On Tue, Apr 29, 2008 at 12:28 AM, Hoyt Koepke <[EMAIL PROTECTED]> wrote:
> Hello,
>
> I have a quick question that I'm hoping will improve my numpy
> understanding. I noticed some behavior when using float64 to convert
> a matrix type that I didn't expect:
>
>
> In [35]: b1 = array([1.0])
>
> In
On Tue, Apr 29, 2008 at 12:20 AM, Alan G Isaac <[EMAIL PROTECTED]> wrote:
> On Mon, 28 Apr 2008, Christopher Barker apparently wrote:
> > I'm going to try to put down what I think are the key,
> > very simple, questions:
>
> For useful reference, these are now here:
> http://www.scipy.org/MatrixIn
Hello,
I have a quick question that I'm hoping will improve my numpy
understanding. I noticed some behavior when using float64 to convert
a matrix type that I didn't expect:
In [35]: b1 = array([1.0])
In [36]: float64(b1)
Out[36]: 1.0
In [37]: b2 = array([1.0, 2.0])
In [38]: float64(b2)
Out[
2008/4/29 David Cournapeau <[EMAIL PROTECTED]>:
> Stéfan van der Walt wrote:
> >
> > What I meant was: would the plugin "slots" be decided beforehand, or
> > could we manipulate them at runtime? I.e. what I would really enjoy
> > doing is define arbitrary ufuncs and plug them in (not only the
On Mon, 28 Apr 2008, Christopher Barker apparently wrote:
> I'm going to try to put down what I think are the key,
> very simple, questions:
For useful reference, these are now here:
http://www.scipy.org/MatrixIndexing#guidelines>
Cheers,
Alan
___
N
Stéfan van der Walt wrote:
>
> What I meant was: would the plugin "slots" be decided beforehand, or
> could we manipulate them at runtime? I.e. what I would really enjoy
> doing is define arbitrary ufuncs and plug them in (not only the blas
> funcs and a select few others).
>
Do you want to de
On Mon, 28 Apr 2008, Bill Spotz apparently wrote:
> If matrix multiplication in my example is replaced with
> np.dot() in yours, then when IS anything gained by using
> matrices?
When matrix algebra is clearer than array algebra.
But that is not the case for this algorithm.
(Just the opposite,
On Apr 28, 2008, at 10:47 PM, Bill Spotz wrote:
> As for this example, my version should work with a properly
> implemented sparse_matrix A, but the array approach precludes that.
> That is to say, I could convert A to a matrix if it is provided as an
> array, but you could not convert a sparse_ma
On Apr 28, 2008, at 10:15 PM, Alan G Isaac wrote:
> On Mon, 28 Apr 2008, Bill Spotz apparently wrote:
>> http://www.scipy.org/ConjugateGradientExample ... provides
>> one small area where the vector classes would be useful.
>
> Maybe not.
> I posted an alternate version of your algorithm,
> just b
On Mon, 28 Apr 2008, Bill Spotz apparently wrote:
> http://www.scipy.org/ConjugateGradientExample ... provides
> one small area where the vector classes would be useful.
Maybe not.
I posted an alternate version of your algorithm,
just below yours,
sticking very close to your example.
Cheers,
Al
As I was looking at Bill's conjugate gradient posting,
I found myself wondering if there would be a payoff
to an output argument for ``numpy.outer``. (It is fairly
natural to repeatedly recreate the outer product of
the adjusted residuals, which is only needed during a
single iteration.)
Cheers,
On Mon, Apr 28, 2008 at 7:41 PM, Charles R Harris <[EMAIL PROTECTED]>
wrote:
>
>
> On Mon, Apr 28, 2008 at 7:03 PM, Charles R Harris <
> [EMAIL PROTECTED]> wrote:
>
> > Yes, indeed.
> >
> > Ticket #707: numpy.array fails if the input is a list of matrixes (with
> > more then one column).
