diff --git a/examples/example_basics.ipynb b/examples/example_basics.ipynb index a4a1365..d12c35e 100644 --- a/examples/example_basics.ipynb +++ b/examples/example_basics.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -14,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -27,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -37,7 +37,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -47,27 +47,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "AttributeError", - "evalue": "`np.infty` was removed in the NumPy 2.0 release. Use `np.inf` instead.", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[6], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# Module imports\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mfourth_day\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Fourth_Day, config\n", - "File \u001b[0;32m~/envs/test/lib/python3.10/site-packages/fourth_day/__init__.py:3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# -*- coding: utf-8 -*-\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mfourth_day\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Fourth_Day\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconfig\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m config\n\u001b[1;32m 6\u001b[0m __all__ \u001b[38;5;241m=\u001b[39m (Fourth_Day, config)\n", - "File \u001b[0;32m~/envs/test/lib/python3.10/site-packages/fourth_day/fourth_day.py:24\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[38;5;66;03m# -----------------------------------------\u001b[39;00m\n\u001b[1;32m 22\u001b[0m \u001b[38;5;66;03m# Package modules\u001b[39;00m\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconfig\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m config\n\u001b[0;32m---> 24\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mgenesis\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Genesis\n\u001b[1;32m 25\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01madamah\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Adamah\n\u001b[1;32m 26\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcurrent\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Current\n", - "File \u001b[0;32m~/envs/test/lib/python3.10/site-packages/fourth_day/genesis.py:13\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpkgutil\u001b[39;00m\n\u001b[1;32m 12\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconfig\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m config\n\u001b[0;32m---> 13\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpdfs\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m construct_pdf\n\u001b[1;32m 16\u001b[0m _log \u001b[38;5;241m=\u001b[39m logging\u001b[38;5;241m.\u001b[39mgetLogger(\u001b[38;5;18m__name__\u001b[39m)\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mGenesis\u001b[39;00m(\u001b[38;5;28mobject\u001b[39m):\n", - "File \u001b[0;32m~/envs/test/lib/python3.10/site-packages/fourth_day/pdfs.py:148\u001b[0m\n\u001b[1;32m 144\u001b[0m pdf \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39masarray(pdf, dtype\u001b[38;5;241m=\u001b[39mdtype)\n\u001b[1;32m 145\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m np\u001b[38;5;241m.\u001b[39mnan_to_num(pdf)\n\u001b[0;32m--> 148\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mNormal\u001b[39;00m(ScipyPDF):\n\u001b[1;32m 149\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\" Class for the normal distributon\u001b[39;00m\n\u001b[1;32m 150\u001b[0m \n\u001b[1;32m 151\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 158\u001b[0m \u001b[38;5;124;03m None\u001b[39;00m\n\u001b[1;32m 159\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m 161\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m 162\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 163\u001b[0m mean: Union[\u001b[38;5;28mfloat\u001b[39m, np\u001b[38;5;241m.\u001b[39mndarray],\n\u001b[1;32m 164\u001b[0m sd: Union[\u001b[38;5;28mfloat\u001b[39m, np\u001b[38;5;241m.