Dear Sirs,
I'm trying to use Numpy to solve a speed problem with Python, I need to
perform agglomerative clustering as a first step to k-means clustering.
My problem is that I'm using a very large list in Pyhton and the script is
taking more than 9minutes to process all the information, so I'm try
On 4/13/07, Bruno Santos <[EMAIL PROTECTED]> wrote:
Dear Sirs,
I'm trying to use Numpy to solve a speed problem with Python, I need to
perform agglomerative clustering as a first step to k-means clustering.
My problem is that I'm using a very large list in Pyhton and the script is
taking more th
I try to use the expression as you said, but I'm not getting the desired
result,
My text file look like this:
# num rows=115 num columns=2634
AbassiM.txt 0.033023 0.033023 0.033023 0.165115 0.4623210.00
AgricoleW.txt 0.038691 0.038691 0.038691 0.232147 0.5416760.215300
AliR.txt 0.0418
Bruno Santos wrote:
> I try to use the expression as you said, but I'm not getting the desired
> result,
> My text file look like this:
>
> # num rows=115 num columns=2634
> AbassiM.txt 0.033023 0.033023 0.033023 0.165115 0.4623210.00
> AgricoleW.txt 0.038691 0.038691 0.038691 0.232147 0.
Finally I was able to read the data, by using the command you sair with some
small changes:
matrix = numpy.array([[float(x) for x in line.split()[1:]] for line in
vecfile])
But that doesn't solve my speed problem, now instead of taking 40seconds in
the slow step, takes 1min ant 10seconds :(
The s
On 4/18/07, Bruno Santos <[EMAIL PROTECTED]> wrote:
Finally I was able to read the data, by using the command you sair with
some small changes:
matrix = numpy.array([[float(x) for x in line.split()[1:]] for line in
vecfile])
But that doesn't solve my speed problem, now instead of taking 40secon
Bruno Santos wrote:
> Finally I was able to read the data, by using the command you sair with
> some small changes:
> matrix = numpy.array([[float(x) for x in line.split()[1:]] for line in
> vecfile])
it doesn't sound like you're concerned about the speed of reading the
files, but you can still
On 4/18/07, [EMAIL PROTECTED]
<[EMAIL PROTECTED]> wrote:
> --
>
> Message: 5
> Date: Wed, 18 Apr 2007 09:11:32 -0700
> From: Christopher Barker <[EMAIL PROTECTED]>
> Subject: Re: [Numpy-discussion] Help using numPy to create a very
>
On Wed, Apr 18, 2007 at 06:09:38PM -0500, Nick Fotopoulos wrote:
> Devs, is there any possibility of moving/copying pylab.load to numpy?
+1
Gaël
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
http://projects.scipy.org/mailman/listinfo/num
Nick Fotopoulos wrote:
> Devs, is there any possibility of moving/copying pylab.load to numpy?
> I don't see anything in the source that requires the rest of
> matplotlib. Among convenience functions, I think that this function
> ranks pretty highly in convenience.
>
I'm supportive of this. B
On 4/19/07, Travis Oliphant <[EMAIL PROTECTED]> wrote:
> Nick Fotopoulos wrote:
> > Devs, is there any possibility of moving/copying pylab.load to numpy?
> > I don't see anything in the source that requires the rest of
> > matplotlib. Among convenience functions, I think that this function
> > ran
Lisandro Dalcin wrote:
> I am also +1 on this, but this functionality should be implemented in
> C, I think.
well, maybe.
> I've just tested numpy.fromfile('name.txt', sep=' ')
> against pylab.load('name.txt') for a 35MB text file, the number are:
>
> numpy.fromfile: 2.66 sec.
> pylab.load: 16
I think it would be a great idea to have pylab.load in numpy. It also seems
to be a lot faster than scipy.io.
One thing that is very nice about pylab.load is that it can read-in dates.
However, it can't, as far a I know, handle other non-float data.
I played around with python's csv module and py
Whats wrong with scipy.io.read_array?
Am 19.04.2007 um 15:50 schrieb Lisandro Dalcin:
On 4/19/07, Travis Oliphant <[EMAIL PROTECTED]> wrote:
Nick Fotopoulos wrote:
Devs, is there any possibility of moving/copying pylab.load to numpy?
I don't see anything in the source that requires the rest o
It seems to be a lot slower than pylab.load for large arrays. Also, it
doesn't handle dates.
Vincent
On 4/22/07 10:33 AM, "Markus Rosenstihl"
<[EMAIL PROTECTED]> wrote:
> Whats wrong with scipy.io.read_array?
>
> Am 19.04.2007 um 15:50 schrieb Lisandro Dalcin:
>
>> On 4/19/07, Travis Oliphant
15 matches
Mail list logo
