{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This information helps with debugging and getting support :)\n",
    "import sys, platform\n",
    "import pandas as pd\n",
    "import bifacial_radiance as br\n",
    "print(\"Working on a \", platform.system(), platform.release())\n",
    "print(\"Python version \", sys.version)\n",
    "print(\"Pandas version \", pd.__version__)\n",
    "print(\"bifacial_radiance version \", br.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 14 - Cement Racking Albedo Improvements\n",
    "\n",
    "This journal creates a paver underneath the single-axis trackers, and evaluates the improvement for one day -- June 17th with and without the pavers for a location in Davis, CA.\n",
    "\n",
    "![Paver](../images_wiki/AdvancedJournals/Pavers.PNG)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Measurements:\n",
    "![Paver](../images_wiki/AdvancedJournals/Pavers_Geometry.PNG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your simulation will be stored in C:\\Users\\mprillim\\sam_dev\\bifacial_radiance\\bifacial_radiance\\TEMP\\Tutorial_14\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from pathlib import Path\n",
    "import pandas as pd\n",
    "\n",
    "testfolder = str(Path().resolve().parent.parent / 'bifacial_radiance' / 'TEMP' / 'Tutorial_14')\n",
    "if not os.path.exists(testfolder):\n",
    "    os.makedirs(testfolder)\n",
    "    \n",
    "print (\"Your simulation will be stored in %s\" % testfolder)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bifacial_radiance import *   \n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "path = C:\\Users\\mprillim\\sam_dev\\bifacial_radiance\\bifacial_radiance\\TEMP\\Tutorial_14\n",
      "Loading albedo, 1 value(s), 0.200 avg\n",
      "1 nonzero albedo values.\n",
      "Getting weather file: USA_CA_Sacramento.Metro.AP.724839_TMY3.epw\n",
      " ... OK!\n",
      "8760 line in WeatherFile. Assuming this is a standard hourly WeatherFile for the year for purposes of saving Gencumulativesky temporary weather files in EPW folder.\n",
      "Coercing year to 2021\n",
      "Saving file EPWs\\metdata_temp.csv, # points: 8760\n",
      "Calculating Sun position for Metdata that is right-labeled  with a delta of -30 mins. i.e. 12 is 11:30 sunpos\n",
      "\n",
      "Module Name: test-module\n",
      "Module test-module updated in module.json\n",
      "Pre-existing .rad file objects\\test-module.rad will be overwritten\n",
      "\n",
      "Module was shifted by 0.078 in X to avoid sensors on air\n",
      "This is a Cell-Level detailed module with Packaging Factor of 0.85 %\n",
      "Module test-module updated in module.json\n",
      "Pre-existing .rad file objects\\test-module.rad will be overwritten\n",
      "\n"
     ]
    }
   ],
   "source": [
    "simulationname = 'tutorial_14'\n",
    "\n",
    "#Location:\n",
    "lat = 38.5449 # Davis, CA\n",
    "lon = -121.7405 # Davis, CA\n",
    "# MakeModule Parameters\n",
    "moduletype='test-module'\n",
    "numpanels = 1  # AgriPV site has 3 modules along the y direction (N-S since we are facing it to the south) .\n",
    "x = 0.95  \n",
    "y = 1.838\n",
    "xgap = 0.02# Leaving 2 centimeters between modules on x direction\n",
    "ygap = 0.0 # 1 - up \n",
    "zgap = 0.06 # gap between modules and torquetube.\n",
    "\n",
    "# Other default values:\n",
    "\n",
    "# TorqueTube Parameters\n",
    "axisofrotationTorqueTube=True\n",
    "torqueTube = False\n",
    "cellLevelModule = True\n",
    "\n",
    "numcellsx = 6\n",
    "numcellsy = 10\n",
    "xcell = 0.156\n",
    "ycell = 0.158\n",
    "xcellgap = 0.015\n",
    "ycellgap = 0.015\n",
    "\n",
    "sensorsy = numcellsy   # one sensor per cell\n",
    "\n",
    "cellLevelModuleParams = {'numcellsx': numcellsx, 'numcellsy':numcellsy, \n",
    "                         'xcell': xcell, 'ycell': ycell, 'xcellgap': xcellgap, 'ycellgap': ycellgap}\n",
    "\n",
    "# SceneDict Parameters\n",
    "gcr = 0.33 # m\n",
    "albedo = 0.2  #'grass'     # ground albedo\n",
    "hub_height = 1.237 # m  \n",
    "nMods = 20 # six modules per row.\n",
    "nRows = 3  # 3 row\n",
    "\n",
    "azimuth_ang = 90 # Facing east \n",
    "\n",
    "\n",
    "demo = RadianceObj(simulationname,path = testfolder)  # Create a RadianceObj 'object'\n",
    "demo.setGround(albedo) #\n",
    "epwfile = demo.getEPW(lat, lon) \n",
    "metdata = demo.readWeatherFile(epwfile, coerce_year=2021) # read in the EPW weather data from above\n",
    "mymodule=demo.makeModule(name=moduletype,x=x,y=y,numpanels = numpanels, xgap=xgap, ygap=ygap)\n",
    "mymodule.addCellModule(numcellsx=numcellsx, numcellsy=numcellsy,\n",
    "                       xcell=xcell, ycell=ycell, xcellgap=xcellgap, ycellgap=ycellgap)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Added material sw_chantillywhite to file ground.rad\n"
     ]
    }
   ],
   "source": [
