Hi,
I have a question about the vectorize function. I'd like to use it to
create a vectorized version of a class method. I've tried the following
code:
from numpy import *
class X:
def func(self, n):
return 2 * n # example
func = vectorize(func)
Now, when I declare an instance of the class X and invoke func() as an
unbound method, it works:
x = X()
print X.func(x, [1, 2]) # output: [2 4]
But an attempt to invoke it "normally", i.e. like
print x.func([1, 2])
fails with the message
Traceback (most recent call last):
File "<stdin>", line 1, in ?
File "/usr/lib/python2.4/site-packages/numpy/lib/function_base.py",
line 823, in __call__
raise ValueError, "mismatch between python function inputs"\
ValueError: mismatch between python function inputs and received arguments
It seems that in this case the class instance (x) isn't passed to the
vectorize.__call__() method, and as a result the number of arguments
does not agree with what this method expects.
Does anybody have an idea of how to do it correctly? As a workaround, I
can write a wrapper function on the module level, which can be
vectorized without problems, and call it from inside the class---but it
looks ugly and is tedious given that I have multiple functions to be
handled in this way.
Thanks in advance for any help,
Wojciech Smigaj
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