\u001b[39mndarray],\n\u001b[1;32m 165\u001b[0m max_val\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39minfty) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "File \u001b[0;32m~/envs/test/lib/python3.10/site-packages/fourth_day/pdfs.py:165\u001b[0m, in \u001b[0;36mNormal\u001b[0;34m()\u001b[0m\n\u001b[1;32m 148\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mNormal\u001b[39;00m(ScipyPDF):\n\u001b[1;32m 149\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\" Class for the normal distributon\u001b[39;00m\n\u001b[1;32m 150\u001b[0m \n\u001b[1;32m 151\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 158\u001b[0m \u001b[38;5;124;03m None\u001b[39;00m\n\u001b[1;32m 159\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m 161\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m 162\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 163\u001b[0m mean: Union[\u001b[38;5;28mfloat\u001b[39m, np\u001b[38;5;241m.\u001b[39mndarray],\n\u001b[1;32m 164\u001b[0m sd: Union[\u001b[38;5;28mfloat\u001b[39m, np\u001b[38;5;241m.\u001b[39mndarray],\n\u001b[0;32m--> 165\u001b[0m max_val\u001b[38;5;241m=\u001b[39m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minfty\u001b[49m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 166\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\" Initializes the TruncatedNormal class\u001b[39;00m\n\u001b[1;32m 167\u001b[0m \n\u001b[1;32m 168\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 175\u001b[0m \u001b[38;5;124;03m None\u001b[39;00m\n\u001b[1;32m 176\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m 177\u001b[0m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__init__\u001b[39m()\n", - "File \u001b[0;32m~/envs/test/lib/python3.10/site-packages/numpy/__init__.py:397\u001b[0m, in \u001b[0;36m__getattr__\u001b[0;34m(attr)\u001b[0m\n\u001b[1;32m 394\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(__former_attrs__[attr])\n\u001b[1;32m 396\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m attr \u001b[38;5;129;01min\u001b[39;00m __expired_attributes__:\n\u001b[0;32m--> 397\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(\n\u001b[1;32m 398\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m`np.\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mattr\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` was removed in the NumPy 2.0 release. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 399\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m__expired_attributes__[attr]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 400\u001b[0m )\n\u001b[1;32m 402\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m attr \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mchararray\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 403\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[1;32m 404\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m`np.chararray` is deprecated and will be removed from \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 405\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mthe main namespace in the future. Use an array with a string \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 406\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mor bytes dtype instead.\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;167;01mDeprecationWarning\u001b[39;00m, stacklevel\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n", - "\u001b[0;31mAttributeError\u001b[0m: `np.infty` was removed in the NumPy 2.0 release. Use `np.inf` instead." - ] - } - ], + "outputs": [], "source": [ "# Module imports\n", "from fourth_day import Fourth_Day, config" @@ -75,7 +57,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -145,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -156,25 +138,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Starting the download. Please note this will take a while!\n", - "Depending on the current server usage this takes a few hours!\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 3612/3612 [00:00<00:00, 39054.30it/s]\n" - ] - } - ], + "outputs": [], "source": [ "# Use this method if you need to download files.\n", "# fd.load_data()" @@ -182,7 +148,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -194,554 +160,11 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": { "scrolled": false }, - "outputs": [ - { - "data": { - "text/html": [ - "
