On 1/25/21, 12:44 PM, Melissa Mendonça wrote:
The NumPy Documentation Team has been discussing video content as part
of our outreach and documentation efforts, in part inspired by the
excellent Spyder IDE channel [1]. At our last meeting, we realized
there is already a good amount of content a
Here are my thoughts on textual capitalization (at first, I thought you
wanted to raise money!):
We all agree that in code, it is "numpy". If you don't use that, it
throws an error. If, in text, we keep "numpy" with a forced lower-case
letter at the start, it is just one more oddball to reme
I have a handout for my PHZ 3150 Introduction to Numerical Computing
course that includes some rules:
(a) All integer-valued floating-point numbers should have decimal points
after them. For
example, if you have a time of 10 sec, do not use
y = np.e**10 # sec
use
y = np.e**10. # sec
instea
nd NOAA to see if there’s anything
similar.
-CHB
On Apr 25, 2019, at 1:04 PM, Ralf Gommers
mailto:ralf.gomm...@gmail.com>>
wrote:
On Sat, Apr 20, 2019 at 12:41 PM Ralf Gommers
mailto:ralf.g
Hi Ralf,
The rejection is disappointing, for sure. Some good ammo for next time
might be the recommendations in this report from the US National
Academies of Science, Engineering, and Medicine:
http://sites.nationalacademies.org/SSB/CurrentProjects/SSB_178892
https://www.nap.edu/read/25217/
imarily used for are likely to be read
by developers working in other languages (i.e. ascontiguousarray gets used
at a lot of "boundaries" with other systems), keeping function names that
make intention very clear is important.
Just my $0.02, anyway. Cheers,
-Joe
On Thu, Oct 25,
Hi,
Download here:
https://pypi.python.org/pypi/neurolab
Though, I can't recommend to use it. I did a while ago and it is
a pretty basic project that seems to be no longer maintained.
I use Keras / Theano now instead, which is a mature and widely used
package.
Kind regards,
Joe
Does someone know of a function or a convenient way to automatically
derive a dtype object from a C typedef struct string or a cffi.typeof()?
Am 27.01.2018 10:30 schrieb Joe:
Thanks for your help on this! This solved my issue.
Am 25.01.2018 um 19:01 schrieb Allan Haldane:
There is a new
Thanks for your help on this! This solved my issue.
Am 25.01.2018 um 19:01 schrieb Allan Haldane:
There is a new section discussing alignment in the numpy 1.14 structured
array docs, which has some hints about interfacing with C structs.
These new 1.14 docs are not online yet on scipy.org, but
/48423725/how-to-handle-member-padding-in-struct-when-reading-cffi-buffer-with-numpy-fromb
Kind regards,
Joe
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`.
It all makes perfect sense if you think of it of a 0-d array
picking
The same thing is true for example for lists of booleans.
- Sebastian
On Thu, Dec 14, 2017, 04:27 Joe wrote:
> Hello,
> thanks for you feedback.
>
> Sorry, if thie question is stupid and the case below does
treated as a tuple of integers, but as a 0d mask
Eric
On Wed, 13 Dec 2017 at 12:44 Joe wrote:
Hi,
yet another question.
I looked through the indexing rules in the
documentation but I count not find which one
applies to x[True] and x[False]
that might e.g result from
import numpy as np
x
r ndarray (of data type
integer or bool)", right?
Or will x[True] trigger basic indexing as it is "a tuple of integers"
because True will be converted to Int?
Cheers,
Joe
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https://
scalar_input:
return np.squeeze(ret)
return ret
Is this as good as it gets or do you have other suggestions?
Cheers,
Joe
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12.2017 09:09 schrieb Nathaniel Smith:
On Tue, Dec 12, 2017 at 12:02 AM, Joe wrote:
Hi,
question says it all. I looked through the basic and advanced
indexing,
but I could not find the rule that is applied to make
x[np.newaxis,:] and x[np.newaxis] the same.
I think it's the genera
Hi,
question says it all. I looked through the basic and advanced indexing,
but I could not find the rule that is applied to make
x[np.newaxis,:] and x[np.newaxis] the same.
Kind regards,
Joe
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me shape
along all but the first axis."
So it was possible to stack an array (3,) and (2, 3) to a (3, 3) array
without using e.g. atleast_2d on the (3,) array.
Is there a possibility to mimic that behavior with np.concatenate or
np.stack?
Joe
Your example doesn't run, but here is one that does:
In [8]: x = np.array([50], dtype=float)
In [9]: np.piecewise(x, [0 < x <= 90, 90 < x <= 180], [1.1, 2.1])
array([ 1.1])
The answer to your second question is that it is returning an array
with the same dtype as its first argument.
The answer
], [1.1, 2.1])
return [2] and not [2.1] ?
Kind regards,
Joe
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being
discussed in Issue#9193 page.
Thanks,
-cheers
Joe
--
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"GNU/Linux: because a PC is a terrible thing to waste" - GNU Generation
********
Joe Philip Ninan
Postdoctoral Researcher
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