On 6/20/06, Bill Baxter [EMAIL PROTECTED] wrote:
I think that one's on the NumPy for Matlab users, no?
http://www.scipy.org/NumPy_for_Matlab_Users
import numpy as num
a = num.arange (10).reshape(2,5)
a
array([[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9]])
v = num.rand(5)
v
array([
On 6/20/06, Bill Baxter [EMAIL PROTECTED] wrote:
a[:,num.where(v0.5)[0]]
array([[1, 2, 4],
[6, 7, 9]])
I'll put that up on the Matlab-Numpy page.
That's a great addition to the Matlab to Numpy page.
But it only works if v is a column vector. If v is a row vector, then
where(v.A
The NumPy for Matlab Users page suggests mat(a.A * b.A) for
element-by-element matrix multiplication. I think it would be helpful
to also include multiply(a, b).
a.*b
mat(a.A * b.A) or
multiply(a, b)
___
Numpy-discussion mailing list
On 6/21/06, Robert Kern [EMAIL PROTECTED] wrote:
Keith Goodman wrote:
The NumPy for Matlab Users page suggests mat(a.A * b.A) for
element-by-element matrix multiplication. I think it would be helpful
to also include multiply(a, b).
a.*b
mat(a.A * b.A) or
multiply(a, b
On 6/22/06, Robert Kern [EMAIL PROTECTED] wrote:
Keith Goodman wrote:
How do I seed rand and randn?
If you can, please use the .rand() and .randn() methods on a RandomState
object
which you can initialize with whatever seed you like.
In [1]: import numpy as np
rs
In [2]: rs
How do I make a NxN diagonal matrix with a Nx1 column vector x along
the diagonal?
Using Tomcat but need to do more? Need to support web services, security?
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On 6/28/06, Travis Oliphant [EMAIL PROTECTED] wrote:
Keith Goodman wrote:
On 6/28/06, Pau Gargallo [EMAIL PROTECTED] wrote:
i don't know why 'where' is returning matrices.
if you use:
idx = where(y.A 0.5)[0]
everything will work fine (I guess)
What about the second
On 6/28/06, Travis Oliphant [EMAIL PROTECTED] wrote:
This should be better behaved now in SVN. Thanks for the reports.
I'm impressed by how quickly features are added and bugs are fixed.
And by how quick it is to install a new version of numpy.
Thank you.
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On 6/29/06, Alan G Isaac [EMAIL PROTECTED] wrote:
On Thu, 29 Jun 2006, Travis Oliphant apparently wrote:
Please make any comments or voice major concerns
A rather minor issue, but I would just like to make sure
that a policy decision was made not to move to a float
default for identity(),
On 6/29/06, Bill Baxter [EMAIL PROTECTED] wrote:
I also find the int behavior of these functions strange.
+1 float default (or double)
Oh, wait. Which do I want, float or double? What does rand, eigh,
lstsq, etc return?
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On 6/29/06, Alan G Isaac [EMAIL PROTECTED] wrote:
On Thu, 29 Jun 2006, Travis Oliphant apparently wrote:
Please make any comments or voice major concerns
A rather minor issue, but I would just like to make sure
that a policy decision was made not to move to a float
default for identity(),
On 6/30/06, Sasha [EMAIL PROTECTED] wrote:
On 6/30/06, Fernando Perez [EMAIL PROTECTED] wrote:
...
Besides, decent unit tests will catch these problems. We all know
that every scientific code in existence is unit tested to the smallest
routine, so this shouldn't be a problem for anyone.
When an array is printed, the numbers line up in nice columns (if
you're using a fixed-width font):
array([[0, 0],
[0, 0]])
But for matrices the columns do not line up:
matrix([[0, 0],
[0, 0]])
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On 6/30/06, David M. Cooke [EMAIL PROTECTED] wrote:
On Fri, 30 Jun 2006 13:37:01 -0700
Keith Goodman [EMAIL PROTECTED] wrote:
When an array is printed, the numbers line up in nice columns (if
you're using a fixed-width font):
array([[0, 0],
[0, 0]])
But for matrices
On 7/6/06, Sven Schreiber [EMAIL PROTECTED] wrote:
Maybe you guys as the developers of numpy should really make up your
mind about the future of matrices in numpy. Either it's supported, then
eventually I would expect matrix versions of ones, zeros, eye, for
example. (Although eye().M would
On 7/6/06, Travis Oliphant [EMAIL PROTECTED] wrote:
Mathew Yeates wrote:
Not working.
