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Hi,
This is copied from ipython console.
In [42]: import numpy as np
In [43]: ST = np.empty([], dtype=np.float32)
In [44]: np..append(ST, 10.0)
Out[44]: array([ 3.8603e-38, 1.e+01])
In [45]: np.append(ST, 10.0)
Out[45]: array([ 3.8603e-38, 1.e+01])
In [46]:
On Thu, Dec 18, 2008 at 03:52:23PM +0530, Prashant Saxena wrote:
In [43]: ST = np.empty([], dtype=np.float32)
In [44]: np.append(ST, 10.0)
Out[44]: array([ 3.8603e-38, 1.e+01])
In [45]: np.append(ST, 10.0)
Out[45]: array([ 3.8603e-38, 1.e+01])
How do I solve this?
Thanks
Prashant
From: Gael Varoquaux gael.varoqu...@normalesup.org
To: Discussion of Numerical Python numpy-discussion@scipy.org
Sent: Thursday, 18 December, 2008 4:03:34 PM
Subject: Re: [Numpy-discussion] array not appending
On Thu, Dec
On Thu, Dec 18, 2008 at 04:19:20PM +0530, Prashant Saxena wrote:
How do I solve this?
If you want appending in place you have to use a python list. If you don't
need modification in place, np.append returns an array with the appended
number.
Gaël
ST = np.empty((), dtype=np.float32)
ST = np.append(ST, 10.0)
This works, is it proper way to do so?
One more prob
ST.size returns 2.
Why? I have added only one element.
Prashant
From: Gael Varoquaux gael.varoqu...@normalesup.org
To: Discussion of
Prashant Saxena wrote:
ST = np.empty((), dtype=np.float32)
ST = np.append(ST, 10.0)
This works, is it proper way to do so?
One more prob
ST.size returns 2.
Why? I have added only one element.
You added one element to an array which as already one element. Empty
does not mean that the
On Thu, Dec 18, 2008 at 11:44 AM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Prashant Saxena wrote:
ST = np.empty((), dtype=np.float32)
ST = np.append(ST, 10.0)
This works, is it proper way to do so?
One more prob
ST.size returns 2.
Why? I have added only one element.
You
On 12/18/2008 5:56 AM Prashant Saxena apparently wrote:
ST = np.empty((), dtype=np.float32)
ST = np.append(ST, 10.0)
If you really need to append elements,
you probably want to use a list and
then convert to an array afterwards.
But if you know your array size,
you can preallocate memory and
Sebastian Haase wrote:
On Thu, Dec 18, 2008 at 11:44 AM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Prashant Saxena wrote:
ST = np.empty((), dtype=np.float32)
ST = np.append(ST, 10.0)
This works, is it proper way to do so?
One more prob
ST.size returns 2.
Why? I
On Thursday 18 December 2008 08:00:09 Sebastian Haase wrote:
So the question remains: how to create an array of empty (i.e. 0) size ?
In [1]: from numpy import *
In [2]: x = array( [] )
In [3]: x
Out[3]: array([], dtype=float64)
In [4]: x.size
Out[4]: 0
In [5]: x.shape
Out[5]: (0,)
In [6]:
On Wed, Dec 17, 2008 at 4:28 PM, Robert Kern robert.k...@gmail.com wrote:
On Wed, Dec 17, 2008 at 17:45, Geoffrey Irving irv...@naml.us wrote:
On Wed, Dec 17, 2008 at 3:34 PM, Robert Kern robert.k...@gmail.com wrote:
On Wed, Dec 17, 2008 at 16:51, Geoffrey Irving irv...@naml.us wrote:
On Wed,
Hi David,
On Wed, Dec 17, 2008 at 8:58 PM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Charles R Harris wrote:
The declarations were for the SPARC. Originally I had them up in an
ifdef up top, but I got curious what different machines would do.
I still don't understand what
On Thu, Dec 18, 2008 at 07:58, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
What would be the need for a 0 item array ? If the point is to append
some data without knowing in advance the size, a list is most likely
more adapted to the task. An array which cannot be indexed does not
On Thu, Dec 18, 2008 at 10:01, Geoffrey Irving irv...@naml.us wrote:
On Wed, Dec 17, 2008 at 4:28 PM, Robert Kern robert.k...@gmail.com wrote:
It just seems to me to be another complication that does not provide
any guarantees. You say Currently numpy arrays are either writable or
unwritable,
This is a new project I just released.
I know it is C#, but some of the design and idioms would be nice in
numpy/scipy for working with discrete event simulators, time series, and
event stream processing.
http://code.google.com/p/incremental-statistics/
Hi Chuck,
On Fri, Dec 19, 2008 at 2:15 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
The undefs need to be there when the functions are defined by numpy, so they
only need to be in the same #if block as those definitions. I moved them out
to cover the function declarations also, but
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