    "description = 'Sherman Williams \"Chantilly White\" acrylic paint'\n",
    "materialpav = 'sw_chantillywhite'\n",
    "Rrefl = 0.5\n",
    "Grefl = 0.5 \n",
    "Brefl = 0.5\n",
    "demo.addMaterial(material=materialpav, Rrefl=Rrefl, Grefl=Grefl, Brefl=Brefl, comment=description)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation without Pavers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Created tutorial_14.oct\n"
     ]
    }
   ],
   "source": [
    "timeindex = metdata.datetime.index(pd.to_datetime('2021-06-17 12:0:0 -8'))  # Davis, CA is TZ -8\n",
    "demo.gendaylit(timeindex)  \n",
    "    \n",
    "tilt = demo.getSingleTimestampTrackerAngle(timeindex=timeindex, gcr=gcr, \n",
    "                                   azimuth=180, axis_tilt=0, \n",
    "                                   limit_angle=60, backtrack=True)\n",
    "# create a scene with all the variables\n",
    "sceneDict = {'tilt':tilt,'gcr': gcr,'hub_height':hub_height,'azimuth':azimuth_ang, 'module_type':moduletype, 'nMods': nMods, 'nRows': nRows}  \n",
    "scene = demo.makeScene(module=mymodule, sceneDict=sceneDict) #makeScene creates a .rad file with 20 modules per row, 7 rows.\n",
    "octfile = demo.makeOct(demo.getfilelist())  # makeOct combines all of the ground, sky and object fil|es into a .oct file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Linescan in process: tutorial_14_noPavers_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_Row2_Module10.csv\n",
      "Simulation without Pavers Finished\n"
     ]
    }
   ],
   "source": [
    "analysis = AnalysisObj(octfile, demo.name)  # return an analysis object including the scan dimensions for back irradiance\n",
    "frontscan, backscan = analysis.moduleAnalysis(scene, sensorsy=sensorsy)\n",
    "analysis.analysis(octfile, simulationname+\"_noPavers\", frontscan, backscan)  # compare the back vs front irradiance  \n",
    "print(\"Simulation without Pavers Finished\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Looping on the day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_1_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_1_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_1_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_2_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_2_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_2_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_3_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_3_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_3_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_4_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_4_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_4_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_5_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_5_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_5_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_6_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_6_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_6_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_7_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_7_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_7_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_8_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_8_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_8_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_9_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_9_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_9_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_10_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_10_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_10_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_11_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_11_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_11_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_noPavers_12_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_noPavers_12_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_noPavers_12_Row2_Module10.csv\n"
     ]
    }
   ],
   "source": [
    "j=0\n",
    "starttimeindex = metdata.datetime.index(pd.to_datetime('2021-06-17 7:0:0 -8'))\n",
    "endtimeindex = metdata.datetime.index(pd.to_datetime('2021-06-17 19:0:0 -8'))\n",
    "for timess in range (starttimeindex, endtimeindex):\n",
    "    j+=1\n",
    "    demo.gendaylit(timess)\n",
    "    tilt = demo.getSingleTimestampTrackerAngle(metdata=metdata, timeindex=timess, gcr=gcr, \n",
    "                                       azimuth=180, axis_tilt=0, \n",
    "                                       limit_angle=60, backtrack=True)\n",
    "    # create a scene with all the variables\n",
    "    sceneDict = {'tilt':tilt,'gcr': gcr,'hub_height':hub_height,'azimuth':azimuth_ang, 'module_type':moduletype, 'nMods': nMods, 'nRows': nRows}  \n",
