size, but nz should be nx * ny. I'd like to wrap
this too, and ideally it would also automatically handle the array lengths, but
I'd be happy to have anything right now. I'm also quite comfortable with the
idea of packing z as a column array and reshaping it as n
I noticed that 1.5.1 was released, and sourceforge is suggesting I use
the package numpy-1.5.1-py2.6-python.org-macosx10.3.dmg. However, I
have an OS X 10.6 machine.
Can/should I use this binary?
Should I just compile from source?
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verse of fft(). Is this a misprint in
> the user guide?
>
> Lutz
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-gideon
ht on your questions.
>
> regards,
> mike
When I first discovered this, I was computing:
numpy.exp(-x**2)
If you try x = 26.7, you'll get
2.4877503498797906e-310
I then confirmed this by dividing 1. by 2. until python decided the
answer was 0.0
-gideon
_
thin the same platform?
I recognize that this isn't specific to Scipy/Numpy, but thought
someone here might have the answer.
-gideon
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So I have some data sets of about 16 floating point numbers stored
in text files. I find that loadtxt is rather slow. Is this to be
expected? Would it be faster if it were loading binary data?
-gideon
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I want to do:
numpy.float(numpy.arange(0, 10))
but get the error:
Traceback (most recent call last):
File "", line 1, in
TypeError: only length-1 arrays can be converted to Python scalars
How should I do this?
-gideon
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o this in numpy?
-gideon
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The first option doesn't accept complex data.
-gideon
On Jan 29, 2009, at 1:18 AM, Nadav Horesh wrote:
> There are at least two options:
> 1. use convolve1d from numpy.numarray.nd_image (or scipy.ndimage)
> 2. use scipy.signal.convolve and adjust the dimensions of the
> con
Is there an easy way to perform convolutions along a particular axis
of an array?
-gideon
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", line 268, in test_against_cmath
assert abs(a - b) < atol, "%s %s: %s; cmath: %s"%(fname,p,a,b)
AssertionError: arcsinh -2j: (-1.31695789692-1.57079632679j); cmath:
(1.31695789692-1.57079632679j)
------
-gi
flag.
-gideon
On Jan 24, 2009, at 11:37 PM, David Cournapeau wrote:
> Gideon Simpson wrote:
>> Having built an up to date lapack and ATLAS against gcc 4.3.2, I
>> tried
>> installing numpy 1.2.1 on Python 2.5.4. When testing I get:
>>
>> Python 2.5.4 (r254:67916, Ja
***
glibc
detected *** python: free(): invalid next size (fast):
0x1196b550 ***
I then have to kill python to get control again.
-gideon
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That's not working for me. Any thoughts on how to troubleshoot it?
-gideon
On Jan 24, 2009, at 6:18 PM, George Nurser wrote:
> I did manage to get it working.
> I remember that both libcblas.a (or a link to it) and libacml.so had
> to be in the same directory.
>
> Also
ing python setup.py build, and looking at the output?
-gideon
On Jan 24, 2009, at 4:05 PM, Pauli Virtanen wrote:
> Sat, 24 Jan 2009 15:26:17 -0500, Gideon Simpson wrote:
>
>> Nadav-
>>
>> That doesn't quite seem to work for me. I added:
>>
>> [blas_
4.2.0/gfortran64/lib
include_dirs = /usr/local/nonsystem/simpson/acml4.2.0/gfortran64/include
libraries = acml
to my site.cfg with no luck. Somewhere else, people indicated that
the ACML lacked a CBLAS which was necessary to make this work.
-gideon
On Jan 24, 2009, at 3:08 PM, Nadav Horesh
Does anyone have a guide on how to get numpy to use the ACML as its
blas/lapack backend?
-gideon
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IL=1, failures=1)
How would you recommend I troubleshoot this? How seriously should I
take it?
This is with a fresh Python 2.5.4 installation too.
-gideon
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ay to make this calculation in numpy? It
certainly makes for nice, clean code, but is it the fastest I can get?
-gideon
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A[1,0,:] u[0,:] + A[1,1,:] u[1,:] = v[1,:]
is there a smart way to perform this computation?
-gideon
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Has anyone gotten the combination of OS X with a fink python
distribution to successfully build numpy/scipy with the intel
compilers and the mkl? If so, how'd you do it?
-gideon
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Is there (or should there be) a routine for reading and writing numpy
arrays and matrices in MATLAB ASCII m-file format?
-gideon
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The fink guys fixed a bug so it now at least builds properly with
python 2.6.
-gideon
On Nov 3, 2008, at 1:35 AM, David Cournapeau wrote:
> Michael Abshoff wrote:
>>
>> Unfortunately numpy 1.2.x does not support Python 2.6. IIRC support
>> is
>> planned for numpy
e/src/
multiarraymodule.o -o build/lib.macosx-10.5-i386-2.6/numpy/core/
multiarray.so" failed with exit status 1
-gideon
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hin numpy/scipy?
I could code it python. However, since python is a high level
language, it's not clear to me that I'd see an execution time benefit
over numpy.dot(A,x). Alternatively, I could write it in a compiled
language and build python bindings to it.
How does python (or numpy/scipy) do exponentiation? If I do x**p,
where p is some positive integer, will it compute x*x*...*x (p times),
or will it use logarithms?
-gideon
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