Python linear algebra module -- requesting comments on interface
Szabolcs Nagy wrote: nice interface, but with 3d apps i prefer cgkit's approach, which has vec3, vec4, mat3, mat4 and quat types with lots of useful functions for 3d graphics (like mat4.looakAt(pos, target, up) or mat3.toEulerXYZ()) there are other libs with similar types and functions: cgkit (http://cgkit.sourceforge.net/) Thanks for the link! I had planned on changing around the constructors: using Matrix.zero(), Matrix.identity(), and Matrix.random() static methods (instead of module functions), and adding Matrix.rotate(), Matrix.translate(), Matrix.scale() for homogenous 4-matrices and with an optional arg that would make a 3-matrix in special cases. Then I thought I'd add affine_transform() and homogeneous_transform() module methods, which could transform several vectors at once if they are stored in a matrix. But I looked over cgkit's interface, and it is EXACTLY what I wanted. I guess my scientific programming background made me think up too general of an interface. So I've cancelled this linear algebra library. If anyone needs the matrix decompositions, and you can't find them elsewhere, you can always make your own library. I was planning on using the public domain code from: http://math.nist.gov/javanumerics/jama/ ftp://math.nist.gov/pub/Jampack/Jampack/AboutJampack.html - Connelly Barnes __ Yahoo! Mail - PC Magazine Editors' Choice 2005 http://mail.yahoo.com -- http://mail.python.org/mailman/listinfo/python-list
Re: Python linear algebra module -- requesting comments on interface
nice interface, but with 3d apps i prefer cgkit's approach, which has vec3, vec4, mat3, mat4 and quat types with lots of useful functions for 3d graphics (like mat4.looakAt(pos, target, up) or mat3.toEulerXYZ()) there are other libs with similar types and functions: cgkit (http://cgkit.sourceforge.net/) pyogre (http://www.ogre3d.org/wiki/index.php/PyOgre) panda3d (http://panda3d.org/) -- http://mail.python.org/mailman/listinfo/python-list
Re: Python linear algebra module -- requesting comments on interface
Terry Reedy wrote: [EMAIL PROTECTED] wrote in message news:[EMAIL PROTECTED] The module will be public domain. Various lawyers have suggested that either you cannot do that (is US) or that you should not do that. (You know the joke -- ask two lawyers and you get three opinions -- but all depends on your country of residence.) Well he can do it, but you are right, it is best not too. If anything, using an open source license will encourage people to share back any additions or bug fixes they make. ANTLR for example was public domain (still is for version 2), but switched to BSD for version 3: http://www.antlr.org/license.html -- http://mail.python.org/mailman/listinfo/python-list
Python linear algebra module -- requesting comments on interface
Hi, I'm in the process of writing a Python linear algebra module. The current targeted interface is: http://oregonstate.edu/~barnesc/temp/linalg/ The interface was originally based on Raymond Hettinger's Matfunc [1]. However, it has evolved so that now it is nearly identical to JAMA [2], the Java matrix library. I am soliticing comments on this interface. Please post up any criticism that you have. Even small things -- if something isn't right, it's better to fix it now than later. I have not made source code available yet, since the current code is missing the decompositions and doesn't match the new interface. I'm in the process of rewritting the code to match the new interface. You can e-mail me and ask for the old code if you're curious or skeptical. [1]. http://users.rcn.com/python/download/python.htm [2]. http://math.nist.gov/javanumerics/jama/ - Brief comparison with Numeric - Numeric and linalg serve different purposes. Numeric is intended to be a general purpose array extension. It takes a kitchen sink approach, and includes every function which could potentially be useful for array manipulations. Linalg is intended to handle real/complex vectors and matrices, for scientific and 3D applications. It has a more restricted scope. Because it is intended for 3D applications, it is optimized for dimension 2, 3, 4 operations. For the typical matrix operations, the linalg interface is much intuitive than Numeric's. Real and imaginary components are always cast to doubles, so no headaches are created if a matrix is instantiated from a list of integers. Unlike Numeric, the * operator performs matrix multiplication, A**-1 computes the matrix inverse, A == B returns True or False, and the 2-norm and cross product functions exist. As previously stated, linalg is optimized for matrix arithmetic with small matrices (size 2, 3, 4). A (somewhat out of date) set of microbenchmarks [3] [4] show that linalg is roughly an order of magnitude faster than Numeric for dimension 3 vectors and matrices. [3]. Microbenchmarks without psyco: http://oregonstate.edu/~barnesc/temp/ numeric_vs_linalg_prelim-2005-09-07.pdf [4]. Microbenchmarks with psyco: http://oregonstate.edu/~barnesc/temp/ numeric_vs_linalg_prelim_psyco-2005-09-07.pdf __ Do You Yahoo!? Tired of spam? Yahoo! Mail has the best spam protection around http://mail.yahoo.com -- http://mail.python.org/mailman/listinfo/python-list
Re: Python linear algebra module -- requesting comments on interface
C. Barnes wrote:
Hi, I'm in the process of writing a Python linear
algebra module.