    "    scene = demo.makeScene(module=mymodule, sceneDict=sceneDict, append=False) #makeScene creates a .rad file with 20 modules per row, 7 rows.\n",
    "    octfile = demo.makeOct(demo.getfilelist())  # makeOct combines all of the ground, sky and object fil|es into a .oct file\n",
    "    frontscan, backscan = analysis.moduleAnalysis(scene, sensorsy=sensorsy)\n",
    "    analysis.analysis(octfile, simulationname+\"_noPavers_\"+str(j), frontscan, backscan)  # compare the back vs front irradiance  \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation With Pavers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Append=False in makeScene. Existing scenes being over-written. \n"
     ]
    }
   ],
   "source": [
    "demo.gendaylit(timeindex)\n",
    "tilt = demo.getSingleTimestampTrackerAngle(metdata=metdata, timeindex=timeindex, gcr=gcr, \n",
    "                                   azimuth=180, axis_tilt=0, \n",
    "                                   limit_angle=60, backtrack=True)\n",
    "# create a scene with all the variables\n",
    "sceneDict = {'tilt':tilt,'gcr': gcr,'hub_height':hub_height,'azimuth':azimuth_ang, 'module_type':moduletype, 'nMods': nMods, 'nRows': nRows}  \n",
    "scene = demo.makeScene(module=mymodule, sceneDict=sceneDict) #makeScene creates a .rad file with 20 modules per row, 7 rows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Custom Object Name objects\\PAVER0.rad\n",
      "\n",
      "Custom Object Name objects\\PAVER1.rad\n",
      "\n",
      "Custom Object Name objects\\PAVER2.rad\n"
     ]
    }
   ],
   "source": [
    "torquetubelength = demo.module.scenex*(nMods) \n",
    "pitch = demo.module.sceney/gcr\n",
    "startpitch = -pitch * (nRows-1)/2\n",
    "p_w = 0.947 # m\n",
    "p_h = 0.092 # m\n",
    "p_w2 = 0.187 # m\n",
    "p_h2 = 0.184 # m\n",
    "offset_w1y = -(p_w/2)+(p_w2/2)\n",
    "offset_w2y = (p_w/2)-(p_w2/2)\n",
    "\n",
    "customObjects = []\n",
    "for i in range (0, nRows):    \n",
    "    name='PAVER'+str(i)\n",
    "    text='! genbox {} paver{} {} {} {} | xform -t {} {} 0 | xform -t {} 0 0'.format(materialpav, i, \n",
    "                                    p_w, torquetubelength, p_h, \n",
    "                                    -p_w/2, (-torquetubelength+demo.module.sceney)/2.0,\n",
    "                                    startpitch+pitch*i)\n",
    "    text += '\\r\\n! genbox {} paverS1{} {} {} {} | xform -t {} {} 0 | xform -t {} 0 0'.format(materialpav, i,\n",
    "                                    p_w2, torquetubelength, p_h2, \n",
    "                                    -p_w2/2+offset_w1y, (-torquetubelength+demo.module.sceney)/2.0,\n",
    "                                    startpitch+pitch*i)\n",
    "    text += '\\r\\n! genbox {} paverS2{} {} {} {} | xform -t {} {} 0 | xform -t {} 0 0'.format(materialpav, i,\n",
    "                                    p_w2, torquetubelength, p_h2, \n",
    "                                    -p_w2/2+offset_w2y, (-torquetubelength+demo.module.sceney)/2.0,\n",
    "                                    startpitch+pitch*i)\n",
    "\n",
    "    customObject = demo.makeCustomObject(name,text)\n",
    "    customObjects.append(customObject)\n",
    "    scene.appendtoScene(customObject=customObject)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Created tutorial_14.oct\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'tutorial_14.oct'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "demo.makeOct()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can view the geometry generated in the terminal with:\n",
    "\n",
    "**rvu -vf views\\front.vp -e .01 -pe 0.01 -vp -5 -14 1 -vd 0 0.9946 -0.1040 tutorial_14.oct**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "## Comment the ! line below to run rvu from the Jupyter notebook instead of your terminal.\n",
    "## Simulation will stop until you close the rvu window\n",
    "\n",
    "#!rvu -vf views\\front.vp -e .01 -pe 0.01 -vp -5 -14 1 -vd 0 0.9946 -0.1040 tutorial_14.oct\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Linescan in process: tutorial_14_WITHPavers_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_Row2_Module10.csv\n",
      "Simulation WITH Pavers Finished\n"
     ]
    }
   ],
   "source": [
    "analysis = AnalysisObj(octfile, demo.name)  # return an analysis object including the scan dimensions for back irradiance\n",
    "frontscan, backscan = analysis.moduleAnalysis(scene, sensorsy=sensorsy)\n",
    "analysis.analysis(octfile, simulationname+\"_WITHPavers\", frontscan, backscan)  # compare the back vs front irradiance  \n",
