[SciPy-User] scipy.stats: Sampling from an arbitrary probability distribution

[josef.pktd at gmail.com]

On Sun, Jun 3, 2012 at 10:07 AM,  <josef.pktd at gmail.com> wrote:
> On Sun, Jun 3, 2012 at 7:20 AM, Daniel Sabinasz
> <d.sabinasz at googlemail.com> wrote:
>> Hi all,
>>
>> I need to sample a random number from a distribution whose probability
>> density function I specify myself. Is that possible using scipy.stats?
>>
>> Here is what I have already:
>>
>> import scipy.stats as st
>>
>> class my_pdf(st.rv_continuous):
>>     def _pdf(self,x):
>>         return x*x/10.0
>>
>> my_cv = my_pdf(name='my_pdf')

I didn't look at the example before

x**2 makes a proper pdf only with a bounded support, so, when creating
the instance, then the bounds .a and .b need to be given as keyword
arguments. (or set as attributes)

It also looks like ppf should have a closed form expression.

(my algebra isn't good enough today to figure out bounds)

Josef



>>
>> Can I now somehow sample a random number from my_cv?
>
> you can define your own distribution with the pdf, then the generic
> methods will calculate the rvs
>
> http://stackoverflow.com/questions/10678546/creating-new-distributions-in-scipy
>
> It will require a large number of calls to generate random numbers,
> numerically calculating ppf and cdf, so this won't be efficient.
> Using a linear interpolated ppf will be faster, and might be accurate enough.
>
> (I still need to write an example for trying out the ppf interpolation version.)
>
> Josef
>
>>
>> Thanks in advance!
>>
>> Daniel
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