xbz00ksN6zz++OMxfPjwhs7zZJtttokZM2bEM888U6GWA0Btkt0AUCyyGwAK3IE+duzY7N8TTjgh/t//+39x2223xcCBA2PTTTeNDz/8MHts4sSJscQSSzR5XlqnZ8+e2WPNSR3s6cxD4xsAILsBoJb43g0AOexATx3idXV1Ld6efvrpmD17drb+z372s/j2t78d66yzTlx11VXZ43/84x8bXi/dn1Maoabc8nqnn356VrZffxs6dGgnbS0AFJ/sBoBikd0AUOBJRA899NDYY489WlwnjX0+ffr07OdVV121YXmvXr1i+eWXj/Hjx2f3l1xyyfif//mfJs+dMmVKfPHFF3NVpjd27LHHxhFHHNFwP1Wg60QHANkNANXA924AKHAH+qBBg7LbvKSK89Rh/tprr8VGG22ULUsd42+++WYMGzYsu7/++uvHqaeeGhMmTMjGSE/uueee7Hnp+c1Jj6cbACC7AaDa+N4NAAXuQG+tNCPqgQceGMcff3xWHZ46zc8+++zssd122y37d+utt84q1Pfee+/ssTQ2+lFHHRUHHHBAq2dUBQBkNwDUIt+7AaDAHehJ6hRfYIEFsg7yzz77LEaOHBn33XdfNlFo0r1797j99tvj4IMPjg033DB69+4de+65Z5xzzjmVbjoA1CTZDQDFIrsBYG51pTTLJk3GQE+TiU6dOlXlOgBdSgbZbwAUi+y23wCo/uzu1umtAgAAAACAAtKBDgAAAAAAZehABwAAAACAMnSgAwAAAABAGTrQAQAAAACgjAXKLaxlpVKpYUZWAOhK9dlTn0W0juwGoFJkd/vIbgCKlN060Ocwffr07N+hQ4d25LEBgDZl0YABA+yxNuyvRHYDUCmyu+37K5HdABQhu+tKytyamD17drz22mux6qqrxttvvx39+/ePaj3bkj6sVPM2Jrazujie1cXxnFuK5BTiQ4YMiW7djLLWWrK7uvjbUF0cz+rieM5NdreP7K4u/jZUF8ezujieHZPdKtDnkHbcUkstlf2cOparuXO5VrYxsZ3VxfGsLo5nUyrP2052Vyd/G6qL41ldHM+mZHfbye7q5G9DdXE8q4vjOX/ZrbwNAAAAAADK0IEOAAAAAABl6EAvo1evXnH88cdn/1arWtjGxHZWF8ezujie+H3y/4y/DT6LVQuZVl1q5XhWWi3s51rYxsR2VhfHs7o4nh3DJKIAAAAAAFCGCnQAAAAAAChDBzoAAAAAAJShAx0AAAAAAMrQgT6Hiy++OJZbbrlYcMEFY5111omHH344iuyEE06Iurq6Jrcll1yy4fFSqZStM2TIkOjdu3dsttlm8dJLL0XePfTQQ7Hjjjtm7U7bdPPNNzd5vDXbNWPGjPjJT34SgwYNioUWWih22mmneOedd6Io27jvvvvOdWy//vWvF2obk9NPPz2+9rWvRb9+/WLxxRePXXbZJV577bWqO56t2c5qOKaXXHJJrLHGGtG/f//stv7668edd95ZVcdyXttYDcexaGS37M4L2R1V9fdedlfPsZTd+SO7ZXdeyO6oqr/3srt6juUlOfverQO9keuvvz5GjRoVP/vZz+K5556LjTfeOLbbbrsYP358FNlqq60WEyZMaLi98MILDY+dddZZMWbMmPjFL34RTz31VNa5vtVWW8X06dMjzz755JNYc801s3aX05rtSsf6pptuiuuuuy4eeeSR+Pjjj2OHHXaIWbNmRRG2Mdl2222bHNs77rijyeN538bkwQcfjEMOOSSeeOKJuPfee+PLL7+MrbfeOtv+ajqerdnOajimSy+9dJxxxhnx9NNPZ7ctttgidt5554awroZjOa9trIbjWCSyW3bn6f8d2S27i/g3X3b/i+zuOrJbdufpb6Dslt2yu5ifT7o8u0s0WG+99UoHHnhgkz2yyiqrlH76058Wdi8df/zxpTXXXLPsY7Nnzy4tueSSpTPOOKNh2eeff14aMGBA6dJLLy0VRfo1vummm9q0XR999FGpR48epeuuu65hnXfffbfUrVu30l133VXK+zYm++yzT2nnnXdu9jlF28Z6kyZNyrb3wQcfrNrjWW47q/mYDhw4sPSrX/2qao9l422s5uOYV7Jbduf1/x3ZXX1/72V39RzLRHZXjuyW3Xn9+yC7ZXc15Jrv3Z1zHFWg/5+ZM2fGM888k1WENpbuP/bYY1Fkr7/+enbZRhqaZo899