On Sat, Jan 14, 2012 at 2:12 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
This sort of makes sense, but is it the 'correct' behavior?
In [20]: zeros(2, 'S')
Out[20]:
array(['', ''],
dtype='|S1')
I think of numpy strings as raw fixed-length byte arrays (since, well,
that's
On 15/01/12 00:53, Nathan Faggian wrote:
Hi,
I am finding it less than useful to have the negative index wrapping
on nd-arrays. Here is a short example:
import numpy as np
a = np.zeros((3, 3))
a[:,2] = 1000
print a[0,-1]
print a[0,-1]
print a[-1,-1]
In all cases 1000 is printed
On Sat, Jan 14, 2012 at 11:53 PM, Nathan Faggian
nathan.fagg...@gmail.com wrote:
Hi,
I am finding it less than useful to have the negative index wrapping on
nd-arrays. Here is a short example:
import numpy as np
a = np.zeros((3, 3))
a[:,2] = 1000
print a[0,-1]
print a[0,-1]
print
On Sun, Jan 15, 2012 at 3:15 AM, Nathaniel Smith n...@pobox.com wrote:
On Sat, Jan 14, 2012 at 2:12 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
This sort of makes sense, but is it the 'correct' behavior?
In [20]: zeros(2, 'S')
Out[20]:
array(['', ''],
dtype='|S1')
I think
Counting the Colors of RGB-Image,
nameit im0 with im0.shape = 2500,3500,3
with this code:
tab0 = zeros( (256,256,256) , dtype=int)
tt = im0.view()
tt.shape = -1,3
for r,g,b in tt:
tab0[r,g,b] += 1
Question:
Is there a faster way in numpy to get this result?
MfG elodw
On Sun, Jan 15, 2012 at 10:45 AM, a...@pdauf.de wrote:
Counting the Colors of RGB-Image,
nameit im0 with im0.shape = 2500,3500,3
with this code:
tab0 = zeros( (256,256,256) , dtype=int)
tt = im0.view()
tt.shape = -1,3
for r,g,b in tt:
tab0[r,g,b] += 1
Question:
Is there a faster
im_flat = im0[...,0]*65536 + im[...,1]*256 +im[...,2]
colours = np.unique(im_flat)
Nadav
From: numpy-discussion-boun...@scipy.org [numpy-discussion-boun...@scipy.org]
On Behalf Of Tony Yu [tsy...@gmail.com]
Sent: 15 January 2012 18:03
To: Discussion of
Hello all,
Is there a recommended (and ideally cross platform)
way to load the frames of a QuickTime movie (*.mov
file) in Python as NumPy arrays? I'd be happy with
an iterator based approach, but random access to
the frames would be a nice bonus.
My aim is to try some image analysis in Python,
On Sun, Jan 15, 2012 at 19:10, Peter
numpy-discuss...@maubp.freeserve.co.uk wrote:
Hello all,
Is there a recommended (and ideally cross platform)
way to load the frames of a QuickTime movie (*.mov
file) in Python as NumPy arrays? I'd be happy with
an iterator based approach, but random
