Created
November 29, 2011 14:47
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This program creates a CArray using PyTables. A numpy array is initialized and used to fill a hyperslab of a CArray. Slices of the array are then printed.
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import sys | |
import numpy as np | |
import tables as tb | |
filename='carrayEx1.h5' | |
fileh=tb.openFile(filename, 'w') | |
carray = fileh.createCArray(fileh.root, 'carray', tb.UInt32Atom(), shape=(200,300)) | |
a=np.array(np.arange(5*3)).reshape((5,3)) | |
carray[10:15,10:15:2] =a | |
print "" | |
print "The array, ", a[:,:] | |
print "" | |
print "is written into a hyperslab in CArray." | |
print "" | |
print "The portion of the CArray," | |
print "carray[10:15,10:15:2] = " | |
print "" | |
print carray[10:15,10:15] | |
print "" | |
print "type of a:", type(a) | |
print "dtype of a: ",a.dtype | |
print "type of carray:", type(carray) | |
#print "type of carray:", carray.dtype | |
print"" | |
print "Converting the pytables array into a numpy array:" | |
#Method for fast conversion from a pytables array to a numpy array | |
def fast_conversion(hdfarray): | |
a=np.empty(shape=hdfarray.shape,dtype=hdfarray.dtype) | |
a[:]=hdfarray[:] | |
return a | |
#Conversion from a pytables array to a numpy array | |
b = fast_conversion(carray) | |
print "type of b:", type(b) | |
print "dtype of b:", b.dtype | |
print "" | |
carray[1,1]=10**9 | |
#print "picking a very high value for carray[1,1]: ", carray[1,1] | |
#print "" | |
fileh.close() | |
#Reopen and read another hyperslab from the hdf file | |
h5f=tb.openFile(filename) | |
print h5f | |
print "" | |
print h5f.root.carray[5:15,5:15] | |
h5f.close() |
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How can i append new data into same group and node?