def readLoop():
heartbeat("Getting image from HDFS\n")
first = True
numSetColors = 0
for key, value in binaryhadoop.mapperInput(sys.stdin):
if key == "metadata":
if not first:
doEverything(metadata, mask, originalBlock, numSetColors, numBands, bandToIndexLookup)
first = False
metadata = value
heartbeat("file: " + metadata["hdfsFileName"] + "\n")
elif key == "mask":
mask = value
numBands = len(metadata["bandNames"])
bandToIndexLookup = dict((y, x) for x, y in enumerate(sorted(metadata["bandNames"])))
heartbeat("numBands is {}, bandNames is {}, bandToIndexLookup is {}\n".format(numBands, metadata["bandNames"], bandToIndexLookup))
originalBlock = numpy.empty([numBands] + list(mask.shape), dtype=numpy.double)
else:
index = bandToIndexLookup[key]
# index = int(key[1:]) - 2
heartbeat("key is {}, index is {}\n".format(key, index))
originalBlock[index,:] = value
numSetColors += 1
doEverything(metadata, mask, originalBlock, numSetColors, numBands, bandToIndexLookup)
analyticresults = value.split(',')
thisimage = analyticresults[0].split('.')[0]
if thisimage in analyticresults_dict.keys():
analyticresults_dict[thisimage].append(analyticresults[1:])
else:
analyticresults_dict[thisimage] = [analyticresults[1:]]
#summary_data = json.load(open('summarystatistics','r'))
#outlier_image = summary_data["outlierImage"]
metadata = None
ny = 0
nx = 0
for key, value in binaryhadoop.mapperInput(sys.stdin):
if key == "metadata":
metadata = value
try:
thisImageKey = metadata['originalDirName']
except KeyError:
thisImageKey = metadata['outputFile']
bands = {}
elif key == "mask":
mask = utilities.rollMask(value > 0)
ny,nx = mask.shape
else:
bands[key] = numpy.array(value[mask], dtype=numpy.float64)
if metadata is not None:
if 'HSI' in metadata.keys():
metadata = None
bands = {}
ny = 0
nx = 0
parameterFile = open("analyticconfig")
for line in parameterFile.readlines():
line = line.rstrip().split('\t')
if line[0]=="contourclusters.percentageOfAnomalyPixels":
anomalyPercentage = float(line[1])
elif line[0]=="contourclusters.numberOfClusters":
numberOfClusters = int(line[1])
elif line[0]=="contourclusters.histogramBinSize":
binSize = int(line[1])
for key,value in binaryhadoop.mapperInput(sys.stdin,typeMap={None: binaryhadoop.TYPEDBYTES_PICKLE}):
regionKey = key
for k,v in value.items():
if k == "metadata":
metadata = v
elif k == "mask":
mask = (v > 0)
ny,nx = mask.shape
else:
bands[k] = v
if metadata is not None:
ny,nx = numpy.mgrid[0:ny,0:nx]
ny = ny[mask]
nx = nx[mask]
outData['UTM'] = utmNum
outData['imgShape'] = shape
outData['geoTrans'] = geoTrans
outData['WGS'] = wgsNum
outData['imgName'] = sceneName
outData['img'] = classImg.tolist()
print json.dumps(outData)
if __name__=="__main__":
imageData = {}
imageData["metadata"] = None
for key, value in binaryhadoop.mapperInput(sys.stdin): # Reading in seqpng line-by-line
if key == "metadata":
imageData["metadata"] = value
bands = {}
sys.stderr.write(" read metadata\n")
elif key == "mask":
bandMask = utilities.rollMask(value > 0)
imageData['mask'] = np.reshape(bandMask,bandMask.size)
sys.stderr.write(" read mask\n")
else:
bands[key] = np.reshape(ma.masked_array(value,mask=~imageData['mask']),value.size)
sys.stderr.write(" read band %s\n" % key)
opts = {}
imageData['metadata']['svmOpts'] = {}
imageData['bands'] = bands
rats = []
iDot.append(iRow)
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)
#!/usr/bin/env python
import binaryhadoop
import sys
import augustus
import report_unknowntruth
import json
if __name__ == "__main__":
cmrecs = []
for key, value in binaryhadoop.mapperInput(sys.stdin, typeMap={None: binaryhadoop.TYPEDBYTES_JSON, "KEY": binaryhadoop.TYPEDBYTES_JSON}):
cmrec = value.split(',')
cmrecs.append('%d, %d'%(float(cmrec[0]), float(cmrec[1])))
if len(cmrecs) > 0:
html, img1, img2, img3 = report_unknowntruth.main(cmrecs, 'SummaryStatistics.json')
record = "%s"%(json.dumps([html, img1, img2, img3]))
binaryhadoop.emit(sys.stdout, "KEY", record, encoding = binaryhadoop.TYPEDBYTES_JSON)