A[row,all_dates == 10] = -1 where all_dates is a matrix with column
length of 14 [[960111,..,..
and A is a matrix with same column length
I get
IndexError: arrays used as indices must be of integer type
On 7/6/06, Mathew Yeates [EMAIL PROTECTED] wrote:
okay, I went back to the binary windows distrib. Based on Keths code I wrote
print numpy.asmatrix(all_dates == start_dates[row],dtype=int)
[[0 0 0 0 0 0 0 0 0 0 0 1 0 0]]
[row,numpy.asmatrix(all_dates == start_dates[row],dtype=int)] = -1
On 7/7/06, Ed Schofield [EMAIL PROTECTED] wrote:
I'd like to help to make matrices more usable. Tell me what you want,
and I'll work on some patches.
I can't pass up an offer like that.
DIAG
diag(M) returns an array. It would be nice if diag(M) returned
asmatrix(diag(M)).T. It would also
On 7/9/06, Bill Baxter [EMAIL PROTECTED] wrote:
I got numpy compiled according the the instruction on the Wiki, but is there
some way to try it out without wiping out my stable install of 0.9.8?
I tried modifying my PYTHONPATH to put the new numpy build directory first,
but 'import numpy'
On 7/9/06, Bill Baxter [EMAIL PROTECTED] wrote:
Thanks for the reply Keith.
On 7/10/06, Keith Goodman [EMAIL PROTECTED] wrote:
One quick hack is to install the new numpy somewhere else and then
rename the directory containing 0.9.8 to numpySTOP. Then you don't
have to worry about
On 7/7/06, Travis Oliphant [EMAIL PROTECTED] wrote:
a numpy.matlib module was started to store matrix versions of the
standard array-creation functions and mat was re-labeled to asmatrix
so that a copy is not made by default.
Holy crap! It works. This is great. Thank you.
import
On 7/11/06, David Huard [EMAIL PROTECTED] wrote:
2006/7/11, JJ [EMAIL PROTECTED]:
1) is it possible to get the function unique() to work with matrices,
perhaps
with a unique_rows() function to work with matrices of more than one
column?
The problem is that applying unique to different
On 7/15/06, Steve Lianoglou [EMAIL PROTECTED] wrote:
1) Did you install ubuntu by way of Parallels, or are you running
linux full steam
Yes, it is a full steam dual boot system. My default boot is Ubuntu.
2) If you did install ubuntu alongside/over/whatever mac os x and
didn't use parallels
On 7/17/06, Travis Oliphant [EMAIL PROTECTED] wrote:
Keith Goodman wrote:
How do you display all of the rows of a matrix?
help(numpy.set_prinoptions)
That is great! Now I can change the precision as well. Eight
significant figures is too precise for me.
Does anyone out there save
Every time I want to make a diagonal matrix from a vector I have to do
a google search. So I'm with you Sven:
diag(NxN matrix) should return a Nx1 matrix
diag(Nx1 or 1xN matrix) should return a NxN matrix
instead of the current behavior:
diag(NxN matrix) returns an array
diag(Nx1 matrix)
On 8/15/06, David Grant [EMAIL PROTECTED] wrote:
My idea is (if I have time) to write an eigs-like function in python
that will only perform a subset of what Matlab's eigs does for. It
will, for example, compute a certain number of eigenvalues and
eigenvectors for a real, sparse, symmetric
On 8/26/06, Bill Baxter [EMAIL PROTECTED] wrote:
On 8/26/06, Travis Oliphant [EMAIL PROTECTED] wrote:
I've come up with adding the functions (not methods at this point)
deletefrom
insertinto
delete and insert really would be better. The current insert
function seems inaptly
I have a very long list that contains many repeated elements. The
elements of the list can be either all numbers, or all strings, or all
dates [datetime.date].
