Gheorghe Postelnicu wrote:
Hi guys,
I just tried to run the 1.3.0 superpack installer and I get the
following message box:
Executing numpy installer failed.
The details show the following lines:
Output folder: C:\DOCUME~1\Ghighi\LOCALS~1\Temp
Install dir for actual installers is
Hi,
I have a large 2D numpy array as input and a 1D array as output.
In between, I would like to use C code.
C is requirement because it has to be fast and because the algorithm
cannot be written in a numpy oriented way :( (no way...really).
Which tool should I use to achieve that?
Hi again,
I noticed numpy includes a copy of distutils. I guess because it's
been modified in some way?
cheers,
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On Sun, Sep 20, 2009 at 13:13, René Dudfield ren...@gmail.com wrote:
Hi again,
I noticed numpy includes a copy of distutils. I guess because it's
been modified in some way?
numpy.distutils is a set of extensions to distutils; it is not a copy
of distutils.
--
Robert Kern
I have come to
Hi,
Would anyone have thoughts about what the best hardware would be for
Numpy? In
particular, I am wondering about Intel Core i7 vs Xeon. Also, I feel
that the
limiting factor might be memory speed and cache rather than processor speed.
What do you think?
Best,
Romain
Hi,
I'm done reviewing all the improved docstrings for NumPy, they can be merged
now from the doc editor Patch page. Maybe I'll get around to doing the SciPy
ones as well this week, but I can't promise that.
There are a few docstrings on the Patch page I did not mark Ok to apply:
1. the generic
On 20-Sep-09, at 2:17 PM, Romain Brette wrote:
Would anyone have thoughts about what the best hardware would be for
Numpy? In
particular, I am wondering about Intel Core i7 vs Xeon. Also, I feel
that the
limiting factor might be memory speed and cache rather than
processor speed.
What do
Hi,
Is the definition and explanation of PyArray_AsCArray in Numpy User
Guide up-to-date?
In the guide, it's like this:
int PyArray_AsCArray(PyObject** op, void* ptr, npy_intp* dims, int nd,
int typenum, int itemsize)
On Sun, Sep 20, 2009 at 3:49 PM, Ralf Gommers
ralf.gomm...@googlemail.comwrote:
Hi,
I'm done reviewing all the improved docstrings for NumPy, they can be
merged now from the doc editor Patch page. Maybe I'll get around to doing
the SciPy ones as well this week, but I can't promise that.
Any clue why I'm seeing this behavior? np.take's documentation says it
does the same thing as fancy indexing, but from this example I'm not
so sure:
import numpy as np
mat = np.random.randn(5000, 1000)
selector = np.array(np.arange(5000)[::2])
In [95]: timeit submat = mat[selector]
10 loops,
10 matches
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