The current targeted interface is:
http://oregonstate.edu/~barnesc/temp/linalg/
Is this going to become free software. If yes, what license
will you use?
So my suggestions:
In cases like these ones:
random_matrix(m, n=-1)
zero_matrix(m, n=-1)
.. I think it's better to set the default value to None
instead of a number:
random_matrix(m, n=None)
zero_matrix(m, n=None)
IMHO, this is more intuitive and more pythonic.
I also suggest to make the random function choosable:
random_matrix(m, n=None, randfunc=random.random)
random_vector(n, randfunc=random.random)
This way it's more easy for those who want another range
of numbers, or want another kind of distribution of the
random numbers.
At the top of your documentation, there is a link overview,
which is broken:
See _overview_ for a quick start.
Greets,
Volker
--
Volker Grabsch
---(())---
\frac{\left|\vartheta_0\times\{\ell,\kappa\in\Re\}\right|}{\sqrt
[G]{-\Gamma(\alpha)\cdot\mathcal{B}^{\left[\oint\!c_\hbar\right]}}}
--
http://mail.python.org/mailman/listinfo/python-list
Python linear algebra module -- requesting comments on interface
Thanks for your commentary.
The module will be public domain.
I fixed the broken link (epydoc was inserting backslashes in URLs),
changed the default arguments to None as you suggested, and added
a randfunc=None and randargs=() default argument for random_matrix()
and random_vector() (the matrix is populated with randfunc(*randargs)
entries if randfunc is not None).
- Connelly Barnes
E-mail address: 'Y29ubmVsbHliYXJuZXNAeWFob28uY29t\n'.
decode('base64')
C. Barnes wrote:
Hi, I'm in the process of writing a Python linear
algebra module.
The current targeted interface is:
http://oregonstate.edu/~barnesc/temp/linalg/
Is this going to become free software. If yes, what license
will you use?
So my suggestions:
In cases like these ones:
random_matrix(m, n=-1)
zero_matrix(m, n=-1)
.. I think it's better to set the default value to None
instead of a number:
random_matrix(m, n=None)
zero_matrix(m, n=None)
IMHO, this is more intuitive and more pythonic.
I also suggest to make the random function choosable:
random_matrix(m, n=None, randfunc=random.random)
random_vector(n, randfunc=random.random)
This way it's more easy for those who want another range
of numbers, or want another kind of distribution of the
random numbers.
At the top of your documentation, there is a link overview,
which is broken:
See _overview_ for a quick start.
