#7920: Common numerical matrix base class
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Reporter: dagss | Owner: was
Type: defect | Status: new
Priority: major | Milestone:
Component: linear algebra | Keywords:
Work_issues: | Author:
Upstream: N/A | Reviewer:
Merged: |
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Currently, Matrix_double_dense inherits from Matrix_dense and
Matrix_double_sparse from Matrix_sparse. However numerical matrices share
a lot compared to other matrices and should probably have a common base
class:
- Docstrings of numerical decompositions should likely be shared
- {{{solve_right}}} implementation should be shared
- Even if one matrix uses SuiteSparse and another LAPACK for making
decompositions, the code for using those decompositions to find solutions,
and iteratively improve the solutions, can be shared
- In general, a place to put docstrings and examples with terminology
more familiar to numerical users
Luckily, Matrix_dense/sparse offers little in terms of implementation for
numerical matrices (the exception is the hash value -- which is useless
for numerical matrices anyway, but should be implemented).
In the future, there might be diagonal, Hermitian, triangular, banded etc.
matrices, and then it makes even more sense to change the hierarchy, so
that sparse/dense isn't a superclass.
So, this ticket should result in:
- Introduce Matrix_numerical
- Change the base class of Matrix_double_dense and Matrix_double_sparse
to Matrix_numerical
- A {{{Matrix_numerical.solve_right}}} centered around matrix
decompositions
Incidentally, this is likely to result in:
- A proper pickle implementation for dense double matrices (just pickle
the NumPy array; and read back the dtype on unpickle)
- Loosing the Matrix_real_double_dense and Matrix_complex_double_dense
subclasses -- these serve no real purpose at all, and prevents introducing
e.g. efficient dense lower-triangular matrices and so on. (Remember to
keep stubs aliased to Matrix_double_dense for unpickling backward
compatability)
--
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/7920>
Sage <http://www.sagemath.org>
Sage: Creating a Viable Open Source Alternative to Magma, Maple, Mathematica,
and MATLAB
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