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speciespos_xpos_yvelocityangleradiusenergyobservedmax_emissionemission fraction...pulse meanpulse sdpulse sizepulse startis_emittingemission_durationencounter photonsshear photonsphotonsis_injected
0long pulse 117.1783930.0800610.00.00.0011351.0000True19.3849040.1...2.01.51.500000e+00FalseFalse-75.000.000000e+000.000000e+00False
1short pulse15.6082296.9498550.00.00.0012741.0000True15.0382860.1...2.00.33.000000e-01FalseFalse-75.000.000000e+000.000000e+00False
2short pulse16.6993555.7141550.00.00.0012501.0000True17.5096040.1...2.00.33.000000e-01FalseFalse-75.000.000000e+000.000000e+00False
3long pulse 130.0705807.8072910.00.00.0013571.0000False14.7136680.1...2.01.51.500000e+00FalseFalse-59.000.000000e+000.000000e+00False
4example pulse 110.3459705.5865790.00.00.0013361.0000True12.0341750.1...2.01.51.500000e+00FalseFalse-75.000.000000e+000.000000e+00False
5example pulse 118.3920587.1320720.00.00.0012261.0000True7.4850000.1...2.01.51.500000e+00FalseFalse-75.000.000000e+000.000000e+00False
6example pulse 129.53666012.9534450.00.00.0015361.0000True19.1693540.1...2.01.51.500000e+00FalseFalse-75.000.000000e+000.000000e+00False
7short pulse12.2691126.0841320.00.00.0014021.0000True17.0669010.1...2.00.33.000000e-01FalseFalse-75.000.000000e+000.000000e+00False
8short pulse30.0764266.6073970.00.00.0004051.0000False0.7638700.1...2.00.33.000000e-01FalseFalse-41.000.000000e+000.000000e+00False
9long pulse 130.0289362.1127130.00.00.0007411.0000False13.6100570.1...2.01.51.500000e+00FalseFalse-64.000.000000e+000.000000e+00False
10short pulse7.0264855.7971480.00.00.0007921.0000True20.6783370.1...2.00.31.000000e+10FalseFalse-71.000.000000e+000.000000e+00True
11short pulse6.9332288.9118750.00.00.0012370.9025True20.0154530.1...2.00.31.000000e+10FalseTrue75.002.001545e+109.705904e-156True
12example pulse 16.5320399.4092310.00.00.0013841.0000True13.6713590.1...2.01.51.000000e+10FalseFalse-64.000.000000e+000.000000e+00True
13long pulse 16.29749512.3721910.00.00.0013701.0000True18.1232400.1...2.01.51.000000e+10FalseFalse-64.000.000000e+000.000000e+00True
14example pulse 16.3162208.1528590.00.00.0013720.9025True2.9596380.1...2.01.51.000000e+10FalseTrue75.002.959638e+091.668752e+01True
15short pulse4.7712438.4993400.00.00.0013801.0000True-2.7090080.1...2.00.31.000000e+10FalseFalse-47.000.000000e+000.000000e+00True
16long pulse 12.2489432.7320920.00.00.0010601.0000True21.7728120.1...2.01.51.000000e+10FalseFalse-23.000.000000e+000.000000e+00True
\n", - "

17 rows × 21 columns

\n", - "
" - ], - "text/plain": [ - " species pos_x pos_y velocity angle radius energy \\\n", - "0 long pulse 1 17.178393 0.080061 0.0 0.0 0.001135 1.0000 \n", - "1 short pulse 15.608229 6.949855 0.0 0.0 0.001274 1.0000 \n", - "2 short pulse 16.699355 5.714155 0.0 0.0 0.001250 1.0000 \n", - "3 long pulse 1 30.070580 7.807291 0.0 0.0 0.001357 1.0000 \n", - "4 example pulse 1 10.345970 5.586579 0.0 0.0 0.001336 1.0000 \n", - "5 example pulse 1 18.392058 7.132072 0.0 0.0 0.001226 1.0000 \n", - "6 example pulse 1 29.536660 12.953445 0.0 0.0 0.001536 1.0000 \n", - "7 short pulse 12.269112 6.084132 0.0 0.0 0.001402 1.0000 \n", - "8 short pulse 30.076426 6.607397 0.0 0.0 0.000405 1.0000 \n", - "9 long pulse 1 30.028936 2.112713 0.0 0.0 0.000741 1.0000 \n", - "10 short pulse 7.026485 5.797148 0.0 0.0 0.000792 1.0000 \n", - "11 short pulse 6.933228 8.911875 0.0 0.0 0.001237 0.9025 \n", - "12 example pulse 1 6.532039 9.409231 0.0 0.0 0.001384 1.0000 \n", - "13 long pulse 1 6.297495 12.372191 0.0 0.0 0.001370 1.0000 \n", - "14 example pulse 1 6.316220 8.152859 0.0 0.0 0.001372 0.9025 \n", - "15 short pulse 4.771243 8.499340 0.0 0.0 0.001380 1.0000 \n", - "16 long pulse 1 2.248943 2.732092 0.0 0.0 0.001060 1.0000 \n", - "\n", - " observed max_emission emission fraction ... pulse mean pulse sd \\\n", - "0 True 19.384904 0.1 ... 