#!/usr/bin/env python

import sys

import json

import numpy

import binaryhadoop

import utilities

def calcNoise(imageArray,mask):

return noiseArray

def main(imageArray):

return iDot, iPartial

if __name__ == "__main__":

imageData = {}

imageData["metadata"] = None

parameterFile = open("analyticconfig","r")

for line in parameterFile.readlines():

line = line.rstrip().split("\t")

if line[0]=="contourclusters.noiseFlag":

noiseFlag = line[1]

for key, value in binaryhadoop.mapperInput(sys.stdin):

if key == "metadata":

imageData["metadata"] = value

bands = {}

elif key == "mask":

mask = utilities.rollMask(value > 0)

imageData["numPixels"] = numpy.nonzero(mask)[0].size

else:

bands[key] = numpy.array(value[mask],dtype=numpy.float64)

if imageData["metadata"] is not None:

if 'HSI' in imageData["metadata"].keys():

wavelengths = {}

multipliers = {}

for w,wave in enumerate(imageData["metadata"][unicode("HSI")][unicode("wavelength")]):

wavelengths["B" + "%03d" % w] = float(wave)

multipliers["B" + "%03d" % w] = 1

else:

wavelengths = imageData["metadata"]["bandWavelength"]

multipliers = imageData["metadata"]["bandMultiplier"]

imageList = utilities.preprocessImage(bands, multipliers, wavelengths, imageData)

sys.stderr.write("This is the number of bands: %r\n" % len(imageList))

iDot,iPartial = main(imageList)

imageData["imageDot"] = iDot

imageData["imagePartial"] = iPartial

if noiseFlag.upper() == "TRUE":

noiseList = calcNoise(imageList,mask)

nDot,nPartial = main(noiseList)

imageData["noiseDot"] = nDot

imageData["noisePartial"] = nPartial

try:

regionKey = imageData["metadata"]["originalDirName"]

except KeyError:

regionKey = imageData["metadata"]["outputFile"]

binaryhadoop.emit(sys.stdout,regionKey,imageData,encoding=binaryhadoop.TYPEDBYTES_JSON)