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Matrix Specification

A design specification for a new matrix class could serve as a guide for making changes to the current matrix class. Or, if the final design breaks too much with current matrix behavior, it could serve as a guide to making a new matrix class.

The most basic, and the most contentious, design decision of a new matrix class is matrix indexing. Several possible approaches have been discussed, as documented at What follows is a summary of options.

1. Matrices should be more like arrays

The matrix class should be more like the array class:

Variant: instead of a 1d array, return a 1d array-like object that contains the orientation (row or column) as an attribute.

Question: is x.sum(1) also 1d array?

2. Operations on matrices should return a matrix or a scalar

All operations on a matrix, including all permissible indexing, should return either a matrix or a scalar.

Variant: scalar indexes raise an error except when a matrix has a single row or single column, like in Gauss.

Question: If dimensions are not reduced, what mechanism will allow matrices to be correctly handled by routines that expect that reduction during iteration?

3. Matrices should behave like Octave/Matlab matrices

Similar to the previous approach except that matrix operations should only return matrices and never return scalars. Thus a scalar becomes a 1x1 matrix. This would make the matrix class similar to Octave and Matlab.

Question: should scalar indexing index elements, as in Matlab? If so, should iteration be across elements? Or should scalar indexing of a matrix with multiple rows and columns be illegal, like in Gauss?

General Questions

Indexing questions: What is x[0]? What is x[0][0]? What is x[0,:]? What is x[\:,0]?

SciPy: NewMatrixSpec (last edited 2015-10-24 17:48:23 by anonymous)