# print inputMeans # print inputStds # print inputs labels = list(charSet) print len(labels), labels # i = 0 # for s in targetStrings: # i += 1 # print i # print s # for point in inputs: # print point # for s in wordTargetStrings: # print s ncFile = netcdf_helpers.NetCDFFile(ncFileName, 'w') netcdf_helpers.createNcDim(ncFile, 'numSeqs', len(seqLengths)) netcdf_helpers.createNcDim(ncFile, 'numTimesteps', len(inputs)) netcdf_helpers.createNcDim(ncFile, 'inputPattSize', len(inputs[0])) netcdf_helpers.createNcDim(ncFile, 'numDims', 1) netcdf_helpers.createNcDim(ncFile, 'numLabels', len(labels)) netcdf_helpers.createNcStrings(ncFile, 'seqTags', seqTags, ('numSeqs', 'maxSeqTagLength'), 'sequence tags') netcdf_helpers.createNcStrings(ncFile, 'labels', labels, ('numLabels', 'maxLabelLength'), 'labels') netcdf_helpers.createNcStrings(ncFile, 'targetStrings', targetStrings, ('numSeqs', 'maxTargetStringLength'), 'target strings') netcdf_helpers.createNcStrings(ncFile, 'wordTargetStrings', wordTargetStrings,
#print 'targetString:',targetString if targetString == '': print 'removing the image' continue targetStrings.append(targetString) seqTags.append(base) readFeatures(fname) counter += 1 #create a new .nc file print '# Creating NetCDFFile:', args.ncFileName ncfile = netcdf_helpers.NetCDFFile(args.ncFileName, 'w') #create the dimensions netcdf_helpers.createNcDim(ncfile, 'numSeqs', len(seqLengths)) netcdf_helpers.createNcDim(ncfile, 'numTimesteps', len(inputs)) netcdf_helpers.createNcDim(ncfile, 'inputPattSize', len(inputs[0])) netcdf_helpers.createNcDim(ncfile, 'numDims', 1) netcdf_helpers.createNcDim(ncfile, 'numLabels', len(labels)) #create the variables netcdf_helpers.createNcStrings(ncfile, 'labels', labels, ('numLabels', 'maxLabelLength'), 'labels') netcdf_helpers.createNcStrings(ncfile, 'targetStrings', targetStrings, ('numSeqs', 'maxTargStringLength'), 'target strings') netcdf_helpers.createNcStrings(ncfile, 'seqTags', seqTags,
parser.add_option("-c", "--booleanColomn", action="store", type="int", dest="booleanColomn", default=-1, help="dont normalize nth colomn of input array") def Std(array,axis): if shape(array)[axis]>1: return (std(array,axis)) return array #parse command line options (options, args) = parser.parse_args() print options if (len(args) != 2): parser.error("incorrect number of arguments") inputFilename = args[0] outputFilename = args[1] print 'inputFilename', inputFilename infile = netcdf_helpers.NetCDFFile(inputFilename, 'r') print "loading in input array" inputVar = infile.variables[options.inputArrayName] outputArray = zeros(inputVar.shape, 'f') if options.bigFile: offset = 0 step = options.maxArraySize while offset < inputVar.shape[0]: max = min (offset+step, inputVar.shape[0]) outputArray[offset:max] = inputVar[offset:max] offset += step else: outputArray = inputVar.getValue() if options.stdMeanFilename <> "":
print len(labels),'labels' print labels totalLen = sum(seqLengths) print 'totalLen', totalLen inputs = zeros((totalLen,1), 'f') offset = 0 for filename in seqTags: print "reading image file", filename image = Image.open(filename).transpose(Image.FLIP_TOP_BOTTOM).transpose(Image.ROTATE_270) for i in image.getdata(): inputs[offset][0] = (float(i) - inputMean)/inputStd offset += 1 #create a new .nc file file = netcdf_helpers.NetCDFFile(outputFilename, 'w') #create the dimensions netcdf_helpers.createNcDim(file,'numSeqs',len(seqLengths)) netcdf_helpers.createNcDim(file,'numTimesteps',len(inputs)) netcdf_helpers.createNcDim(file,'inputPattSize',len(inputs[0])) netcdf_helpers.createNcDim(file,'numDims',2) netcdf_helpers.createNcDim(file,'numLabels',len(labels)) #create the variables netcdf_helpers.createNcStrings(file,'seqTags',seqTags,('numSeqs','maxSeqTagLength'),'sequence tags') netcdf_helpers.createNcStrings(file,'labels',labels,('numLabels','maxLabelLength'),'labels') netcdf_helpers.createNcStrings(file,'wordTargetStrings',wordTargetStrings,('numSeqs','maxWordTargStringLength'),'target strings') netcdf_helpers.createNcStrings(file,'targetStrings',targetStrings,('numSeqs','maxTargStringLength'),'target strings') netcdf_helpers.createNcVar(file,'seqLengths',seqLengths,'i',('numSeqs',),'sequence lengths') netcdf_helpers.createNcVar(file,'seqDims',seqDims,'i',('numSeqs','numDims'),'sequence dimensions')