oixY8dmy8eNGxcTJ05sss29evWKTTfdtNDb3JrtSsf6iy++aLJO2kfDhw8v1LY/8MAD2XAgX/nKV+KAAw6ISZMmNTxW1G2cOnVq9u8iiyxS1cdzzu2sxmOazuqmM72pqiNdblWNx3LObazG45hnsvtfZHex/t+pxr8Psrt6jqnsro7jmGey+19kd7H+35Hdxfyulvje/S++d8//7+sCbX5Glfrggw+yD4xLLLFEk+XpfurwKaqRI0fGNddck30Q/Oc//xmnnHJKbLDBBtklD/XbVW6b33rrrSiq1mxXWqdnz54xcODAwh7vNLzQbrvtFsOGDcs6Jn/+859nl7SkUEt/HIu4jemk/xFHHBEbbbRR9ketWo9nue2spmOaholKncmff/559O3bN7tkatVVV20IqWo4ls1tYzUdxyKQ3f8mu4vx/041/n2Q3dVxTGV3dRzHIpDd/ya7i/H/juwu3ne1er53+97dswN/X3WgzyENOj/n/3BzLiuS9Me+3uqrr551+Kywwgrxm9/8pmFw/Wrb5nrt2a4ibfvuu+/e8HPqhF133XWzD/2333577LrrroXcxkMPPTT+9re/ZWNTVfPxbG47q+WYrrzyyvH888/HRx99FDfccEPss88+2Rjw1XQsm9vG1IleLcexSKotx2R3sf8+tKQa/z7I7uo4prK7Oo5jkcju6vn9qYbP9i2R3cU9nr53F///zZVz9L3bEC7/J83I2r1797nOQqRL9+asliyyNOts6khPw7qkyfuSatvm1mxXWiddPjhlypRm1ymawYMHZ38s0rEt4jammZFvvfXWuP/++7PJIqr1eDa3ndV0TNNZ3hVXXDELsDQLepoM94ILLqiqY9ncNlbTcSwC2V09vz/V9PehLYr+90F2V88xld3VcRyLQHZXz++P7C7m3wfZXT1/82V31x5HHeiNfvHWWWeduPfee5vsoHQ/DXlSLWbMmBGvvPJK9ouVxkRPv1CNtzn9cqWzOUXe5tZsVzrWPXr0aLJOmrH3xRdfLOy2T548Od5+++3s2BZpG9PZv3Rm+MYbb4z77rsvO37VeDzntZ3VdEzLbXv621Mtx7Klbazm45hHsvtfZHdx/98p6t8H2V19x3ROsrs6jmMeye5/kd3F/X+nqH/nZXf1HdM5ye7JnXsc2zztaBVLM7OmGVqvvPLK0ssvv1waNWpUaaGFFiq9+eabpaI68sgjSw888EBp7NixpSeeeKK0ww47lPr169ewTWeccUZpwIABpRtvvLH0wgsvlL773e+WBg8eXJo2bVopz6ZPn1567rnnslv6NR4zZkz281tvvdXq7TrwwANLSy+9dOkvf/lL6dlnny1tscUWpTXXXLP05ZdflvK+jemxdGwfe+yx0rhx40r3339/af311y8ttdRShdrG5KCDDsqOVfo9nTBhQsPt008/bVinGo7nvLazWo7pscceW3rooYeybfjb3/5W+q//+q9slut77rmnao5lS9tYLcexSGS37M7T/zuyW3YX8W++7JbdXU12y+48/Q2U3bJbdhfv88n0CmS3DvQ5/PKXvywNGzas1LNnz9Laa69devDBB0tFtvvuu2edU+nEwJAhQ0q77rpr6aWXXmp4fPbs2aXjjz++tOSSS5Z69epV2mSTTbJOrbxL/3OkTuU5b/vss0+rt+uzzz4rHXrooaVFFlmk1Lt37+zkwvjx40tF2MbU6br11luXFltssezYLrPMMtnyOduf921Mym1jul111VUN61TD8ZzXdlbLMd1vv/0a/oambdlyyy0bOs+r5Vi2tI3VchyLRnbL7ryQ3bK7iH/zZbfsrgTZLbvzQnbLbtldvM8nn1Ygu+vSfzrykgEAAAAAAKgGxkAHAAAAAIAydKADAAAAAEAZOtABAAAAAKAMHegAAAAAAFCGDnQAAAAAAChDBzoAAAAAAJShAx0AAAAAAMrQgQ4AAAAAAGXoQKdmbbbZZjFq1Kiqet999903dtlll/l6jWWXXTbq6uqy20cffdTseldffXUsvPDC8/VetHws64/DzTffbFcByO5mye58kN0Ac/O9uzzZnQ+ym9bSgQ5d7MYbb4yTTz65SXCef/75uToOJ510UkyYMCEGDBhQ6aZUvQceeKDsyYoLLrggOwYAVJ7spjHZDZB/spvGZDfza4H5fgWgTRZZZJHc77F+/frFkksuGXnwxRdfRI