On Feb 28, 2010, at 6:24 AM, Friedrich Romstedt wrote:
> 2010/2/28 Robert Love <rblove_li...@comcast.net>:
>> What is the efficient numpy way to compare data from two different files?
>> For the nth line in each file I want to operate on the numbers. I've been
>> using loadtxt()
>>
>> data_5x5 = N.loadtxt("file5")
>>
>> data_8x8 = N.loadtxt("file8")
>>
>> for line in data_5x5:
>> pos5 = N.array([line[0], line[1], line[2]])
>
> I believe there are several ways of doing that, and mine might not be
> the most efficient at all:
>
> for line5, line8 in zip(data_5x5, data_8x8):
> # line5 and line8 are row vectors of paired lines
> pass
>
> complete = numpy.hstack(data_5x5, data_8x8) # If data_5x5.shape[0] ==
> data_8x8.shape[0], i.e., same number of rows.
> for line in complete:
> # complete is comprised of concatenated row vectors.
> pass
>
> for idx in xrange(0, min(data_5x5.shape[0], data_8x8.shape[0])):
> line5 = data_5x5[idx]
> line8 = data_8x8[idx]
> # Do sth with the vectors. Or:
> a1 = data_5x5[idx, (0, 1, 2)] # Extract items 0, 1, 2 of line idx
> of first file.
> a2 = data_8x8[idx, (0, 42)] # Extract items 0, 42 of line idx of
> second file.
>
Thank you, I will try this last method listed. I need to actually compute with
the values from the two files to perform my comparison and the time tag is in
different formats. Your method will get me access to the contents of two files.
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