2.0 1.5 \n", - "1 True 15.038286 0.1 ... 2.0 0.3 \n", - "2 True 17.509604 0.1 ... 2.0 0.3 \n", - "3 False 14.713668 0.1 ... 2.0 1.5 \n", - "4 True 12.034175 0.1 ... 2.0 1.5 \n", - "5 True 7.485000 0.1 ... 2.0 1.5 \n", - "6 True 19.169354 0.1 ... 2.0 1.5 \n", - "7 True 17.066901 0.1 ... 2.0 0.3 \n", - "8 False 0.763870 0.1 ... 2.0 0.3 \n", - "9 False 13.610057 0.1 ... 2.0 1.5 \n", - "10 True 20.678337 0.1 ... 2.0 0.3 \n", - "11 True 20.015453 0.1 ... 2.0 0.3 \n", - "12 True 13.671359 0.1 ... 2.0 1.5 \n", - "13 True 18.123240 0.1 ... 2.0 1.5 \n", - "14 True 2.959638 0.1 ... 2.0 1.5 \n", - "15 True -2.709008 0.1 ... 2.0 0.3 \n", - "16 True 21.772812 0.1 ... 2.0 1.5 \n", - "\n", - " pulse size pulse start is_emitting emission_duration \\\n", - "0 1.500000e+00 False False -75.0 \n", - "1 3.000000e-01 False False -75.0 \n", - "2 3.000000e-01 False False -75.0 \n", - "3 1.500000e+00 False False -59.0 \n", - "4 1.500000e+00 False False -75.0 \n", - "5 1.500000e+00 False False -75.0 \n", - "6 1.500000e+00 False False -75.0 \n", - "7 3.000000e-01 False False -75.0 \n", - "8 3.000000e-01 False False -41.0 \n", - "9 1.500000e+00 False False -64.0 \n", - "10 1.000000e+10 False False -71.0 \n", - "11 1.000000e+10 False True 75.0 \n", - "12 1.000000e+10 False False -64.0 \n", - "13 1.000000e+10 False False -64.0 \n", - "14 1.000000e+10 False True 75.0 \n", - "15 1.000000e+10 False False -47.0 \n", - "16 1.000000e+10 False False -23.0 \n", - "\n", - " encounter photons shear photons photons is_injected \n", - "0 0 0.000000e+00 0.000000e+00 False \n", - "1 0 0.000000e+00 0.000000e+00 False \n", - "2 0 0.000000e+00 0.000000e+00 False \n", - "3 0 0.000000e+00 0.000000e+00 False \n", - "4 0 0.000000e+00 0.000000e+00 False \n", - "5 0 0.000000e+00 0.000000e+00 False \n", - "6 0 0.000000e+00 0.000000e+00 False \n", - "7 0 0.000000e+00 0.000000e+00 False \n", - "8 0 0.000000e+00 0.000000e+00 False \n", - "9 0 0.000000e+00 0.000000e+00 False \n", - "10 0 0.000000e+00 0.000000e+00 True \n", - "11 0 2.001545e+10 9.705904e-156 True \n", - "12 0 0.000000e+00 0.000000e+00 True \n", - "13 0 0.000000e+00 0.000000e+00 True \n", - "14 0 2.959638e+09 1.668752e+01 True \n", - "15 0 0.000000e+00 0.000000e+00 True \n", - "16 0 0.000000e+00 0.000000e+00 True \n", - "\n", - "[17 rows x 21 columns]" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# Example poplation state\n", "# This includes all information needed for analyses except the light propagation and detector response\n", @@ -751,7 +174,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -765,7 +188,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -777,32 +200,11 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": { "scrolled": false }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "findfont: Font family ['sans-serif'] not found. Falling back to DejaVu Sans.\n", - "findfont: Generic family 'sans-serif' not found because none of the following families were found: Helvetica\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# ---------------------------------------------\n", "# Detector light yields\n", @@ -861,22 +263,9 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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e1IpVxFdfS+WGSz3jCCEhNhE1sHGJqsH+lb8lVdfJ81c9wGLzOppu2MKWf7ue1v1TOawufZIlQZaE2IPuEXhSMHDzh8kXSExDTSZrBQvsKvaZSbrMdI68wfEw4E0J+4Ir1Mr5YbO4xxSFKpqkxfpDTzYccUGhXzz3kKHejbPFzVnGCWz2Gj0ApKWfoyQHuVbCQ1uhBF6mGmSBlG88HJYEG9YvYu6Kh5hz1l5mf3IVdT+93OuP/9JkxcUV5XlLueOrb+KQ1U5SbBxxcXD9cKLyYuSwF8lZ8Tha20NqxSrMjcv9eLhBH1lMDFLiEFeTP1h/K7+66Jdc/sw76FlsELkqwdwNW3n88WW0G1mSvkoQuKTCBA273gI3Utjv6aL0k6XDsEn5ftOc6yt0P2Ag7DsS0kvW4OwdB8NJRF5W1QuPdZ8TgcAJHhDVQXMuk3zndzAouWrk9hvOQZ5/jrBx4wB9kuWJgw2898FGnlizmLsuWMluq