From 9b5a1e21cb101527ecf8324efd05149e28d3566d Mon Sep 17 00:00:00 2001 From: Silvana Ayala Date: Mon, 3 May 2021 10:40:32 -0600 Subject: [PATCH] Albedo tutorial asdf --- ... - Beginer - Plot ALBEDOs from Smarts.html | 13459 ++++++++++++++++ ...- Beginer - Plot ALBEDOs from Smarts.ipynb | 287 + .../1 - Beginer - Plot ALBEDOs from Smarts.py | 162 + 3 files changed, 13908 insertions(+) create mode 100644 docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.html create mode 100644 docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.ipynb create mode 100644 docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.py diff --git a/docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.html b/docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.html new file mode 100644 index 0000000..f52e5d3 --- /dev/null +++ b/docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.html @@ -0,0 +1,13459 @@ + + + + +1 - Beginer - Plot ALBEDOs from Smarts + + + + + + + + + + + + + + + + + + + + + + + +
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1 - Beginner - Plot ALBEDOs from SMARTS

Generate & Plot Albedos from SMARTS
     * Plot Ground Albedo AM 1.0
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     * Plot Ground Albedo for SRRL Data, Oct 21 2020 at 12:45 PM
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Generate spectras for albedo and plot them, for different airmass / weather data:

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import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from matplotlib import style
+import pvlib
+import datetime
+import pprint
+import os
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plt.rcParams['timezone'] = 'Etc/GMT+7'
+font = {'family' : 'DejaVu Sans',
+'weight' : 'normal',
+'size'   : 22}
+plt.rc('font', **font)
+plt.rcParams['figure.figsize'] = (12, 5)
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import pySMARTS
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pySMARTS.__version__
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'0+untagged.17.ga4c2078'
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Real Input data from SRRL for OCTOBER 21st, 12:45 PM

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Plot Albedos from SMARTS

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IOUT = '30' # Albedo
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Plot Ground Albedo AM 1.0

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materials = ['WetSoil', 'DryGrass', 'Grass', 'Snow']
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+alb_db = pd.DataFrame()
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+for i in range (0, len(materials)):
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+    alb = pySMARTS.SMARTSAirMass(IOUT=IOUT, AMASS='1.0', material=materials[i])
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+    alb_db[materials[i]] = alb[alb.keys()[1]]
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+alb_db.index = alb.Wvlgth
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+alb_db_10 = alb_db
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+for col in alb_db:
+    alb_db[col].plot(legend=True)
+plt.xlabel('Wavelength [nm]')
+plt.xlim([300, 2500])
+plt.ylim([0,1])
+plt.ylabel('Reflectance')
+plt.legend(bbox_to_anchor=(1.04,0.75), loc="upper left")
+plt.title('Ground albedos AM 1')
+plt.show()
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Plot Ground Albedo for SRRL Data, Oct 21 2020 at 12:45 PM

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Real Input data from SRRL for OCTOBER 21st, 12:45 PM

