ValueError: shape mismatch: objects cannot be broadcast to a single shape

[Saad Bin Ahmed]

Hey,

I got the following error in python program. If anybody knows about this error then please share the solution.

from numpy import array
inputMeans =array([1, 2, 3])
inputStds =array([4, 5, 6])

inputs = ((array(inputs)-inputMeans)/inputStds).tolist()

---------------------------------------------------------------------------
ValueError Traceback (most recent call last)

/home/saad/<ipython console> in <module>()

ValueError: shape mismatch: objects cannot be broadcast to a single shape

This is the error message which shows to me when I try to execute program. Your timely help would be highly appreciated.

[bvdet]

Where is inputs defined? I suspect inputs has different dimensions than the other objects.

>>> inputMeans =array([1., 2., 3.])
>>> inputStds = array([4., 5., 6.])
>>> inputs = array([7., 15., 5.67])
>>> inputs = ((array(inputs)-inputMeans)/inputStds).tolist()
>>> inputs
[1.5, 2.6000000000000001, 0.44500000000000001]
>>>

[Saad Bin Ahmed]

from numpy import array
inputMeans =array([1, 2, 3])
inputStds =array([4, 5, 6])
inputs=[]
inputs = ((array(inputs)-inputMeans)/inputStds).toli st()

// inputs is of array type

[Saad Bin Ahmed]

sorry for inconvenience. Here is the code with good readability.

#!/usr/bin/python
from Scientific.IO import NetCDF
from numpy import arange, array, vectorize, newaxis
import netcdf_helpers
from scipy import *
from optparse import OptionParser
import sys
import os
from xml.dom.minidom import parse

labels = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', 'a', 'b', 'c', 'd', 'e', 'f', 'g','ga', 'h', 'i', 'j', 'k', 'km', 'l', 'm', 'n', 'o', 'p', 'pt', 'q','r','s','sc','sp','t','u','v','w','x','y','z']
inputMeans =array([0.03199977,102.7592,511.8343])
inputStds =array([0.1758981,24.34094,134.0498])

#command line options
parser = OptionParser()
#parse command line options
(options, args) = parser.parse_args()
if (len(args)<2):
	print "usage: -options input_filename output_filename"
	print options
	sys.exit(2)

inputFilename = args [0]
ncFilename = args[1]
print options
print "input filename", inputFilename
print "data filename", ncFilename
seqDims = []
seqLengths = []
targetStrings = []
wordTargetStrings = []
seqTags = []
inputs = []
contain=[]
new=[]
print "reading data files"
for l in file(inputFilename).readlines():
	xmlfile = l.strip()
	if len(xmlfile):
		print xmlfile
		seqTags.append(xmlfile)
		upxfile = xmlfile.replace('xml', 'upx')
		if os.path.exists(upxfile):
			word = parse(upxfile).getElementsByTagName('hwData')[0].getElementsByTagName('label')[0].getElementsByTagName('alternate')[0].getAttribute('value').strip().replace(' ','*')
			print word
			wts = word.encode('spell')
			print wts
			wordTargetStrings.append(wts)	
			ts = ""
			for c in word:
				label = c.encode('spell')
				ts += label + ' '
			ts = ts.strip()
			print ts
			targetStrings.append(ts)
		else:
			wordTargetStrings.append(' ')
			targetStrings.append(' ')			
		oldlen = len(inputs)
		for trace in parse(xmlfile).getElementsByTagName('trace'):		
			for coords in trace.firstChild.nodeValue.split(','):
				pt = coords.split()
				inputs.append([float(pt[0]), float(pt[1]), 0.0])
			inputs[-1][-1] = 1
		seqLengths.append(len(inputs) - oldlen)
		seqDims.append([seqLengths[-1]])

[B]inputs = ((array(inputs)- inputMeans)/inputStds).tolist()[/B]
print len(labels), labels
print labels

#create a new .nc file
file = netcdf_helpers.NetCDFFile(ncFilename, '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',1)
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,'targetStrings',targetStrings,('numSeqs','maxTargStringLength'),'target strings')
netcdf_helpers.createNcStrings(file,'wordTargetStrings',wordTargetStrings,('numSeqs','maxWordTargStringLength'),'word target strings')
netcdf_helpers.createNcVar(file,'seqLengths',seqLengths,'i',('numSeqs',),'sequence lengths')
netcdf_helpers.createNcVar(file,'seqDims',seqDims,'i',('numSeqs','numDims'),'sequence dimensions')
#netcdf_helpers.createNcVar(file,'inputs',inputs,'f',('numTimesteps','inputPattSize'),'input patterns')

#write the data to disk
print "closing file", ncFilename
file.close()

If I give .inkml file then it works fine but it gives an error when I give .xml file

[bvdet]

It would help immensely if you would post the error message and full traceback. Here's some code that you can call to trap the error and print the traceback:

import sys, traceback

def formatExceptionInfo(level=3):
    error_type, error_value, trbk = sys.exc_info()
    info_list = ["Error: %s \nDescription: %s \nTraceback:\n" % (error_type.__name__, error_value), ]
    info_list.extend(traceback.format_tb(trbk, level))
    return ''.join(info_list)

Example:

    def test_formatExceptionInfo():
        try:
            # Code to be executed here
        except Exception, e:
            print formatExceptionInfo()