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On 02-Apr-15 4:35 PM, Eric Firing wrote:
On 2015/04/02 10:22 AM, josef.p...@gmail.com wrote:
Swapping the axis when slices are mixed with fancy indexing was a
design mistake, IMO. But not fancy indexing itself.
I'm not saying there should be no fancy indexing capability; I am saying
that it
Thanks Ryan.
There are a number of good thoughts in your message. I'll try to keep
track of them.
Another respondent reported different results than mine. I'm in the
process of re-installing to check.
Colin W.
On 11 February 2015 at 16:18, Ryan Nelson rnelsonc...@gmail.com wrote:
Colin,
On 06/01/2015 8:38 PM, Alexander Belopolsky wrote:
On Tue, Jan 6, 2015 at 8:20 PM, Nathaniel Smith n...@pobox.com
mailto:n...@pobox.com wrote:
Since matrices are now part of some high school curricula, I urge that
they
be treated appropriately in Numpy. Further, I suggest that
On 08/01/2015 1:19 PM, Ryan Nelson wrote:
Colin,
I'll second the endorsement of Sage; however, for teaching purposes, I
would suggest Sage Math Cloud. It is a free, web-based version of
Sage, and it does not require you or the students to install any
software (besides a new-ish web
One of the essential characteristics of a matrix is that it be rectangular.
This is neither spelt out or checked currently.
The Doc description refers to a class:
- *class *numpy.matrix[source]
http://github.com/numpy/numpy/blob/v1.9.1/numpy/matrixlib/defmatrix.py#L206
Returns a matrix
This version of Numpy does not appear to be available as an installable binary.
In any event, the LAPACK and other packages do not seem to be available with
the installable versions.
I understand that Windows Studio 2008 is normally used for Windows compiling.
Unfortunately, this is no
Oliver,
Thanks. I've installed Windows Studio 2008 Express.
I'll read your building on Winods Document.
Colin W.
On 29 July 2014 08:50, Olivier Grisel olivier.gri...@ensta.org wrote:
2014-07-29 14:24 GMT+02:00 Colin J. Williams c...@ncf.ca:
This version of Numpy does not appear
On 25-Mar-2014 1:00 PM, numpy-discussion-requ...@scipy.org wrote:
Message: 3 Date: Mon, 24 Mar 2014 17:58:57 -0600 From: Charles R
Harris charlesr.har...@gmail.com Subject: Re: [Numpy-discussion]
Resolving the associativity/precedence debate for @ To: Discussion of
Numerical Python
Julian,
I can see the need to recognize both column and row vectors, but why not
with np.matrix?
I can see no need for a new operator and hope to be able to comment more
fully on PEP 465 in a few days.
Colin W.
On 17-Mar-2014 7:19 PM, numpy-discussion-requ...@scipy.org wrote:
Send
I would like to see the case made for @. Yes, I know that Guido has
accepted the idea, but he has changed his mind before.
The PEP seems neutral to retaining both np.matrix and @. Nearly ten
years ago, Tim Peters http://legacy.python.org/dev/peps/pep-0020/ gave us:
/There should be
Ralf,
Could you please elaborate on the matrix weaknesses?
Is there any work planned to eliminate the peculiarities?
Regards,
Colin W.
Subject: Re: [Numpy-discussion] Relative speed
To: Discussion of Numerical
This is to respond to Alan's message:
Message: 7
Date: Fri, 16 Aug 2013 11:20:32 -0400
From: Alan G Isaac alan.is...@gmail.com
Subject: [Numpy-discussion] PEP 450 (stats module for standard
library)
To: Discussion of Numerical Python
To: Discussion of Numerical Python numpy-discussion@scipy.org
Message-ID:
CAN06oV9E2Xsf=tgbyqgxpnt4lhan6twtbuyi8gagt-vg2qa...@mail.gmail.com
Content-Type: text/plain; charset=ISO-8859-1
On Wed, Jul 24, 2013 at 8:53 AM, St?fan van der Walt ste...@sun.ac.za wrote:
On Wed,
ence, attempting to be extremely concise in technical
writing is a common cause of awkward grammar problems like this. I
do
it all the time :)
-Rob
On Thu, Jul 18, 2013 at 9:18 AM, Colin J. Williams
cjwilliam...@gmail.com wrote:
Re
Returning to numpy after a while away, I'm impressed with
the style and content of the User Guide and the Reference. This
is to offer a Guide correction - I couldn't figure out how to
offer the correction on-line.
