[SciPy-User] scipy.stats pmf evaluation

[nicky van foreest]

On 14 May 2011 22:10,  <josef.pktd at gmail.com> wrote:
> On Sat, May 14, 2011 at 4:06 PM, nicky van foreest <vanforeest at gmail.com> wrote:
>> Hi,
>>
>> I wanted to compute a probability mass function on a range and a grid
>> at the same time, but this fails. Here is an example.
>>
>> In [1]: from scipy.stats import poisson
>>
>> In [2]: import numpy as np
>>
>> In [3]: print poisson.pmf(1, 1)
>> 0.367879441171
>>
>> In [4]: grid = np.arange(np.finfo(float).eps,1.1,0.1)
>>
>> In [5]: print poisson.pmf(1, grid)
>> [  2.22044605e-16   9.04837418e-02 1.63746151e-01   2.22245466e-01
>>   2.68128018e-01   3.03265330e-01   3.29286982e-01   3.47609713e-01
>>   3.59463171e-01   3.65912694e-01   3.67879441e-01]
>>
>> In [6]: print poisson.pmf(range(2), 1)
>> [ 0.36787944  0.36787944]
>>
>>
>> +++
>>
>> Up to now everything works as expected. But this fails:
>>
>> +++
>>
>> In [7]: print poisson.pmf(range(2), grid)
>>
>> ValueError: shape mismatch: objects cannot be broadcast to a single shape
>>
>> +++
>>
>> Why is the call to  poisson.pmf(range(2), grid)  wrong, while it works
>> on either a range or a grid?
>>
>> Does anybody perhaps know the right way to compute
>> poisson.pmf(range(2), grid)" without using a for loop?
>
> You are not broadcasting, (range(2), grid) need to broadcast against
> each other. If it doesn't work then, then it's a bug.

Thanks Josef. But how do I do this? The range will, usually, not
contain the same number of elements as the grid. What I would like to
compute is something like this:

for j in range(3):
   for x in grid:
       poisson.pmf(j, x)

By the above example I can use two types of shortcuts::

for j in range(3):
   poisson.pmf(j, grid)

or

for x in grid:
   poisson.pmf(range(3), x)


but the pmf function does not support broadcasting on both directions
at the same time, or (more probable) it can be done, but I make a
mistake somewhere.

Nicky
>
> Josef
>
>>
>> thanks
>>
>> Nicky
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