Tue, 14 Jul 2009 14:45:11 -0400, Pierre GM kirjoitti:
Consider the following code:
a = np.array(zip(np.arange(3)),dtype=[('a',float)]) np.isfinite(a)
NotImplemented
That is, when the input is a structured array, np.isfinite returns an
object of type NotImplementedType. I would have
Might want to look into masked arrays: numpy.ma.array.
a = numpy.array([1,5,4,99])
b = numpy.array([3,7,2,8])
arr = numpy.array([a, b])
masked = numpy.ma.array(arr, mask = arr==99)
masked.mean(axis=0)
masked_array(data = [2.0 6.0 3.0 8.0],
mask = [False False False False],
Simple question. I want to save a complex vector as text in format
real_0 imag_0\n
real_1 imag_1\n
...
I thought to use something like:
np.savetxt ('gen_qpsk.txt', (mod_out.real, mod_out.imag), fmt='%g %g\n')
I need a way to reinterpret the complex data as an array with 2 columns to
make this
Neal Becker ndbecker2 at gmail.com writes:
Simple question. I want to save a complex vector as text in format
real_0 imag_0\n
real_1 imag_1\n
...
I thought to use something like:
np.savetxt ('gen_qpsk.txt', (mod_out.real, mod_out.imag), fmt='%g %g\n')
I need a way to reinterpret
On Jul 15, 2009, at 4:23 AM, Pauli Virtanen wrote:
Tue, 14 Jul 2009 14:45:11 -0400, Pierre GM kirjoitti:
Consider the following code:
a = np.array(zip(np.arange(3)),dtype=[('a',float)]) np.isfinite(a)
NotImplemented
Seems like a bug. As I understand, NotImplemented is intended to be
Is it straightforward to generate a record array (preferably a standard
numpy.ndarray, not the numpy.rec variant) where some named fields
contain pairs of numbers, for example:
named field pos contains pairs of floats
named field rot contains floats
Any pointers to relevant documentation would
In article rowen-1ff89a.11051515072...@news.gmane.org,
Russell E. Owen ro...@uw.edu wrote:
Is it straightforward to generate a record array (preferably a standard
numpy.ndarray, not the numpy.rec variant) where some named fields
contain pairs of numbers, for example:
named field pos
On Wed, Jul 15, 2009 at 13:05, Russell E. Owenro...@uw.edu wrote:
Is it straightforward to generate a record array (preferably a standard
numpy.ndarray, not the numpy.rec variant) where some named fields
contain pairs of numbers, for example:
named field pos contains pairs of floats
named
Suppose I have a record array where one of the fields is a nested array:
from numpy import *
desc = dtype([('point', 'i4', 3), ('unimportant', 'S3')])
a = array([((1,2,3), 'foo'), ((7,8,9), 'bar')], dtype=desc)
a
array([([1, 2, 3], 'foo'), ([7, 8, 9], 'bar')],
dtype=[('point', 'i4',
On Wed, Jul 15, 2009 at 14:19, Vebjorn Ljosavebj...@ljosa.com wrote:
Suppose I have a record array where one of the fields is a nested array:
from numpy import *
desc = dtype([('point', 'i4', 3), ('unimportant', 'S3')])
a = array([((1,2,3), 'foo'), ((7,8,9), 'bar')], dtype=desc)
a
On Jul 15, 2009, at 15:28, Robert Kern wrote:
Generally, scalars are never views. a[0] pulls out a record scalar.
Thank you, that explains it. I should have noticed that a[0] was just
a tuple.
Vebjorn
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On Wed, Jul 15, 2009 at 14:38, Pauli Virtanenpav...@iki.fi wrote:
On 2009-07-15, Robert Kern robert.k...@gmail.com wrote:
On Wed, Jul 15, 2009 at 14:19, Vebjorn Ljosavebj...@ljosa.com wrote:
Suppose I have a record array where one of the fields is a nested array:
from numpy import *
desc
Here's an interesting problem, and it might've already been solved by
some of you folks that do image processing:
Suppose I have an 8-bit integer 2-d array, X, and I want a 256x256
matrix that tells me how many times a pixel value v was horizontally
(along second dimension) adjacent to a
On Jul 15, 2009, at 17:51, David Warde-Farley wrote:
Suppose I have an 8-bit integer 2-d array, X, and I want a 256x256
matrix that tells me how many times a pixel value v was horizontally
(along second dimension) adjacent to a pixel value b
Is there an efficient way to do such a thing with
Hi,
I'm using a C api to create numpy array
I create them in my C as follow:
np_ow = (PyArrayObject *)PyArray_SimpleNew(4, dims, NPY_DOUBLE);
np_osfc = (PyArrayObject *)PyArray_SimpleNew(3, dims, NPY_DOUBLE);
np_ospc = (PyArrayObject *)PyArray_SimpleNew(3, dims, NPY_DOUBLE);
On 15-Jul-09, at 6:40 PM, Vebjorn Ljosa wrote:
On Jul 15, 2009, at 17:51, David Warde-Farley wrote:
Suppose I have an 8-bit integer 2-d array, X, and I want a 256x256
matrix that tells me how many times a pixel value v was horizontally
(along second dimension) adjacent to a pixel value b
I think i can answer my own question
I need to return Py_BuildValue((NNN))
C.
On Jul 15, 2009, at 4:27 PM, Charles سمير Doutriaux wrote:
Hi,
I'm using a C api to create numpy array
I create them in my C as follow:
np_ow = (PyArrayObject *)PyArray_SimpleNew(4, dims, NPY_DOUBLE);
On Jul 15, 2009, at 19:37, David Warde-Farley wrote:
Just curious - I noticed in the comments that you (or someone) said
there's a problem in the original paper's definition. Do you have any
idea which feature that concerned?
The comments in our previous (Matlab) version of CellProfiler [1]
The SciPy conference committee is pleased to announce the schedule of the
conference:
http://conference.scipy.org/schedule
This year’s program is very rich. In order to limit the number of
interesting talks that we had to turn down, we decided to reduce the
length of talks. Although this results
Hi all,
I sure wish I was able to attend this year's event.
I'm wondering, and really hoping, if/that the lectures will be recorded and
then posted for the whole community's benefit?
thanks,
~Peter
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On Jul 13, 2009, at 1:54 PM, Ralf Gommers wrote:
On Sun, Jul 12, 2009 at 1:24 PM, Citi, Luca lc...@essex.ac.uk wrote:
That is what I thought at first, but then what is the difference
between
array_types and scalar_types? Function signature is:
*find_common_type(array_types,
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