What is Numpy?
On 12/04/2013 3:57 PM, Chris Barker -
NOAA Federal wrote:
On Fri, Apr 12, 2013 at 9:52 AM, Riccardo De Maria
riccardodema...@gmail.com wrote:
Not related to leap seconds and physically accurate time deltas, I have just
noticed that SQLite has a nice
On 11/04/2013 7:20 PM, Paul Hobson
wrote:
On Wed, Apr 3, 2013 at 4:28 PM, Doug Coleman doug.cole...@gmail.com
wrote:
Also, gmail "bottom-posts" by default.
On 09/04/2013 5:46 PM, Mark Wiebe
wrote:
On Mon, Apr 8, 2013 at 12:24 PM, Chris Barker -
NOAA Federal chris.bar...@noaa.gov
wrote:
Recent
discussion has made it clear that the timezone handling in
On 07/04/2013 1:03 AM, Ondřej Čertík
wrote:
On Tue, Mar 26, 2013 at 6:32 PM, Ondřej Čertík ondrej.cer...@gmail.com wrote:
[...]
Yes. I created an issue here for them to test it:
https://github.com/scikit-learn/scikit-learn/issues/1809
Just to make
On 07/04/2013 10:32 AM, Happyman wrote:
Hello,
I started using python
4-5 months ago. At that time I didn't realize there are
incredibly many resource like modules, additional programs
(ready one) in python. The problem is to which
On 03/04/2013 7:11 PM,
huangkan...@gmail.com wrote:
Agree with the row-vector and column-vector thing.
I notice that in ndarray
multiplication, the 1-d array is treated as a column-vector. But
in matrix multiplication, 1-d array is converted
On 23/03/2013 7:21 AM, Ralf Gommers
wrote:
On Fri, Mar 22, 2013 at 10:39 PM,
Colin J. Williams cjwilliam...@gmail.com
wrote:
On 20/03/2013 11:12 AM, Frédéric Bastien
On 23/03/2013 12:05 AM, Chris Barker -
NOAA Federal wrote:
On Fri, Mar 22, 2013 at 2:39 PM, Colin J. Williams
cjwilliam...@gmail.com wrote:
I have updated to numpy 1.7.0 for each of the Pythons 2.7.3, 3.2.3 and
3.3.0
On 20/03/2013 11:12 AM, Frédéric
Bastien wrote:
On Wed, Mar 20, 2013 at 11:01 AM, Colin J. Williams
cjwilliam...@gmail.com wrote:
On 20/03/2013 10:30 AM, Frédéric Bastien wrote:
Hi,
win32 do not mean it is a 32 bits windows
I have a small program which builds random matrices for
increasing matrix orders, inverts the matrix and checks the
precision of the product. At some point, one would expect
operations to fail, when the memory capacity is exceeded. In
both Python 2.7
))
2.41799631031e-05
1.13955868701e-05
3.64338191541e-05
1.13484781021e-05
1 loops, best of 3: 156 s per loop
Intel i5, 4 GB of RAM and SSD. ATLAS installed from Fedora repository
(I don't run heavy stuff on this computer).
On 20 March 2013 14:46, Colin J. Williams c...@ncf.ca wrote:
I have
. ATLAS installed from Fedora
repository
(I don't run heavy stuff on this computer).
On 20 March 2013 14:46, Colin J. Williams c...@ncf.ca
wrote:
I have a small program which builds random matrices
. ATLAS installed from Fedora repository
(I don't run heavy stuff on this computer).
On 20 March 2013 14:46, Colin J. Williams c...@ncf.ca wrote:
I have a small program which builds random matrices for increasing matrix
orders, inverts the matrix and checks the precision of the product. At some
On 20/03/2013 11:06 AM, Jens Nielsen
wrote:
The python3 version is compiled without
any optimised library and is falling back on a slow version.