I want to convert the list into a matrix where each unique element of
the list is assigned a consecutive integer starting from zero.
On 8/29/06, Tim Hochberg [EMAIL PROTECTED] wrote:
Keith Goodman wrote:
I have a very long list that contains many repeated elements. The
elements of the list can be either all numbers, or all strings, or all
dates [datetime.date].
I want to convert the list into a matrix where each
On 8/29/06, Torgil Svensson [EMAIL PROTECTED] wrote:
something like this?
def list2index(L):
uL=sorted(set(L))
idx=dict((y,x) for x,y in enumerate(uL))
return uL,asmatrix(fromiter((idx[x] for x in L),dtype=int))
Wow. That's amazing. Thank you.
On 8/29/06, Mathew Yeates [EMAIL PROTECTED] wrote:
I have an M by N array of floats. Associated with the columns are
character labels
['a','b','b','c','d','e','e','e'] note: already sorted so duplicates
are contiguous
I want to replace the 2 'b' columns with the sum of the 2 columns.
In what order would you like argsort to sort the values -inf, nan, inf?
In numpy 1.0b1 nan is always left where it began:
EXAMPLE 1
x
matrix([[ inf],
[ -inf],
[ nan]])
x[x.argsort(0),:]
matrix([[ -inf],
[
On 9/19/06, A. M. Archibald [EMAIL PROTECTED] wrote:
On 19/09/06, Tim Hochberg [EMAIL PROTECTED] wrote:
Keith Goodman wrote:
In what order would you like argsort to sort the values -inf, nan, inf?
Ideally, -inf should sort first, inf should sort last and nan should
raise an exception
I like the salutation of the letter below: Please read this letter
attentively!
Why does so much spam make it through the sourceforge filters?
Or maybe they only let through the very good deals. You will earn
from 1500 up to 3000 USD per week, working only some hours per day.
On Wed, 20 Sep
On 10/9/06, Eric Emsellem [EMAIL PROTECTED] wrote:
thanks for the pointer to pida. I installed it successfully but I didn't
manage to
makeit really work [snip]
I was excited to see that pida can use meld. But when I try to do a
diff, pida complains that it cannot find meldembed.py. Has
On 10/11/06, Keith Goodman [EMAIL PROTECTED] wrote:
This works:
M.asmatrix(['a', 'b', None])
matrix([[a, b, None]], dtype=object)
But this doesn't:
M.asmatrix(['a', 'b', None, 'c'])
TypeError: expected a readable buffer object
M.__version__
'1.0rc1'
It also doesn't work
On 8/15/06, David Grant [EMAIL PROTECTED] wrote:
My idea is (if I have time) to write an eigs-like function in python
that will only perform a subset of what Matlab's eigs does for. It
will, for example, compute a certain number of eigenvalues and
eigenvectors for a real, sparse, symmetric
On 10/22/06, Aric Hagberg [EMAIL PROTECTED] wrote:
On Sat, Oct 21, 2006 at 02:05:42PM -0700, Keith Goodman wrote:
Did you, or anybody else on the list, have any luck making a numpy
version of eigs?
I made a start at an ARPACK wrapper, see
http://projects.scipy.org/scipy/scipy/ticket/231
On 10/23/06, Travis Oliphant [EMAIL PROTECTED] wrote:
Keith Goodman wrote:
On 10/20/06, JJ [EMAIL PROTECTED] wrote:
My suggestion is to
create a new attribute, such as .AR, so that the
following could be used: M[K.AR,:]
It would be even better if M[K,:] worked. Would such a patch
On 10/27/06, jeremito [EMAIL PROTECTED] wrote:
I am using a = numpy.linalg.eig(A) to get the eigenvalues and
eigenvectors. I am interested only in the largest eigenvalue so I
would like to sort the first element of a. But if I do that, I won't
know what is the associated eigenvector. Is
On 11/8/06, izak marais [EMAIL PROTECTED] wrote:
Sorry if this is an obvious question, but what is the easiest way to
multiply matrices in numpy? Suppose I want to do A=B*C*D. The ' * ' operator
apparently does element wise multiplication, as does the 'multiply' ufunc.
