On 8/19/2013 2:37 AM, Juan Luis Cano wrote:
https://github.com/numpy/numpy/issues/2880
it was suggested that we deprecate and eventually remove the financial
functions in NumPy
IDL has financial functions. Matlab has financial functions. Financial
functions are something that a subset of
We considered lowering the review standard near the end of my direct
involvement in the doc project but decided not to. You didn't mention
any benefit to the proposed changes, so while I'm not active in the doc
project anymore, let me relate our decision.
It's often the case that docstrings get
On Wed, Feb 15, 2012 at 1:00 PM, Perry Greenfield pe...@stsci.edu wrote:
On Feb 15, 2012, at 3:01 PM, Matthew Brett wrote:
[...]
My 2 cents.
[...]
I am both elated and concerned. Since it's obvious what there is to be
elated about, this post has a concerned tone. But overall, I think
I had intended to stay quiet in this discussion since I am not a core
developer and also no longer even lead the doc project. However, I've
watched two organizations go very wrong very fast recently. Both were
similar in structure to this one. I've done some study as a result and
there are some
Christopher Barker, Ph.D. wrote
quick note on this: I like the FALSE == good way, because:
So, you like to have multiple different kinds of masked, but I need
multiple good values for counts. We could do it with negative masks
and positive counts, but that doesn't reduce to a boolean for
Mark Wiebe mwwi...@gmail.com:
With a non-boolean alpha mask, there's an implication of a
multiplication operator in there somewhere, but with a boolean mask,
the data can be any data whatsoever that doesn't necessarily support
any kind of blending operations.
My goal in raising the point is
As with Travis, I have not had time to wade through the 150+ messages
on masked arrays, but I'd like to raise a concept I've mentioned in
the past that would enable a broader use if done slightly differently.
That is, the masked array problem is a subset of this more-general
problem. Please
It seems that the Other parameters section is not
getting included in the output.
The Other parameters is not often used in numpy because there are
not generally dozens of tweaking parameters in its basic numerical
routines. It will probably be more common in certain scipy pages, and
if other
On Thu, 19 Aug 2010 09:06:32 -0500, G?khan Sever gokhanse...@gmail.com wrote:
On Thu, Aug 19, 2010 at 9:01 AM, greg whittier gre...@gmail.com wrote:
I frequently deal with 3D data and would like to sum (or find the
mean, etc.) over the last two axes. I.e. sum a[i,j,k] over j and k.
I find
While this thread is super off-topic (and long enough that I'm not
going to quote it), I'm actually finding it very interesting, as a
non-MATLAB person, to find out what I need to say to the MATLAB mafia
here to demonstrate that MATLAB has sufficient flaws and non-followers
out in the real world
Hi folks,
We are (finally) about to begin reviewing and proofing the NumPy
docstrings! This is the final step in producing professional-level
docs for NumPy. What we need now are people willing to review docs.
There are two types of reviewers:
Technical reviewers should be developers or
Over on [Numpy-discussion] Extending documentation to c code, David
G. gave voice to a frustration he and I share about the status of
documentation in the new-code development process. I don't want to
paint with a broad brush, yet in recent months there have been a
number of checkins, unanimously
On Tue, 25 May 2010 15:54:26 -0500, Travis Oliphant oliph...@enthought.com
wrote:
On May 25, 2010, at 2:50 PM, Charles R Harris wrote:
On Tue, May 25, 2010 at 1:37 PM, Travis Oliphant oliph...@enthought.com
wrote:
Hi everyone,
There has been some talk about re-factoring NumPy to
Chuck Harris writes (on numpy-discussion):
Since there has been talk of deprecating the numarray and numeric
compatibility parts of numpy for the upcoming 2.0 release I thought maybe we
could consider a few other changes. First, numpy imports a ton of stuff by
default and this is maintained
...numpy clean-up...
...cruft...
...API breakage...
...etc
At the risk of starting a flame war, the cleanest way out of the
legacy API trap is some level of fork, with the old code maintained
for some years while new uses (new users and new code by old users)
get done in the new package,
Christopher Barker wrote:
Following the full
PEP procedure
or a parallel NPEP system.
