Fri, 03 Sep 2010 08:53:00 +0300, Åsmund Hjulstad wrote:
I have a f2py wrapped fortran extension, compiled using gcc-mingw32
(v.4.5.0), numpy 1.5, Python 2.7, where I am experiencing the strangest
behaviour. It appears that loading pygtk breaks my fortran extension.
Be aware that import gtk
Can someone help me replace a slow expression with a faster one based on
tensordot? I've read the documentation and I'm still confused.
I have two matrices b and d. b is n x m and d is m x m. I want to replace
the expression
bdb = zeros(n,'d')
for i in xrange(n):
bdb[i,:] =
Sorry for the rapid repost, but I thought of a much easier way to ask the
question I asked a few minutes ago.
I have two matrices, A and B, both of which are n x m. n is big (~10,000),
and m is small (~10).
I want to take the product AB such that I get a length-n vector, as in:
AB =
On Fri, Sep 3, 2010 at 7:48 AM, Rick Muller rpmul...@gmail.com wrote:
Sorry for the rapid repost, but I thought of a much easier way to ask the
question I asked a few minutes ago.
I have two matrices, A and B, both of which are n x m. n is big (~10,000),
and m is small (~10).
I want to take
Josef and Pauli,
Wow, you guys rock! I'm amazed you could pull that out so quickly.
I thank you, and PyQuante thanks you (hopefully this will make for faster
density functional theory grids).
Rick
On Fri, Sep 3, 2010 at 5:59 AM, josef.p...@gmail.com wrote:
On Fri, Sep 3, 2010 at 7:48 AM,
Hello,
I'd like to know if there is a convenient routine to write recarrays
into cvs files, with the first line of the file being the name of the
fields.
Thanks,
Guillaume
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Great, Thank you. I also found out about csv2rec. I've been missing
these two a lot.
Le 03/09/2010 15:35, Pierre GM a écrit :
On Sep 3, 2010, at 3:32 PM, Guillaume Chérel wrote:
Hello,
I'd like to know if there is a convenient routine to write recarrays
into cvs files, with the first
On Fri, Sep 3, 2010 at 8:35 AM, Pierre GM pgmdevl...@gmail.com wrote:
On Sep 3, 2010, at 3:32 PM, Guillaume Chérel wrote:
Hello,
I'd like to know if there is a convenient routine to write recarrays
into cvs files, with the first line of the file being the name of the
fields.
Excerpts from Guillaume Chérel's message of Fri Sep 03 09:32:02 -0400 2010:
Hello,
I'd like to know if there is a convenient routine to write recarrays
into cvs files, with the first line of the file being the name of the
fields.
Thanks,
Guillaume
Yes, you can do this with the
2010/9/3 Guillaume Chérel guillaume.c.che...@gmail.com:
Great, Thank you. I also found out about csv2rec. I've been missing
these two a lot.
Some other handy rec functions in mlab
http://matplotlib.sourceforge.net/examples/misc/rec_groupby_demo.html
On Fri, Sep 3, 2010 at 8:50 AM, Benjamin Root ben.r...@ou.edu wrote:
Why is this function in matplotlib? Wouldn't it be more useful in numpy?
I tend to add stuff I write to matplotlib. mlab was initially a
repository of matlab-like functions that were not available in numpy
(load, save,
There just *has* to be a better way of doing this. I want to cut off small
values of a vector, and I'm currently doing something like:
for i in xrange(n):
if abs(A[i]) tol: A[i] = 0
Which is slow, since A can be really long. Is there a way to write a Ufunc
that would do something like this
On Fri, Sep 3, 2010 at 9:39 AM, Rick Muller rpmul...@gmail.com wrote:
There just *has* to be a better way of doing this. I want to cut off small
values of a vector, and I'm currently doing something like:
for i in xrange(n):
if abs(A[i]) tol: A[i] = 0
Which is slow, since A can be
Sweet! Guess I need to learn more about numpy indexing: this is pretty
powerful.
On Fri, Sep 3, 2010 at 10:42 AM, Keith Goodman kwgood...@gmail.com wrote:
On Fri, Sep 3, 2010 at 9:39 AM, Rick Muller rpmul...@gmail.com wrote:
There just *has* to be a better way of doing this. I want to cut off
Hello,
I recently had to get data from a mysql database into a recarray. The result
was not very long but nontrivial to figure out:
def recarray_from_db(db, command):
executes a command and turns the results into a numpy recarray
(record array)
cursor = db.cursor()
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