5OEbzgF7SXUps1IcJRkTsLk2vHJGiC++rqcJA1eDPB8pZ1+rN0VE33yJu548hYywKO701z+h1W07D6DrT0W3WYfrgy4hpwCL1wYhaRdh5EiITYZHOLqRbB6JE0Kp2Cc3kULOvtNNUivWAX7SzecRo04iUgS2D7SLkCdqo44Ve94YqSI02iRpmJSGxbab7jzmOrNB21048x2a9hr9NJheFMZAimaWPrCoKE7QLFDYBAQqPCt56gaJMQmhU29xqgigihMcytoUIs0Ll2GTbt4/tg+f1QJRpJizx2c10SI+kO/hcEB6aNPhq5tCkfHghcw7K/uW/oC7fseQA/Zxz3idFYR+xz7JMjjhPAQVmj7cPvnY7TZUGGpnVGhw0h5EzT8GUgQinCtWJULHsTy2hru/PlRs8ySNbSvfJRLn7yN816+jk1mH21GMjdhBIGE7+OMq0mtRohh4oZGiFIxMCJ5E527JUMGh4SvpoTDt8H1hnXW8NTESrWoX38V/c7zJfdjVJKeKrpoPo51ulsxiSKCh5QVh8SSF0iueJyK1dcR33AJMCCt4quvzUnSsfTPROhc+Sh2bRfbbv4xD1zTw8+/dwvPHG2iXxy2WF0536SNy2QqiKjBEUkXXApSCjyiGr4BZg+rqwf7BnptQNC4v86qSi36xc7ZCKWgmOUj7y251dMAxSaKCB5WYsXjuLXdJFY87umXoaEwtvFi6r51N6Y/T6AYgubvU//MjcS7G7jtlVvYs2keV163jiuasnx0+X4W2/VUEskt7UjjcNBIksbOOebD+miplnZwPVlxhhA0v5/htoOVB1X+oj7Ld8uVimKG+/eJyHLgk6o6YYb18UYpiSJstKC0DH47FniuIKFqw6XMXn8Ntl1P9/LdqAqHumI0ddQB3hKOjChT3UomuTH2mwkSYufcQPkzloa7jlKRPwt/wHAdkKjB9D5Tx2mqnogI8Pd4s+9vV9WTPjG5mKl6pwvCSRmqNEKzVjLZjWOq0GtkSeHQJWmPkLjUapRmraTVSNAj6SEELSRFj+9Sj8H5pirUolajRDAxgM32PfTr3uNrOKnH4rtF5B3A0yLyNWADsFlVEyVfRRklI+z7PUAfR8zkoInL4al7fZLlIP25CNXJIGiALC74QQTLX1nqyFikdREQkVuBDwEZ4ELgvcA5ItKpqgtKPmsZRWOI71e8YASQM2IKLgDM48J4EzTcXq6/gOP7gwNDaiyehmKc+buA14B/UtVH836bUfIZyygZYaI6edsBbH8WUhijGUfjnXI86LON5vrn6uh6cSEUI0nfpKpbC/2gqi0ln7GMMWE0UuX7LMfazrEg34ga8v8Y4/fF6KQFCVrGxMNw0bQTVaghJ9lHCJyMpSflhGWnMYr1yR4rxjuR7mlH0jdC3vuJhuFC0ccLpx1Jj7XSRRmjY6SkFcP9diwEPu1IejrmvZ+IKJT9Lz9pxpAkGkvW4o7zQrxTAqdT3vuJiuEs9SAEmssOHcyGUm97aozzSU87SVrGiUFglAX6aCAxg3xXXuGIKHUayy3zrjwBC/HKOA1xrG6qQakvkUETs0287M9JbPrIeok4si+O4RxllDEMRsszWrjGk7fEO64D2auzofkFY+tHGW9ojETCUqVrsKI1riaVPrXCa/EddEw2/oTQSUXkZhF5XUR2iMhpnTf/dEI+iYPCDyre/FZLB1aoBp+xyNKTLklFxAS+BdwAtABrReRhVd1ycnv2xsNIw/touqsjLhF/onM/WTBAFLLikhA7l2VwbP06+bgY2KGquwBE5Md4BR/KJM3DaIsDxxMjDf3B0uaU2P4yEcNbjChg45KQrJ9tb7SV+YUxEUh6BrA/9L0FuCR/p3BhByDdl/7s5vx9TjImAUfH9Qx7OZ/9RDLuL7KZ9C+KybI9/n3KQ9fouywqtc2JQNJCL9eQ1zZc2EFE1qnqsvHuWCko96k4iMi6Uo+ZCIZTCzAz9H0GXt2oMsoAJgZJ1wILRWSuiESBP8Ir+FBGGcAEGO5V1RaRjwGP4FXWu1dVXx3lsH8f/56VjHKfikPJfSq6+kgZZZwsTIThvowyRkSZpGVMeJRJWsaER5mkZUx4lElaxoTHSXdBjQWmVKkpjcCIBdr830ePFgd7DE1TNPyxxcSg88890jE66P/wbCFvVpEW+C0o5FWob+KfXRAMDb4LBuQqoxiD9ve2R0QRQxEB1xGcAs4fw78QRwVloGqJhtoL9zH4K0A/R0hp77jVFp0wMKWRqZG/PKY2wslcg9Ixhbbl7x+s4xn0WyizcX4t0/D+paSYydVRCiUcC28Lny+/GEN+n2AgYZilQgSTKAbRoIIyBuLn1E+Jg+1Xbq7BIiJD+WTjFcrIiosZyu+UDRXGyPoJfYNz2352vy323xd9DwKckiSFoQ8j/KAKEWnI8QWyuxXalmtPguwc7pBEsIPOrQNFusIkDaRNeB5Q8FuhIr0G4i1gkwIEDFVUyb8POeRdSlBG0RbI4NKLekQVbxZ9MIO+XVJkcLAwqJcYMUxEB7ef9ksIBX03fZms/gsV5PMfkNiSI6w9hlQ7pyxJ85H/kMLkLUSGMEb6bbTzhNsACo7plhpEw5JRNEc0q4BZMOgl8/8EZA2OH61P4XMECL9gAXkyflHbQDWJ+5Whgz4ksQe9cAaSKw1k6ECe/kBaBgXGsngF0sIvmqVjyfN8GpC02CG00FCZf/xww/hI5w3vM+yL4pcMz98nePjD9jlEsrC6kf/SjdRG8FtQijFM0vAL7PoECwpBZPz0ksH+4dz7uWsX79iAoDZujpBBftTgGh3/5TolZ+afCBR6iPnbitmnECFHI/lwL0Uh1WKIGlFAVw63EQydOSlXhE4dnMdST/qZIdK7gKr3QllIiLDe8B++lrCuPJoKFKg6Tp5JWCxOG5I66IjzvvN1wkI64mjHhct+j9RmoT4NqzsyWI8ND49hg2Q45Pc/136+miCa2xYYTxZCxC/BE5DOEfWNKK/KcrjNQLcM65rh9UsBwgvvgj6OdaUonEYkHY1s+QZLvs46HMIGjKUDQ1jwW6F9h2tntP9R/wEXMHrCf0fCIG9CaKg1Q8SKYhJTg0osImrk1jZlxSWrLhlxyQBx9Yd5MXJEDHToQiNEvvoSEDO19EV6VjxK9errYe34VB+ZcAj75saCQhIvH+G335QBSTdaW8jQbfkvkBmSTAGGI3d4yC9k6eeOD70gOSnnZ1Y2ZIBgUTWoVIsajVDvRqj0e2Gj9ItDnziADQLp0MuR7woLD//BPobKoDKZQS3S9hWP4tZ207fiMYy11QWvcySckiQtBqMRpRASS1+gb8VjVK++fnB5xSJeiPDQHj5XPiENlYKSNF9a5r8QI7lu8i32/GEZhThWjqCT3BjTNEKzBQ1VWSKWS0dvlAMZK9df9a36oJ3Acg+fIyBqsM9wEr969fX0rXiMytXXk2R8S4mfUvBWJw4mZphIhXTYvhWP5d74mg2XDdt2IT/saHpXzpL2dcN8x3/+MBrOL+9KYZUkbDCFSR0M6WHpGeRoanSjzNYIy+d1MGPmIeaetxMrarNt3Vk8++KZOGmTrG/geNVNTDIhyz2qJlE1iOLldMq5o/LuSfheVG64lJoNl5HBJfVGJmkh0gU1PmFAogXbAlKFlfvgja9eff2gm5zf7nAPYyQEZApLonx3UH6EChhiROVfMzDINxvFxAgMJEwqfAlarRFqXYt5hsGFZx7myj94moq/3ESmzqt4fy5r2DHvsxw4WEOtnxXPxat2klWDlHgSuVItmjROnUYxFDqMjF9Haqg/OngmwX327uMbRCeFwuTIJ1ahIX44/RC8Nz48zA+nIoSH6OEs+5EQHi4Bn1SeywfIDa0uOqBXIsO6rQbpogoxLCyEmHolE+vUok5Nmgxhen2KWz76C1If3kMmr61r3vQcXT+5lp6kxR7biyO56qXGCbwBk9w4Z7hRJhvQp0JWlbRfATrjewPy8z4NHmXeMC6o4nTEsWI0N1W+VAv7AUdqLyBmFDPnpwwiPYpiq4sdjiwFn5DVnD9iBAQO2g1qeVb6BJ2kFpMMaK7LcNEF25mxsIXUh/cU7GfdvzzJn1+7mWe++RZk7UL22CbiCoYITWowyY1wWXOKZcteYur8g3S2NnHfz65gndp0ShpbhvpLwyPDG06SjidG8qEWE+UZDoGuGFWDGGbORxm054iSUZcsDhmRgShOAdUjPLTmXEt+u3UaYZIbYbYlzJrSR11NAiviMP+C7UTvGbmWQO87jnLB9rW0H22A3ZNw1GSDukx2IyyudnjXRx/EvctbJzkNuG7XGXS8NJsjkgRhkIWf/9IOvJKl4YSRVETuBW4F2lT1XH9bI/ATYA6wB3iXqnaW0m7+xJLjhXxLPWydh7+7MlSPzG/Hi/B4kq5CrZyk89IjCi6Q9SvdCTYqhauGFJLUYUlqIFSqxRQ3ypL6DNffuJYFt64je7SaF+6/ileeWcIyRi94UX1WK1f9wVP0/eAmzjp7N0tbptByqIHGugQVZ3TQH9r34me/Q/+ST7B9RxUZ9YZ8Q2VoNCw3YpSOYkqJNxbxqS/iXPcBN+dtuxt4XFUXAo/738eMUqTboOG0QNQkjJzRU8DwsdTIbQ+rCWGjzFBPglaqRa1GaHJjzHDjzNMo84kwjwhnuBEmuVEvK7JvQQfEG6lGfLgvpm/JNxvC9TetYep//5q+dx0m/Wc7ueqr32fK9CNF3ZvuDbMAsEyH6to+TMtl/uw2KivSdG0ZWgTx1rt/wgVONU0ap1ojXr9DrrbwfR0vSXrQ/4zUvgnMGqkRVX1aRObkbX4bcLX///eAJ4HPFNEnYPh4+2gStVgy56I0OtQiHwINT4dzcwS11CCORbVGaNAYU50Ysw2T2ZMSTJncTXV1AscxaT3UxPbWGlAvDJrKmxASxqAIUiDZNeiGEjWUBX/9CH2hY3qWZVh008ski7hu4wvrqV8b4/YFh0j88QHO8LdHOyOYD04f0kb/Ha1c9qV29u2qJWIYdJDyfKzqjo2VeSiGpK+p6gUj7SAi68d4/mZVbQVQ1VYRmVLKwYWG2fBDDeuUxRpSA3MkQ5Iyz4ENhNw8xiAp6gJptcnIwITfuJrUaZSpToyzo8KlF+xgyTXrqV1wCPvmNrJ1gvHN+az6wY30vDqNDs1iimepW6GQ5HBzUg3fM+CoS5/YtNpg7KyGhd2Drq1n1xQi7CvqPvQsT8PyA4O2ZRqyxN9ygOi3FpD56I5Bv1VXJanTBjIaISk2KRxscQeFko0x1rsvhqTDe7VL2+eYEM6qZ1Cf257vmwtQyNU0WlltU40hBA1I6A1hA6QMlmJYeFGcJjfKFLWIAkdxaTPS9EgWFW+O5mQ3xnzT4Irl21j5f39Mz+WpQbqd+8mt3DKlh5c/8rHcjCSvD+CKkQsAwMADDwyxABlx6SLNa6bw0Gf+hGtu/vqg64t8qeRcYUNgJJX/+OL7WP7r1znrNz/0+vO3F/D4KzN41eriDKeSao3QKelBUamxGJoBiqktmjoe+wyDwyIyzZei04C2Ec6Ry6oXMWYMuuKAWGFJExAtwEhT6mCAoOmlL9K/4jEanrmJyRtWYmmezoeBGdK3IhhMcWJcPTnN+7/8bfrf00r2r5fxvW+9jXWpCF2SJYZBk5qcNauLS9+zip7LC9+u/vceJPKnSqdmcHBzLqqoBmrEgO80QFiyB37WpNhs3DGFa798Lnr3ZsxUBOcfz6b6zEP03T70FqfuugzHNqn62urhbn8ObV+7gojl8tprc4n+wW20H2nk1+vmst1IUaEWFWrS6Xtg42oNPINc3GEcXVAisgz4HDDbP04AVdXzSz7rAB4G7gS+7P99qJiDwhQLW+GD/JEh9w6EDCX/QWd0sKoQEL1/xWM4td10r/g9C9ZfN0hSR9Wgwi9YAJDGW+cTQXj7nb+l/z2tgCexbuuoYe+9N9JuZHAVqkWYPecAyQ+MPNymHKHfzObcSTE1B9J8+/qq55byaskHcXXwiBrBpMmNMWdqHwh0/u/rsKI28ZoEUumRp/bxanrXzeHw1hnYGYu2g5OprE5S9e63cMYPfzl85+45j4O7ptPU0Ec6HeHp1eezpddim9nn3Qc1aDcyGAhNGieiBo4f/w/GrUMjGIHDoRQX1A+ATwObgJIXqojIj/CMpEki0gJ8AY+c94vIB4F9wO2ltBkmZqD7gBcaDBadhWPitnhSyMYl6hs42dClxNRk8jO38Pbah/jC0xl+Za/hV8ZVdEkGAWo1Qr1rUY2BC3SKQ4skSIpD001b6An1beZNr1Bx7410Spo6olRIlNqG8B6F0eFCleG9Bl4oM0KNmph4M5XSoqTEc/WkfQMtKXZOlTHwpPvK69bCp7cw6xeH6H2Hl0e31z+Hc6iGI9ums33zAjo6a7j82nU0f/1J7Mrs8Pf6q4vZvWEBRw5NorGxm9bWSfQmvbsb98OoAsQwmO7EcCGniEQR+nBpMZNjchOWQtIjqjrmlIyqescwP1031jYDhHXHwFcYxKwDSeT4znIbl5YLnuLAlb9iytM3U7PxUlLiLZWIYzHn5ev5O+f3NNLB+2L3k4xfxYN93rDa7EaZH3OZPb0L03Q42FbH7p5amiwlu20yrNyb61PrqnOIGcoMt4pG1+KMyUlUhZrNFr3n2gWv48mlH2ebmaRfsjRojEY3wkKJMK+5n3gsQ19/nM7eKN2ZKL0KXTj0i0O3IfRIFhuHM9wqvvjmV2j6j0dRQOqGqhbZripa902jvrGbbNZkxhdWkawcOae983+2MIstLL6/mZYnF7O/ZQppVzBRmt0oWVG6JMs0N8rCSgfDgMVnHuCc5VvIpiM8/8RFPLCvenSfZ6HnW8K+XxCR7+L5M9PBRlV9cAznPWYEUjQY1oPZPjEs6jVKoxuhQS0aRKgwlawLCUfIAutW/ppMbScdKx/hivU30GL0kyDLJDfOeU417Qsupz75W5zPRnnfB7/A7Iv+gqdencbMmiw33LCWWf/1O5xYFuMr57Dh98tIp2Js/d1FNL0ym8YzD3LolTms+t1l2CosIsr8SUkuuWwzzfMP8uSfvZ8V7/99btivXRfF3dXAmntvYNXWqXRanbgocTWZR4R33PQS537954gDPd9byq71C+jqqKOjo46DbbW09EVpc0xMUzgqLnPcGOf834dy7qdn7rmNJdfdN+jexWZ2cNFbnyPz59sBhriU0n91CbG/H1oUbMfb3kVNQy97ts2mraOSdteT3L3i0KQR6tSk2YSm+iTnnLuThQ//JHfsm3ic6ov+gideLZ2mpZD0T4CzgAgDw70CJ5ykwYARDB0BQSuwqNMo0504Z0Zh8bzDnHX+DibPa6XnUAM7Ns+nt6eKqrZL+O+aJ/lM3RksvvAQ31s7G4D3WKu4JvpTrJVN9PzrgNv3ypf+mZnvuI2ujlrO+OEvCWSOe9erLK9Jsvf5s9m/6wx+8qvl2Ao1lvKKY1OrLgticNmKjcz8saduX8Q6MukI+qUlrP7FlfT2VrDo7N1s2zaLo35hhDqNMsmNsmROJ/N+/jMS/vnMv32Js/teIXbUxX5kFq/97iJ2bJtDW3s13f1xROLcfMtLGF0R8Hu55PH7hty/3rd2AB0F723t7+p4Zs3ZyPVncf5j3xv026qnzqc3Y2DnVrr6/UKIIzSZyhmNSebMbmXWOXuGtH3LJ39K9IPjO9wvUdXzSj7DuGCwkRS4YirVYrIT49wKlxtveJlz7/o1Pcs8Y6EBuOKb+9j25Plc+59b+QxTgT64+z8IksrXztuPcdDG/X0/+bGJuQ/+rHBPLJfqhl6mz2rlPbNaqaxNcOTAZPY8eh4KpG3JETSAE8siovx881QqEGbNrmDKpG6c1jj9YlOnUerUYtr0wZa4mY5gV2exq4GP7GbJtG7qfnUR6giNs45Q8bFNpJtsRtd8C+PIB25i66Emqmv6ee75c5nxkeuZ8dknwIA9n7+BiphDa8rksNi0GimupIq4