Actually, I originally intended just to mean follow the procedure
not do it in their system. But, in thinking about it, if it's
compatible with their system to develop a whole subpackage in their
About sixteen months ago, I launched the SciPy Documentation Project
and its Marathon. Dozens pitched in and now numpy docs are rapidly
approaching a professional level. The pink wave (Needs Review
status) is at 56% today! There is consensus among doc writers that
much of the rest can be
Let's Finish Documenting SciPy!
Last year, we began the SciPy Documentation Marathon to write
reference pages (docstrings) for NumPy and SciPy. It was a huge
job, bigger than we first imagined, with NumPy alone having over 2,000
functions.
We created the doc wiki (now at
On Sun, 24 May 2009 18:14:42 -0400 josef.p...@gmail.com wrote:
On Sun, May 24, 2009 at 4:33 PM, Joe Harrington j...@physics.ucf.edu wrote:
I hate to ask for another function in numpy, but there's an obvious
one missing in the financial group: xirr. ?It could be done as a new
function
On Mon, 25 May 2009 13:51:38 -0400, josef.p...@gmail.com wrote:
On Mon, May 25, 2009 at 11:50 AM, Joe Harrington j...@physics.ucf.edu wrote:
On Sun, 24 May 2009 18:14:42 -0400 josef.p...@gmail.com wrote:
On Sun, May 24, 2009 at 4:33 PM, Joe Harrington j...@physics.ucf.edu
wrote:
I hate
Let's keep this thread focussed on the original issue:
just add a floating array of times to irr or a new xirr
continuous interest
no more
Anyone can use the timeseries package to produce a floating array of
times from normal dates, if those are the dates they want. If they
want some
I hate to ask for another function in numpy, but there's an obvious
one missing in the financial group: xirr. It could be done as a new
function or as an extension to the existing np.irr.
The internal rate of return (np.irr) is defined as the growth rate
that would give you a zero balance at the
william ratcliff william.ratcl...@gmail.com writes:
Hi! I'd like to suggest a patch for:
numpy
http://docs.scipy.org/numpy/docs/numpy/.corehttp://docs.scipy.org/numpy/docs/numpy.core/
.fromnumeric http://docs.scipy.org/numpy/docs/numpy.core.fromnumeric/.put
The docstring contains:
for i,
2009/4/24 william ratcliff william.ratcl...@gmail.com:
Actually, if I look here:
http://docs.scipy.org/numpy/docs/numpy.core.fromnumeric.put/
The text that appears in by browser is:
put(a, ind, v, mode='raise')
Changes specific elements of one array by replacing from another
scipy-u...@scipy.org,
Numpy Discussion numpy-discussion@scipy.org
Subject: JOB: write numpy docs
From: Joe Harrington j...@physics.ucf.edu
CC: j...@physics.ucf.edu
Reply-to: j...@physics.ucf.edu
Last year's Doc Marathon got us off to a great start on documenting
NumPy! But, there's still much
Last year's Doc Marathon got us off to a great start on documenting
NumPy! But, there's still much work to be done, and SciPy after that.
It's time to gear up for doing it again.
Critical to last year's success was Stefan van der Walt's committed
time, but he will be unable to play that role
Hi Lutz,
what you say is of course correct, but I am wondering if there is a
mistake in the user guide (p. 180 of
http://numpy.scipy.org/numpybook.pdf): according to the expressions in
the user guide, both fft and ifft are not normalized. The
implementation if ifft, on the other hand, has
If you're willing to do arithmetic you might even be able to
pull it off, since NaNs tend to propagate:
if (newmin) min -= (min-new);
Whether the speed of this is worth its impenetrability I couldn't say.
Code comments cure impenetrability, and have no cost in speed. One
could write a
I'm doing nothing. Someone else must volunteer.
Fair enough. Would the code be accepted if contributed?
There is a
reasonable design rule that if you have a boolean argument which you
expect to only be passed literal Trues and Falses, you should instead
just have two different functions.
On Tue, Aug 12, 2008 at 19:28, Charles R Harris
[EMAIL PROTECTED] wrote:
On Tue, Aug 12, 2008 at 5:13 PM, Andrew Dalke [EMAIL PROTECTED]
wrote:
On Aug 12, 2008, at 9:54 AM, Anne Archibald wrote:
Er, is this actually a bug? I would instead consider the fact that
np.min([]) raises an
Masked arrays are a bit clunky for something as simple and standard as
NaN handling. They also have the inverse of the standard truth sense,
at least as used in my field. 1 (or True) usually means the item is
allowed, not denied, so that you can multiply the mask by the data to
zero all bad
SciPy Documentation Marathon 2008 Status Report
We are now nearing the end of the summer. We have a ton of great
docstrings, a nice PDF and HTML reference guide, a new package with
pages on general topics like slicing, and a glossary.