Where did you get this installation from?
Jens
From the
On 20/03/2013 11:12 AM, Frédéric
Bastien wrote:
On Wed, Mar 20, 2013 at 11:01 AM, Colin J. Williams
cjwilliam...@gmail.com wrote:
On 20/03/2013 10:30 AM, Frédéric Bastien wrote:
Hi,
win32 do not mean it is a 32 bits windows
It seems that these standards
have been adopted, which is good:
The following import conventions are used throughout the NumPy
source and documentation:
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
Source:
PM, Colin J. Williams fn...@ncf.ca wrote:
It seems that these standards have been adopted, which is good:
The following import conventions are used throughout the NumPy source and
documentation:
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
Source: https
On 26/07/2012 4:57 PM, Benjamin Root
wrote:
On Thu, Jul 26, 2012 at 4:45 PM, Colin J.
Williams fn...@ncf.ca
wrote:
It seems that these standards have been
adopted, which is good
If you are using integers, why not use Python's Long?
Colin W.
On 11/10/2011 2:00 PM, Matthew Brett wrote:
Hi,
Can anyone think of a clever way to round an integer to the next
lowest integer represented in a particular floating point format?
For example:
In [247]: a = 2**25+3
This is out
On 04-Dec-09 10:54 AM, Bruce Southey wrote:
On 12/04/2009 06:18 AM, yogesh karpate wrote:
@ Pauli and @ Colin:
Sorry for the late reply. I was
busy in some other assignments.
# As far as normalization by(n) is concerned then its common
assumption that
On 04-Dec-09 05:21 AM, Pauli Virtanen wrote:
pe, 2009-12-04 kello 11:19 +0100, Chris Colbert kirjoitti:
Why cant the divisor constant just be made an optional kwarg that
defaults to zero?
It already is an optional kwarg that defaults to zero.
Cheers,
I suggested that 1
On 04-Dec-09 07:18 AM, yogesh karpate wrote:
@ Pauli and @ Colin:
Sorry for the late reply. I was busy
in some other assignments.
# As far as normalization by(n) is concerned then its common
assumption that the population is normally distributed and
Yogesh,
Could you explain the rationale for this choice please?
Colin W.
On 03-Dec-09 00:35 AM, yogesh karpate wrote:
The thing is that the normalization by (n-1) is done for the no. of
samples 20 or23(Not sure about this no. but sure about the thing that
this no isnt greater than 25) and
On 29-Nov-09 17:13 PM, Dr. Phillip M. Feldman wrote:
All of the statistical packages that I am currently using and have used in
the past (Matlab, Minitab, R, S-plus) calculate standard deviation using the
sqrt(1/(n-1)) normalization, which gives a result that is unbiased when
sampling from a
Access by the interpreter prevents array resizing.
Yes, one can use the function, in place of the method but this appears
to require copying the whole array.
If one sets b= a, then that reference can be deleted with del b.
Is there any similar technique for the interpreter?
Colin W.
Python
Christopher Barker wrote:
Colin J. Williams wrote:
Access by the interpreter prevents array resizing.
yup -- resize is really fragile for that reason. It really should be
used quite sparingly.
Personally, I think it should probably only be used when wrapped with
a higher level layer
Basilisk96 wrote:
On Jan 12, 1:36 am, Timothy Hochberg [EMAIL PROTECTED] wrote:
I believe that you need to look at __array_finalize__ and __array_priority__
(and there may be one other thing as well, I can't remember; it's late).
Search for __array_finalize__ and that will probably help get
Basilisk96 wrote:
Hello folks,
In the course of a project that involved heavy use of geometry and
linear algebra, I found it useful to create a Vector subclass of
numpy.matrix (represented as a column vector in my case).
Why not consider a matrix with a shape
of (1, n) as a row vector and
Charles R Harris wrote:
On 3/26/07, *Travis Oliphant* [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED] wrote:
I think that might be the simplest thing, dot overrides subtypes.
BTW,
here is another ambiguity
In [6]: dot(array([[1]]),ones(2))
Alan G Isaac wrote:
On Mon, 26 Mar 2007, Colin J. Williams apparently wrote:
One would expect the iteration over A to return row
vectors, represented by (1, n) matrices.