> >
> > T
On Tue, Apr 29, 2008 at 4:03 AM, Stéfan van der Walt <[EMAIL PROTECTED]> wrote:
>
> What I meant was: would the plugin "slots" be decided beforehand, or
> could we manipulate them at runtime? I.e. what I would really enjoy
> doing is define arbitrary ufuncs and plug them in (not only the blas
>
On Mon, Apr 28, 2008 at 7:03 PM, Charles R Harris <[EMAIL PROTECTED]>
wrote:
> Yes, indeed.
>
> Ticket #707: numpy.array fails if the input is a list of matrixes (with
> more then one column).
>
> The subroutine discover_dimensions in arrayobject.c indexes a matrix with
> a scalar. It is a recursi
Yes, indeed.
Ticket #707: numpy.array fails if the input is a list of matrixes (with more
then one column).
The subroutine discover_dimensions in arrayobject.c indexes a matrix with a
scalar. It is a recursive routine and expects to find the next lower
dimension as it recurses down into the matri
On Apr 24, 2008, at 8:52 PM, Bill Spotz wrote:
On Apr 24, 2008, at 5:45 PM, Timothy Hochberg wrote:
Bill Spotz wrote:
> I have generally thought about this in the context of, say, a
> Krylov-space iterative method, and what that type of interface
would
> lead to the most readable code.
Can
On Mon, 28 Apr 2008, Timothy Hochberg apparently wrote:
> Can you clarify what you
> mean by submatrix extraction? It sounds like you want to be able index into
> an MxN array and get out a 1xN or Mx1 matrix. If that's the case, wouldn't
> the natural way to spell that under the RowVector/Column
oops, typo!
Christopher Barker wrote:
> Gael Varoquaux wrote:
>> I don't know why people are indexing matrices with A[x][y], but they
>> shouldn't.
>
> I think there has been a misunderstanding here. I don't think anyone is
> suggesting that if a coder wants an element of a matrix, that s/he
>
Alan G Isaac wrote:
> I am starting to feel that I have abused my interlocutors.
Not at all -- you have contributed a great deal to the conversation, and
your maintenance of:
> http://www.scipy.org/MatrixIndexing>
Is particularly valuable.
Thank you,
-Chris
--
Christopher Barker, Ph.D.
Oce
A couple suggestions:
wilson wrote:
> I am setting
> the each row using pixel values of each image in some folder.
As an image is generally a 2-d array of pixels, you may want to use a N
X Width X Height 3-d array, rather than flattening each image to a
single row.
> def putrow(myarray,inrow ,
2008/4/28 David Cournapeau <[EMAIL PROTECTED]>:
> On Tue, Apr 29, 2008 at 1:00 AM, Stéfan van der Walt <[EMAIL PROTECTED]>
> wrote:
>
> > I assume that, since you call it a plugin system, it can be done at
> > runtime a-la ctypes?
What I meant was: would the plugin "slots" be decided beforeha
Gael Varoquaux wrote:
> * to use a syntax similar to dictionnaries:
>
> for row in A.rows():
> for col in row.cols()
>
> I actually think this is much better than the code you currently use,
>
> * or implement row and column objects.
>
> The problem in your code is that you do not d
Gael Varoquaux wrote:
> On Fri, Apr 25, 2008 at 01:40:29PM -0400, Alan G Isaac wrote:
>> In contrast, there *is* universal agreement that
>> x[0][0]==x[0,0] is desirable. Or so I've understood the
>> discussion.
> I don't know why people are indexing matrices with A[x][y], but they
> shouldn't.
On Sat, Apr 26, 2008 at 7:12 AM, Alan G Isaac <[EMAIL PROTECTED]> wrote:
> On Fri, 25 Apr 2008, "Travis E. Oliphant" apparently wrote:
> > At this point, I'm leaning in the direction of the
> > RowVector / ColumnVector approach (even if these are not
> > really advertised and just used during inde
> This would be a *fantastic* addition, especially if a user can add his
> own ufuncs written in, say Cython.
I'd like to add some large number to whatever *fantastic* means in terms of +N!
Best,
Matthew
___
Numpy-discussion mailing list
Numpy-discus
On Tue, Apr 29, 2008 at 1:00 AM, Stéfan van der Walt <[EMAIL PROTECTED]> wrote:
> I assume that, since you call it a plugin system, it can be done at
> runtime a-la ctypes?