pfSnTSqAc+a2c8k16zBMFzsdIZbX/r3R3RxtHtaBMyxKIekLIrJ4ItRXyn8XA79lhZpMxmTpubuYdf/PhzyszJ9vZ6HrDfmFkPpcHfF7ukh9tr7ovjz/g2u56vP3U33tQHynAfiX77zID+55LzvbKgsf+LlXWPndt7Dsks3M/PFDJD99GU9teisdbiWValKPkErGqdpp0j/fk4pmApzQk7eXd9Ow8QjRT72KXZkd0MGKQN/Hr6T6G08P2jb/T55h8soEtY9Xs2/3GezfMYPM52+iv7uKLZsXcLAnSr8fVKhUi+a6DDs7Y2yyupjvVHP7vBYm/82z9H9jCfs3z+XcH0+l/48GSod/cWcnjjG+VZpXABv8ynWviMgmESmmTMtxh8AQ9xJ4Vm2NoZwxx3MF/eqhfn75i/5Bx2Y/vm3YdjMfrKVn5ywyH6wtui+zztxPz7V9Q7anP7Kbq69/kaa4TeJTVxQ89qyz9jDtzBYAKv7f8yybf5SbY1EuMqJUW8qBg5N4+ePvIvrNhdRstsg0DH69ev7lQlLdlSNa5YWgX1rC1pcXUbPZGrRt23ev5vVb7+D1+66meZrnEejrqmbrlnnsOVRDm7r0+OugztU4IsoGs59eydBuZNiw/kwiR5RMIsYrG8/kpf++lth35lKzxeLQH7+Za1f9ITjjW6U5f3LISUd4Yojil7ZWoa+7CoDZcy3qagfew9oX4vRcWlzcoebhRvb88iLmvuc5eq4eTPSqPSbJ+8/CvetVzvjSEwzX4uSFB2luSrDzlQWcx7NDfl/2nid48t9uZfkXX6Jqp0lNdYIPdvwje29/B3cf6OHZqx7g1rVv5Q++81YWrd7JWV/9JYmZA5Io8ndr+eGGHr7yrS7uuqKeO5cO/3Id+uM303W0DjGUndtncrCthpeu+BumNCaprMiQSEbZ21ZFheWSsA0OOjDTgr9+8MssuLGH6p9O4ZPv+0uSuMxz40yttnmuI8LhSF8uOcT2I9V0/XApZsShsiLNoYOT6f/Bdey+ZxovHq6g3UhR5T5Z1P0Po2iSqure0fc6cQjW9bgh32dGXDpdZeuWeSz+xpmcF5KaNesjbPiHW3nu+XO54vLNzH3wZ/R/csWQKIv1tbPYvWYRr7x8Fq+11NP+P9dQg1BjKTHLpbEuTXVlmmnT21jcU4FRm4S7CtehqHrna8z43cUcPDCFqR+4icn3PjLo9yMb5vDYS3Npmfs5Ght6ufmjD5EExHBZddXPyNR18vPlD8HXr+fsPRcTq0jTfN9vB7XxlWe7ONjr8JVnu4YlaeJTV/D9n63AFCVmKl0ZgwM47DX7oQ1muLXU+9MGq12TVnVpN7JMcmL03OgpTX23tzH/o1mMnggzKmw6EiZdRiYXZWp249RYimG6NF67mZubetm2+hy2bF7A9rZKeiTLrgufILGvpdRHPTpJReRlVb3wWPcZD4SngtmiJNWmXWw2tdRifvvtnLN6B/XNHSS6q3l+2yxe3zWV1r4I3//NRcQqLsIQuPCx5Sw6dweGqbQdnMSePdPZe7ianbbLTrOHo5FULiCQcmymH61iplPL5N0N/PrZRVSayifu+mzh/vUaHDnSyOpdjazedTV3ttex4KH7c7+veuhK1hn9vNxmsKB1Kq2ffz9Tv9nF/a9PYupFbRxa+RumP/NmtpjdpJwazttwJgufeoqeqxJU+freXVfU85VnPUk6HLLpCDMaUrR1x+jIGHTi0mVk/WCAS7uRIetGqFSDtBp+tWVI5UWPz154gPpDTRw6WomtgiHQoFFSOFSqwdxpPRgRG+2OkzhaSzYTIZW26FGlz3DYs/KX6I9L10mLkaRnj6J7ClBX8pmPM2xc0uLd/L0upPY2sOPAMmKmS8Yx6LCFozj0Ghl/hSNUqEXbtsms3T4FS5SkK3Ti0ilZjppp2owkCckOimZ1SRpMaFfv1sXUIHXXZcS/8vyQPm39x5vYvq+BJy/6HduueoitT97GJ5Z/jGkzDrFz+2zW7K8jZiRJisM+I01HhwkdTXRLlrnrr2H2+qtzXowmjdA4qYsd913JzC3bOLqrmYo/OsSdS2tHHOYBKmoTzJ5xhHR2Kn09ERy8F7xKrZy6lPIL1AYrRSv8KNLe29/BeX/xO3b+10qu/vCvydx+mPVvezf/88wiqjA9X2RojX7nvim0vjabp1ZdREdvlPaMQQSY78Zxn7qNR5x7S362xZD0rCL2GXsJ3jEif1Gai5LGpk8E11BS6nLYMRBHyGKTMhz6xaZfbJJi5xasdajFAX8ihGt4DyslDv1kc3k6g/NZamD7M+gd8Szcesfi+Ucu4ZoQSZ+68C+orEyxY9c0DmUNdlz5EJnaTp696gHO+qdvE9t0Bt0oR4wMaT8022Vk6A4tdfZCjN46pcluhIua0iy+fDPWF18iDUzZso9DBdSVQnCyJpFoFtMYvHo2riZZf11SkJs0488TiGDQp8rzz51H6/5mlt+0hsSd3lA9efoRDBbR66eAjKlJRlx2tdaij11M1jZ5uT1GPy4XVNhcsmwH02a1MmVRKxfeM73kZ13MLKgJpYsWQiANMuJiqJfUII2DJR7BbH8iSBKblDgkJIshQlwdn9gDCRgdvARdbRes5ujK31L3zI25NfjBpOaUOLjqTTxOiMvabc08dttyHjj/N7xr883Mb5lEd8KiwxY6cFj49NvYduVDzHv6LewzPEdRUhwS2F5qG38tE+KRNJhYElOhzjVZEHNp/8P/ZEnzc9y1wTOQehfbTHv3GnqA2FGL9KTCoVaAbCqK6xqoSi4KYygYMqAyOeK5lgKfiarSLvBye4y+xHTmnDmVeftNEv99Dj/+2Qp2mUm6xZtMUq0RIipst116WmqJCkRQFlkGlyx7nSv+4Yf0XOjNkqj5xeGSn28xOul7VfX7Jbc8jghkaHgeaUCgjHjpZbIyOBGXLR75Uv5kDE/vcvxy14On8bkoR1f+1psNtfL3VG30ljmHjTQEkjh0GVl2uvDrhY/RH+3jvvmruPPh2+jHJSFebL15w5U0bliBi9IpGU/qi7fgLuhXOCuyq4rhr3OPYtBUn+RvZz0/xEAKAhVmUun/5AqmvXU9vS/ORT8zUMC6ZpNFeypKMhkjmTaxGToBPDh3sFUARzxCHwWcpMWRn66g6sEr2G677LJ6vdWhuDRpHBelz7DBhU4VqtSg2YILzmpl2W1P03NhaS6yfBQz3L9PRJYDn1TVEz6sD4chCRT8rxkcXDEKEi94GLlZ9P4Sh0JzTeueuZGulb+nZvUNg34Pr4k3gB4B23CZ9/Rb2XHlwyx46m0ckAxZUbK4uazIjr+4ThnwRARtZfx9wPP1etMCPenvoti2wd0yn3tqdhQ0kBIzHaq/+hxsMKk5v2VQEKP3l2fT1jKFzq5q+rMGaZSseJNtXP961b+u/Fl0aRzS4tCLzX4gqy4py/ES6/r3JJCmUTXoNrJEXMFUwTKUKVOPkv7I7uIf6jAohqQ3A38PrBKR21W19LjWcUZYDuSnr4HB+TLD+YkKTXa2xR2a/1OUio2XEN14MZAneYK15Qop8bN8oNRsvJxlG67AQOgwPGkZzLpy0AFyC4OWKg9dGuJJ1gwGaRz6xaUvYfFHuy/hPV/PT+cQuieGiz1ZSFzYldtm/uPZ7Fi3iIMtzbR1VNLjCElcMngqRpDj3vZfomBFgOKlf1TRXPrHQJ3KvVg4VBKhTqPYuJ6ejxDxVayOTIRUMj8wOjaMGnFSD3cD3wCeFpEPi8jFIjJMvO/EILwaM5wzKbcYLkSEAYIMNbZyx/mfIA99OOFD/sdTH7z2PRXCM7T6xPv0i01CbJLYpHE80kmQUtEZ6J94+ZXyh9+AEGlx6RWbfUmL5x69hOg3Fw57P6x/WsTeL1w/aNvuNYvY/voc9rU2cDRl0oNLUrx5qFkZKMDgTaT2JH/W72/Sv4aE2PRJNpcHP+h/4MBP43h6vLgI4kt/yACvbpkD9xz7dI+inPkicivwIf/cFwLvBc4RkU5VXXDMvTgGBCsnh6SiyROaw+VUGinH0mipfGxxB6S3FF5NOtzS6UKpyPPVkCwO3ZKhRQzW7Gwi+813cNWO55l29RbSLQ30H67jwGuzOdw6mUOHG+nsidMSvxoDOHtaH8lUhPbeKF220IVLnzgk/JclkKTDSXrIV20kN+oEicsMhD7JYviegiDVo2d8Kts7Y/z6vjdxbWc1k5fvwr7yKGZv6VP1Rq3SLCK7gNeAr6vqo3m/zVDV0kMIx4iIMUMnRT6R+56/enIkjLQgLEzA0VaXhtdRhZeqFDp//rr+4ZLNBu0GbcaxqFQrlw1vikZoNiFuKT0Zg1Z16ReHuBpEELJ4OUYFoT402TuFN5s/JZ5ET+N42VJ8jXTQ+qnQJ8ikl7/MJiBtpb/G3sbNVTAxMaj2o1BxNUmLS51aXFKjnHf2Xv73pn9lW39LSfP1ipGkb1LVrYV+OBkELYTR0n4Xs1LxWHJHjdR+WCeGkQka/h7ofcFl2IZLHzYH1MTNKr1GlqOGV86mQeNUq5Wr9mHiTYAOkMvi7OuigRHnBOpQSE3K190L3c/AdxwM/S5ewtzAkZcRb2l11Nert0uGg/1VvLhmDu0aLe3mUpyftCBBJzqOZQktFJfnPZx60cXPd1/gmEKqxkj59R0UQqoE/hCcxsXwjbW0rx+6eGucFCWGmZPwysCUxrD1HgzvA5KSggQNVJL85Bj4bQUSNJMrlyNE/OXLpgqOeJE7IKcWtBqQdd4wdZyGz+pRCkYi4Ui/FcqyF+jDI6XEGe1cQzLmBVlAgv/zJFxAHM+A81NRipGzhsMejsBqD/uNC+nKYYRT5YRJmssMiIGtLnEsYpg511TaVyuCVJAWBgmx/ZehdOFxipL0+GCkDCelEj73gGWY7cOcJx+FcvAHvtxCpWgC2KKQ5/Md1ogb4dIGBUjyiqIFL0SQ8CGuJrYY1GiELC49ksmVhwyOCfY31MsKXSgpx2g4bUgakKp/6Qv0rHiU2tU3UBVKiDsSxqqPDlueJm9bscbasL8JBdPR5fuCbcn3KWouHVBAzCE6cgFS50aG0G8BMYOMLYGxZehAMuFmrRxURsjFS1QRpENPjzEWdFqQNEyWHr/SRc+KR4sm6bHWGQqQb2QUIudYzxUEK8LDfEH9N98Sl8K/gbdePshZFeik1RrJHZPQbO6YoFZoXL21ZDFMEthEfAJG1aBGLTJ44WDHj7hZeBGoCMag8pCl4JQmaaEhuXb1DTlJeixtlaKT5qMUyTlSoYlweyN5K8KEzSfxcH3J5bhSr1ZoFHOQKyrYJyj3GAzjGd+gm+LE6DIMX8/1wrlT1aIX1zPe1MuVFVWDTiNLFpcDFzxFZv/BEe9d4b6eghCGJ0rVhkuLlqBhFCvdRiLoSD7a4MEP9zIUk98/rCMO0h3zhuewA76QXhr0NZhDGsTeM+Lk9MlwiZ3AHRa02SdZ2o1MzkAyVah3I1QbYLkGc0yhoTpDY12CSMSh5VA9a/tN9l75K/RH4zPp+Q2BUg2lQjje/tgwgcOGWZioMHwKzGB7uHhtmLhxNX0yGjnCBqHewAUV6JgVauXK7ti4HDT6c4SOiTetMGoq583p5Pp3PU7d4gMY9UmoztD7zALOefgKDj95G0+M06TnUxKFJMhoRsyJQKGXYaShvpjcSfnqQFj6hdMPwcAQ7uJNbK7VKCZCJ16Zm7D1jpIrFhEQ2hYlI0ECN2/uq/hTCqc3Jbnyzasx/+blQQl8uXwzK6pTpP/rFja0jZhruSBOW5IWY1QMt18hDJcHdax9CSM/bWV+H4e0V8AfWyhKFK5YFyAlds7/mcXFEIeYH9IM59Ky8AyibvFmXvWFHPOBBI1gUKUWlgpRoLY6SfN1Wwomp3CSUQ4fqSfyRjKcxkKWY20n33gp9tjh4vlhFJKkhYbw3G/DlBkPv0yDSjcGv6sQx1vb1CVpT9KK5KRrPJcVdaiqEM5UGPQtogbVauIAO1saYEqCQrBTETq6YxhjGMnGkuTsuENEbvaTTuwQkWMq7nCiEBR0AHJFH/L/HwnhiSmWGoPSng/3f9B+GMF0v3yEtw86PvQ3sNiDTxBFSohNt6TplgxxNb0UlBrNSdgA3vQUz7rPoEyqTUF7vOD1JjuraU2ZJWVZCXDSJamImMC3gBuAFmCtiDw8EdL5wPBD9aCKycP8H6Cgkz9UDzQoJ5NzG+XVEg2vVg1/D0vLsLspHG8PS8PcBJDQuslABw3SZaZxyMhAODMY9gfi9t6CR8Cfj6q4CglxqalOk9rWDDf0Ekbtb+v5xc+vomeMFsFJJylwMbBDVXcBiMiP8aqSjCtJRwtXDmeFDzluhDCfGSKXN41tYHrfwLKSkcOEEUzimFhq0LP0ebpX/p6mZ25m0oYVRHUgf793jqCPAwji9cH5+/3Jy1HMkHQeGpu3VAbNLQ3O4zCw9CWDS7VGqFaDw0aG7+yLMPknV3PNJfvoWZYh1m5hPTqJx775NubPP8DsWSa/Lb3+7ejzSccbInIbcLOqfsj//j7gElX9WN5+ucIOwLnAZiYWJuGtWxs/NHM+BhFcshymmDxc49+n0rFIVWtKOWAiSNJCCtyQNydc2EFE1qnqsiFHnUSU+1QcRKTkEigTwXBqAWaGvs/AK25WRhnAxCDpWmChiMwVkSjwR3hVScooA5gAw72q2iLyMeARvIIV96pq4TR1A/j38e9ZySj3qTiU3KeTbjiVUcZomAjDfRlljIgyScuY8DilSDpRwqcicq+ItInI5tC2RhF5VES2+38bTmB/ZorIEyLymoi8KiIfnwB9iovIGhHZ6Pfpb8fap1OGpKHw6S3AYuAOEVl8krpzH0NrCNwNPK6qC/EKsp3Il8gGPqWqZwOXAh/1783J7FMauFZVlwBLgZtF5NIx9UlVT4kPXrnyR0Lf/wr4q5PYnznA5tD314Fp/v/TgNdPYt8ewpsLMSH6BFQCLwOXjKVPp4wkBc4A9oe+t/jbJgqaVbUVwP875WR0QkTmABcAL57sPomIKSIb8ErEP6qqY+rTqUTSosKnb2SISDXwAPAJVR1rYbzjBlV1VHUpXhTxYhE5dyztnEoknejh08MiMg3A/3tC87iKSASPoD/QgaLEJ7VPAVS1C3gST48vuU+nEkknevj0YeBO//878fTCEwIREeA/gddU9WsTpE+TRaTe/78CuB7YOqY+nSzlfowK+JuAbcBO4HMnsR8/AlqBLJ6E/yDQhGetbvf/Np7A/qzAU31eATb4nzed5D6dD6z3+7QZ+Ly/veQ+lcOiZUx4nErDfRlvUJRJWsaER5mkZUx4lElaxoRHmaRlTHiUSVrGhEeZpOMMEflTEfl26PuXROR/Qt/niEjSj3GX0m6FiGwQkYyITDqOXZ5wKJN0/PE94C0iUu8XbXszA/kDAuxUL8ZdNFQ16R8zkULD44IySccZqprAi1D9HfDPwG2qmhxuf1+ybhWR74rIZhH5gYhcLyLP+hOFLz5RfZ8oOOmrRd8guBevquDbVHVnEfsvAG7Hk7hrgXfjhT7fCnwWePv4dHNioixJTww+DxyheKGwW1U3qaoLvIo3k12BTXiTrd9QKJN0nCEinwLiwLuAjxd5WDhDohv67vIGHP3ecBd8IiEi1wJ/Alymqr0iUisiS1V1w0nu2imFsiQdJ4jILOC7wO2qGiTs/AbwiZPWqVMU5al6Jxn+mqRfqeqYllaIyB5gmapOtBSPxw1lSXry4QB1Y3XmAxEG58097VCWpGVMeJQlaRkTHmWSljHhUSZpGRMeZZKWMeFRJmkZEx5lkpYx4VEmaRkTHmWSljHh8f8BTn1hHQRI+oEAAAAASUVORK5CYII=", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# ---------------------------------------------\n", "# Creating a view plot\n",