[Numpy-discussion] genfromtxt converter question
Fri Jun 17 21:48:52 CDT 2011
Thanks guys - I'm happy with the solution for now. FYI, Derek's
suggestion doesn't work in numpy 1.5.1 either.
For any developers following this thread, I think this might be a nice
use case for genfromtxt to handle in future.
As a corollary of this problem, I wonder whether there's a
human-readable text format for complex numbers that genfromtxt can
currently easily parse into a complex array? Having the hard-coded
value for the number of columns in the converter and the genfromtxt
call goes against the philosophy of the function's ability to form an
array of shape matching the input layout.
On Sat, Jun 18, 2011 at 7:24 AM, Derek Homeier
> On 17.06.2011, at 11:01PM, Olivier Delalleau wrote:
>>> You were just overdoing it by already creating an array with the converter, this apparently caused genfromtxt to create a structured array from the input (which could be converted back to an ndarray, but that can prove tricky as well) - similar, if you omit the dtype=None. The following
>>> cnv = dict.fromkeys(range(4), lambda x: complex(*eval(x)))
>>> b = np.genfromtxt(a,converters=cnv, dtype=None, delimiter=18, usecols=range(4))
>>> directly produces a shape(4,4) complex array for me (you may have to apply an .astype(np.complex64) afterwards if so desired).
>>> BTW I think this is an interesting enough case of reading non-trivially structured data that it deserves to appear on some examples or cookbook page.
>>> NumPy-Discussion mailing list
>> I had tried that as well and it doesn't work with numpy 1.4.1 (I get an object array). It may have been fixed in a later version.
> OK, I was using the current master from github, but it works in 1.6.0 as well. I still noticed some differences between loadtxt and genfromtxt behaviour, e.g. where loadtxt would be able to take a string from the converter and automatically convert it to a number, whereas in genfromtxt the converter still had to include the float() or complex()...
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