I was just about to respond that _substantial_ support by a non-
profit best describes Travis Oliphant's many contributions through
BYU. I see now that BYU/SciPy/NumPy has been nominated ... excellent!
It might be appropriate for people from various constituencies to
comment...
On 4/1/07, Christopher Hanley [EMAIL PROTECTED] wrote:
The following test fails on a Solaris 8 system:
==
FAIL: check_basic (numpy.core.tests.test_multiarray.test_clip)
Sun hardware is big endian. To be specific, this test was done on a Sun
Ultra 10. I don't have access to a PPC right now. I can check tomorrow
once I am in the office.
Chris
Hmm, Sun hardware is big endian, no? I wonder what happens on PPC? I
don't see any problems here on Athlon64.
El ds 31 de 03 del 2007 a les 21:54 -0600, en/na Travis Oliphant va
escriure:
I'm going to be tagging the tree for the NumPy 1.0.2 release tomorrow
evening in preparation for the release on Monday. I've closed several
bugs. Are there any show-stoppers remaining to be fixed?
Mmm... PyTables
Just asking.
In [35]: type(array(1.0)*2)
Out[35]: type 'numpy.float64'
In [36]: type(array(1.0))
Out[36]: type 'numpy.ndarray'
Chuck
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
Charles R Harris wrote:
Just asking.
In [35]: type(array(1.0)*2)
Out[35]: type 'numpy.float64'
In [36]: type(array(1.0))
Out[36]: type 'numpy.ndarray'
No, in ufuncs 0-d arrays are considered scalars, as are Python scalars
and array scalars.
Also, ufuncs that result in scalars return
Hi Chris
Would you please run the following commands and show their output?
import sys
print sys.byteorder
import numpy as N
print N.array([1,2,3],N.dtype(N.int16).newbyteorder('')).dtype.byteorder
print N.array([1,2,3],N.dtype(N.int16).newbyteorder('')).dtype.byteorder
print
Hi Stefan,
This is what I get:
import sys
print sys.byteorder
big
import numpy as N
print
N.array([1,2,3],N.dtype(N.int16).newbyteorder('')).dtype.byteorder
print
N.array([1,2,3],N.dtype(N.int16).newbyteorder('')).dtype.byteorder
print
I get the same failure on ppc. Here is the result of your commands:
big
=
On Apr 1, 2007, at 16:22, Stefan van der Walt wrote:
Hi Chris
Would you please run the following commands and show their output?
import sys
print sys.byteorder
import numpy as N
print
What's the best way of assembling a big matrix from parts?
I'm using lagrange multipliers to enforce constraints and this kind of
matrix comes up a lot:
[[ K, G],
[ G.T , 0]]
In matlab you can use the syntax
[K G; G' zeros(nc)]
In numpy I'm using
vstack([ hstack([ K,G ]), hstack([
I had to poke around before finding it too:
bmat( [[K,G],[G.T, zeros(nc)]] )
On 4/1/07, Bill Baxter [EMAIL PROTECTED] wrote:
What's the best way of assembling a big matrix from parts?
I'm using lagrange multipliers to enforce constraints and this kind of
matrix comes up a lot:
[[ K, G],
[
The following test fails on a Solaris 8 system:
==
FAIL: check_basic (numpy.core.tests.test_multiarray.test_clip)
--
Traceback (most recent call last):
File
12 matches
Mail list logo