Greets,
Volker
--
Volker Grabsch
--
http://mail.python.org/mailman/listinfo/python-list
Re: Python linear algebra module -- requesting comments on interface
Since one of the module's targeted applications is for 3D applications, I think there should be some specific support for applying the Matrix-vector product operation to a sequence of vectors instead of only one at a time -- and it should be possible to optimize the module's code for this common case. I'd also like to see some special specific errors defined and raised from the Matrix det(), inverse(), and transpose() methods when the operation is attempted on an ill-formed matrices (e.g. for non-square, non-invertible, singular cases). This would allow client code to handle errors better. Very nice work overall, IMHO. Best, -Martin -- http://mail.python.org/mailman/listinfo/python-list
Re: Python linear algebra module -- requesting comments on interface
Connelly, Apologies, my first message was sent in error. I like your general setup. You appear to permit matrix operations, which the folk at Numeric and, later, numarray did not. My own package, PyMatrix, has similar aims to yours but it may be slower as it is based on numarray. My package is just about ready for another release but I'm toiling to improve the documentation. I felt that it could be of value to newcomers to matrices and so my new documentation is more long-winded than yours. Your overview sets the whole thing out very neatly. I have made use of Python's properties for transpose, inverse etc. This uses abbreviations and avoids redundant parentheses. My work was based on the ideas of Huaiyu Zhu, who developed MatPy: http://matpy.sourceforge.net/ You might be interested in looking at PyMatrix: http://www3.sympatico.ca/cjw/PyMatrix/ Best wishes, Colin W. C. Barnes wrote: Hi, I'm in the process of writing a Python linear algebra module. The current targeted interface is: http://oregonstate.edu/~barnesc/temp/linalg/ The interface was originally based on Raymond Hettinger's Matfunc [1]. However, it has evolved so that now it is nearly identical to JAMA [2], the Java matrix library. I am soliticing comments on this interface. Please post up any criticism that you have. Even small things -- if something isn't right, it's better to fix it now than later. I have not made source code available yet, since the current code is missing the decompositions and doesn't match the new interface. I'm in the process of rewritting the code to match the new interface. You can e-mail me and ask for the old code if you're curious or skeptical. [1]. http://users.rcn.com/python/download/python.htm [2]. http://math.nist.gov/javanumerics/jama/ - Brief comparison with Numeric - Numeric and linalg serve different purposes. Numeric is intended to be a general purpose array extension. It takes a kitchen sink approach, and includes every function which could potentially be useful for array manipulations. Linalg is intended to handle real/complex vectors and matrices, for scientific and 3D applications. It has a more restricted scope. Because it is intended for 3D applications, it is optimized for dimension 2, 3, 4 operations. For the typical matrix operations, the linalg interface is much intuitive than Numeric's. Real and imaginary components are always cast to doubles, so no headaches are created if a matrix is instantiated from a list of integers. Unlike Numeric, the * operator performs matrix multiplication, A**-1 computes the matrix inverse, A == B returns True or False, and the 2-norm and cross product functions exist. As previously stated, linalg is optimized for matrix arithmetic with small matrices (size 2, 3, 4). A (somewhat out of date) set of microbenchmarks [3] [4] show that linalg is roughly an order of magnitude faster than Numeric for dimension 3 vectors and matrices. [3]. Microbenchmarks without psyco: http://oregonstate.edu/~barnesc/temp/ numeric_vs_linalg_prelim-2005-09-07.pdf [4]. Microbenchmarks with psyco: http://oregonstate.edu/~barnesc/temp/ numeric_vs_linalg_prelim_psyco-2005-09-07.pdf __ Do You Yahoo!? Tired of spam? Yahoo! Mail has the best spam protection around http://mail.yahoo.com -- http://mail.python.org/mailman/listinfo/python-list
Re: Python linear algebra module -- requesting comments on interface
[EMAIL PROTECTED] wrote in message news:[EMAIL PROTECTED] The module will be public domain. Various lawyers have suggested that either you cannot do that (is US) or that you should not do that. (You know the joke -- ask two lawyers and you get three opinions -- but all depends on your country of residence.) A license lets you say I wrote this, you cannot claim that you did and If you use this, you agree not to sue me. PD apparently allow both theft and (legal) assault. Somewhere on the python site is a reference to the 'Academic License' which I believe says about this much (as does the Python license) and which is compatible with possible donation to PSF. Terry J. Reedy -- http://mail.python.org/mailman/listinfo/python-list
Re: Python linear algebra module -- requesting comments on interface
On Fri, 9 Sep 2005 04:58:43 -0700 (PDT), C. Barnes [EMAIL PROTECTED] wrote: Hi, I'm in the process of writing a Python linear algebra module. The current targeted interface is: http://oregonstate.edu/~barnesc/temp/linalg/ The interface was originally based on Raymond Hettinger's Matfunc [1]. However, it has evolved so that now it is nearly identical to JAMA [2], the Java matrix library. I am soliticing comments on this interface. Please post up any criticism that you have. Even small things -- if something isn't right, it's better to fix it now than later. Wondering whether you will be supporting OpenGL-style matrices and operations for graphics. UIAM they permit optimizations in both storage and operations due to the known zero and one element values that would appear in full matrix representations of the same. http://www.rush3d.com/reference/opengl-redbook-1.1/appendixg.html Also wondering about some helper function to measure sensitivity of .solve results when getting near-singular, but maybe that's an out-side-of-the package job. From a quick look, it looks quite nice ;-) Regards, Bengt Richter -- http://mail.python.org/mailman/listinfo/python-list