We had hoped to have all the numpy docstrings in
Hi Jarrod,
I'm just catching up on my numpy lists and I caught this; sorry for
the late reply!
Another issue that we should address is whether it is OK to postpone
the planned API changes to histogram and median. A couple of people
have mentioned to me that they would like to delay the API
This is an interim status report on the Summer Documentation Marathon.
It is also an invitation and plea for all experienced users to
participate! I am cross-posting in an effort to get broader
participation. Please hold any discussion on the scipy-dev mailing
list.
As you know, our immediate
Just to clarify, the documentation Stefan refers to is topical
*reference* documentation for the numpy package infrastructure,
conventions, etc. The contemplated .doc module will be a few kB of
distilled reference text. Its contents will be included in the PDF
and HTML reference guides.
It may
Ryan writes:
This is very good news. I will find some way to get involved.
Great! Please dive right in, and sign up on the Developer_Zone page
so we can keep track of who's involved.
One thing I forgot to mention in my too-wordy announcement was that
discussion of documentation is on the
I didn't see Travis's Numpy book mentioned at all in your writeup, so
I am wondering where its role in the doc effort is.
Is it OK to copy material out of the book and into
other parts of the documentation?
No worries, Travis is on board here. We included him and others on
the Steering
. It is a marathon, and this time we are going to
finish. We hope you will join us!
--jh-- and Stefan and Perry and Pauli and Emmanuelle...and you!
Joe Harrington
Stefan van der Walt
Perry Greenfield
Pauli Virtanen
Emmanuelle Guillart
...and you!
___
Numpy
Just cast your arrays to booleans if you want to do boolean operations
on them.
It turns out there's an even better way: logical_and() and its friends
do boolean operations on arrays.
IDL solves the problem exactly as numpy does, erroring on arrays in
conditionals and short-circuiting boolean
For that matter, is there a reason logical operations don't work on
arrays other than booleans? What about:
import numpy
x = numpy.ones((10), dtype='Bool')
y = numpy.ones((10), dtype='Bool')
y[6] = False
z = x and y # logical AND: this one fails with an error about arrays
Absolutely. Let's please standardize on:
import numpy as np
import scipy as sp
I hope we do NOT standardize on these abbreviations. While a few may
have discussed it at a sprint, it hasn't seen broad discussion and
there are reasons to prefer the other practice (numpy as N, scipy as
S, pylab
+1 for simple financial functions in numpy, and congrats that it's on
OLPC! If we have an FFT in numpy, we should have an internal rate of
return. Anyone with investments needs that, and that's more people
than those needing an FFT.
I agree that Excel will bring in the most familiarity, but
Every once in a while the issue of how to split things into packages
comes up. In '04, I think, we had such a discussion regarding scipy
(with Numeric as its base at the time). One idea was a
core-plus-many-modules approach. We could then have metapackages that
just consisted of dependencies
I think it would enhance broadcasting if functions like sum, mean, etc
didn't change the number of dimensions.
I strongly favor doing it, but with keepshape (or just keep, to make
it short) and not by default. It's at least as common to take a mean
down an axis of a 2D array and plot it
A couple of thoughts on parallelism:
1. Can someone come up with a small set of cases and time them on
numpy, IDL, Matlab, and C, using various parallel schemes, for each of
a representative set of architectures? We're comparing a benchmark to
itself on different architectures, rather than
Is it perhaps possible to make all numpy functions accessible in
submodules (in addition to in numpy, for backwards compatibility) and
then promote accessing them that way?
I would caution on breaking functionality out into too many
categories.
It is *very* cumbersome to constantly import
I was misinformed about the status of numdisplay's pages. The package
is available as both part of stsci_python and independently, and its
(up-to-date) home page is here:
http://stsdas.stsci.edu/numdisplay/
Googling numdisplay finds that page.
My apologies to those inconvenienced by my prior
If you want to explore the array interactively, blink images, mess with
colormaps using the mouse, rescale the image values, mark regions, add
labels, look at dynamic plots of rows and columns, etc., get the ds9
image viewer and the xpa programs that come with it that allow it to
communicate with
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