    "print(\"Simulation WITH Pavers Finished\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LOOP WITH PAVERS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_1_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_1_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_1_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_2_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_2_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_2_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_3_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_3_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_3_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_4_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_4_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_4_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_5_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_5_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_5_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_6_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_6_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_6_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_7_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_7_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_7_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_8_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_8_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_8_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_9_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_9_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_9_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_10_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_10_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_10_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_11_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_11_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_11_Row2_Module10.csv\n",
      "Append=False in makeScene. Existing scenes being over-written. \n",
      "Created tutorial_14.oct\n",
      "Linescan in process: tutorial_14_WITHPavers_12_Row2_Module10_Front\n",
      "Linescan in process: tutorial_14_WITHPavers_12_Row2_Module10_Back\n",
      "Saved: results\\irr_tutorial_14_WITHPavers_12_Row2_Module10.csv\n"
     ]
    }
   ],
   "source": [
    "j=0\n",
    "for timess in range (starttimeindex, endtimeindex):\n",
    "    j+=1\n",
    "    demo.gendaylit(timess)\n",
    "    tilt = demo.getSingleTimestampTrackerAngle(metdata=metdata, timeindex=timess, gcr=gcr, \n",
    "                                       azimuth=180, axis_tilt=0, \n",
    "                                       limit_angle=60, backtrack=True)\n",
    "    # create a scene with all the variables\n",
    "    sceneDict = {'tilt':tilt,'gcr': gcr,'hub_height':hub_height,'azimuth':azimuth_ang, 'module_type':moduletype, 'nMods': nMods, 'nRows': nRows}  \n",
    "    scene = demo.makeScene(mymodule, sceneDict=sceneDict) #makeScene creates a .rad file with 20 modules per row, 7 rows.\n",
    "    # Appending Pavers here\n",
    "    scene.appendtoScene(customObject=customObjects[0])\n",
    "    scene.appendtoScene(customObject=customObjects[1])\n",
    "    scene.appendtoScene(customObject=customObjects[2])\n",
    "    octfile = demo.makeOct(demo.getfilelist())  # makeOct combines all of the ground, sky and object fil|es into a .oct file\n",
    "    frontscan, backscan = analysis.moduleAnalysis(scene, sensorsy=sensorsy)\n",
    "    analysis.analysis(octfile, simulationname+\"_WITHPavers_\"+str(j), frontscan, backscan)  # compare the back vs front irradiance  \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# RESULTS ANALYSIS NOON"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_0 = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_noPavers_Row2_Module10.csv'))\n",
    "df_w = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_WITHPavers_Row2_Module10.csv'))                        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
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       "9 -0.765  0.0  1.381  1.352  a9.1.a2.9.0.cellPVmodule.6457   \n",
       "\n",
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       "5  a9.1.a2.5.0.cellPVmodule.2310   945.269   95.482            0.101 -0.086   \n",
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       "9  a9.1.a2.9.0.cellPVmodule.2310   945.571  112.271            0.119 -0.769   \n",
       "\n",
       "   rearY  \n",
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       "1    0.0  \n",
       "2    0.0  \n",
       "3    0.0  \n",
       "4    0.0  \n",
       "5    0.0  \n",
       "6    0.0  \n",
       "7    0.0  \n",
       "8    0.0  \n",
       "9    0.0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
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       "      <td>0.121</td>\n",
       "      <td>0.427</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>109.955</td>\n",
       "      <td>0.116</td>\n",
       "      <td>0.256</td>\n",
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       "      <td>a9.1.a2.4.0.cellPVmodule.2310</td>\n",
       "      <td>945.070</td>\n",
       "      <td>108.491</td>\n",
       "      <td>0.115</td>\n",
