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Commit 730beb92 authored by Benedikt Zoennchen's avatar Benedikt Zoennchen
Browse files

vornoi intersection computation - not finished jet.

parent ba1a7dd6
......@@ -2,7 +2,61 @@
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 151,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"from vadere_analysis_tool import ScenarioOutput, VadereProject\n",
"sns.set(style=\"darkgrid\")\n",
"\n",
"def plotDensityTime(vproject, ending, axes):\n",
" dataFrames = []\n",
" for outStr in project.output_dirs :\n",
" out = project.output_dirs[outStr]\n",
" for fileStr in out.files :\n",
" if fileStr.endswith(ending) :\n",
" ndf = pd.DataFrame();\n",
" df = out.files[fileStr]()\n",
" #df = df[df.velocity > 0]\n",
" ndf['density'] = df.density.astype(float)\n",
" ndf['timeStep'] = df.timeStep.astype(int)\n",
" ndf['scenario'] = [out.scenario['name']] * len(df.velocity)\n",
" dataFrames.append(ndf)\n",
" concatFrames = pd.concat(dataFrames)\n",
" return sns.lineplot(x=\"timeStep\", y=\"density\", data=concatFrames, ax=axes)\n",
" #plt.show()\n",
" \n",
"def plotFundamentalDiagram(vproject, ending):\n",
" dataFrames = []\n",
" for outStr in project.output_dirs :\n",
" out = project.output_dirs[outStr]\n",
" for fileStr in out.files :\n",
" if fileStr.endswith(ending) :\n",
" ndf = pd.DataFrame();\n",
" df = out.files[fileStr]()\n",
" df = df[df.velocity > 0]\n",
" ndf['density'] = df.density.astype(float)\n",
" ndf['velocity'] = df.velocity.astype(float)\n",
" ndf['scenario'] = [out.scenario['name']] * len(df.velocity)\n",
" dataFrames.append(ndf)\n",
" concatFrames = pd.concat(dataFrames)\n",
" sns.relplot(x=\"density\", y=\"velocity\", hue=\"scenario\", data=concatFrames)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Load the Vadere project"
]
},
{
"cell_type": "code",
"execution_count": 153,
"metadata": {},
"outputs": [
{
......@@ -11,12 +65,391 @@
"text": [
"loaded 1 out of 1 output directories. \n"
]
}
],
"source": [
"projectFolder = \"./../../../../VadereModelTests/TestOSM_zhang-2011/\"\n",
"project = VadereProject(projectFolder)\n",
"#out = project.named_output.C_050_180_180_2018_11_26_16_30_29_355() "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Method A Plots"
]
},
{
"cell_type": "code",
"execution_count": 154,
"metadata": {},
"outputs": [
{
"data": {
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NJaSf8KFpGu1aNCIy3FXi/skXtsdVRpHwqtB1DZfLqFKBcd3QcHSd5VuPsm1/Nppp4HPgr/9Yxp7DRfOEW9OyePl/V2NZCmynyguFDKX40++SaBEXCRQNI/9pVBJGCPeYhRBCeopVYCl4/oOVge0Jx3O8PPc/K3npnkGYSvHqxMF8PG8bGdmFXHF+W7q1bYpVDWcRaoZO+gkv2/dm0aNDLI0iXFDJXpeua+T5HO57bTHe4lM+2jSL5pHx55CZXXKbxfa9WSg4o56tZTlEug2euf18/JaDy9QxNbDlsGIhRAiTpHiadF3DAo5mFZRoP3aiENtx0JTCrWmMH9EV2ymqL3rqo6YqRzN0Zv+QxmcLdwbaJlzdkwuTWmBXIuFqus6P6/fz2B8G4HEZrNxymJkLduI2DSLDShYFb1ncuztTPl/R4hw3gGWXWqEqhBChRoZPK0kzdDKPF7DrcA55BX7+clN/PK5fjodq1jQCI7AnT2FbDjhOtSREKDrmadbiXSXaPpy7lcqWHtV0jf7dm/P5ol28O3sjzWMjee3PQziR7+X+G/sR7in6fhQT5eb+G/vhMSq4oBBC1ENB7ynm5uZy/fXX884779CqVasSt6WmpjJp0iSys7OJj4/n1VdfJSYmJtghnTbD0MnI9fHI20sDxcGHnt2Ku6/tzSsf/UyrhCgeuqk/JipovSFHUWpLh89vV3qY028r/vLmkkD8O/Yd574bzqZ/1wSaRnl4+8GL8PpsPG4Dl64aTAUfIYT4taD2FNetW8fYsWNJS0srdZtSijvuuIMJEyYwe/ZsunXrxrRp04IZTpXZCqbP2hBIKAALf95Px1aNeffRS3j61oE0DjeDemKEoUGfLvEl2ob2a41eifMNPR6T9bsySsQP8O3yvXh9dtE8n2Xj0QHLxu+T1aFCiIYpqD3FGTNmMGnSJB566KFSt23atImIiAgGDx4MwO23386JEyeCGU6VOUDWCW+p9rwCP+FRLpQi6PU/NUdx7+/7smD1PjbuyqR/t2acn9QCpxLHWNm2Q1xMeKn2pjEejOI5UiGEEEFOipMnTy73tr179xIXF8ejjz7Kli1b6NChA0888UQww6kytwEXn9Oaj77ZFmhrFOkmNiYMVQ2rSitDKYXyW1zSL5FhfROLFvxU8lxHy3JolRBF9/ZNA4UFosJdjL2sK04I12b1eEwMQ6Ow0I8TumEKIeqRWlt9alkWK1as4MMPPyQpKYnXXnuN559/nueff77S14iNjQpihCWNOL894R6TBav20SIukvFX9iA2Jhy9mvYfBkt8fHTg54du6k96VgEn8nx0SIwhJspTZpHv2nQy3szsAlZuS+fIsXwG9UkkJspDo0h3LUdX0q/f27pA4hWiYrWWFOPj42nbti1JSUkAJCcnk5KSclrXyMzMrdF6oldd2IHzejTH1DVQiszM3Bp77qqIj48mPT0n8LtuGsQ3CaNZ0wiwbY5n5dVidKWdjFdzmTz97jLSDhUNp//ft9t45vbzaRMfha+Mw49rw2/f21An8VYfSdb1W611E/r27cuxY8fYunUrAAsWLKBHjx61FU6lGIaOrhSO7YR0cW+PxwDTYP/RHJRhoLuK/v1n4S4mPDufO19cwLItR8EIrV4iFB03deRYfiAhQtHK24++2YZPysMJIYKsxnuKEyZMICUlhaSkJN5++20ef/xxCgoKaN68OS+++GJNh1PvuN0GOYUOT077kaNZBZiGzoP/1Y+8Aj9fLE0FigpzT/3Pel778xBiwkyUCp0Er+vgL2Oe1mc5OEo21gohgqtGkuKCBQsCP0+fPj3wc+/evZk5c2ZNhNBg+Bx457P1gYo7lu2wfW8Wew+XHopatyOdYX0Tq63AQHUoWhQUTVzjMDKO/1J+btTQjkS4DQoLpbcohAgeKfNWzziOYvfB7BJtBzPy6NquCSu3HCnR3rl1kzLPQqxtLk3x4t2DmPPjbo5mFTB8YFtaxkZSWOiv7dCEEPWcjEbVMy5TL7XJf932dC4+pw09O8QCxQcHD2xLi6YRITk36vMVFRO4ZkhHbru6J23iImps64sQomGTnmIdoOugGUZRnVMFLlPD7y1nFaZtcfOV3ckvtFi95QjNmkZyz3V9MDS4b2xfLEehaxqGBsoO7URTUCA9QyFEzZKkWBeYJv/8chNL1x4kOtLNrSN70r19kzLL6Ng2GCjuvKYXCg3lKCLcGgUFRUnUBFCqEsXhapfLpeNTGrbtYOg6Lh2sEJr7FELUTzJ8GuLcHhdzfkhj0c8HsB3F8Rwvr3y0Gr9VflqzbQflt4lvHI5m24GEWFeYpk6BBX/7x3L+9Nx87p2ykK37jmO45OgOIURwSVIMcYV+mzXbj5ZoUwq27c3C7S47Seg6uN11dxDAQuO/P10X2KuYk+/npQ9XV/qYLCGEqCpJiiHOY+p0TCx5nNbQs1uR1DEWvwMREa4St2mmQZ5fsWp7OnsOnwCz7vWuHKXYtierRJvfcjiR56uliIQQDUXd7U40ELZlcd0lXdi+7zipB7J57A/nEBcTwdsz11Potbh6SEc6JcagLBvDZbBk3UHenb0p8Pg/XNWDoX0SsStZPDwUGJpGt3ZNWb31lx6y29SLap/KKlQhRBBJUgxxjgOmrnj8DwOwLAc0jTtfXIBVvL9wY2omf73tPDq1iKbAUnw4d2uJx3/0zVYu7NWy1EHELpcBGihHFV03hBgobh/dixc+WMXO/ceJiXKTcl1fdIqO8RJCiGCRpFgHnExajaM8zF2+N5AQT5rzQxp3j+kFyqHQV7In5fXZKFSJpKi5DFbvyGDt9nQGdG9Gt3ZNq7QP0DR1/A4owKWDXU3J1bIcPKbOozefg62KtpC4DfD7pJcohAguSYp1iG0rkjrF8tSEgaQdOsEXS1LJzC6kSSMPuqahaRr9uiaUGHbs2yUeXftVSjR03v9qM4t+PgDAwp/3M+L8dlw3rDPOaSRG3dA5esLL3z/bQGZ2IRf1a8VVF3ao1KHHlXHyi8DJGVHZjSGEqAmSFOsIw9A5UeDn3Vmb2LnvON07NOXhm8/hnU/XM3poJ/w+H7rSuOe6PsxanMqm1Ey6t2/K1UM6ollOYNjRARavOVDi2vOW7+GaizqXGmI9FRuNR6b+gL84ef3n+52Ee0wuO6e17CcUQtRZkhTrCBv46z+WcyC96AzHNdvSyS+weGz8ADymhrfQART4LEYP6cCVF7QjJspDTnZBiY36GqBpWomTMTTt9A5K1nWNtCMnAgnxpMVrDzD07ERZ0iyEqLPk71cdYdkqkBBP2rY3C8dReAtLDln6vRa67RBWxl5FHRh+btsSbVcP7ohxGnlRKUVc4/BS7a3iozD000uwwaIbOhgGPgUYBkYInh0phAg90lOsIwxDJzLMJO9XCTA2JozT7OShbIfrLu7MgB7NWL8zg7PPSqBVfNRpzScqBREek8vPa8vcn/YA0Djaw7gR3dGc2i8hpxkaOw+e4JWPfqbAa9G0URhPTRhITJgZkqeCCCFCh6ZC6YTZ05SZmVujpzzEx0eTnl76XMKaoBs6Ow6e4KV/rcJnOYS5DZ645Vxax0aUu6XiVPEaho5h6Ni2jV3VUjGGjt9W5BdaxES50ZXCOYOkU13vrzIM7nppQYmVuO1aNOKJPwxAc6onKdbmZ6EqJN7qEx8fXdshiCCSnmId4dgOnVo24p2HLya/0CIizERTVd9jaNvOmfeabAcXEBNmgGWHzB5Cn98utTUl7dAJNF0DB3Sz6MQRn2XjcRm49eLjqoQQDZ4kxTpEFSexCFMDy671YcpQ5XEZNIp0lygL17NDbNG4r2nw7ap9fDxvG7ajaBEbydN/Og+PocvQqhBCFtqI+kH/1SdZx+GpCQNJjI8CoHv7pky8vi+6Uvgsh/+duxW7eNj9UGYe73+5CRUiC4SEELVLeoqiTtNNHQeN9F8VMXAsm7goN3+dMBA0DQ2FrhS6rnEkI6/UNXYfPIHfdqh7pdOFENVNkqIo2reoa9gKdK2oisyZLJipKR6PyY6DJ5j83gr8loOua9w1pjf9z4rH8tslihE4gOMoWiVEYRoa1q8WF/XtGk+YaeD31Z2i6UKI4JDhU4HmMnjzk3VMePY7bnt+Ad+u2o9WB/b1FVqKN2esDRQRcBzFtM83cIrzlzE0eOKWgTRrGoGhawzq05JrL+4iCVEIAUhPsUEzDA3dNPnqx92s2Z4OgGU7/O83WzmnezNiwkxCfcdOZnZhid+9Phu/5eAu5/6O36ZTi2ieveN8NF0r+lZoWbJoSQgBSE+xQbPQWfDzfjamZpa6bee+4xinU+amFmga9OocV6KtVUIULvPUH2uv10KzHfDbOH6batq6KISoByQpNlAul8HXP6WxfU8W3dvFlrr9rLZNQn6LgqEU9/6+Lxf2aUnjKA/9uibw5C3n4pFPtRCiimT4tKHSIPN4Acs2HuKZ289n/9Eclm08hMdtctMV3YgMMwP7IkOVbRctrrn1qh5YtsLQNQyUbMQXQlSZJMUGyrYcRlzQju9/3s8z/1zONcM6M3JwR+Iah+PSFbY/tBPiSY6jwLHRAeWALJcRQpwJGWhqoBxHEdcojKcnDKR9YgwbdmVgGhomTp1JiEIIUd2kp9iAKduhfbMo7ru+LxpF35BCfR5RCCGCSXqKDZxlObjdRVVh/BTtWZSzB4UQDZX0FBs6U2fV1nTe/XwjuQV+zj4rgXuu6wPSYxRCNEDSJWjgLBte/3gNuQV+AH7edpSZC7bj8rhqOTIhhKh5khQbMLfbIO3QCX5btGbDzsxS5xHWFYahg66jdA3TJSW+hRCnR4ZPGzCfz6ZN89KniJ/Vtglhbh2/t24NoWq6zpHsQv5nzhbyC/2MHNSBPp3jUFU8iFkI0fBIT7GB85g6t47sgae4V3VWmyaMvewsHKvu7fjzK8UjU39gU2omuw+e4PX/W8vO/ScwKyj7JoQQJ0lPsYFTls2gPomc16sltq0wDXBp4K8gJ4aHu9A0jcJCX0jUDjVNgxWbDwcODz5p7rI0Oo/pVUtRCSHqGkmKAttnoVH8YbDAf4r7ut0GPqXx7ar95OT5GHZOa8LdBo6/ducglXJo1jSiVHuL2Miig4drISYhRN0jSVGcFr/SeOjNxWQcLzqy6bNFO3k5ZTBNI11YtTh3Z9uKds0b0b19UzbvPgZAk2gPvxvaEduqm4uGhBA1T5JiA6ZplFp5eiput8naXZmBhAhg2YoZ323n9lFJUNv9MdvhgRv7kZ3ro8Br0Tw2AkM52L96jVFRHhwFynEoKDhVn1gI0RBVuALhnnvu4ccff6yJWEQN0Q0NTIP0HB8+BVSygo2mgV3GBKKjFCoEjulVSoFl0zjcoGWTMLBs7OKMaBigu02+XbmPqZ+u5+cdGehu+U4ohCipwr+Gl156KVOnTmX48OH84x//4Pjx45W+eG5uLsnJyezfv7/c+yxcuJBhw4ZV+prizBiGRk6hzT0vf89Dby3l9hcW8OmiXZVKjF6vRVKnOGKifjnXXtdgzLDO6KfT5QwypYpPz/gVWzN47eM1TJ+1kcVrDvDSh6uZtTgV0yOJUQjxiwr/Eo4cOZIPP/yQqVOnkpmZyZgxY3jwwQdZv379KR+3bt06xo4dS1paWrn3ycjI4IUXXjjtoEXV2WhM+3wjeYW/LC/9culufJWcDzQ1xasThzBmWGeGD2zLa38eSlyjMPwhfrKGZSvWbk8v0Tbnh91YdugkcyFE7avUuJnjOOzZs4e0tDRs2yY2NpannnqKN954o9zHzJgxg0mTJpGQkFDufR5//HHuvvvu049aVJmj4MixvFLt2bk+NE2r8PGWz0GzbcYM7cgfruxGTLiJUwcWsuhlvDTDqPj1CiEalgrHjqZMmcKnn35K69atueGGG3j99ddxuVzk5+dz0UUXkZKSUubjJk+efMrrfvDBB3Tv3p3evXtXLXJRJS5DY3DfVsxcsCPQFhlmEt8kHHUayS0/3xeM8ILGMDQG9WnJkrUHA23XXtwFt0vHVweSuhCiZlSYFI8dO8b06dPp2rVrifaIiAheeeWVKj3p9u3bmTdvHu+//z6HDx+u0jUAYmOjqvzYqoqPL10WLZSVFe/vhnREAxat2U8VfvAMAAAgAElEQVSzppHcNjqJpo3CQuLIqGC+v7dc1ZPBfVqxZc8xBnRvRvPYSGKiwiAqrErXqw+fhVBW1+IV9UOFSdG27VIJMSUlhTfeeIMLL7ywSk86d+5c0tPTueaaa/D7/Rw9epQbbriBjz766LSuk5mZW2pBRTDFx0eTnp5TY893pk4Vb/IF7Rg+sA26pmGgOFbGkGpNq4n3t0e7xvTpHIfX68fns6r8fHFxUWQcLyDrhJeIMBOPSw/p47bq02e3tkmyrt/KTYqTJk3iyJEjrF69mmPHjgXaLcti3759Z/SkKSkpgWHX/fv3M27cuNNOiOLM2H67eEJZ0ZAGDwsLLQoLz6yuq6ZpHM0q4ME3FpOV4wVgcN9Exo/oDnZDejeFqH/KTYpjxoxhx44dbNu2jeHDhwfaDcOgT58+VXqyCRMmkJKSQlJSUpUeL0Qo0AydD7/eEkiIAIvXHOB3gzvSJMJVtF9SCFEnlZsUk5KSSEpK4oILLqBZs2ZVfoIFCxYEfp4+fXqp21u1alXiPkKEOttxOHA0t1T70ax8YqMaBwoGCCHqnnKT4sSJE3n99de59dZby7z9iy++CFpQQoQyt6EzrH9rduz7pZCFaeh0atUYO4TnFYUQFSs3KU6YMAGAJ554osaCEaIu8PttBvVNJLfAz7fL99A4OoxbR/bA0EKh2J0Q4kyUuwa/Z8+eALRp04Y5c+YwYMAA4uLieP/992nfvn2NBShEKIqJ9DD8nFY8e8cF/OW/+tG8cRhKhk2FqPMq3Jj28MMP06FDBwASExMZMGAAjz76aNADEyLUWX4H3XHQHKdWj80SQlSfCpNiVlYW48aNA8Dj8TB+/HjS09MreJQQQghR91SYFG3b5siRI4HfMzIyZMm5EEKIeqnCijbjx4/nd7/7HYMGDQLgp59+4qGHHgp6YEIIIURNqzApjhkzhp49e7Js2TIMw+DWW2+lS5cuNRGbEEIIUaMqdcKq1+slNzcXv99PdnZ2sGMSQgghakWFc4qff/45KSkpnDhxgry8PO677z5mzJhRE7EJIYQIcRs2bOCxxx6r7TCqTYU9xffff59PPvkkcFjwhAkTuOWWW7juuuuCHpwQQojQdrIkaH1RYVJ0HCeQEAGaNWuGrtf+uXtC1CWmaaC0oqEZv19O0hDV5/DhwzzwwAPk5+ej6zqPP/44+fn5PP/88yilaNmyJa+88grh4eG8+OKLrFixAtu2GT16NOPHj2f58uX8/e9/JywsjF27dnHWWWfx8ssv43a7mTJlCj/99BPZ2dkkJCQwZcoU4uLiGDhwID179iQ9PZ2HHnqId955h3/961/s3r2bJ598kuPHjxMREcFjjz1Gr169avstOi0VZrfGjRvz3XffBX7/7rvviImJCWpQQtQnmmmwYfcx/vuzDcxbtR/NZaDrWm2HJeqJmTNnMnToUD799FNSUlJYsWIFDzzwAC+88AJffPEFXbp04bPPPgtMe3322WfMnDmT+fPns2rVKgDWrFnDk08+yddff83BgwdZunQpe/bsITU1lY8//phvvvmGFi1aMHv2bKBo//qECROYNWsWpvlL3+rBBx/kpptu4osvvuCRRx5h4sSJ+Hy+mn9TzkCFPcUnnniCO++8k7/97W8AuFwu3nrrraAHJkR9YJg6Xy/fw8ffbgdg2cbDLNt4iEfG9QeplCqqwXnnncc999zDli1bGDJkCGeffTZff/013bp1A+D+++8His6x3bJlC8uWLQMgPz+fbdu20alTJzp37kzz5s0B6NixI9nZ2bRt25a//OUvfPLJJ+zevZu1a9fSpk2bwPP27t27RBx5eXns3buXyy67DIA+ffoQExNDampqqYPqQ1mFSbFz587MnTuXtLQ0bNumQ4cOJb4ZCCHKZyn4YklqibYd+47jtxWuWopJ1C/9+vXjq6++YuHChcyZM4e8vDw07ZeRiJycHPLy8rBtmwcffDCQtI4dO0ZkZCRr167F4/EE7q9pGkopNm7cyP3338/48eMZPnw4uq6XKNwSFhZWIo6yiroopbDr2MHb5Wa3Z5555pQPfPzxx6s9GCHqI4/bJK/QKtFm6Bo40lMUZ+7FF1+kWbNm3HzzzZx77rmMGjWKsLAwdu7cSadOnXj33XcBGDhwIDNmzOCiiy7C5/Nxww038PTTT5d73ZUrVzJgwADGjh1LVlYWCxcuDCTUskRFRdGqVSvmzZvHZZddxtq1a8nIyKBz587V/pqDqdyk2Lhx45qMQ4h6yaXBzSO6MeXjNYG2C3snIlOKorrcdNNN3H///Xz66acYhsELL7xAREQEDz30EH6/nzZt2vDiiy/idrvZs2cPo0aNwrIsRo8ezbnnnsvy5cvLvO6IESO4++67ueqqq4Cik5P2799/ylheeuklnnrqKd58801cLhdvvvkmbre72l9zMGmqEoVMCwsL2bNnD507d8br9RIeHl4TsVUoMzMXpwa/bcfHR5OenlNjz3emJN7gOa1YDZ3cAovVW4/QITGGNs2iUVbNDinVpfcWQjve+Pjo2g5BBFGFq0/XrVvHJZdcwm233cbRo0cZOnQoP//8c03EJkT9YDtEewwu6deKdgmRNZ4QhRCVV2FSfOGFF3j//fdp3LgxzZs358UXX2Ty5Mk1EZsQ9YZSCr/fxq7kQcSmqWMYsh9YiJpW4f+6wsJCOnXqFPh9yJAhdW41kRB1hWHoYBqs353FjoMn0EwDw5AJSCFqSoV7K0zTJDs7O7DENzU1tYJHCCGqQtPAp+DPry4kt8APQIvYSJ6983yQL6JC1IgKe4p33HEH//Vf/8WhQ4e47777GDt2LHfccUdNxCZEg2K6DGYv2RVIiACHMvNYvzMD05ShVCFqQoU9xdmzZzNu3Dh8Ph9KKe666y46duxYE7EJ0aAoBdk5pUtincjzldiMLYQIngq/fg4YMIBPPvmE999/n7y8PBo1alQTcQnR4Di2w1WDOpRoc5k6A3u0kCLiQtSQCpPi2LFjmTFjBu+88w7Z2dlcf/313HXXXTURmxANiuMo4hp5eO7OC+jXNYELerfg1YmDccnIqaiE3Nxcnn76aZKTk7n66qu56aab2LRpU6n7KaV44YUXuPzyyxkxYgSrV68O3HbxxRdz9dVXB/4dOnQIgH/+859cfvnlDB8+nHnz5p0yjm3btnHllVeWaHv33Xe54oorGDFiBO+9916g/ccff+Sqq67isssuY8qUKRW+vuTk5BIFBJYuXcrIkSNJTk7moYceChQfP3jwIDfeeCOXX345d9xxB3l5eae89q9V+r9bYWFhYAjVMIxKP4EQovKU7dCySTh3j+nFn67qSbTHwLGd2g5LhDjHcZgwYQIxMTF8/vnnzJo1i7vuuosJEyaQlZVV4r7ffPMNu3btYs6cObz99ts88sgjWJZFVlYWLpeLWbNmBf61aNGC9evXM3v2bGbNmsVHH33Eiy++yPHjx8uM4/PPP+fWW2+loKAg0LZnzx4++uijwOkcH3zwAXv27KGwsJBHH32UqVOnMmfOHDZu3MiiRYvKvO66desYO3YsaWlpJdofe+wxpkyZwpdffklhYSGzZs0C4Omnn+aGG25g7ty59OzZk6lTp1b6vawwKb733ntcddVV3HfffTRr1owZM2bwxhtvVPoJhBCnx7YdlOVgW3aNVmwSwbVw9T7++Mw8Rt4/iz8+M4+Fq/dV27WXL1/OoUOHSElJCRzYMHDgQJ577jkcp+SXqkWLFjFixAh0Xad9+/a0aNGCNWvWsGHDBpRSXH/99YwaNYqvv/4agMWLF3PppZfi8XiIjY1lwIABLFy4sFQMOTk5zJ8/n1dffbVEu+M4+P1+vF5voGNlmibr16+nbdu2tG7dGtM0ueqqq5g7d26Zr2/GjBlMmjSpxNm+ALZtk5ubi23beL1ePB4Pfr+flStXMnz4cABGjx5d7nXLUuFCm40bN/L4449z7rnnVvqiQgghfrFw9T7e+mQd3uK54fSsAt76ZB0AQ/u1PuPrb968ma5du5Y6AH7IkCGl7nv06NESySU+Pp7Dhw8THh7OoEGDeOCBB8jIyODGG2+kS5cuHD16lKSkpFL3/63o6GjefPPNUvVR27dvT3JyMsOGDcNxHK699loSExNZs2YN8fHxgfslJCRw5MiRMl9feQVjnnrqKW666aZAMfLLL7+crKwsoqKiAl8O4uPjy71uWSrsKb7yyiuSEIUQ4gx88PWWQEI8yeu3+eDrLdVyfV3XSxz/dCqO45RYzayUQtd1LrnkEh5//HHCwsJo1aoVl156KUuXLi3V0zz5fJW1ePFiNm7cyOLFi1myZAkbNmxgzpw5ZcZxOqus09PTefnll/nyyy9ZunQpvXv35rnnnivzOqdzXZnCF0KIIMvIKjit9tPVs2dPNm/eXOpMw1dffZUbbrghsHBm/vz5NG/enKNHj/4SQ0YGCQkJfP/992zYsKHE403TpHnz5qSnpwfa0tPTSUhI4PXXXy9x3fJ8//33DB8+nMjISKKiokhOTmblypXlXnf+/PmB677++uvlXnfVqlV06dKFNm3aoOs61113HStWrKBp06bk5OQEKq+dvG5lSVIUog7SdYiIcBMe/stRxS6XgdttIFsaQ09ck7JPFiqv/XT179+f2NhY3nrrrUAyWLJkCZ9++ilvvPFGYOHMxRdfzODBg/niiy+wbZs9e/aQlpZGUlISBw4c4O2338ZxHDIyMliwYAFDhw5l8ODBzJs3j4KCAo4dO8ayZcs477zzmDhxYonrlqdr1658//332LaN3+9n8eLFJCUl0bt3b3bv3s2ePXuwbZsvv/ySwYMHc/HFFweuO3HixHKv26VLF9avX09GRgYA8+fPJykpCZfLRf/+/ZkzZw5QtPhn8ODBlX4vK5xTFEJULDzchQKUo/B6rQrvfyYMl0GB3+HrJalEh7sY1DcRx4ElGw6SX2gxuG8ibkOTVashZNwV3UrMKQJ4XAbjruhWLdfXNI2pU6fy3HPPkZycjGmaNGnShGnTphEXF1fivpdffjnr169n5MiRQNF8XVhYGNdffz3btm0jOTkZx3F44IEHSExMJDExkZEjRzJmzBgsyyIlJYVmzZpVOrZrr72W1NRUrrzySkzTZMiQIYwaNQpN03j++ee555578Hq9DBkyhMsvv7zS1+3YsSMTJ05k3LhxGIZB27Zt+etf/wrApEmTePjhh/nv//5vWrRoUWrxz6lU6jzFUCXnKZ6axBs8J2PVdcA0+WH9IbamHePcHs3p2SEWxx+cxGiaOtmFNn+esgjLdtA1eCllMJPfW8GxE4VA0Yb/1/88hHBTDwyn1aX3FkI73qqep7hw9T4++HoLGVkFxDUJZ9wV3aplkY2oXtJTFOIMOLrBm/+3hjXbiuZGlqw9wO+GdGT0kA5YvuqvQqMbBp/M34JV3Avs3LoJW9KOBRIigN9y+M/Cndx8eVcsqYQTMob2ay1JsA6QOUUhzoDtqEBCPOnrH9OwgjRyqVCBhAhgGBp2GcOkluVQZ4eAhKhFkhSFOANlLWoJ5vmHyna45qLO6MVPsW1PFj07xhH5qwU3uq4x+qJOKJlTFOK0yfCpEGdA1zSG9E1k0ZoDgbYxwzrj0nX8VP/QpWU5xEZ7mPLnoXz1QyqR4W6aNvLw+n1DmPNjGnkFfpIvbE+Ux5SFNkJUgSRFIc6EZTM+uQeD+iayefcxBnRvRkKTCPw+f8WPrSLHsmkcbvKHK7uhAfn5fnRg9KD2APj9jvQShagiSYpCnCHlt+jaKoae7Zri81lYVvAXt9i2Q0F+ycTnC8LCHiEamqDPKZZ13MdJ3333HVdffTUjR47kzjvvJDs7O9jhCBEUPp9Nfr4PK1grbIQQNSKoSbG84z6gKFk+9dRTTJs2jdmzZ3PWWWfx5ptvBjMcIYQQ4pSCmhTLO+4DwO/3M2nSpEBlhLPOOitwoKUQQghRG4I6p1jecR8ATZo04dJLLwWKDjCeNm0aN910UzDDEUIIIU6p1hfa5OTkcNddd9G1a1dGjRp1Wo+NjY0KUlTlq2qJp9oi8QZPXYoVJF4hKqNWk+LRo0e55ZZbGDhwII8++uhpP15qn56axBs8dSlWkHirkyTr+q3WkqJt29x+++1cccUV3HnnnbUVhhBCCBFQ40lxwoQJpKSkcPjwYTZv3oxt23zzzTdA0UGZp5qHFEIIIYKpRpLiggULAj9Pnz4dgKSkJLZu3VoTTy+EEEJUihQEF6IeM8NcYBqkZ+UTEeWu7XCECHm1vvpUCBEchtvk43nb+G7FXiLCXYy/sju9OsVBDZShE6Kukp6iEPVQdHQYS9YdZM6Pafgsh+M5Xl77eA0FXgu3dBiFKJckRSHqodwCPys3HynVvm5HOpGR4bUQkRB1gyRFIeqh8DCTDokxpdo7tmqML4jHWglR10lSFKIeys/1MnJQBzq2KkqMmgbDz21LQpMI8vKsWo5OiNAlC22EqKci3BqPjR+A33IwDA1D01F+SYhCnIr0FIWop/Ly/GDZuFA0axqJsiQhClERSYpCCCFEMUmKQgghRDFJikIIIUQxSYpCCCFEMUmKQgghRDFJikKIMhmGhmHInwjRsMgnXghRgq5raKZB2tE8Nu7JAtPAMLTaDkuIGiGb94UQJShd56l3l7HncA4AkWEmr947BLemoetFvUfLsnEcVcuRClH9pKcoyqRpYJg6jqahGTq6Lj2FhsAwdHYdyA4kRIC8QouZC3ZguA3Sjuby+dLdHDhWgGYYtRipEMEhPUVRiqZpYOr8+9vtrN56lA6JMdwysgceQ8e2ndoOTwSRpkF2rrdU+/EcL5t3H+P5D1YBMHPBDm4blcSQPi3x+yxsW3qNon6QnqIoTdeY/vlG5i7bQ/rxApZvOsykacuQo2nrP8ty6N0lHo+rZC9w5OAO/N932wHwuAweHT+AMLfJjAU72Z9ZgGbKnxJRP0hPUZSiNI1lGw+VaDuUmYfPcnDLKGq9Z6J49d7B/HveNnIL/PxucEcS46NIO3QCgOsvO4sf1h1g0ZoDAHy+aBc3Du/KZee0xrbkq5Oo2+TrnShFKUVc45IH0ZqGhsuUOaSGwLEVkS6dW6/qzsRre9OheRSaUlzQqyUAPTrEsnjtgRKPmfn9DmQEVdQHkhRFKaYGKdf1wSzeo6ZpMD65OzryV6+hcByFYzko28GyHHAcbh3Zk5Tr+uBxGajffBTUaaxE1XWdiAg3Ho8MVInQI59KUYptOSTGRjDtkYs5ciyfuJhwTB2ULLJpsJQC5bc456x4bDTOS2rBTxt+GWK/8sL26BpU9AnRTIMTBX6+XJZGq4Ro+nSJR7MdWcAlQoYkRVEm5ShwbJrHhKGUg5KpIgH4/TamqXHbqCT6dW3GptQMzktqQZfWTXAqOMA4LMzF5r1ZPPPPFYG2zq0b8+j4ASBJUYQIGT4Vp6R+O04mGjy/0rn31UUsXL0Pl6kzb/kenEp8TvJ9Nh99s61E2459x8nO9aLLXyIRIqSnKISoNLfb5Kuf0jie6+V4rpeNqZkA/LThEIN7tcDvP/WQgmWV7hFatgPIIi4RGuT7mQgphqGBoeNHQxkGuhSkDimaBsdzfaXas3O9RUUfTiHcbTBqaMcSbS3jIomNCceR0VMRIqSnKEJKvqX467vLOJSZR0SYyZ+v70unxBhZ5BMi/H6bK85vxzfL0ji54NTQNS7q1xp/BXOK3kI/fbrE87fbzmP+yn20jI/k0gFtMZTDqR8pRM3RVB2eNMrMzK3RosTx8dGkp+dUfMcQUdfi9US4mfzeCjbvPhZoc5s67/zlYrBDa6VPXXtvqzNeTdfIzPUxY/4ODE3j95d2ISbchapkd8/lMjBMAw1FQYE/6PFWt/j46NoOQQSR9BRFyLBtxY59x0u0+SyHAp9FuBxdFDKUo4iPdnPnqJ5FDY7COY3xT7/frnDuUYjaIhM2ImS4TJ2eHWJLtIV7TMJlk3fIse2izf2O5cgRUqJekaQoQkZUhJu7xvSma7smAMQ3CefJW85FVzKfKISoGfIVXIQUE8VDN/YLFJQztaIKOyJ0uNwGqKJScFKJRtQ3khRFSCkailOcnEGUmafQoesaStf5ZsU+9h7J4ZJz2tA6IRIlX1pEPSJJUQhRKY6m8+S0n9h/NBeAxWsOkHJdH/p3iceSI6NEPSFzikKICmkaZOf7AgnxpP98vxOfLLQR9YgkRSEaCJer6qXUlCrapF/qmqZOZTfLuFwG4eEuqXMqQpp8PIWox3RdQzMNflh/kCUbDmFpWpVL50WHu+hWvDL4pJuu6Iq7gj2kpktHc5ls25/N3BX7yPMrNDmwWoQoqWhzGkK5ykZZJN7gqc1YdV3D0TQsW2EYGjrln3WpmQaTpi9j75GiWE1D59WJg2kUZpz2/x1N08DU2ZqWxd4jOZyf1IKoMPPUJfgMHctRvDVzHet3ZBRfBx7/47l0a92YwkKpaCNCi/QURa3QdQ3DNDBcBvpvhuU8HpOoKA9ut6wD+y1NA0fXmfw/K/nT8/P503Pz+XbVPiij96frGnuP5AQSIhSdSPHRvK1UZQxTKYXy2/Ro25grB7Yhym2cMiFqGnj9Dl6/E0iIRdeBf83ZQoFUtREhKOhJMTc3l+TkZPbv31/qti1btjB69GiGDx/OY489hmVJWeCGQDN0crw2783ZwntfbSHHa6MV/1HX3SYrt6UzbfYmNu3JQndJYvw13dD5z4Kd7NqfDYDtKD76Zhv5XpvfHlKhaRoF3tKJJ99rndE5mZbl4PPZFV5D13UOZOTiL2NlaoHXgjo7RiXqs6AmxXXr1jF27FjS0tLKvP3BBx/kySef5JtvvkEpxYwZM4IZjggBmgaFfoc/v7aIhT/vZ+HP+7l3yiIK/Q5ZJwp5d9ZGXvt4Dd+t2Mtz/7OSzxbtwjjNHqMnzIWj6zi6jsfjCtIrqR2Wo9i2N6tU+74jOei/6f3ZtkOXNo2Jjij5HlwztBM1UUrWth1aJ0QTGeaiRVxkiduSL+yAxyUDVSL0BPVTOWPGDCZNmkRCQkKp2w4cOEBhYSF9+vQBYPTo0cydOzeY4YgQ4HabzFuxF8v+pZtgO4pvlu/BZzn8sP5gifvP+XE31unMfZkGq7YdZdL0ZTwx7SeWbTlcrxZ1uAyNfl1L/n/SNOiQGFNmdRlDKV69dwjJF7bn/KQWPHfHBbRJiCrzsN9gxXsoI4+/3XY+oy/qxLk9mvOXcf0Z1LslPq+MDInQE9SxqcmTJ5d729GjR4mPjw/8Hh8fz5EjR07r+rGxUVWOrarq2iR7KMb7254LQFSEq8yl/Vrxv8q+jq1px5jy7zWB39+csY7n7ryAnh3jqhbsKdTWe5t8YQcOZeSxdP1BoiNc3DYqicbRHiLCyu8V33JVT2yl8JzBtoyqimkURm6+nzHDOuE4ipiosEo9LhQ/u6L+q7UJG8dxSpzUrZSq8OTu35LVp6cWqvEO6duKWYt3kV18gnujSDcXnd0at0tnSN9WLPz5l/nn5EEdMHUq9ToiIz0sWlN67nrBqn10bNmI3Fxvtb2G2nxvNQ3+cGU3xid3RymFS4O8nELycgrLfUx8fDRZtfxZsIvf/vRyzlD8tVD97IIk6/qu1pJi8+bNSU9PD/yekZFR5jCrqB9M00DXi87S03F47d4hrN2RgVKKPl3iiXDrREaGcfOV3RnQozkbUzM5p2sC7Vo2wvJVbpWibTu0bd6oVHu7Fo3qVeFqpYDi16OBnFovRDWqtaSYmJiIx+Nh9erV9OvXj1mzZjF48ODaCkcEiWFoOLrOqm3pZOV4ubB3S9xoKMumX+dYDNOgwG/z9fK9uAyD83u1oG/nWPp1icfns07rMNrCQj/ndG9GlzZN2F68GKVjYgwX9G5Z7gnvQgjxazWeFCdMmEBKSgpJSUm8/PLLPP744+Tm5tKjRw/GjRtX0+GIIHM0nUen/sihzDwA/j1vKy+nDKZxuInjOBR6FRNfXVS0RB/4ZMF2ptw7BKwqJjHL4eFx/ckrsFAoosJd6I5D/eknCiGCqUaS4oIFCwI/T58+PfBz165dmTlzZk2EIGqBYWjsOnQikBABLFvx73nbuON3PQnzuPjPvG2BhAiQnetj6bqDXNq/VZV6d47jgAORruIlOpYtw4tCiEqTjUINlKZpYBj40bDQwNBLbf6uhmfB5y/dR/NZNkWnJiq8ZQyP+vylN6ILURVhYS6pjCROi3xaGijNNHjxXyvZklY099anczwTf98HqvFcvJObx2Oi3IGVpgDXDuuCDngLbUYO6sj8lfuwi1cRe9wGQ85uRX6+zAGKqjNcBn5H8f2aA8REe+jRPhZDOTW2P1PUXZIUGyCXy+CHTYcCCRFg7Y50Nu8+RlL7JtX6h8NQilcnDmbOj2kcO1FI8gXtaRLlCawGjQ43ee2+ocxevAuXqXP14I64DY16tFhU1DDT1MkusLj/tUX4ij/LrZtF89c/nQcyuywqIEmxAdI0je17j5dq37H/OL07xlKdfzhs20EDRg1qjwJsyyma9zt5u98m2m3wh+RuhHlcnMjOx5ZC0eIMKF3j3/O2BhIiFJXB27X/OGe1aoS/jCF9IU6SOcUGyLYdhvRNLNV+Qa+WWNU4fPprPp+N32eXWWzBcRwK8/24TANH/l6JM+Q4UFhGIfS8Qn+p+rBC/JZ8Qhog23Zo0yyaW6/uQeNoD00bhXHXmN7ENfLUaIUgIYLBbWhcPbhjibbIcBdJHePwSr1VUQEZPm2glGUzOKkl5/VsAQpcOrIIQdQLXq9Fm+ZRTL79fL5YuptGkW7GDOuES1fI8i1REUmKDZhl2YEi3JIPxa95wkxsBwyNOtm7Un6bNvGR3Dk6CV3XsHx+/D4ZBREVk6QohAgwTR1b0/nihzTSDp3ggl4tSeoYh+P///buPziq8t7j+Pvs2WRDIBiJCRGlAXV6DZQUBryl3CAGNa/Wys8AABAhSURBVLExAXFV5JeMqS2O10nhOlxAQe9ABS2O1h+1NVyVaRuG0iIkzB1jQA1Vg4ZbW1OiFGmq5KIhQWgSQkiye577R5bFyI+NLZvNhs/rL86Tk93PZnb4nuf8eL7RVxi/zhKBIiepKIpIkA+LH7/0HrUHmwB4d089s7L/hdzvptEZhTNGka9LN9qISFB7pz9YEE/6n3f+1u3xBpH+TEVRRILsMzyy4Int/cbEIpGioij9nmVZWLYL3DbG5cK29bU/G7dtMfFbqd3G5t6UTpxbhVEuDLqmKP2aZVkY28UvtlTz/t4GvpE6mB/dMZbEeDd+v+5G/CqX42fBjAxyvpPG/oNN/OuoVAbHx9DerocZ5MKgQ2bp31wWv9hSTVXNIXx+Q+3BJlYU7cKvr/4ZOQ6YTh9XDRtM3nfTuCjOxoRplSORvkgzRenXjGXx/t7GbmPNrR2c6PARZ6s/1dl0dvr1SINckHS4LP2aMYa01IRuY27bhUc99kTkDFQUpV9zAz+aOY7BA2O7tm0X/35bBi50PVFETqfDZenX/H6HiwbY/HTRlK5TprFuXMbgRFHDRssC43LhmK5/2xDR/LGxNn4s7MDyaepsIv2JiqL0e113mfqJc1ng80ddm1nL7ebnm6up+rAe29XVASLv30YQkU7Mbpu/1h/j1cpPuHiwh1uvu4q4WIvODl1/lP5BRVGkD3O7bXZ+cJCqD+sB8DuGVyr2853RqQy9qHdbfXk8bmo+Pcrq9buDY+988Bk/XTQl9C+7bRzTldW2LN3RKn2WiqJIH+ZgqP748Gnjez89wrBxl+E4vVdc2v2Gkt/Xdhtrbu3g4//7O6OGX3TWjvauWDf/XbKHd6o/A2Dy2Mu4O280JgoXGZf+TzfaiPRhLgvGp6ecNv6tKy7B38unT11A3BmWfIv3xGDOMmH1eNx88PFh3v7gM4wBY+D3fzzIh3/7Ao9Hx+TS96goivRhvk6HiaMvZeqE4bhcFp5Ym/m56QxJiO3VU6cAtmWYe1M67i8tkzfi0sFcnjLorA2qY2Js9vz19JluTe0XuLV0nPRBOlQT6eOcTh933XQ1c3KuBgxuC/wR6FrR2ekwJCGG5/8zi/dq6kkaPID0kUOwjcPZToR2dPi5ZtRQtlcd6DY+IX0onTp9Kn2QZooiUcDx+bH8fiy/E5GCeJK/08FtDDeMv5yMK4ZgOn1nnSUCdHT4+Obwi7llypXEuF14YmxuzbqKkcMuokN3rEofpJmiRA2Xy8KxrODzepGaMQm0tfV8gXCn08eMKVeSP/kKLMDtAl+HZonSN6koSlSwLAu/ZbG2+A/s/eQoiQkeFt45jrTkgZhevrYmX5+/w8fJlWZVDqUv0+lTiQ4ui3Vb97D3k6MA/L2lnUdfrsKcoSmuiMg/Sv+jSFTwG9hT+0W3sU6fQ9OxjgglEpH+SEVRooLLgm9+I7HbmNu2ggt9h5snzo3jcoHbJiZGjxKI9FcqihIVXMZw760ZfGNoVxuo+Dg3/zF7fK90u3DFuHnj/YOsfOk9frrxjxxu6aBNnehF+iXdaCNRwXEMHtvFf93zHXx+g21bvdItwhMXw9vVn/NiaQ0AB2hhyXNv8fMl16MWxSL9j2aKEjX8fgf8Dm4Mlt/plfZJJzr8vPG/dd3GOnwOf/n0iE6jivRDKooi5+C2LZITB5w2nnxxfKAllYj0JyqKIufiGOZ+L52E+Jjg0PirU0i+eACOuuuK9Du6pihyDn6/w8BYm6cfuI6DDccYPDCWhIGxJF00gMbGlkjHE5HzTEVRJITOzq41OtOSB+I4Dk6n1uwU6a9UFEV66FwLX4tI/6BriiIiIgFhLYrbtm0jNzeX7OxsiouLT/t5TU0NXq+XadOmsWDBApqbm8MZR0QE27YgsDoRLlfXtkhA2IrioUOHeOqpp9iwYQNbt27lN7/5Dfv37++2z6OPPkphYSGlpaWMHDmSF198MVxxRESwbRcnfPD4r/9AwY+38/iv/0Cbz2DbOmkmXcL2TaisrGTixIkkJiYSHx9PTk4OZWVl3fZxHIfW1lYA2traiIuLC1ccERF8wKPrq/jLga5uK385cJRH1+/Gp0dOJSBsN9o0NDSQnJwc3E5JSaG6urrbPkuXLqWgoIDVq1czYMAANm3a9LXeIylp0HnJ+nUkJyf0+nv+M5Q3fKIpKygvQOPR4xw41P1RmrpDLeCySE6Krr+PhEfYiqLjOFjWqXP1xphu2ydOnOChhx5i/fr1ZGRk8PLLL7NkyRKKiop6/B5ffHEMpxcbzCYnJ0TVs2nKGz7RlBWU9yRju7g4wcPRlvbgWGKCB4zp8ftF28GFfD1hO32amppKY2NjcLuxsZGUlJTg9r59+/B4PGRkZAAwc+ZMqqqqwhVHRAS3BYvnTiA+rms+EB/nZvHc8WgVWzkpbDPFSZMm8eyzz3LkyBEGDBhAeXk5q1atCv48LS2N+vp6amtrueKKK3j99dcZM2ZMuOKIiOD3OQwbEsezD2TR3uknLtbGNk7XYvMihLEoDh06lEWLFnHXXXfR2dnJbbfdRkZGBj/4wQ8oLCxkzJgxrFmzhoULF2KMISkpidWrV4crjogIAI7fYOEnzgX4/Gh9IvkyyxgTtfdd6ZriuSlv+ERTVlDe80nXFPs3PZwjIiISoKIoIiISoKIoIiISoKIoIiISoKIoIiISoKIoIiISoKIoIiISELaH93uDy9X7fdAi8Z7/DOUNn2jKCsor0hNR/fC+iIjI+aTTpyIiIgEqiiIiIgEqiiIiIgEqiiIiIgEqiiIiIgEqiiIiIgEqiiIiIgEqiiIiIgEqiiIiIgEqimewbds2cnNzyc7Opri4+Kz7VVRUMHXq1F5Mdmah8j733HNkZWUxffp0pk+ffs7PFG6hstbW1jJv3jymTZvG97//fZqamiKQ8pRz5f3oo4+Cf9Pp06czefJk8vLyIpS0S6i/b01NDV6vl2nTprFgwQKam5sjkLJLqKw7d+4kPz+f/Px8HnjgAVpbWyOQUi44Rrqpr683WVlZ5ujRo6a1tdXk5+ebjz/++LT9GhsbzU033WSysrIikPKUnuRdsGCBef/99yOU8JRQWR3HMdnZ2Wbnzp3GGGPWrl1rfvKTn0Qqbo+/C8YYc/z4cXPzzTeb3bt393LKU3qSd9asWaaiosIYY8yaNWvMk08+GYmoIbM2NTWZiRMnBseKiorMqlWrIpJVLiyaKX5FZWUlEydOJDExkfj4eHJycigrKzttv+XLl