processNGB.py

#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, either version 3 of the License, or
#(at your option) any later version.

#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 <http://www.gnu.org/licenses/>.


import os
import sys

import matplotlib.image as mpimg
import matplotlib.pyplot as plt

import numpy as numpy
from PIL import Image

import gc

# function for generating NIR imagery from NGB input files

def nir(imageInPath,imageOutPath):
	img=Image.open(imageInPath)
	imgN, imgG, imgB = img.split() #get channels
	arrR = numpy.asarray(imgN).astype('float64')

	arr_nir=arrR

	fig=plt.figure()
	fig.set_frameon(False)
	ax=fig.add_subplot(111)
	ax.set_axis_off()
	ax.patch.set_alpha(0.0)

	nir_plot = ax.imshow(arr_nir, cmap=plt.cm.gist_gray, interpolation="nearest")

	#fig.colorbar(nir_plot)
	fig.savefig(imageOutPath)

	#needed to clear memory if used to process many frames ...
	fig.clf()
	plt.close()
	gc.collect()


# function for generating NDVI imagery from NGB or NBG input files
def ndvi(imageInPath,imageOutPath,vmin,vmax,histogramOption):

	img=Image.open(imageInPath)
	imgR, imgB, imgG = img.split() #get channels from NGB
	#imgR, imgG, imgB = img.split() #get channels from NBG

	arrR = numpy.asarray(imgR).astype('float64')
	arrG = numpy.asarray(imgG).astype('float64')
	arrB = numpy.asarray(imgB).astype('float64')

	num=(arrR - arrB)
	denom=(arrR + arrB)

	arr_ndvi=num/denom

	if arr_ndvi.max()>0:
		
		img_w,img_h=img.size
	
		dpi=600. #need this to be floating point!
		fig_w=img_w/dpi
		fig_h=img_h/dpi

		fig=plt.figure(figsize=(fig_w,fig_h),dpi=dpi)

		fig.set_frameon(False)

		ax_rect = [0.0, #left
		       0.0, #bottom
		       1.0, #width
		       1.0] #height
		ax = fig.add_axes(ax_rect)
		ax.yaxis.set_ticklabels([])
		ax.xaxis.set_ticklabels([])   
		ax.set_axis_off()
		ax.axes.get_yaxis().set_visible(False)
		ax.patch.set_alpha(0.0)



		axes_img = ax.imshow(arr_ndvi,
				          cmap=plt.cm.spectral, 
				          vmin = vmin,
				          vmax = vmax,
				          aspect = 'equal',
				          interpolation="nearest"
				         )

#		axes_img = ax.imshow(arr_ndvi,
#				  cmap=plt.cm.spectral, 
#				  aspect = 'equal',
#				  interpolation="nearest"
#				 )


		if histogramOption==1:

			#plot the Red histogram
			x=arrR.ravel()
			a = plt.axes([.05,.7,.18,.18], axisbg='y')
			bins=numpy.arange(0,255,8)
			n, bins, patches = plt.hist(x, bins, normed=1,linewidth=.2)
			plt.setp(patches, 'facecolor', 'r', 'alpha', 0.75)
			plt.setp(a,xticks=[0,120,255],yticks=[])
			plt.setp(a,xticks=[],yticks=[])
			plt.xticks(fontsize=2)

			#plot the Blue histogram
			x=arrB.ravel()
			a = plt.axes([.05,.4,.18,.18], axisbg='y')
			bins=numpy.arange(0,255,8)
			n, bins, patches = plt.hist(x, bins, normed=1,linewidth=.2)
			plt.setp(patches, 'facecolor', 'b', 'alpha', 0.75)
			plt.setp(a,xticks=[0,120,255],yticks=[])
			plt.setp(a,xticks=[],yticks=[])
			plt.xticks(fontsize=2)

			#plot the NDVI histogram
			x=arr_ndvi.ravel()
			a = plt.axes([.05,.1,.18,.18], axisbg='y')
			bins=numpy.arange(-1,1,.01)
			n, bins, patches = plt.hist(x, bins, normed=1,linewidth=.2)
			plt.setp(patches, 'facecolor', 'w', 'alpha', 0.75)
			plt.setp(a,xticks=[-1,0,1],yticks=[])
			plt.setp(a,xticks=[],yticks=[])
			plt.xticks(fontsize=2)


		# Add colorbar 
		#make an axis for colorbar
		cax = fig.add_axes([0.8,0.05,0.05,0.85]) #left, bottom, width, height
		cbar = fig.colorbar(axes_img, cax=cax)  #this resizes the axis
		cbar.ax.tick_params(labelsize=2) #this changes the font size on the axis

		#position of the colorbar
		#cbar.ax.yaxis.set_ticks_position('left')
	
		#color of the colorbar text
		#cbytick_obj = plt.getp(cbar.ax.axes, 'yticklabels')                #tricky
		#plt.setp(cbytick_obj, color='r')

		fig.savefig(imageOutPath, 
		        dpi=dpi,
		        bbox_inches='tight',
		        pad_inches=0.0, 
		       )

		#plt.show()  #show the plot after saving
		fig.clf()
		plt.close()
		gc.collect()

	
###### testing the code #######

indir = str(sys.argv[1])  #the input directory
outdir = str(sys.argv[2]) #the output directory
VMIN = float(sys.argv[3]) #minimum value for the colorbar
VMAX = float(sys.argv[4]) #max value for the colorbar
histogramOption = int(sys.argv[5]) #whether to include histograms of R, B, and NDVI -- 0: no histogram, 1: include histogram

import glob

indir=indir+'*' #add all files in the inputdirectory to the list

# get the files from the directory, and sort them in case we're making a movie
files= sorted(glob.glob(indir))

print "Detected ",len(files), "files in", str(indir)

#process all the files
index=0
for f in files:
	index=index+1 #update the index
	inFilePath=f
	inFileName= os.path.basename(f)
	print "File ",index," of ",len(files),":",inFilePath
	outFileName='ndvi_'+inFileName
	outFilePath= os.path.join(outdir,outFileName)
	ndvi(inFilePath,outFilePath,VMIN,VMAX,histogramOption)
	print "---->", outFilePath