       "      <td>0.085</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>1.245</td>\n",
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       "      <td>945.510</td>\n",
       "      <td>107.211</td>\n",
       "      <td>0.113</td>\n",
       "      <td>-0.086</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>1.272</td>\n",
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       "      <td>945.526</td>\n",
       "      <td>110.106</td>\n",
       "      <td>0.116</td>\n",
       "      <td>-0.257</td>\n",
       "      <td>0.0</td>\n",
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       "      <th>7</th>\n",
       "      <td>-0.423</td>\n",
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       "      <td>1.328</td>\n",
       "      <td>1.299</td>\n",
       "      <td>a9.1.a2.7.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.7.0.cellPVmodule.2310</td>\n",
       "      <td>945.542</td>\n",
       "      <td>110.943</td>\n",
       "      <td>0.117</td>\n",
       "      <td>-0.428</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-0.594</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.355</td>\n",
       "      <td>1.325</td>\n",
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       "      <td>945.557</td>\n",
       "      <td>113.852</td>\n",
       "      <td>0.120</td>\n",
       "      <td>-0.599</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-0.765</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.381</td>\n",
       "      <td>1.352</td>\n",
       "      <td>a9.1.a2.9.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.9.0.cellPVmodule.2310</td>\n",
       "      <td>945.573</td>\n",
       "      <td>119.270</td>\n",
       "      <td>0.126</td>\n",
       "      <td>-0.769</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       x    y      z  rearZ                        mattype  \\\n",
       "0  0.773  0.0  1.142  1.112  a9.1.a2.0.0.cellPVmodule.6457   \n",
       "1  0.602  0.0  1.168  1.139  a9.1.a2.1.0.cellPVmodule.6457   \n",
       "2  0.431  0.0  1.195  1.166  a9.1.a2.2.0.cellPVmodule.6457   \n",
       "3  0.260  0.0  1.222  1.192  a9.1.a2.3.0.cellPVmodule.6457   \n",
       "4  0.089  0.0  1.248  1.219  a9.1.a2.4.0.cellPVmodule.6457   \n",
       "5 -0.082  0.0  1.274  1.245  a9.1.a2.5.0.cellPVmodule.6457   \n",
       "6 -0.252  0.0  1.302  1.272  a9.1.a2.6.0.cellPVmodule.6457   \n",
       "7 -0.423  0.0  1.328  1.299  a9.1.a2.7.0.cellPVmodule.6457   \n",
       "8 -0.594  0.0  1.355  1.325  a9.1.a2.8.0.cellPVmodule.6457   \n",
       "9 -0.765  0.0  1.381  1.352  a9.1.a2.9.0.cellPVmodule.6457   \n",
       "\n",
       "                         rearMat  Wm2Front  Wm2Back  Back/FrontRatio  rearX  \\\n",
       "0  a9.1.a2.0.0.cellPVmodule.2310   944.889  125.396            0.133  0.769   \n",
       "1  a9.1.a2.1.0.cellPVmodule.2310   944.934  119.225            0.126  0.598   \n",
       "2  a9.1.a2.2.0.cellPVmodule.2310   944.980  114.055            0.121  0.427   \n",
       "3  a9.1.a2.3.0.cellPVmodule.2310   945.024  109.955            0.116  0.256   \n",
       "4  a9.1.a2.4.0.cellPVmodule.2310   945.070  108.491            0.115  0.085   \n",
       "5  a9.1.a2.5.0.cellPVmodule.2310   945.510  107.211            0.113 -0.086   \n",
       "6  a9.1.a2.6.0.cellPVmodule.2310   945.526  110.106            0.116 -0.257   \n",
       "7  a9.1.a2.7.0.cellPVmodule.2310   945.542  110.943            0.117 -0.428   \n",
       "8  a9.1.a2.8.0.cellPVmodule.2310   945.557  113.852            0.120 -0.599   \n",
       "9  a9.1.a2.9.0.cellPVmodule.2310   945.573  119.270            0.126 -0.769   \n",
       "\n",
       "   rearY  \n",
       "0    0.0  \n",
       "1    0.0  \n",
       "2    0.0  \n",
       "3    0.0  \n",
       "4    0.0  \n",
       "5    0.0  \n",
       "6    0.0  \n",
       "7    0.0  \n",
       "8    0.0  \n",
       "9    0.0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_w"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Improvement in Rear Irradiance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(9.5)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round((df_w['Wm2Back'].mean()-df_0['Wm2Back'].mean())*100/df_0['Wm2Back'].mean(),1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# RESULT ANALYSIS DAY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_0 = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_noPavers_1_Row2_Module10.csv'))\n",
    "df_w = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_WITHPavers_1_Row2_Module10.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "      <th>rearZ</th>\n",
       "      <th>mattype</th>\n",
       "      <th>rearMat</th>\n",
       "      <th>Wm2Front</th>\n",
       "      <th>Wm2Back</th>\n",
       "      <th>Back/FrontRatio</th>\n",
       "      <th>rearX</th>\n",
