Dear Per,
I guess you know that you can run the sampler (unfortunately not
changing the parameters k, and phi)
adding an additonal variable (like all rng methods and pdf functions):
<snip>
>>> r = pygsl.rng.rng()
>>> k = 1
>>> phi = (.9, .05)
>>> r.multinomial(phi, k, 10)
array([[1, 0]])
</snip>
I should have implemented the parameters phi and k as arrays in the
first place (accepting the
additional twist for the novice). For these functions a C loop is
roughly 100 - 1000 times faster than
a python loop
I will have a look what it would mean to change the code to iterate
internally.
Sincerely yours
Pierre
> hi all,
>
> i have a series of probability vector that i'd like to feed into
> multinomial to get an array of vector outcomes back. for example,
> given:
>
> p = array([[ 0.9 , 0.05, 0.05],
> [ 0.05, 0.05, 0.9 ]])
>
> i'd like to call multinomial like this:
>
> multinomial(1, p)
>
> to get a vector of multinomial samplers, each using the nth list in
> 'p'. something like:
>
> array([[1, 0, 0], [0, 0 1]]) in this case. is this possible? it seems
> like 'multinomial' takes only a one dimensional array. i could write
> this as a "for" loop of course but i prefer a vectorized version since
> speed is crucial for me here. the 'multinomial' function from scipy
> does not support this, it seems. is there a way to do this in pygsl?
>
> thanks very much.
>
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