3P//fdHIGF3Pcm7Z88eXnjhBfLz81m5ciXt7e19MmtNTQ3x8fFce+21ANx7773MmTMnIlmh598FgBdeeIFrrrmGCRMm9HLKU3qS13Gc4Iyrra2NuLi4SEQNmfWTTz5h2LBhXHXVVQBkZWWxY8eOiGSVC4uK4lc0NDSQnJwc3E5JSeHQoUPd9vnlL3/JqFGj+Pa3v93b8U4TKm9rayvp6eksXryYLVu20NzczPPPPx+JqCGzHjhwgEsuuYQHH3yQGTNm8MgjjxAfHx+JqEDPvgsALS0tbNq0KeIHST3Ju3TpUpYvX05mZiaVlZXceeedvR0TCJ11xIgR1NfXs3fvXgBeffVVDh8+3Os55cKjovgVjuNgWada1hhjum3v27eP8vJy7rvvvkjEO02ovAMHDmTdunVceeWVuN1uCgoK2LlzZySihszq8/moqqpi1qxZbNmyheHDh/PYY49FIioQOu9JpaWl3HDDDSQlJfVmvNOEynvixAkeeugh1q9fz9tvv83s2bNZsmRJJKKGzDp48GAef/xxVqxYgdfrJSUlhZiYmEhElQuMiuJXpKam0tjYGNxubGwkJSUluF1WVkZjYyNer5cf/vCHNDQ0MHv27EhEBULn/eyzz/jd734X3DbG4HZHpo1mqKzJycmkpaUxZswYAPLy8qiuru71nCeFynvSjh07yM3N7c1oZxQq7759+/B4PGRkZAAwc+ZMqqqqej0nhM7q9/tJTU3lt7/9LZs3byY9PZ3hw4dHIqpcYFQUv2LSpEns2rWLI0eO0NbWRnl5efAaF0BhYSGvvfYaJSUlFBUVkZKSwoYNG/ps3ri4ONauXUtdXR3GGIqLi7nxxhv7ZNZx48Zx5MiR4CmzN954g9GjR0ckK4TOC10HGTU1NYwbNy5CKU8JlTctLY36+npqa2sBeP3114MHIH0tq2VZFBQUcOjQIYwxrF+/vk8ceMgFIFJ3+PRlpaWl5uabbzbZ2dmmqKjIGGPMPffcY6qrq7vtV1dXF/G7T40JnbesrCz486VLl5r29vY+m/VPf/qT8Xq9Jjc31xQUFJjDhw9HLKsxofMePnzYTJo0KZIRuwmVt6KiwuTn55u8vDwzf/58c+DAgT6b9c033zR5eXkmOzvbPPLII6ajoyNiWeXCYRljTKQLs4iISF+g06ciIiIBKooiIiIBKooiIiIBKooiIiIBKooiIiIBKooStcrKypg3b955fc0///nPFBYWAlBdXc3DDz98Xl9fRPo2FUWRLxkzZgzPPPMMAPv37z/jWqci0n9FZr0vkX/Q008/zbZt20hMTCQtLQ2Ajo4OnnjiCXbv3o3f72fUqFEsX76cQYMGMXXqVGbMmMGuXbv4/PPPmT59OgsXLqS1tZVly5bx6aef4nK5GD16NCtXrmT37t2sWrWKdevW8cwzz9DS0sKyZcuwbZukpCQWLVoEQElJCeXl5fzsZz+L5J9DRM4zzRQlauzYsYPy8nK2bt3Kxo0bOXbsGABFRUXYts0rr7xCaWkpKSkpPPHEE8HfO378OBs2bGDjxo289NJL1NXVsX37dlpbWykpKQmuDVtXVxf8nUsvvZTCwkImTJjAmjVrmDNnDps3b8bn8wGwadOmiHWYEJHw0UxRosauXbu48cYbGTRoEABer5df/epXVFRU0NLSQmVlJQCdnZ3dOlZcf/31AAwdOpSkpCSampoYP348Tz31FPPmzWPSpEnMnz8/uDbomaSnp3P55ZdTUVHByJEjaWhoIDMzM8yfWER6m4qiRJUvr0po2zbQ1YbowQcfZMqUKUBXD8kvN1L2eDzBf1uWhTGG4cOHs337dt577z3effdd7r77blauXMnAgQPP+t4nZ4sjRozgjjvuOGMbKRGJbjp9KlHj2muvpaysjObmZhzHoaSkBIDMzEyKi4vp6OjAcRxWrFjBk08+ec7X2rBhA8uWLSMzM5PFixeTmZnJhx9+2G0f27aDp0sBcnJy+Oijj3jttdfwer3n/wOKSMSpKErUmDJlCl6vF6/Xy+23305CQgIA9913H5dddhkzZswgNzcXYwxLly4952vdcsst+P1+cnNzufXWW2lpaTnt8Y6xY8dSV1fH/fffD0BsbCw5OTmMGzeOIUOGhOdDikhEqUuGSA8dP36cuXPn8vDDDzN27NhIxxGRMNBMUaQH3nrrLa677jomT56sgijSj2mmKCIiEqCZooiISICKooiISICKooiISICKooiISICKooiISICKooiISMD/A2jHyWv+ClfYAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1a1c0f5cf8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# transform data frame\n",
"plotFundamentalDiagram(project, \"aTimeStep.fundamentalDiagram\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Method B Plots"
]
},
{
"cell_type": "code",
"execution_count": 155,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1a1c477630>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plotFundamentalDiagram(project, \"bPedestrian.fundamentalDiagram\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Method C Plots (classical density)"
]
},
{
"cell_type": "code",
"execution_count": 156,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1a1c751eb8>"
]
},
"execution_count": 156,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"image/png": 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JbLKIiKDmf7fBW3jIqhe8PPQEHvWkEgaFzYm3xj+ZDQCJyexRkGVq9m+Fe+d7cO9cZ80LBvcoAuspOPSkBAaF3XlroCUGehRJ7FGQJTxHd6Nm7yZo6S1gFJ+AUX7+p79o8MZF8AcGNy9SQ1SDonv37ujcuTM6d+6MW2+9Fd9++615X2FhIXr27Gne37lzZ/z1r3+NZjm25T17BIaz/Kr3mYfHApyjIEuItwbune9Bz74JabnPAwA8x/ZY8MJcR6GqqAXFyy+/DI/Hg4yMDAwZMgQ+nw8bN240758zZw6qqqowfPhwNG/eHACQl5cXrXJsy/Of7XBuXQDn1oUQd9WVDwiazLb7HIXhLL/6z2AjRsVFlO3aDHFVxrqUmPF8/9+Q6jIk9xkLvVkr6Nk3wVuw14JXDj48lpPZKkmI1gsfOXIEAJCZmYmdO3dC0zR8/fXXAACPx4Pdu3cDAL766iukpaUBAAoKCqJVjsnr9eLI15/B6wr8QhP/glJz0i3oL6Dav4a0kAk5CXqIQAu+Peg5V9wvV76+w+dGy8Kv4Exvi5RL53B+wyvwJqQhsaYclc064ljzNsgWH05cdKHoYCFuqPChaUUZTmzbhCYVBWhalo/q9DYob9EFhp4Y5qcOVCFweJ1I8Fb7r2kOeBPTYWhBXwNNu/LpIa8B6IYHDm81DD0RvoRUCHS0cJ9Gk7P7YGgOlLTsBVdqTph6wnN4q5FWeRrQNFSnt4WhJ0GD4T+XkAg08SHZVYwU53m4UrNRnd4WojnM2nXDC83wANAgmu7fv1nT4fBWo2XhV3AYNfAkbsT51v1hOJJ/tB7dqEFG2Q9IcpeiollHuNJqfzYR87sR/E3QIEh0X0KipxKepCbwJqSH1BHclpFISUmEy+UJeY9IaeKDw6gBxIBoDoimo9Xpz1Hd7BYcuJABXChEdmpntD2Zh/z/9zdoIvAmpMFwJNVbZ5K7FKlVZ+FJyoAzvTWk9vvTqrIc5UlO/HCwEFlF5WgPIP/Lj+BzpDS47ob/oA1vm0C7Br3Ijz7nRz+DiMpoeK2pKYlw1taqaTra33U3Mmr/wG4MUQuKw4cPIyMjAzfeeCNOnjwJEYHb7f9ruLS0FAkJCfB4PHC5XEhI8JcRuD9SWVlNGlzXqfwfkPP9Gjg0e3SJj3my8fape9At6Qx+a3yNcqMpyow03Fz9bySd8wEA/vuwC3sPHsb9qT4MT61G++NbUGkkY5+nLW6suYi25R816D1rxAGBhgT4rrkdDAH0oO97jTjwP+5bkKrV4K6zu35y+573ZUCHoE3J91e9/5KRitO+ZmhVcRjt9AMRv+5hT2t84boVI1L3o/3JjxtUz2lfU3R07kW25v3Rx3tFR6WkIEtzIUGz11/VXtHx9smf4UzBYQBACz0Ns5o50OrMF/CJ9qOfnU80nPM1RzP9BLL0fSH3fX3Cjf86dBi3Jpbj9xlAm1PbovZzXM/Oal7c/Oj4Rns/TaJwesf169dj+fLlaNOmDe655x6sWLECPp8PDocDBw4cQFFREYYNGwan04l//OMfyMrKwtChQwFc7olEori4EobRsPKzszNw7MhxuF2uoGDX/P+FXEedv1K0q1yP9PlhXk/TL9/u81w+VYfPgxZpQOklJ5DS1H+bCOAqByBAcgagO/y3uSvCjAXXuT0x7fIJBkUAjxMwvJev1yvoPj0RSEoFfF7/80WQmfN/UFJR+zo1TsD3E4bIHMn+1wcAjwswfJfbSXf4L+uOyzW7K4OGOMTfho5k/2XD57/P8CHQbllZGSguLgeC54XC/ZGn6Zc/A58HcFfVfna1n3vdXqimAUlN/Ef+iOEfLhQDMAxAfA1ujhbN01Faeo1DepoGJKb4fwbD5/9P14HE1NDHeWsut6vXVedUMRJ6Man2O2R+9y4HYWabNigp9fdYUVNV2+5Rdo2/wlo0T0dpWdDIwo++z09+wDW/T4vmaSgt87errmlontMKut7wmQNd167pD+yo9Cg++ugjlJWVoaioCPv370dycjI0TTNXa2ZmZpq9h3nz5sHpdEajjHplZGYho1HfMVKpIZezszPgSKmo85i0qzzvardF6qc8FwCaAfAHsK4Hak2t/+ENFslrNexnyM5Mg+bzAc3Tr7Gepg18zrW8z2VX/x5YLbidG9KeoY/NzmoC3fzjzcrvgfUap12tkZ2dAUda7GqNymT26tWrMWjQIBiGgdzcXPTr1w9utxt9+/YFACQmJqJnz54AgHvvvRf33nsvAJhzFUREZB9Rm6PIzMwEAGzZsgUAoOs6SkpK0LlzZ+Tm5mLRokUYPXo03n77bfM57733XrTKISKiaxS1oJg9ezZmz54d9jF79lhw7DYREUUVV2YTEVFYDAoiIgqLQUFERGFFbY6iMeh6w1c4/pTnxQJrjY54qhWIr3pZa3RYUeu1vkZUFtwREZE6OPRERERhMSiIiCgsBgUREYXFoCAiorAYFEREFBaDgoiIwmJQEBFRWAwKIiIKi0FBRERhxfUpPBpi69ateOutt+D1ejFhwgT85je/iXVJId544w18/LF/D+cBAwZgxowZeOGFF7Bv3z6kpvp3CnvmmWcwZMiQWJZpGj9+PEpKSsz9zufPn4+TJ0/aro3Xr1+PNWvWmNdPnz6NBx54AE6n01ZtW1lZibFjx+Ltt99Gu3btsGPHDixYsAButxvDhw/HtGnTAACHDh3Ciy++iKqqKvTq1Qvz5s0zP4NY1fr+++/j3XffhaZp6N69O+bNm4ekpCS88cYb2LhxI5o29e8I+MgjjzT6d6JurfX9P1Vfe8eq1qNHj+K1114z7ysqKsIdd9yBFStWxKZd5Tpw7tw5GThwoJSWlkpVVZWMHDlS8vPzY12Wafv27fLoo4+K2+2Wmpoaeeyxx2Tbtm2Sm5srRUVFsS7vCoZhyN133y0ej8e8ze5tLCLyn//8R4YMGSLFxcW2atsDBw5Ibm6udOvWTU6dOiVOp1MGDBggJ0+eFI/HIxMnTpQvvvhCRERGjBgh+/fvFxGRF154QdauXRvTWo8dOyZDhgyRiooKMQxDZsyYIatXrxYRkd///vfyzTffNGp94WoVkat+7uHaO5a1Bpw/f14GDx4sBQUFIhKbdr0uhp527NiBPn36oHnz5khLS8OwYcOQl5cX67JM2dnZmDlzJpKSkpCYmIiOHTuisLAQhYWFmDVrFkaOHIlly5bBMIwff7FGcOzYMQDAxIkTMWrUKKxZs8b2bQwAc+fOxbRp05Cammqrtv3ggw/w0ksvoWXLlgCAgwcP4sYbb0T79u2RkJCAkSNHIi8vD2fOnIHL5UKPHj0AAA899FCjt3HdWpOSkvDSSy+hSZMm0DQNt9xyCwoLCwEA3333HVasWIGRI0di/vz5cLvdMa3V6XRe9XOvr71jWWuwRYsWYezYsejQoQOA2LTrdREU58+fR3Z2tnm9ZcuWKCoqimFFoX72s5+Z//MfP34cH3/8Me655x706dMHr7zyCj744APs3bsXGzZsiHGlfuXl5ejbty+WL1+Ov/3tb1i3bh0KCwtt3cY7duyAy+XC8OHDcfHiRVu17Z///Gf06tXLvF7f97Xu7dnZ2Y3exnVrbdu2Lfr16wcAKCkpwdq1azF48GBUVVWha9eumD59Oj788EOUl5fjzTffjGmt9X3udvj9ULfWgOPHj2P37t147LHHACBm7XpdBIVhGNC0y6fXFZGQ63aRn5+PiRMnYsaMGbj55puxfPlytGzZEqmpqRg/fjy+/PLLWJcIALjzzjuxaNEiZGRkIDMzE2PGjMGyZcts3cbr1q3D7373OwBA+/btbdu2QP3fVzt/j4uKijBhwgQ8/PDD+MUvfoH09HSsXLkSHTt2REJCAiZOnBjzNq7vc7dzu77//vsYN24ckpKSACBm7XpdBEWrVq1w4cIF8/qFCxeu2sWLpX379uHxxx/Hc889hwcffBBHjhzBJ598Yt4vIo0+aVmfvXv3YufOneZ1EUHbtm1t28Y1NTXYs2cPBg0aBAC2blug/u9r3dsvXrxoizY+evQoxo4diwcffBBPP/00AKCwsDCkl2aHNq7vc7fz74fPPvsMv/rVr8zrsWrX6yIofvnLX2Lnzp0oKSmB0+nEtm3b0L9//1iXZTp79iyefvppLFmyBCNGjADg/wK88soruHTpEjweD95//33bHPFUUVGBRYsWwe12o7KyEh9++CEWL15s2zY+cuQIOnTogLS0NAD2blsAuOOOO1BQUIATJ07A5/Phn//8J/r374+2bdsiOTkZ+/btAwBs3rw55m1cWVmJSZMmYerUqZg4caJ5e0pKChYvXoxTp05BRLB27dqYt3F9n3t97R1rJSUlcLlcaN++vXlbrNrVPn9GRVFOTg6mTZuGxx57DB6PB2PGjMHtt98e67JMq1atgtvtxsKFC83bxo4diyeffBK//vWv4fV6MXToUOTm5sawyssGDhyIb7/9FqNHj4ZhGBg3bhzuuusu27bxqVOn0KpVK/N6ly5dbNu2AJCcnIyFCxdiypQpcLvdGDBgAO6//34AwJIlSzB79mxUVlaiW7du5th1rGzYsAEXL17E6tWrsXr1agDAoEGDMHXqVMyfPx9PPfUUPB4PevbsaQ79xUq4z72+9o6l06dPh3xvASAzMzMm7cod7oiIKKzrYuiJiIiuHYOCiIjCYlAQEVFYDAoiIgqLQUFERGExKOi6NXHiRJSUlGDy5Mn44YcfLHvdTZs24aGHHsKoUaMwYsQIvPjii6ioqADgP1R3ypQplr0XUWNgUNB1a/v27QCAlStXolOnTpa85sGDB7F8+XK888472LJlC7Zs2QKHw4G5c+cC8K+sLSgosOS9iBrLdbHgjqiuF154AQAwYcIE/PDDD/jggw9QXV2N1157Da1bt0ZBQQFSU1Px5JNP4t1330VBQQGGDh2KWbNmAQA+//xzvPXWW/B4PEhJScHzzz+PO++8ExcuXICIwOVyAQAcDgemTp2K/Px8+Hw+zJ49G0VFRZg0aRJWrVqFb775BkuWLIHT6YSu63jmmWcwcOBAbNq0CXl5eTAMA4WFhcjJycHChQuRk5MTszaj61ijntScyEZuueUWKS4uloEDB8rBgwdl165d0rVrV/n+++9FRGTSpEnmPiHFxcXSrVs3OXfunBQUFEhubq6UlJSIiH+fi379+klVVZXU1NTIs88+K127dpXRo0fLvHnz5F//+pcYhiEiIrt27ZIRI0aIiEhZWZkMHTrU3H/g3Llz0r9/fzlz5oxs3LhRevToIceOHRMRkcWLF8uUKVMau4mIRESEPQqiIO3atcOtt94KALjhhhuQkZGBpKQkZGZmIj09HZcuXcKePXtw/vx5PP744+bzNE3DyZMn0aVLF7z66quYMWMG/v3vf2PPnj14/vnn0bdvX7z++ush73XgwAFcuHDBPJFe4HWOHDkCAOjXrx9uuukmAP5dzB544IEo//REV8egIAoSOJ1zwNXOzGkYxhW/+M+ePYuWLVtiw4YNaNGiBQYPHoxRo0Zh1KhReOqppzBo0CCUlJSEvI7P50PHjh2xfv1687aioiJkZmZi69atcDgcIe8ZfJ2oMXEym65bDocDXq+3wc/r27cvtm/fjqNHjwIAvvzyS4waNQoulwu6rmPJkiU4d+6c+fj8/Hy0adMGzZo1g8PhgMfjAQD06NEDJ06cwJ49ewD498MeNmyYuWnOrl27zMvr1q3DwIEDf9LPS3St2KOg69b999+P8ePHo6qqqkHP69SpE+bPn49nn33W3A/grbfeQnp6Oh566CE4nU5MnjwZNTU10DQNHTp0wKpVq+BwONCpUyckJydjzJgxWL9+PZYtW2aesl1EsGjRIrRr1w67d+9GTk4Opk+fjgsXLpjvSRQLPHsskQ1t2rQJn3zyCVasWBHrUog49EREROGxR0FERGGxR0FERGExKIiIKCwGBRERhcWgICKisBgUREQUFoOCiIjC+v8fESaeutCGUwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1a1c76f400>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"axes=plt.axes()\n",