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In [7]:
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alb = 0.2205
+YEAR='2020'; MONTH='10'; DAY='21'; HOUR = '12.75' 
+LATIT='39.74'; LONGIT='-105.17'; ALTIT='1.0'; ZONE='-7'
+TILT='33.0';  WAZIM='180.0'; HEIGHT='0' 
+material='DryGrass'
+min_wvl='280'; Max_wvl='4000'
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+TAIR = '20.3'
+RH = '2.138'
+SEASON = 'WINTER'
+TDAY = '12.78'
+SPR = '810.406'
+RHOG = '0.2205'
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+WAZIMtracker = '270'
+TILTtracker = '23.37'
+tracker_tetha_bifrad = '-23.37'
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+TAU5='0.18422'     # SRRL-GRAL "Broadband Turbidity"
+TAU5 = '0.037'    # SRRL-AOD [500nm]
+GG = '0.7417'     # SSRL-AOD Asymmetry [500nm]
+BETA = '0.0309'   # SRRL-AOD Beta
+ALPHA = '0.1949'  # SRRL-AOD Alpha [Angstrom exp]
+OMEGL = '0.9802'  # SRRL-AOD SSA [500nm]
+W = str(7.9/10)   # SRRL-PWD  Precipitable Water [mm]
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material = 'DryGrass'
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+alb_db = pd.DataFrame()
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+alb = pySMARTS.SMARTSSRRL(
+    IOUT=IOUT, YEAR=YEAR, MONTH=MONTH,DAY=DAY, HOUR='12.45', LATIT=LATIT, 
+    LONGIT=LONGIT, ALTIT=ALTIT, 
+    ZONE=ZONE, W=W, RH=RH, TAIR=TAIR, 
+    SEASON=SEASON, TDAY=TDAY, TAU5=None, SPR=SPR, 
+    TILT=TILT, WAZIM=WAZIM,
+    ALPHA1 = ALPHA, ALPHA2 = 0, OMEGL = OMEGL,
+    GG = GG, BETA = BETA,
+    RHOG=RHOG, HEIGHT=HEIGHT, material=material, POA = True)
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+alb_db[material] = alb[alb.keys()[1]]   
+alb_db.index = alb.Wvlgth
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+alb_db[material].plot(legend=True, color='y')
+plt.xlabel('Wavelength [nm]')
+plt.xlim([300, 2500])
+plt.ylim([0,1])
+plt.ylabel('Reflectance')
+plt.legend(bbox_to_anchor=(1.04,0.75), loc="upper left")
+plt.title('Albedo @ 12.45 Oct 21, 2020 for SRRL Weather Data ')
+plt.show()
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+ + + + + + diff --git a/docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.ipynb b/docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.ipynb new file mode 100644 index 0000000..68e7719 --- /dev/null +++ b/docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.ipynb @@ -0,0 +1,287 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 1 - Beginner - Plot ALBEDOs from SMARTS\n", + "\n", + "##### Generate & Plot Albedos from SMARTS\n", + "######      * Plot Ground Albedo AM 1.0\n", + "######      * Plot Ground Albedo for SRRL Data, Oct 21 2020 at 12:45 PM\n", + "> Generate spectras for albedo and plot them, for different airmass / weather data:\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib import style\n", + "import pvlib\n", + "import datetime\n", + "import pprint\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "plt.rcParams['timezone'] = 'Etc/GMT+7'\n", + "font = {'family' : 'DejaVu Sans',\n", + "'weight' : 'normal',\n", + "'size' : 22}\n", + "plt.rc('font', **font)\n", + "plt.rcParams['figure.figsize'] = (12, 5)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import pySMARTS" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'0+untagged.17.ga4c2078'" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pySMARTS.