8ePaLWpJMXTmAA5IPsbhvZDUClye62kd3QMhXo8H+mTJkS3//+92PgwIHRp0+f2G677eL111+fa8iSu+++O7761a9G3759Y9ttt21SJfzll1/GYYcdlq236KKLxjHHHBP77LNPk2FVGl/Cln5+66234j//8z8bhutITjjhhFhrrbWaHJtUpZ6q1evNmjUrjjjiiIb3Gj16dJRKpSbPSffPOuusWH755aN3796x5pprxp/+9Kd2HfO0/csss0y2b771rW/F5MmT51rnz3/+c6yzzjqx4IILZu954oknZvuk3quvvhobbbRR9viqq64af/nLX5oMUfLmm29m9//whz9k+yat99///d/ZY1dddVW239OyVVZZJS6++OIm7/3uu+/G7rvvnh2/tD923nnn7PUan3Feb731YqGFFsr22YYbbpjt+9aY13aNGTMmVl999ey1hw4dGgcffHB8/PHHDY+n99lxxx2ztqV1Vltttbjjjjuy9m2++ebZOumxtO3pEjIAWkd2t0x2y26AvJHdLZPdspt80oEO/yd1XD799NNx6623xuOPP551Pn/zm9/MzsTW+/TTT+Occ86J3/72t/HQQw/F+PHj46ijjmp4/Mwzz4zf/e53WWfvo48+GtOmTWtx/Op0WdnSSy/dMGRKW4bsOPfcc+PXv/51XHnllfHII4/Ehx9+GDfddFOTdf7f//t/WVsuueSSeOmll7KO+u9973vx4IMPtum4/8///E/st99+Wcfw888/n3X6nnLKKU3WSScW0munEwgvv/xyXHbZZVn4n3rqqdnjs2fPzk4kpA749HqXX355/OxnPyv7funEQ3qdV155JbbZZpu44oorsnXTa6Vlp512Wvz85z+P3/zmNw3HJbUpndRIxyXtj/oTHDNnzsw6u9N7b7rppvG3v/0tO74/+tGPGk5YtGRe25V069YtLrzwwnjxxRezNt13333ZCY16hxxySMyYMSNr2wsvvJD9nqT2pc72G264IVvntddey45/GroFgNaR3c2T3bIbII9kd/Nkt+wmx0pQozbddNPS4Ycfnv3897//PZVulx599NGGxz/44INS7969S3/4wx+y+1dddVW2zhtvvNGwzi9/+cvSEkss0XA//Xz22Wc33P/yyy9LyyyzTGnnnXcu+77JsGHDSuedd16Tth1//PGlNddcs8mytE5at97gwYNLZ5xxRsP9L774orT00ks3vNfHH39cWnDBBUuPPfZYk9fZf//9S9/97neb3S/l2pPW33bbbZss23333UsDBgxouL/xxhuXTjvttCbr/Pa3v83amdx5552lBRZYoDRhwoSGx++9995sn950003Z/XHjxmX3zz///CavM3To0NK1117bZNnJJ59cWn/99bOfr7zyytLKK69cmj17dsPjM2bMyI7f3XffXZo8eXL2ug888ECprea1XeWk35lFF1204f7qq69eOuGEE8que//992dtmzJlStnHG+8fgFonu8uT3U3JboD8kN3lye6mZDd5Zwx0iMiqmhdYYIEYOXJkw/5Iw4CsvPLK2WP1UvX0Cius0HB/8ODBMWnSpOznqVOnxj//+c9smJB63bt3z4b+SNXXHSm9V6pWXn/99RuWpfavu+66DcO4pGrpzz//PLbaaqsmz00V2SNGjGjT+6V9kIZtaSy991133dVw/5lnnomnnnqqSWV2GmYmtSFViKcK61Rx3Xhs9cb7qrG0HfXef//9ePvtt2P//fePAw44oGF5qiqvHyM8vfcbb7yRjd3eWHrvf/zjH7H11ltnlQ6pmj3tj2984xvxne98Jzt+8zKv7Uq/E/fff39WFZ/2ebrqILUtPf7JJ59kQ7ak6vWDDjoo7rnnnuy9v/3tb8caa6wxz/cGoHmyu2WyW3YD5I3snvf+8b3b927ySQc6/N9Y4c0tbzzMx5yTWabH5nzunMOCNPfaLUlDgsz5vMZDybRGfaf97bffHksttVSTx3r16tWm12rNNqT3S2OD77rrrnM9lsYOn3NftiR1Ojd+3SQN49L4BEf9CYr6ddKJijR8zpwWW2yx7N80lE3qyE6d/tdff302vM29994bX//61+dru9L45mmonwMPPDBOPvnkbLKaNIRM6vCvP2Y//OEPs877dCxSJ/rpp5+eDcHzk5/8pFX7A4C5ye6WyW7ZDZA3srt9+6cx37t976YydKBDRDahZaoaTmOObbDBBtk+SZNk/v3vf88mrmyNVA29xBJLxJNPPhkbb7xxQ6Xyc889N9eEoI317NkzW2/OTt+JEyc26XROY483fq9UPf3EE0/EJptski1L7U/V0muvvXbDNqWO8jROexr7e36k10rv1dic99P7pirzFVdcsexrpIk/U1tSlX7aT0mq7J6XtG46ATB27NjYa6+9yq6T3jt1ii+++OLRv3//Zl8rVd6n27HHHptV0F977bXz7ECf13alcfPTvk8d4unER5ImQZ1Tqr5Pnezplt4/nRBIHejp+Cdz/g4A0DLZPe/9I7tlN0CeyO557x/ZLbvJJx3oEBErrbRS7LzzztkQIWmSyDQUyE9/+tOs4zYtb63UIZqqi1Nna+owvuiii7JZxluqvF522WWzySX32GOPrMN70KBBsdlmm2VDl5x11lnxH//xH1nV9J133tmkc/jwww+PM844I2t76uQfM2ZMfPTRRw2Pp21IE5ymiUPTWeqNNtooG17kscceyyaw3GeffVq9XalyO51YSO1Jk3GmKurGw7ckxx13XOywww5ZR/Fuu+2WdSanCTvTpJlpwtE0dEoa/ia9b3qd6dOnN0wiOq/K9BNOOCFrQ9r+7bbbLpuQM3Vcp317xBFHZB3rZ599dnas0oSsaWLW1FmfJmk9+uijs0rwNGnpTjvtFEOGDMk6xNPJke9///vz3PZ5bVfaptSBno71jjvumE0ee+mllzZ5jVGjRmXt/spXvpK1OU0yWn9iZtiwYdn233bbbVkle+/evbPjA0DLZHfLZLfsBsgb2d0y2S27ybFKD8IOlTLnZJ4ffvhhae+9984mxkyTT26zzTbZ5KL10iSijSfNTNLkjo3/N0oTeR566KGl/v37lwYOHFg65phjSrvttltpjz32aPZ9H3/88dIaa6xR6tWrV5PXuuSSS7LJMxdaaKHS97///dKpp57aZBLR9F7pddJ7LbzwwqUjjjgiW6/xhKVpUs0LLrggm2CzR48epcUWWyzbrgcffLBNk5nUT9SZJilN+2bHHXcsnXPOOXPtj7vuuqu0wQYbZOukdq233nqlyy+/vOHxV155pbThhhuWevbsWVpllVVKf/7zn7NtTs9rPInoc889N9f7/+53vyuttdZa2XPTvt1kk01KN954Y8PjaXLStP2DBg3K9uXyyy9fOuCAA0pTp04tTZw4sbTLLrtkE3+m56dtPO6440qzZs1qdj+0ZbvGjBmTvXb9780111zTZGLQ9DuxwgorZO1KxyD9nqVJauuddNJJpSWXXLJUV1dX2meffZq8t0lEAf5Ndpcnu2U3QF7J7vJk99x87ybP6tJ/Kt2JD9UqVX6nSuM0YWUaH7sIUkV8qphOt86WqrVTZXyaALTx5Kz8W6pOv+mmm7LKfwA6n+xumeyeN9kN0LVkd8tk97zJbublXwP2Ah0iTSiZxrZOw4OkIT4OOuigGDduXOy5556F2sPHHHNMNozI1KlTO/R1U0dwmrjzzTffjL/85S/xox/9KDbccEOd52WksdIN5QLQ+WR3y2R368lugK4hu1smu1tPdtNaKtChA7399tvZWOYvvvhiNgHo8OHDs3HK6yf6LMqHkTRmeLL88ss3TIzZEa655pqsEj/tpzTW+ze+8Y1s8s1FF100KmW11VbLtrmcNB5+cxOXdrZJkyZlY9YnacLYhRZaqCLtAKh2srtlsrv1ZDdA15DdLZPdrSe7aS0d6EBNa3zCYE5LLLFENhkrAJAfshsAikV2U3Q60AEAAAAAoAxjoAMAAAAAQBk60AEAAAAAoAwd6AAAAAAAUIYOdAAAAAAAKEMHOgAAAAAAlKEDHQAAAAAAytCBDgAAAAAAZehABwAAAACAmNv/B2X4aWeEkLL8AAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def plot_surface_labels(result, timesteps, cmap='prism'):\n", " vmax = int(np.nanmax(result.values))\n", " fig, axes = plt.subplots(1, len(timesteps), figsize=(5 * len(timesteps), 4))\n", " if len(timesteps) == 1:\n", " axes = [axes]\n", " for ax, t in