On 1/31/11 4:39 AM, Robert Cimrman wrote: > I work with text files which contain several arrays separated by a few > lines of other information, for example: > > POINTS 4 float > -5.000000e-01 -5.000000e-01 0.000000e+00 > 5.000000e-01 -5.000000e-01 0.000000e+00 > 5.000000e-01 5.000000e-01 0.000000e+00 > -5.000000e-01 5.000000e-01 0.000000e+00 > > CELLS 2 8 > 3 0 1 2 > 3 2 3 0
> I have used custom Python code with loops to read similar files, so the > speed was not too good. Now I wonder if it would be possible to use the > numpy.loadtxt() function for the "array-like" parts. It supports passing > an open file object in, which is good, but it wants to read the entire > file, which does not work in this case. > > It seems to me, that an additional parameter to loadtxt(), say "nrows" or > "numrows", would do the job, I agree that that would be a useful feature. However, I'm not sure it would help performance much -- I think loadtxt is written in python as well. One option in the meantime. If you know how many rows, you presumable know how many items on each row. IN that case, you can use: np.fromfile(open_file, sep=' ', count=num_items_to_read) It'll only work for multi-line text if the separator is whitespace, which it was in your example. But if it does, it should be pretty fast. -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