       "      <th>rearY</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.411</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.575</td>\n",
       "      <td>0.560</td>\n",
       "      <td>a9.1.a2.0.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.0.0.cellPVmodule.2310</td>\n",
       "      <td>579.375</td>\n",
       "      <td>27.061</td>\n",
       "      <td>0.047</td>\n",
       "      <td>0.385</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.325</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.725</td>\n",
       "      <td>0.710</td>\n",
       "      <td>a9.1.a2.1.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.1.0.cellPVmodule.2310</td>\n",
       "      <td>583.680</td>\n",
       "      <td>27.821</td>\n",
       "      <td>0.048</td>\n",
       "      <td>0.299</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.238</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.875</td>\n",
       "      <td>0.859</td>\n",
       "      <td>a9.1.a2.2.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.2.0.cellPVmodule.2310</td>\n",
       "      <td>590.756</td>\n",
       "      <td>26.454</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.212</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.151</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.024</td>\n",
       "      <td>1.010</td>\n",
       "      <td>a9.1.a2.3.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.3.0.cellPVmodule.2310</td>\n",
       "      <td>595.177</td>\n",
       "      <td>26.714</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.065</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.174</td>\n",
       "      <td>1.159</td>\n",
       "      <td>a9.1.a2.4.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.4.0.cellPVmodule.2310</td>\n",
       "      <td>601.549</td>\n",
       "      <td>26.534</td>\n",
       "      <td>0.044</td>\n",
       "      <td>0.039</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-0.021</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.324</td>\n",
       "      <td>1.309</td>\n",
       "      <td>a9.1.a2.5.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.5.0.cellPVmodule.2310</td>\n",
       "      <td>605.290</td>\n",
       "      <td>26.858</td>\n",
       "      <td>0.044</td>\n",
       "      <td>-0.047</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-0.108</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.474</td>\n",
       "      <td>1.459</td>\n",
       "      <td>a9.1.a2.6.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.6.0.cellPVmodule.2310</td>\n",
       "      <td>611.543</td>\n",
       "      <td>26.762</td>\n",
       "      <td>0.044</td>\n",
       "      <td>-0.134</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-0.195</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.624</td>\n",
       "      <td>1.609</td>\n",
       "      <td>a9.1.a2.7.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.7.0.cellPVmodule.2310</td>\n",
       "      <td>614.750</td>\n",
       "      <td>27.401</td>\n",
       "      <td>0.045</td>\n",
       "      <td>-0.221</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-0.281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.773</td>\n",
       "      <td>1.758</td>\n",
       "      <td>a9.1.a2.8.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.8.0.cellPVmodule.2310</td>\n",
       "      <td>619.741</td>\n",
       "      <td>28.306</td>\n",
       "      <td>0.046</td>\n",
       "      <td>-0.307</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-0.367</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.923</td>\n",
       "      <td>1.908</td>\n",
       "      <td>a9.1.a2.9.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.9.0.cellPVmodule.2310</td>\n",
       "      <td>622.469</td>\n",
       "      <td>29.369</td>\n",
       "      <td>0.047</td>\n",
       "      <td>-0.393</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       x    y      z  rearZ                        mattype  \\\n",
       "0  0.411  0.0  0.575  0.560  a9.1.a2.0.0.cellPVmodule.6457   \n",
       "1  0.325  0.0  0.725  0.710  a9.1.a2.1.0.cellPVmodule.6457   \n",
       "2  0.238  0.0  0.875  0.859  a9.1.a2.2.0.cellPVmodule.6457   \n",
       "3  0.151  0.0  1.024  1.010  a9.1.a2.3.0.cellPVmodule.6457   \n",
       "4  0.065  0.0  1.174  1.159  a9.1.a2.4.0.cellPVmodule.6457   \n",
       "5 -0.021  0.0  1.324  1.309  a9.1.a2.5.0.cellPVmodule.6457   \n",
       "6 -0.108  0.0  1.474  1.459  a9.1.a2.6.0.cellPVmodule.6457   \n",
       "7 -0.195  0.0  1.624  1.609  a9.1.a2.7.0.cellPVmodule.6457   \n",
       "8 -0.281  0.0  1.773  1.758  a9.1.a2.8.0.cellPVmodule.6457   \n",
       "9 -0.367  0.0  1.923  1.908  a9.1.a2.9.0.cellPVmodule.6457   \n",
       "\n",
       "                         rearMat  Wm2Front  Wm2Back  Back/FrontRatio  rearX  \\\n",
       "0  a9.1.a2.0.0.cellPVmodule.2310   579.375   27.061            0.047  0.385   \n",