"axes.set_yticks([0.4,0.8,2.5,3,4,5])\n",
"#axes.set_xticks(np.linspace(0, 199, num=5).tolist())\n",
"plotDensityTime(project, \"cTimeStep.fundamentalDiagram\", axes)\n",
"plotDensityTime(project, \"dTimeStep.fundamentalDiagram\", axes)\n",
"#axes.set_yticks([0.4,1.4,2.5,3,4,5])\n",
"#axes.set_xticks(np.linspace(0, 200, num=201).tolist())"
]
},
{
"cell_type": "code",
"execution_count": 157,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1a1c90ea58>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plotFundamentalDiagram(project, \"cTimeStep.fundamentalDiagram\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Method D Plots (voronoi density)"
]
},
{
"cell_type": "code",
"execution_count": 158,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1a1c90eac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plotFundamentalDiagram(project, \"dTimeStep.fundamentalDiagram\")"
]
},
{
"cell_type": "code",
"execution_count": 128,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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" 115.0,\n",
" 116.0,\n",
" 117.0,\n",
" 118.0,\n",
" 119.0,\n",
" 120.0,\n",
" 121.0,\n",
" 122.0,\n",
" 123.0,\n",
" 124.0,\n",
" 125.0,\n",
" 126.0,\n",
" 127.0,\n",
" 128.0,\n",
" 129.0,\n",
" 130.0,\n",
" 131.0,\n",
" 132.0,\n",
" 133.0,\n",
" 134.0,\n",
" 135.0,\n",
" 136.0,\n",
" 137.0,\n",
" 138.0,\n",
" 139.0,\n",
" 140.0,\n",
" 141.0,\n",
" 142.0,\n",
" 143.0,\n",
" 144.0,\n",
" 145.0,\n",
" 146.0,\n",
" 147.0,\n",
" 148.0,\n",
" 149.0,\n",
" 150.0,\n",
" 151.0,\n",
" 152.0,\n",
" 153.0,\n",
" 154.0,\n",
" 155.0,\n",
" 156.0,\n",
" 157.0,\n",
" 158.0,\n",
" 159.0,\n",
" 160.0,\n",
" 161.0,\n",
" 162.0,\n",
" 163.0,\n",
" 164.0,\n",
" 165.0,\n",
" 166.0,\n",
" 167.0,\n",
" 168.0,\n",
" 169.0,\n",
" 170.0,\n",
" 171.0,\n",
" 172.0,\n",
" 173.0,\n",
" 174.0,\n",
" 175.0,\n",
" 176.0,\n",
" 177.0,\n",
" 178.0,\n",
" 179.0,\n",
" 180.0,\n",
" 181.0,\n",
" 182.0,\n",
" 183.0,\n",
" 184.0,\n",
" 185.0,\n",
" 186.0,\n",
" 187.0,\n",
" 188.0,\n",
" 189.0,\n",
" 190.0,\n",
" 191.0,\n",
" 192.0,\n",
" 193.0,\n",
" 194.0,\n",
" 195.0,\n",
" 196.0,\n",
" 197.0,\n",
" 198.0,\n",
" 199.0,\n",
" 200.0]"
]
},
"execution_count": 128,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.linspace(0, 200, num=201).tolist()"
]
},
{
"cell_type": "code",
"execution_count": 149,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1a15236be0>"
"<matplotlib.figure.Figure at 0x1a1c0f5ef0>"
]
},
"metadata": {},
......@@ -25,64 +458,47 @@
],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"from vadere_analysis_tool import ScenarioOutput, VadereProject\n",
"sns.set(style=\"darkgrid\")\n",
"#g = sns.FacetGrid(tips, row=\"smoker\", col=\"time\", margin_titles=True)\n",
"\n",
"\n",
"projectFolder = \"./../../../../VadereModelTests/TestOSM_zhang-2011/\"\n",
"project = VadereProject(projectFolder)\n",
"\n",
"#out = project.named_output.C_050_180_180_2018_11_26_16_30_29_355()\n",
"\n",
"# transform data frame\n",
"dataFrames = []\n",
"for outStr in project.output_dirs :\n",
" out = project.output_dirs[outStr]\n",
" for fileStr in out.files :\n",
" if fileStr.endswith(\".fundamentalDiagram\") :\n",
" ndf = pd.DataFrame();\n",
" df = out.files[fileStr]()\n",
" df = df[df.velocity > 0]\n",
" ndf['density'] = df.density.astype(float)\n",
" ndf['velocity'] = df.velocity.astype(float)\n",
" ndf['scenario'] = [out.scenario['name']] * len(df.velocity)\n",
" dataFrames.append(ndf)\n",
"\n",
"concatFrames = pd.concat(dataFrames)\n",
"\n",
"sns.relplot(x=\"density\", y=\"velocity\", hue=\"scenario\", data=concatFrames); "
"coord1 = [[22.587603203249614,10.1], [22.587603203249614,10.1], [22.579258151260344,11.9], [22.579258151260344,11.9], [24.0,11.9], [29.0,11.9], [29.0,10.1], [24.0,10.1]]\n",
"coord2 = [[22.0,11.9], [22.579258151260344,11.9], [24.0,11.9], [24.0,11.9], [24.0,10.1], [24.0,10.1], [22.587603203249614,10.1], [22.0,10.1]]\n",
"coord1.append(coord1[0]) #repeat the first point to create a 'closed loop'\n",
"coord2.append(coord2[0])\n",
"xs1, ys1 = zip(*coord1) #create lists of x and y values\n",
"xs2, ys2 = zip(*coord2) \n",
"plt.figure()\n",
"plt.plot(xs1,ys1)\n",
"plt.plot(xs2,ys2)\n",
"plt.show() # if you need...\n"
]
},
{
"cell_type": "code",
"execution_count": 105,
"execution_count": 145,
"metadata": {},
"outputs": [
{
"data": {
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