I need to bang out an image processing library (it's schoolwork, so I
can't just use an existing one). But I see three libraries competing
for my love: numpy, numarray, and numeric.
Can anyone recommend which one I should use? If one is considered the
officially blessed one going forward, that would be my ideal.
Thanks,
Christian 4 3262
On Feb 15, 5:40 pm, "Christian Convey" <christian.con...@gmail.com>
wrote:
I need to bang out an image processing library (it's schoolwork, so I
can't just use an existing one). But I see three libraries competing
for my love: numpy, numarray, and numeric.
Can anyone recommend which one I should use? If one is considered the
officially blessed one going forward, that would be my ideal.
Thanks,
Christian
Use numpy; it is the "officially blessed one" that you refer to. It
has all of the advantages of the other two.
Numeric was the first library, but it had some drawbacks that led some
people to develop Numarray, which had some additional features.
Finally, the numpy project was started to unify the two groups by
providing some of the new features in a code base consistent with the
old library as well.
On Feb 15, 4:40 pm, "Christian Convey" <christian.con...@gmail.com>
wrote:
I need to bang out an image processing library (it's schoolwork, so I
can't just use an existing one). But I see three libraries competing
for my love: numpy, numarray, and numeric.
Can anyone recommend which one I should use? If one is considered the
officially blessed one going forward, that would be my ideal.
Thanks,
Christian
Hi,
yeah numpy is the newest one. It has only one drawback, there is no
comprehensive documentation available that would be free but of course
you could buy one. numpy is very similar to the other two packages but
not identical that means one has always some troulbe finding out how
things work. For example, in numarray you can calculate the
eigenvectors of a matrix with eigenvectors(A), in numpy it is eig(A).
This looks similar, but the difference is that in numarray the
eigenvectors are returned as rows and in numpy as columns.
If someone knows of a free manual, let me know.
Frank
On Feb 15, 11:23 pm, "Frank" <super...@gmail.comwrote:
On Feb 15, 4:40 pm, "Christian Convey" <christian.con...@gmail.com>
wrote:
I need to bang out an image processing library (it's schoolwork, so I
can't just use an existing one). But I see three libraries competing
for my love: numpy, numarray, and numeric.
Can anyone recommend which one I should use? If one is considered the
officially blessed one going forward, that would be my ideal.
Thanks,
Christian
Hi,
yeah numpy is the newest one. It has only one drawback, there is no
comprehensive documentation available that would be free but of course
you could buy one. numpy is very similar to the other two packages but
not identical that means one has always some troulbe finding out how
things work. For example, in numarray you can calculate the
eigenvectors of a matrix with eigenvectors(A), in numpy it is eig(A).
This looks similar, but the difference is that in numarray the
eigenvectors are returned as rows and in numpy as columns.
If someone knows of a free manual, let me know.
Frank
Frank,
I bought the manual, and I do recommend it, but I find the most useful
documentation is in the docstrings, which I view via "pydoc -g" and
then view in a browser.
Rick
In article <11*********************@l53g2000cwa.googlegroups. com>,
"RickMuller" <rp******@gmail.comwrote:
Use numpy; it is the "officially blessed one" that you refer to. It
has all of the advantages of the other two.
Numeric was the first library, but it had some drawbacks that led some
people to develop Numarray, which had some additional features.
Finally, the numpy project was started to unify the two groups by
providing some of the new features in a code base consistent with the
old library as well.
I agree completely, having converted all my code from Numeric to NumPy.
Just my 2 cents.
-- Lou Pecora (my views are my own) REMOVE THIS to email me. This thread has been closed and replies have been disabled. Please start a new discussion. Similar topics
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