       "1  a9.1.a2.1.0.cellPVmodule.2310   583.680   27.821            0.048  0.299   \n",
       "2  a9.1.a2.2.0.cellPVmodule.2310   590.756   26.454            0.045  0.212   \n",
       "3  a9.1.a2.3.0.cellPVmodule.2310   595.177   26.714            0.045  0.126   \n",
       "4  a9.1.a2.4.0.cellPVmodule.2310   601.549   26.534            0.044  0.039   \n",
       "5  a9.1.a2.5.0.cellPVmodule.2310   605.290   26.858            0.044 -0.047   \n",
       "6  a9.1.a2.6.0.cellPVmodule.2310   611.543   26.762            0.044 -0.134   \n",
       "7  a9.1.a2.7.0.cellPVmodule.2310   614.750   27.401            0.045 -0.221   \n",
       "8  a9.1.a2.8.0.cellPVmodule.2310   619.741   28.306            0.046 -0.307   \n",
       "9  a9.1.a2.9.0.cellPVmodule.2310   622.469   29.369            0.047 -0.393   \n",
       "\n",
       "   rearY  \n",
       "0    0.0  \n",
       "1    0.0  \n",
       "2    0.0  \n",
       "3    0.0  \n",
       "4    0.0  \n",
       "5    0.0  \n",
       "6    0.0  \n",
       "7    0.0  \n",
       "8    0.0  \n",
       "9    0.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.411</td>\n",
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       "      <td>0.575</td>\n",
       "      <td>0.560</td>\n",
       "      <td>a9.1.a2.0.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.0.0.cellPVmodule.2310</td>\n",
       "      <td>581.281</td>\n",
       "      <td>20.666</td>\n",
       "      <td>0.036</td>\n",
       "      <td>0.385</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.325</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.725</td>\n",
       "      <td>0.710</td>\n",
       "      <td>a9.1.a2.1.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.1.0.cellPVmodule.2310</td>\n",
       "      <td>585.068</td>\n",
       "      <td>21.210</td>\n",
       "      <td>0.036</td>\n",
       "      <td>0.299</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.238</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.875</td>\n",
       "      <td>0.859</td>\n",
       "      <td>a9.1.a2.2.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.2.0.cellPVmodule.2310</td>\n",
       "      <td>591.558</td>\n",
       "      <td>21.006</td>\n",
       "      <td>0.036</td>\n",
       "      <td>0.212</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.151</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.024</td>\n",
       "      <td>1.010</td>\n",
       "      <td>a9.1.a2.3.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.3.0.cellPVmodule.2310</td>\n",
       "      <td>594.920</td>\n",
       "      <td>21.761</td>\n",
       "      <td>0.037</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.065</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.174</td>\n",
       "      <td>1.159</td>\n",
       "      <td>a9.1.a2.4.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.4.0.cellPVmodule.2310</td>\n",
       "      <td>602.971</td>\n",
       "      <td>22.816</td>\n",
       "      <td>0.038</td>\n",
       "      <td>0.039</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-0.021</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.324</td>\n",
       "      <td>1.309</td>\n",
       "      <td>a9.1.a2.5.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.5.0.cellPVmodule.2310</td>\n",
       "      <td>607.095</td>\n",
       "      <td>23.659</td>\n",
       "      <td>0.039</td>\n",
       "      <td>-0.047</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-0.108</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.474</td>\n",
       "      <td>1.459</td>\n",
       "      <td>a9.1.a2.6.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.6.0.cellPVmodule.2310</td>\n",
       "      <td>612.259</td>\n",
       "      <td>24.504</td>\n",
       "      <td>0.040</td>\n",
       "      <td>-0.134</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-0.195</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.624</td>\n",
       "      <td>1.609</td>\n",
       "      <td>a9.1.a2.7.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.7.0.cellPVmodule.2310</td>\n",
       "      <td>615.350</td>\n",
       "      <td>25.132</td>\n",
       "      <td>0.041</td>\n",
       "      <td>-0.221</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-0.281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.773</td>\n",
       "      <td>1.758</td>\n",
       "      <td>a9.1.a2.8.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.8.0.cellPVmodule.2310</td>\n",
       "      <td>620.853</td>\n",
       "      <td>26.077</td>\n",
       "      <td>0.042</td>\n",
       "      <td>-0.307</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-0.367</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.923</td>\n",
       "      <td>1.908</td>\n",
       "      <td>a9.1.a2.9.0.cellPVmodule.6457</td>\n",
       "      <td>a9.1.a2.9.0.cellPVmodule.2310</td>\n",