__version__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Real Input data from SRRL for OCTOBER 21st, 12:45 PM" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Plot Albedos from SMARTS" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "IOUT = '30' # Albedo" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot Ground Albedo AM 1.0" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "materials = ['WetSoil', 'DryGrass', 'Grass', 'Snow']\n", + "\n", + "alb_db = pd.DataFrame()\n", + "\n", + "for i in range (0, len(materials)):\n", + "\n", + " alb = pySMARTS.SMARTSAirMass(IOUT=IOUT, AMASS='1.0', material=materials[i])\n", + "\n", + " alb_db[materials[i]] = alb[alb.keys()[1]]\n", + " \n", + "alb_db.index = alb.Wvlgth\n", + "\n", + "alb_db_10 = alb_db\n", + "\n", + "for col in alb_db:\n", + " alb_db[col].plot(legend=True)\n", + "plt.xlabel('Wavelength [nm]')\n", + "plt.xlim([300, 2500])\n", + "plt.ylim([0,1])\n", + "plt.ylabel('Reflectance')\n", + "plt.legend(bbox_to_anchor=(1.04,0.75), loc=\"upper left\")\n", + "plt.title('Ground albedos AM 1')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Plot Ground Albedo for SRRL Data, Oct 21 2020 at 12:45 PM" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Real Input data from SRRL for OCTOBER 21st, 12:45 PM" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "alb = 0.2205\n", + "YEAR='2020'; MONTH='10'; DAY='21'; HOUR = '12.75' \n", + "LATIT='39.74'; LONGIT='-105.17'; ALTIT='1.0'; ZONE='-7'\n", + "TILT='33.0'; WAZIM='180.0'; HEIGHT='0' \n", + "material='DryGrass'\n", + "min_wvl='280'; Max_wvl='4000'\n", + "\n", + "TAIR = '20.3'\n", + "RH = '2.138'\n", + "SEASON = 'WINTER'\n", + "TDAY = '12.78'\n", + "SPR = '810.406'\n", + "RHOG = '0.2205'\n", + "\n", + "WAZIMtracker = '270'\n", + "TILTtracker = '23.37'\n", + "tracker_tetha_bifrad = '-23.37'\n", + "\n", + "TAU5='0.18422' # SRRL-GRAL \"Broadband Turbidity\"\n", + "TAU5 = '0.037' # SRRL-AOD [500nm]\n", + "GG = '0.7417' # SSRL-AOD Asymmetry [500nm]\n", + "BETA = '0.0309' # SRRL-AOD Beta\n", + "ALPHA = '0.1949' # SRRL-AOD Alpha [Angstrom exp]\n", + "OMEGL = '0.9802' # SRRL-AOD SSA [500nm]\n", + "W = str(7.9/10) # SRRL-PWD Precipitable Water [mm]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "material = 'DryGrass'\n", + "\n", + "alb_db = pd.DataFrame()\n", + "\n", + "alb = pySMARTS.SMARTSSRRL(\n", + " IOUT=IOUT, YEAR=YEAR, MONTH=MONTH,DAY=DAY, HOUR='12.45', LATIT=LATIT, \n", + " LONGIT=LONGIT, ALTIT=ALTIT, \n", + " ZONE=ZONE, W=W, RH=RH, TAIR=TAIR, \n", + " SEASON=SEASON, TDAY=TDAY, TAU5=None, SPR=SPR, \n", + " TILT=TILT, WAZIM=WAZIM,\n", + " ALPHA1 = ALPHA, ALPHA2 = 0, OMEGL = OMEGL,\n", + " GG = GG, BETA = BETA,\n", + " RHOG=RHOG, HEIGHT=HEIGHT, material=material, POA = True)\n", + "\n", + "alb_db[material] = alb[alb.keys()[1]] \n", + "alb_db.index = alb.Wvlgth\n", + "\n", + "alb_db[material].plot(legend=True, color='y')\n", + "plt.xlabel('Wavelength [nm]')\n", + "plt.xlim([300, 2500])\n", + "plt.ylim([0,1])\n", + "plt.ylabel('Reflectance')\n", + "plt.legend(bbox_to_anchor=(1.04,0.75), loc=\"upper left\")\n", + "plt.title('Albedo @ 12.45 Oct 21, 2020 for SRRL Weather Data ')\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.py b/docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.py new file mode 100644 index 0000000..694be46 --- /dev/null +++ b/docs/tutorials/1 - Beginer - Plot ALBEDOs from Smarts.py @@ -0,0 +1,162 @@ +#!