Hi all,
Although I like the look of the newly designed numpy/scipy web pages, I
have to say that I really miss the search capability. Is there any motion
toward restoring that?
Jon
--
Jonathan D. Slavin
Answering part of my own question, I see that there is still a search
capability on one of the numpy web pages, but it's not where it used to be
and, in my opinion, is not easy to find. There used to be a search box on
each web page of the numpy docs.
Jon
On Thu, Dec 5, 2013 at 1:00 PM,
Hey,
there was a discussion that for numpy booleans math operators +,-,* (and
the unary -), while defined, are not very helpful. I have set up a quick
PR with start (needs some fixes inside numpy still):
https://github.com/numpy/numpy/pull/4105
The idea is to deprecate these, since the binary
On Thu, Dec 5, 2013 at 5:37 PM, Sebastian Berg
sebast...@sipsolutions.netwrote:
For the moment I saw one annoying change in
numpy, and that is `abs(x - y)` being used for allclose and working
nicely currently.
It would probably be an improvement if allclose returned all(x == y) unless
one of
Hi,
If I pass a masked array through np.asarray, I get original unmasked array.
Example:
test = np.array([[1, 0], [-1, 3]])
testMasked = ma.masked_less_equal(test, 0)
print testMasked
[[1 --]
[-- 3]]
print testMasked.fill_value
99
print np.asarray(testMasked)
[[ 1 0]
[-1 3]]
On Thu, Dec 5, 2013 at 5:37 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Hey,
there was a discussion that for numpy booleans math operators +,-,* (and
the unary -), while defined, are not very helpful. I have set up a quick
PR with start (needs some fixes inside numpy still):
On Thu, Dec 5, 2013 at 10:33 PM, josef.p...@gmail.com wrote:
On Thu, Dec 5, 2013 at 5:37 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Hey,
there was a discussion that for numpy booleans math operators +,-,* (and
the unary -), while defined, are not very helpful. I have set up a
On Thu, Dec 5, 2013 at 5:37 PM, Sebastian Berg sebast...@sipsolutions.net
wrote:
there was a discussion that for numpy booleans math operators +,-,* (and
the unary -), while defined, are not very helpful.
It has been suggested at the Github that there is an area where it is
useful to have
On Thu, Dec 5, 2013 at 10:35 PM, josef.p...@gmail.com wrote:
what about np.dot,np.dot(mask, x) which is the same as (mask *
x).sum(0) ?
I am not sure which way your argument goes, but I don't think you would
find the following natural:
x = array([True, True])
dot(x,x)
True
(x*x).sum()
On Thu, Dec 5, 2013 at 10:56 PM, Alexander Belopolsky ndar...@mac.com wrote:
On Thu, Dec 5, 2013 at 5:37 PM, Sebastian Berg sebast...@sipsolutions.net
wrote:
there was a discussion that for numpy booleans math operators +,-,* (and
the unary -), while defined, are not very helpful.
It has
For + and * (and thus `dot`), this will fix something that is not broken.
It is in fact in conformance with a large literature on boolean arrays
and boolean matrices. That not everyone pays attention to this literature
does not constitute a reason to break the extant, correct behavior.
I'm sure
On Thu, Dec 5, 2013 at 11:05 PM, Alan G Isaac alan.is...@gmail.com wrote:
For + and * (and thus `dot`), this will fix something that is not broken.
+ and * are not broken - just redundant given | and .
What is really broken is -, both unary and binary:
int(np.bool_(0) - np.bool_(1))
1
Hi Faraz
On Thu, 05 Dec 2013 19:14:01 -0800, Faraz Mirzaei wrote:
If I pass a masked array through np.asarray, I get original unmasked array.
`asarray` disregards any information attached to the underlying ndarray by the
subclass. To preserve the subclass, you'd need to use `asanyarray`.
The
On Thu, Dec 5, 2013 at 11:00 PM, Alexander Belopolsky ndar...@mac.com wrote:
On Thu, Dec 5, 2013 at 10:35 PM, josef.p...@gmail.com wrote:
what about np.dot,np.dot(mask, x) which is the same as (mask *
x).sum(0) ?
I am not sure which way your argument goes, but I don't think you would
On 2013/12/05 5:14 PM, Faraz Mirzaei wrote:
Hi,
If I pass a masked array through np.asarray, I get original unmasked array.
Example:
test = np.array([[1, 0], [-1, 3]])
testMasked = ma.masked_less_equal(test, 0)
print testMasked
[[1 --]
[-- 3]]
print testMasked.fill_value
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