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Flexbrdf/hytools/plotting/brdf_diagnostics.py

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+# -*- coding: utf-8 -*-
+"""
+HyTools:  Hyperspectral image processing library
+Copyright (C) 2021 University of Wisconsin
+
+Authors: Adam Chlus, Zhiwei Ye, Philip Townsend.
+
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, version 3 of the License.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+Plotting functions for BRDF
+"""
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib.lines import Line2D
+
+def universal_diagno_plot(hy_obj,config_dict):
+    ''' Generate a diagnostic plot of BRDF correction results.
+    '''
+    #Flip sign of zenith angle at minimum
+    sensor_zn = hy_obj.get_anc('sensor_zn',radians =False)
+    sensor_zn[~hy_obj.mask['no_data']] = np.nan
+    for i,line in enumerate(sensor_zn):
+        line[:np.nanargmin(line)] *= -1
+        sensor_zn[i] = line
+    sensor_zn = (sensor_zn[hy_obj.mask['calc_brdf']]//2)*2
+
+    diagno_df = pd.DataFrame()
+    diagno_df['sensor_zn'] =sensor_zn
+
+    bands = [hy_obj.wave_to_band(wave) for wave in config_dict['brdf']['diagnostic_waves']]
+    for band_num in bands:
+        band = hy_obj.get_band(band_num,mask='calc_brdf')
+        diagno_df['uncorr_%s' % band_num] =  band
+
+        band = hy_obj.get_band(band_num,
+                               corrections = hy_obj.corrections + ['brdf'],
+                               mask='calc_brdf')
+
+        diagno_df['corr_%s' % band_num] =  band
+        fvol, fgeo, fiso  = hy_obj.brdf['coeffs'][band_num]
+
+        brdf = fvol*hy_obj.ancillary['k_vol']
+        brdf += fgeo*hy_obj.ancillary['k_geom']
+        brdf+=fiso
+        brdf = brdf[hy_obj.mask['calc_brdf']]
+        diagno_df['brdf_%s' % band_num] =  brdf
+
+    # Average every 2 degrees of zenith angle
+    diagno_df=  diagno_df.groupby(by= 'sensor_zn').mean()
+
+    fig = plt.figure(figsize= (8,6))
+    fig.suptitle(hy_obj.base_name)
+    for a,band_num in enumerate(bands,start=1):
+        ax = fig.add_subplot(2,2,a)
+        ax.plot(diagno_df.index,diagno_df['brdf_%s' % band_num],c='k',ls ='--')
+        ax.scatter(diagno_df.index,diagno_df['uncorr_%s' % band_num],marker ='o',fc='w',ec='k')
+        ax.scatter(diagno_df.index,diagno_df['corr_%s' % band_num],marker ='o',fc='k',ec='k')
+        ax.text(.85,.9, "%s nm" % int(hy_obj.wavelengths[band_num]), transform=ax.transAxes,
+                ha = 'center', fontsize = 12)
+        if a > 2:
+            ax.set_xlabel('View zenith angle')
+        if a in [1,3]:
+            ax.set_ylabel('Reflectance')
+
+    #Create legend
+    custom_points = []
+    custom_points.append(Line2D([0],[0], marker = 'o',label='Uncorrected',
+                          markerfacecolor='w', markersize=10,lw=0,markeredgecolor='k'))
+    custom_points.append(Line2D([0],[0], marker = 'o',label='Corrected',
+                          markerfacecolor='k', markersize=10,lw=0,markeredgecolor='k'))
+    custom_points.append(Line2D([0],[1],label='Modeled BRDF',c='k', ls ='--'))
+    ax.legend(handles=custom_points, loc='center',frameon=False,
+              bbox_to_anchor=(-.15, -.3), ncol =3,columnspacing = 1.5,labelspacing=.25)
+
+    plt.savefig("%s%s_brdf_plot.png" % (config_dict['export']['output_dir'],hy_obj.base_name),
+                bbox_inches = 'tight')
+    plt.close()
+
+
+def flex_diagno_plot(hy_obj,config_dict):
+    ''' Generate a diagnostic plot of BRDF correction results.
+    '''
+    #Flip sign of zenith angle at minimum
+    sensor_zn = hy_obj.get_anc('sensor_zn',radians =False)
+    sensor_zn[~hy_obj.mask['no_data']] = np.nan
+    for i,line in enumerate(sensor_zn):
+        line[:np.nanargmin(line)] *= -1
+        sensor_zn[i] = line
+    sensor_zn = (sensor_zn[hy_obj.mask['calc_brdf']]//2)*2
+
+    diagno_df = pd.DataFrame()
+    diagno_df['sensor_zn'] =sensor_zn
+
+    bands = [hy_obj.wave_to_band(wave) for wave in config_dict['brdf']['diagnostic_waves']]
+
+    for band_num in bands:
+        band = hy_obj.get_band(band_num,mask='calc_brdf')
+        diagno_df['uncorr_%s' % band_num] =  band
+
+        band = hy_obj.get_band(band_num,
+                               corrections = hy_obj.corrections + ['brdf'],
+                               mask='calc_brdf')
+
+        diagno_df['corr_%s' % band_num] =  band
+
+    # Average every 2 degrees of zenith angle
+    diagno_df=  diagno_df.groupby(by= 'sensor_zn').mean()
+
+    fig = plt.figure(figsize= (8,6))
+    fig.suptitle(hy_obj.base_name)
+    for a,band_num in enumerate(bands,start=1):
+        ax = fig.add_subplot(2,2,a)
+        ax.scatter(diagno_df.index,diagno_df['uncorr_%s' % band_num],marker ='o',fc='w',ec='k')
+        ax.scatter(diagno_df.index,diagno_df['corr_%s' % band_num],marker ='o',fc='k',ec='k')
+        ax.text(.85,.9, "%s nm" % int(hy_obj.wavelengths[band_num]), transform=ax.transAxes,
+                ha = 'center', fontsize = 12)
+        if a > 2:
+            ax.set_xlabel('View zenith angle')
+        if a in [1,3]:
+            ax.set_ylabel('Reflectance')
+
+    #Create legend
+    custom_points = []
+    custom_points.append(Line2D([0],[0], marker = 'o',label='Uncorrected',
+                          markerfacecolor='w', markersize=10,lw=0,markeredgecolor='k'))
+    custom_points.append(Line2D([0],[0], marker = 'o',label='Corrected',
+                          markerfacecolor='k', markersize=10,lw=0,markeredgecolor='k'))
+    ax.legend(handles=custom_points, loc='center',frameon=False,
+              bbox_to_anchor=(-.15, -.3), ncol =2,columnspacing = 1.5,labelspacing=.25)
+    plt.savefig("%s%s_flexbrdf_plot.png" % (config_dict['export']['output_dir'],hy_obj.base_name),
+                bbox_inches = 'tight')
+    plt.close()