/usr/bin/env python +# coding: utf-8 + +# # 1 - Beginner - Plot ALBEDOs from SMARTS +# +# ##### Generate & Plot Albedos from SMARTS +# ######      * Plot Ground Albedo AM 1.0 +# ######      * Plot Ground Albedo for SRRL Data, Oct 21 2020 at 12:45 PM +# > Generate spectras for albedo and plot them, for different airmass / weather data: +# + +# In[1]: + + +import numpy as np +import pandas as pd +import matplotlib.pyplot as plt +from matplotlib import style +import pvlib +import datetime +import pprint +import os + + +# In[2]: + + +plt.rcParams['timezone'] = 'Etc/GMT+7' +font = {'family' : 'DejaVu Sans', +'weight' : 'normal', +'size' : 22} +plt.rc('font', **font) +plt.rcParams['figure.figsize'] = (12, 5) + + +# In[3]: + + +import pySMARTS + + +# In[4]: + + +pySMARTS.__version__ + + +# #### Real Input data from SRRL for OCTOBER 21st, 12:45 PM + +# # Plot Albedos from SMARTS + +# In[5]: + + +IOUT = '30' # Albedo + + +# #### Plot Ground Albedo AM 1.0 + +# In[6]: + + +materials = ['WetSoil', 'DryGrass', 'Grass', 'Snow'] + +alb_db = pd.DataFrame() + +for i in range (0, len(materials)): + + alb = pySMARTS.SMARTSAirMass(IOUT=IOUT, AMASS='1.0', material=materials[i]) + + alb_db[materials[i]] = alb[alb.keys()[1]] + +alb_db.index = alb.Wvlgth + +alb_db_10 = alb_db + +for col in alb_db: + alb_db[col].plot(legend=True) +plt.xlabel('Wavelength [nm]') +plt.xlim([300, 2500]) +plt.ylim([0,1]) +plt.ylabel('Reflectance') +plt.legend(bbox_to_anchor=(1.04,0.75), loc="upper left") +plt.title('Ground albedos AM 1') +plt.show() + + +# # Plot Ground Albedo for SRRL Data, Oct 21 2020 at 12:45 PM + +# ### Real Input data from SRRL for OCTOBER 21st, 12:45 PM + +# In[7]: + + +alb = 0.2205 +YEAR='2020'; MONTH='10'; DAY='21'; HOUR = '12.75' +LATIT='39.74'; LONGIT='-105.17'; ALTIT='1.0'; ZONE='-7' +TILT='33.0'; WAZIM='180.0'; HEIGHT='0' +material='DryGrass' +min_wvl='280'; Max_wvl='4000' + +TAIR = '20.3' +RH = '2.138' +SEASON = 'WINTER' +TDAY = '12.78' +SPR = '810.406' +RHOG = '0.2205' + +WAZIMtracker = '270' +TILTtracker = '23.37' +tracker_tetha_bifrad = '-23.37' + +TAU5='0.18422' # SRRL-GRAL "Broadband Turbidity" +TAU5 = '0.037' # SRRL-AOD [500nm] +GG = '0.7417' # SSRL-AOD Asymmetry [500nm] +BETA = '0.0309' # SRRL-AOD Beta +ALPHA = '0.1949' # SRRL-AOD Alpha [Angstrom exp] +OMEGL = '0.9802' # SRRL-AOD SSA [500nm] +W = str(7.9/10) # SRRL-PWD Precipitable Water [mm] + + +# In[8]: + + +material = 'DryGrass' + +alb_db = pd.DataFrame() + +alb = pySMARTS.SMARTSSRRL( + IOUT=IOUT, YEAR=YEAR, MONTH=MONTH,DAY=DAY, HOUR='12.45', LATIT=LATIT, + LONGIT=LONGIT, ALTIT=ALTIT, + ZONE=ZONE, W=W, RH=RH, TAIR=TAIR, + SEASON=SEASON, TDAY=TDAY, TAU5=None, SPR=SPR, + TILT=TILT, WAZIM=WAZIM, + ALPHA1 = ALPHA, ALPHA2 = 0, OMEGL = OMEGL, + GG = GG, BETA = BETA, + RHOG=RHOG, HEIGHT=HEIGHT, material=material, POA = True) + +alb_db[material] = alb[alb.keys()[1]] +alb_db.index = alb.Wvlgth + +alb_db[material].plot(legend=True, color='y') +plt.xlabel('Wavelength [nm]') +plt.xlim([300, 2500]) +plt.ylim([0,1]) +plt.ylabel('Reflectance') +plt.legend(bbox_to_anchor=(1.04,0.75), loc="upper left") +plt.title('Albedo @ 12.45 Oct 21, 2020 for SRRL Weather Data ') +plt.show() + + +# In[ ]: + + + + + +# In[ ]: + + + +