zip(axes, timesteps):\n", " result.isel(time=t).plot(\n", " ax=ax, cmap=cmap, vmin=1, vmax=vmax, add_colorbar=False\n", " )\n", " try:\n", " t_label = str(result.time.values[t])[:7]\n", " except Exception:\n", " t_label = f't={t}'\n", " ax.set_title(t_label)\n", " plt.tight_layout(); plt.show(); plt.close()\n", "\n", "plot_surface_labels(result, timesteps=list(range(0, min(9, result.shape[0]), 3)))" ] }, { "cell_type": "code", "execution_count": 42, "id": "a2feaa50-e8d3-463e-bdef-368772dc7e13", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n_per_t = [\n", " len(np.unique(result.isel(time=t).values[\n", " ~np.isnan(result.isel(time=t).values)\n", " ]))\n", " for t in range(result.shape[0])\n", "]\n", "\n", "fig, ax = plt.subplots(figsize=(10, 3))\n", "ax.plot(n_per_t, lw=1.5, color='steelblue')\n", "ax.set_xlabel('Timestep'); ax.set_ylabel('Active events')\n", "ax.set_title('Number of tracked surface heatwave events over time')\n", "plt.tight_layout(); plt.show(); plt.close()" ] }, { "cell_type": "code", "execution_count": 43, "id": "e7601fa1-67d7-48e4-a9da-0bd3c26ee9c4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total events : 60\n", "Duration min/median/max : 1 / 1 / 22\n", " 1 ts : 30\n", " 2 ts : 10\n", " >= 3 : 20\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "durations = tracker.event_duration()\n", "durs = np.array(list(durations.values()))\n", "\n", "print(f\"Total events : {len(durs)}\")\n", "print(f\"Duration min/median/max : \"\n", " f\"{durs.min()} / {int(np.median(durs))} / {durs.max()}\")\n", "print(f\" 1 ts : {(durs == 1).sum()}\")\n", "print(f\" 2 ts : {(durs == 2).sum()}\")\n", "print(f\" >= 3 : {(durs >= 3).sum()}\")\n", "\n", "fig, ax = plt.subplots(figsize=(7, 3))\n", "ax.hist(durs, bins=range(1, durs.max() + 2), edgecolor='white', linewidth=0.5,\n", " color='steelblue')\n", "ax.set_xlabel('Duration (months)'); ax.set_ylabel('Count')\n", "ax.set_title('Event duration distribution')\n", "plt.tight_layout(); plt.show(); plt.close()" ] } ], "metadata": { "kernelspec": { "display_name": "NPL 2026a", "language": "python", "name": "npl-2026a" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.11" } }, "nbformat": 4, "nbformat_minor": 5 }