Your syntax is not as intuitive as you may think.
Suppose I take a matrix instead
a = np.array([1,2,3,4]).reshape(2,2)
b = (a1) # np.array([[False,True],[True,True]])
How would a[b,np.newaxis] be supposed to work?
Note that other (simple) slices work perfectly with newaxis, such as
Hi,
I'm wondering how to do RGB - HSV conversion in numpy. I found a
couple solutions through stackoverflow, but somehow they can't be used
in my array format. I understand the concept of conversion, but I'm
not that familiar with numpy.
My source buffer format is 'RGBA' sequence. I can take it
On 2011-08-20, at 4:01 AM, He Shiming wrote:
Hi,
I'm wondering how to do RGB - HSV conversion in numpy. I found a
couple solutions through stackoverflow, but somehow they can't be used
in my array format. I understand the concept of conversion, but I'm
not that familiar with numpy.
My
On Sun, Aug 14, 2011 at 09:15:35PM +0200, Charanpal Dhanjal wrote:
Incidentally, I am confused as to why numpy calls the lapack lite
routines - when I call numpy.show_config() it seems to have detected my
ATLAS libraries and I would have expected it to use those.
My rule of thumb is to never
On Fri, Aug 19, 2011 at 11:37 AM, Bruce Southey bsout...@gmail.com wrote:
Hi,
Just some immediate minor observations that are really about trying to
be consistent:
1) Could you keep the display of the NA dtype be the same as the array?
For example, NA dtype is displayed as 'f8' but should
On Fri, Aug 19, 2011 at 4:52 PM, Bruce Southey bsout...@gmail.com wrote:
On Fri, Aug 19, 2011 at 3:05 PM, Mark Wiebe mwwi...@gmail.com wrote:
On Fri, Aug 19, 2011 at 11:44 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
snip
My main peeve is that NA is upper case ;) I suppose
On Sat, Aug 20, 2011 at 2:47 AM, Olivier Verdier zelb...@gmail.com wrote:
Your syntax is not as intuitive as you may think.
Suppose I take a matrix instead
a = np.array([1,2,3,4]).reshape(2,2)
b = (a1) # np.array([[False,True],[True,True]])
How would a[b,np.newaxis] be supposed to work?
Hi All,
What's the best type of array to use for decimal values?
(ie: where I care about precision and want to avoid any possible
rounding errors)
cheers,
Chris
--
Simplistix - Content Management, Batch Processing Python Consulting
- http://www.simplistix.co.uk
On Sat, Aug 20, 2011 at 17:37, Chris Withers ch...@simplistix.co.uk wrote:
Hi All,
What's the best type of array to use for decimal values?
(ie: where I care about precision and want to avoid any possible
rounding errors)
dtype=object
--
Robert Kern
I have come to believe that the whole
On 20/08/2011 15:38, Robert Kern wrote:
On Sat, Aug 20, 2011 at 17:37, Chris Withersch...@simplistix.co.uk wrote:
Hi All,
What's the best type of array to use for decimal values?
(ie: where I care about precision and want to avoid any possible
rounding errors)
dtype=object
Thanks!
What
Hi All,
I've got a tree of nested dicts that at their leaves end in numpy arrays
of identical sizes.
What's the easiest way to persist these to disk so that I can pick up
with them where I left off?
What's the most correct way to do so?
I'm using IPython if that makes things easier...
I had
On Sat, Aug 20, 2011 at 4:49 PM, Chris Withers ch...@simplistix.co.ukwrote:
On 20/08/2011 15:38, Robert Kern wrote:
On Sat, Aug 20, 2011 at 17:37, Chris Withersch...@simplistix.co.uk
wrote:
Hi All,
What's the best type of array to use for decimal values?
(ie: where I care about
On Sat, Aug 20, 2011 at 17:49, Chris Withers ch...@simplistix.co.uk wrote:
On 20/08/2011 15:38, Robert Kern wrote:
On Sat, Aug 20, 2011 at 17:37, Chris Withersch...@simplistix.co.uk wrote:
Hi All,
What's the best type of array to use for decimal values?
(ie: where I care about precision and
On Sat, Aug 20, 2011 at 4:17 PM, David Warde-Farley
warde...@iro.umontreal.ca wrote:
There are functions for this available in scikits.image:
http://stefanv.github.com/scikits.image/api/scikits.image.color.html
Although you may need to reshape it with reshape(arr, (width, height, 4)) or
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