[Numpy-discussion] efficient use of numpy.where() and .any()
Mon Apr 23 11:16:16 CDT 2007
Excellent suggestions...just a few comments:
Pierre GM wrote:
> On Monday 23 April 2007 10:37:57 Mark.Miller wrote:
>> In some of my code, I need to use large matrix of random numbers that
>> meet specific criteria (i.e., some random numbers need to be removed and
>> replaces with new ones).
>> I have been working with .any() and .where() to facilitate this process.
> Have you tried nonzero() ?
Nonzero isn't quite what I'm after, as the tests are more complicated
than what I illustrated in my example.
> a[a<0] = numpy.random.normal(0,1)
This is a neat construct that I didn't realize was possible. However,
it has the undesirable (in my case) effect of placing a single new
random number in each locations where a<0. While this could work, I
ideally need a different random number chosen for each replaced value.
Does that make sense?
> will put a random number from the normal distribution where your initial a is
> negative. No Python loops needed, no Python temps.
>> Traceback (most recent call last):
>> File "<pyshell#71>", line 1, in <module>
>> while (0<a<1).any():
> The double condition (0<a<1) is not legit. You should try
> (a>0) & (a<1)
> Note the () around each condition in case #2.
This makes perfect sense. Thanks for pointing it out to me. It should
easily do the trick.
Any and all additional suggestions are greatly appreciated,
> Numpy-discussion mailing list
More information about the Numpy-discussion