Hi!
On 21. aug. 2011, at 00.18, Chris Withers wrote:
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?
Probably giving them names like
Hi
My bad. Very sorry about that, guys.
There's a patch for this here:
https://github.com/walshb/numpy/tree/fix_np_lookfor_segv
And I submitted a pull request. I'll add something to the tests too when I
have a little more time.
Cheers
Ben
--
Message: 3
On Sat, 20 Aug 2011 16:18:55 -0700, Chris Withers wrote:
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?
Depends on your requirements.
You can use
Since the result is one-dimensional after using boolean indexing you
can always do:
a[b][:, np.newaxis]
array([[2],
[3],
[4]])
a[b][np.newaxis, :]
array([[2, 3, 4]])
//Torgil
On Sat, Aug 20, 2011 at 10:17 PM, Benjamin Root ben.r...@ou.edu wrote:
On Sat, Aug 20, 2011 at 2:47
On Sunday, August 21, 2011, Torgil Svensson torgil.svens...@gmail.com
wrote:
Since the result is one-dimensional after using boolean indexing you
can always do:
a[b][:, np.newaxis]
array([[2],
[3],
[4]])
a[b][np.newaxis, :]
array([[2, 3, 4]])
//Torgil
Correct, which I
On Sat, Aug 20, 2011 at 4:17 PM, David Warde-Farley
warde...@iro.umontreal.ca wrote:
Thanks, I'll check it out.
--
Best regards,
He Shiming
Hi again. Project scikits.image appeared to be difficult to install
under ubuntu. It complains about something related to OpenCV, and I
didn't see