       "      <td>623.744</td>\n",
       "      <td>26.856</td>\n",
       "      <td>0.043</td>\n",
       "      <td>-0.393</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       x    y      z  rearZ                        mattype  \\\n",
       "0  0.411  0.0  0.575  0.560  a9.1.a2.0.0.cellPVmodule.6457   \n",
       "1  0.325  0.0  0.725  0.710  a9.1.a2.1.0.cellPVmodule.6457   \n",
       "2  0.238  0.0  0.875  0.859  a9.1.a2.2.0.cellPVmodule.6457   \n",
       "3  0.151  0.0  1.024  1.010  a9.1.a2.3.0.cellPVmodule.6457   \n",
       "4  0.065  0.0  1.174  1.159  a9.1.a2.4.0.cellPVmodule.6457   \n",
       "5 -0.021  0.0  1.324  1.309  a9.1.a2.5.0.cellPVmodule.6457   \n",
       "6 -0.108  0.0  1.474  1.459  a9.1.a2.6.0.cellPVmodule.6457   \n",
       "7 -0.195  0.0  1.624  1.609  a9.1.a2.7.0.cellPVmodule.6457   \n",
       "8 -0.281  0.0  1.773  1.758  a9.1.a2.8.0.cellPVmodule.6457   \n",
       "9 -0.367  0.0  1.923  1.908  a9.1.a2.9.0.cellPVmodule.6457   \n",
       "\n",
       "                         rearMat  Wm2Front  Wm2Back  Back/FrontRatio  rearX  \\\n",
       "0  a9.1.a2.0.0.cellPVmodule.2310   581.281   20.666            0.036  0.385   \n",
       "1  a9.1.a2.1.0.cellPVmodule.2310   585.068   21.210            0.036  0.299   \n",
       "2  a9.1.a2.2.0.cellPVmodule.2310   591.558   21.006            0.036  0.212   \n",
       "3  a9.1.a2.3.0.cellPVmodule.2310   594.920   21.761            0.037  0.126   \n",
       "4  a9.1.a2.4.0.cellPVmodule.2310   602.971   22.816            0.038  0.039   \n",
       "5  a9.1.a2.5.0.cellPVmodule.2310   607.095   23.659            0.039 -0.047   \n",
       "6  a9.1.a2.6.0.cellPVmodule.2310   612.259   24.504            0.040 -0.134   \n",
       "7  a9.1.a2.7.0.cellPVmodule.2310   615.350   25.132            0.041 -0.221   \n",
       "8  a9.1.a2.8.0.cellPVmodule.2310   620.853   26.077            0.042 -0.307   \n",
       "9  a9.1.a2.9.0.cellPVmodule.2310   623.744   26.856            0.043 -0.393   \n",
       "\n",
       "   rearY  \n",
       "0    0.0  \n",
       "1    0.0  \n",
       "2    0.0  \n",
       "3    0.0  \n",
       "4    0.0  \n",
       "5    0.0  \n",
       "6    0.0  \n",
       "7    0.0  \n",
       "8    0.0  \n",
       "9    0.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(16.9)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round((df_w['Wm2Back'].mean()-df_0['Wm2Back'].mean())*100/df_0['Wm2Back'].mean(),1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16.8"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round((df_w['Wm2Back'].mean()-df_0['Wm2Back'].mean())*100/df_0['Wm2Back'].mean(),1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16.9\n",
      "38.4\n",
      "36.4\n",
      "24.2\n",
      "9.8\n",
      "10.6\n",
      "9.3\n",
      "9.4\n",
      "18.5\n",
      "32.4\n",
      "36.8\n",
      "40.5\n"
     ]
    }
   ],
   "source": [
    "average_back_d0=[]\n",
    "average_back_dw=[]\n",
    "average_front = []\n",
    "hourly_rearirradiance_comparison = []\n",
    "\n",
    "timessimulated = endtimeindex-starttimeindex\n",
    "\n",
    "for i in range (1, timessimulated+1):\n",
    "    df_0 = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_noPavers_'+str(i)+'_Row2_Module10.csv'))\n",
    "    df_w = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_WITHPavers_'+str(i)+'_Row2_Module10.csv'))\n",
    "    print(round((df_w['Wm2Back'].mean()-df_0['Wm2Back'].mean())*100/df_0['Wm2Back'].mean(),1))\n",
    "    hourly_rearirradiance_comparison.append(round((df_w['Wm2Back'].mean()-df_0['Wm2Back'].mean())*100/df_0['Wm2Back'].mean(),1))\n",
    "    average_back_d0.append(df_0['Wm2Back'].mean())\n",
    "    average_back_dw.append(df_w['Wm2Back'].mean())\n",
    "    average_front.append(df_0['Wm2Front'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Increase in rear irradiance:  20.6\n"
     ]
    }
   ],
   "source": [
    "print(\"Increase in rear irradiance: \", round((sum(average_back_dw)-sum(average_back_d0))*100/sum(average_back_d0),1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BG no Pavers:  8.3\n",
      "BG with Pavers:  10.0\n"
     ]
    }
   ],
   "source": [
    "print(\"BG no Pavers: \", round(sum(average_back_d0)*100/sum(average_front),1))\n",
    "print(\"BG with Pavers: \", round(sum(average_back_dw)*100/sum(average_front),1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#metdata.datetime[starttime].hour # 7\n",
    "#metdata.datetime[endtimeindex].hour # 17\n",
    "xax= [7, 8, 9, 10, 11, 12,13,14,15,16,17,18]  # Lazy way to get the x axis...\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Hour')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(xax,hourly_rearirradiance_comparison)\n",
    "plt.ylabel('$\\Delta$ in G$_{rear}$ [%] \\n(G$_{rear-with}$ - G$_{rear-without}$ / G$_{rear-without}$)')\n",
    "plt.xlabel('Hour')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}