Datatype of python universal function created with frompyfunc

Question

I have the following question concerning universal functions in numpy. How can I define a universal function which returns the same type of numpy array as the numpy build-in functions. The following sample code:

import numpy as np
def mysimplefunc(a):
    return np.sin(a)
mysimpleufunc = np.frompyfunc(mysimplefunc,1,1)
a = np.linspace(0.0,1.0,3)
print(np.sin(a).dtype)
print(mysimpleufunc(a).dtype)

results in the output:

float64
object

Any help is very much appreciated :)

PS.: I am using python 3.4

Community · Accepted Answer · 2017-05-23 10:33:57Z

0

I found the solution (see also discussion on stackoverflow): use vectorize instead of frompyfunc

import numpy as np
def mysimplefunc(a):
    return np.sin(a)
mysimpleufunc = np.vectorize(mysimplefunc)
a = np.linspace(0.0,1.0,3)
print(np.sin(a).dtype)
print(mysimpleufunc(a).dtype)

edited May 23, 2017 at 10:33

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answered Apr 21, 2016 at 11:38

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1 Comment

hpaulj Over a year ago

I knew from other SO discussions that frompyfunc returned object and was faster, but didn't realize it was used by vectorize. vectorize is often misused as a replacement for simple iteration.

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