I have a rather big numpy array of M*N ints and I want to end up with a M array of strings that have all N corresponding ints concatenated. I tried using a view but this is probably not the way to go with numpy.
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1Please shows some example input and the desired output.NPE– NPE2014-09-20 14:30:10 +00:00Commented Sep 20, 2014 at 14:30
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3 Answers
Hope this is what you want
numpy.apply_along_axis(numpy.array_str,0,array)
Look the documentation of apply_along_axis
http://docs.scipy.org/doc/numpy/reference/generated/numpy.apply_along_axis.html
and array_str
http://docs.scipy.org/doc/numpy/reference/generated/numpy.array_str.html
for deeper understanding
if you want to concatenating ints to string it wasnt be numpy array longer ! you will have a list with string indexes.
this is an example that concatenate 'a' to a numpy zero array :
>>> np.zeros(10)
array([ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
>>> [str(i)+'a' for i in np.zeros(10)]
['0.0a', '0.0a', '0.0a', '0.0a', '0.0a', '0.0a', '0.0a', '0.0a', '0.0a', '0.0a']
>>>
Comments
Without an example, your request is unclear. But here's one way of understanding it
In [13]: X=np.arange(12).reshape(3,4)
In [14]: np.array([''.join([str(i) for i in x]) for x in X])
Out[14]:
array(['0123', '4567', '891011'],
dtype='|S6')
I have a 3x4 array; I convert each element to a string using str(i), and use join to concatenate the strings of a row into one longer string.
That's not a very satisfying answer, especially when joining '9' to '10'. Of course it could be refined by elaborating on the 'int' to 'string' formatting (ie. fixed width), maybe adding delimiters in the 'join', etc.
In [21]: np.array([','.join(['{:*^8}'.format(i) for i in x]) for x in X])
Out[21]:
array(['***0****,***1****,***2****,***3****',
'***4****,***5****,***6****,***7****',
'***8****,***9****,***10***,***11***'],
dtype='|S35')
A view would only work if what you want is some sort of string to bytes representation, or str to char.
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