On Mon, May 23, 2011 at 3:27 PM, Bruce Southey wrote:
> On 05/23/2011 02:02 PM, Robert Kern wrote:
>> On Mon, May 23, 2011 at 13:33, wrote:
>>> I have a function in two versions, one vectorized, one with loop
>>>
>>> the vectorized function gets all randn variables in one big array
>>> rvs = dis
On Mon, May 23, 2011 at 12:34 PM, wrote:
> Obviously I was working by columns, using a transpose worked, but
> rewriting to axis=1 instead of axis=0 which should be more efficient
> since I had almost all calculations by columns, I needed
> params = map(lambda x: np.expand_dims(x, 1), params)
>
On Mon, May 23, 2011 at 3:02 PM, Robert Kern wrote:
> On Mon, May 23, 2011 at 13:33, wrote:
>> I have a function in two versions, one vectorized, one with loop
>>
>> the vectorized function gets all randn variables in one big array
>> rvs = distr.rvs(args, **{'size':(nobs, nrep)})
>>
>> the loo
On 05/23/2011 02:02 PM, Robert Kern wrote:
> On Mon, May 23, 2011 at 13:33, wrote:
>> I have a function in two versions, one vectorized, one with loop
>>
>> the vectorized function gets all randn variables in one big array
>> rvs = distr.rvs(args, **{'size':(nobs, nrep)})
>>
>> the looping versio
On Mon, May 23, 2011 at 13:33, wrote:
> I have a function in two versions, one vectorized, one with loop
>
> the vectorized function gets all randn variables in one big array
> rvs = distr.rvs(args, **{'size':(nobs, nrep)})
>
> the looping version has:
> for irep in xrange(nrep):
> rvs
On Mon, May 23, 2011 at 11:42 AM, Keith Goodman wrote:
> On Mon, May 23, 2011 at 11:33 AM, wrote:
>> I have a function in two versions, one vectorized, one with loop
>>
>> the vectorized function gets all randn variables in one big array
>> rvs = distr.rvs(args, **{'size':(nobs, nrep)})
>>
>> t
On Mon, May 23, 2011 at 11:33 AM, wrote:
> I have a function in two versions, one vectorized, one with loop
>
> the vectorized function gets all randn variables in one big array
> rvs = distr.rvs(args, **{'size':(nobs, nrep)})
>
> the looping version has:
> for irep in xrange(nrep):
>
I have a function in two versions, one vectorized, one with loop
the vectorized function gets all randn variables in one big array
rvs = distr.rvs(args, **{'size':(nobs, nrep)})
the looping version has:
for irep in xrange(nrep):
rvs = distr.rvs(args, **{'size':nobs})
the rest should