I am not sure to understand what you mean exactly by a-la ctypes, but
yes, the actual implementation of the npyw_* functio
On Mon, 28 Apr 2008, Hoyt Koepke wrote:
> I may not understand what you are asking, Rich, but I'm
> not sure I agree with Alan. A Gaussian fit to data
> x should fit exactly as well as data fit to ax, a > 0,
> just with a variance a^2 times the original
My point was different.
If you truncate
2008/4/28 David Cournapeau <[EMAIL PROTECTED]>:
> - this could also be used for core numpy, for example ufuncs: if we
> want to start implementing some tight loop with aggressively optimized
> code (SSE, etc...), we could again ship with a default pure C
> implementation, and choose the best
On Mon, 28 Apr 2008, Hoyt Koepke wrote:
> A Gaussian fit to data x should fit exactly as well as data fit to ax, a >
> 0, just with a variance a^2 times the original. The only way this would
> not be true is if:
Hoyt,
This is what I expected, too.
> 1. You are not fitting the variance, but o
Student Intern – Scientific Computing Group 5900 5900-7259
A student internship is available in the National Renewable Energy
Laboratory's (NREL) Scientific Computing Group. NREL is the nation's
primary laboratory for research, development and deployment of
renewable energy and energy efficiency
Wait, I think I see what Alan is saying. When you use a gaussian
approximation on truncated data, the accuracy of the truncation is
very dependent on where in the interval the mean is. If it's near the
edges, the results will be worse. The width of the interval, though,
is a separate factor.
--
I may not understand what you are asking, Rich, but I'm not sure I
agree with Alan. A Gaussian fit to data x should fit exactly as well
as data fit to ax, a > 0, just with a variance a^2 times the original.
The only way this would not be true is if:
1. You are not fitting the variance, but only
Hi,
I've just started working on a prototype for a plugin system for
numpy. The plugin aims at providing a framework for the following user
cases:
- runtime selection of blas/lapack/etc...: instead of harcoding in
the binary one blas/lapack implementation, numpy could choose the SSE
op
Hi Rich,
If your data is truncated at zero, it is not Gaussian (drawn
from a normal). You will notice this when you shrink the
range of values (unless the variance is tiny).
Cheers,
Alan Isaac
___
Numpy-discussion mailing list
Numpy-discussion@sci
Hi All,
On Mon, Apr 28, 2008 at 12:41 PM, Andrea Gavana wrote:
> Hi All,
>
> I have 2 matrices coming from 2 different simulations: the first
> column of the matrices is a date (time) at which all the other results
> in the matrix have been reported (simulation step). In these 2
> matrices, very
AFter the extensive input from folks here last week, and my examination of
alternatives, I accepted the visual appearance of Gaussian curves in our
model. As I check the plots for data errors I find a behavior change when
the x-axis length is 14 rather than 100, and I do not understand why.
Hi All,
I have 2 matrices coming from 2 different simulations: the first
column of the matrices is a date (time) at which all the other results
in the matrix have been reported (simulation step). In these 2
matrices, very often the simulation steps do not coincide, so I just
want to interpolate
2008/4/28 Pearu Peterson <[EMAIL PROTECTED]>:
> Hi,
>
> As far as I am concerned, the issue needs a cosmetic fix of renaming
> pythonxerbla to python_xerbla
Done.
> and the rest of the issue can be postponed to 1.2.
Cheers
Stéfan
___
Numpy-discussion
Hi,
As far as I am concerned, the issue needs a cosmetic fix of renaming
pythonxerbla to python_xerbla and the rest of the issue can be
postponed to 1.2.
Note that this isn't purely a numpy issue. To fix the
issue, system or user provided blas/lapack libraries need to be changed,
we can only give
On Wed, Apr 9, 2008 at 6:34 AM, Stéfan van der Walt <[EMAIL PROTECTED]> wrote:
> Unfortunately, I couldn't get this patch to work, and my time has run
> out. Maybe someone with more knowledge the precedences/order of
> functions during linking can take a look. I don't know how to tell
> the sy
40 matches
Mail list logo
