Hi, I have a problem using memmap correctly. I need to read a data file which consists of an ASCII header and appended binary single precision floating point values. memmap complains that the "Size of available data is not a multiple of the data-type size." But as far as I can tell, the size *doas* match the data-type size.
The problem is illustrated by the following code: ---8<------- url = "http://www.iup.uni-bremen.de/~hilboll/download/20120204.XD4_N2"; localfile = "np_memmap.dat" import os import urllib import numpy as np # download data file if not os.access(localfile, os.R_OK): urllib.urlretrieve(url, localfile) with open(localfile, "r") as fd: # read offset from first line of file offset = int(fd.readlines()[0].split()[-2]) # jump to begin of data block fd.seek(offset) # read until EOF blob = fd.read() print("Size of data blob [bytes]: {}".format(len(blob))) print("This can actually be divided by 4: {} / 4.0 = {}".format( len(blob), len(blob) / 4.0)) # go back to begin of data block fd.seek(offset) print("But it cannot be loaded as np.memmap with dtype float32:") np.memmap(fd, dtype="float32", mode="r") ---8<------- Any help is greatly appreciated :) -- Andreas. _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