All I could find was
I accidentally wrote a unit test using int32 instead of float64 and
ran into this problem:
x = M.matrix([[1, 2, 3]])
x[0,1] = M.nan
x
matrix([[1, 0, 3]]) --- Got 0 instead of NaN
But this, of course, works:
x = M.matrix([[1.0, 2.0, 3.0]])
x[0,1] = M.nan
x
matrix([[ 1.,
On 11/11/06, Stefan van der Walt [EMAIL PROTECTED] wrote:
On Sat, Nov 11, 2006 at 10:40:22AM -0800, Keith Goodman wrote:
I accidentally wrote a unit test using int32 instead of float64 and
ran into this problem:
x = M.matrix([[1, 2, 3]])
x[0,1] = M.nan
x
matrix([[1, 0, 3
x.min() and x.max() depend on the ordering of the elements:
x = M.matrix([[ M.nan, 2.0, 1.0]])
x.min()
nan
x = M.matrix([[ 1.0, 2.0, M.nan]])
x.min()
1.0
If I were to try the latter in ipython, I'd assume, great, min()
ignores NaNs. But then the former would be a bug in my program.
Is this
On 11/11/06, Robert Kern [EMAIL PROTECTED] wrote:
Barring a clever solution (at least cleverer than I feel like being
immediately), the way to solve this would be to check for nans in the array
and
deal with them separately (or simply ignore them in the case of x.min()).
However, this
On 11/11/06, Robert Kern [EMAIL PROTECTED] wrote:
Keith Goodman wrote:
How about a nanmin() function?
Already there.
In [2]: nanmin?
Type: function
Base Class: type 'function'
Namespace: Interactive
File:
/Library/Frameworks/Python.framework/Versions/2.5/lib
On 11/12/06, George Sakkis [EMAIL PROTECTED] wrote:
This must be pretty trivial but I couldn't find it in the docs: what's
the numpythonic way to find the (first) index of an element, i.e. the
equivalent to list.index ?
Does where work?
x = M.matrix([[1, 2], [3, 4]])
x
matrix([[1, 2],
[3, 4]])
y = M.matrix([[5], [6]])
y
matrix([[5],
[6]])
idx = M.where(x[:,0].A 100)[0]
idx
array([0, 1])
x[idx,0] # This works
matrix([[1],
[3]])
x[idx,0] = y# But this doesn't work. How can I
On 11/12/06, Keith Goodman [EMAIL PROTECTED] wrote:
x = M.matrix([[1, 2], [3, 4]])
x
matrix([[1, 2],
[3, 4]])
y = M.matrix([[5], [6]])
y
matrix([[5],
[6]])
idx = M.where(x[:,0].A 100)[0]
idx
array([0, 1])
x[idx,0] # This works
matrix([[1
Is anybody interested in making x.max() and nanmax() behave the same
for matrices, except for the NaN part? That is, make
numpy.matlib.nanmax return a matrix instead of an array.
Example
=
import numpy.matlib as M
x = M.rand(3,2)
x.max(0)
matrix([[ 0.91749823, 0.94942954]])
On 11/14/06, Jeff Strunk [EMAIL PROTECTED] wrote:
Good afternoon,
We will be performing the migration of this mailing list from Sourceforge to
SciPy on Thursday at 2pm central.
After this time, the new mailing list address will be
[EMAIL PROTECTED] . Any mail sent to the Sourceforge address
On 11/14/06, Erin Sheldon [EMAIL PROTECTED] wrote:
As an aside, your database is running on a local disk, right, so
the overehead of retrieving data is minimized here?
For my tests I think I am data retrieval limited because I
get exactly the same time for the equivalent of retrieve1
and
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