It appears that the only reliable way to do this may be to use a loop to
modify an object arrays in-place. Pandas has a version of this written in
Cython:
https://github.com/pydata/pandas/blob/c1a0dbc4c0dd79d77b2a34be5bc35493279013...
To quote Wes McKinney "Seriously can't believe I had to write this function"
Best,
Stephan
On Mon, Feb 9, 2015 at 8:31 AM, Benjamin Root
I am trying to write up some code that takes advantage of np.tile() on arbitrary array-like objects. I only want to tile along the first axis. Any other axis, if they exist, should be left alone. I first coerce the object using np.asanyarray(), tile it, and then coerce it back to the original type.
The problem seems to be that some of my array-like objects are being "over-coerced", particularly the list of tuples. I tried doing "np.asanyarray(a, dtype='O')", but that still turns it into a 2-D array.
Am I missing something?
Thanks, Ben Root
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