This is again simple assertion.
**Why** would one expect this?
Some people clearly do not.
One person commented
Bill Baxter wrote:
On 3/26/07, Colin J. Williams [EMAIL PROTECTED] wrote:
Bill Baxter wrote:
This may sound silly, but I really think seeing all those brackets is
what makes it feel wrong. Matlab's output doesn't put it in your
face that your 4 is really a matrix([[4]]), even though that's
Alan G Isaac wrote:
On 3/26/07, Alan G Isaac [EMAIL PROTECTED] wrote:
finds itself in basic conflict with the idea that
I ought to be able to iterate over the objects in an
iterable container. I mean really, does this not feel
wrong? ::
for item in x: print item.__repr__()
Alan G Isaac wrote:
Alan G Isaac wrote:
So this ::
x[1]
matrix([[1, 0]])
feels wrong. (Similarly when iterating across rows.)
Of course I realize that I can just ::
x.A[1]
array([1, 0])
On Sun, 25 Mar 2007, Colin J. Williams apparently wrote:
An array
Alan G Isaac wrote:
On Mon, 26 Mar 2007, Colin J. Williams apparently wrote:
Perhaps things would be clearer if we thought of the
constituent groups of data in a matrix as being themselves
matrices.
This thinking of is what you have suggested before.
You need to explain why
Alan G Isaac wrote:
On Sat, 24 Mar 2007, Charles R Harris apparently wrote:
Yes, that is what I am thinking. Given that there are only the two
possibilities, row or column, choose the only one that is compatible with
the multiplying matrix. The result will not always be a column vector, for
Colin J. Williams wrote:
Alan G Isaac wrote:
On Sat, 24 Mar 2007, Charles R Harris apparently wrote:
Yes, that is what I am thinking. Given that there are only the two
possibilities, row or column, choose the only one that is compatible with
the multiplying matrix. The result
Bill Baxter wrote:
On 3/25/07, Robert Kern [EMAIL PROTECTED] wrote:
Bill Baxter wrote:
I don't know. Given our previous history with convenience functions with
different calling semantics (anyone remember rand()?), I think it probably
will
confuse some people.
I'd really like to see it
Alan G Isaac wrote:
One thing keeps bugging me when I use numpy.matrix.
All this is fine::
x=N.mat('1 1;1 0')
x
matrix([[1, 1],
[1, 0]])
x[1,:]
matrix([[1, 0]])
But it seems to me that I should be able
to extract a matrix row as an array.
This
Alan G Isaac wrote:
Em Dom, 2007-03-25 Ã s 13:07 -0400, Alan G Isaac escreveu:
x[1]
matrix([[1, 0]])
feels wrong. (Similarly when iterating across rows.)
On Sun, 25 Mar 2007, Paulo Jose da Silva e Silva apparently wrote:
I think the point here is that if you are using matrices,
Bill Baxter wrote:
On 3/26/07, Alan G Isaac [EMAIL PROTECTED] wrote:
Em Dom, 2007-03-25 às 13:07 -0400, Alan G Isaac escreveu:
x[1]
matrix([[1, 0]])
feels wrong. (Similarly when iterating across rows.)
On Sun, 25 Mar 2007, Paulo Jose da Silva e Silva apparently wrote:
I think the
Charles R Harris wrote:
On 3/24/07, *Alan G Isaac* [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED] wrote:
On Fri, 23 Mar 2007, Charles R Harris apparently wrote:
the following gives the wrong result:
In [15]: I = matrix(eye(2))
In [16]: I*ones(2)
Out[16]:
Travis Oliphant wrote:
I'm attaching my latest extended buffer-protocol PEP that is trying to
get the array interface into Python. Basically, it is a translation of
the numpy header files into something as simple as possible that can
still be used to describe a complicated block of
zhang yunfeng wrote:
Hi, I'm newbie to Numpy.
When reading tutorials at
http://www.scipy.org/Tentative_NumPy_Tutorial
http://www.scipy.org/Tentative_NumPy_Tutorial, I found a snippet about
addition of two arrays with different shape, Does it make sense? If
array shapes are not same, why
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