> from scipy import stats
>>> stats.poisson.pmf(2,1)
array(0.18393972058572114)
thanks all anyway,
culpritNr1
Jervis Whitley wrote:
>
> On Wed, Jan 14, 2009 at 8:27 AM, culpritNr1
> wrote:
>
>>
>>
>> there some kind of random.poisson()?
>>
>&
his functionality is extremely poor. Look
>>> help("scipy.stats.distributions.poisson.rvs")
Help on method rvs in scipy.stats.distributions.poisson:
scipy.stats.distributions.poisson.rvs = rvs(self, *args, **kwds) method of
scipy.stats.distributions.poisson_gen instance
Do yo
Hello All,
OK. This time a less trivial question.
Is there a function to enable us sample from a Poisson distribution?
There is random.uniform, random.normalvariate(), random.expovariate()... Is
there some kind of random.poisson()?
Thank you,
culpritNr1
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Thanks Marc and Kent and all. math.exp() is what I was looking for.
culpritNr1
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call
that computation millions of times. Anything more efficient than
2.718182**10 may be good.
Thank you,
culpritNr1
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#x27; I really meant 'convert'. Sorry, my badness.
Thanks for pointing that out.
culpritNr1
Kent Johnson wrote:
>
> On Fri, Jan 9, 2009 at 11:23 AM, culpritNr1
> wrote:
>> That is EXACTLY what I was looking for.
>>
>> Actually, int() does not really work bu
Thanks Daniel,
That is EXACTLY what I was looking for.
Actually, int() does not really work but this does:
[ [line[0], eval(line[1]), eval(line[2])] + line[3:] for line in LoL]
Again, thanks.
culpritNr1
Daniel Sarmiento-2 wrote:
>
> I am not an expert and don't know
BP', 'PLoS Biol 6(10): e255'],
['chrX', '162030736', '162030737', 'gnfX.146.867', '67.05'],
['chrX', '164171913', '164171914', 'gnfX.148.995', '70.45']]
Do you
to python, my question was if there was an ELEGANT
way to do this casting, perhaps as a list comprehension operation. I
wondered if the beauty of python could reach that far.
I thank you all for your comments,
culpritNr1
trias wrote:
>
> Hi Your,
>
> I work with genomic data
Hi All,
Say I have this nice list of lists:
LoL = [['chrX', '160944034', '160944035', 'gnfX.145.788', '63.60'],
['chrX', '161109992', '161109993', 'rs13484104', '63.60'],
['chrX', '161414112', '161414113', 'rs13484105', '63.60'],
['chrX', '161544071', '1615
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