test_code_quality: Exclude local backup~ files.
Remove non-test.

It's highly unlikely that the initial bug report will resurface without
raising a failure elsewhere. A similar test is already in test_arit.py
Merge pull request #1545 from jrioux/tests

Some fixed tests, increased coverage.
matrices: docstring edit of shape; add to tutorial re slicing
3401: fix matrix indexing error
matrices.rst: minor edits and 0-size matrix sliced
allow submatrix assignment given top left indices

There is no need for the redundant slice when assigning a matrix
to a subregion of another matrix; it is sufficient to just give
the top left target position in the matrix and the list form (or
Matrix form) of what should be put there:

>>> i = eye(3)
>>> i[0,0] = Matrix(range(3))
>>> i
[0, 0, 0]
[1, 1, 0]
[2, 0, 1]
>>> i[0,0] = Matrix([range(3)])
>>> i
[0, 1, 2]
[1, 1, 0]
[2, 0, 1]
>>> i[0,0]=[[4,4]]
>>> i
[4, 4, 2]
[1, 1, 0]
[2, 0, 1]

Also, is_sequence(Matrix) is True so the include values were removed
from tests of is_sequence that included some sort of Matrix.

A little care needs to be used when checking types:
  Matrix, SparseMatrix derive from MatrixBase
  MatrixBase and MatrixExpr (which doesn't derive from MatrixBase)
    are all sequences -- hence the use of `ismat` when checking
    for submatrix assignment.
matrix cleanup

Add a copy method to replace M[:, :] (which requires slice calculations)

simplified tolist

simplified examples to show the salient feature being deomonstrated;
rather than using a variety of numbers, zeros and ones are now used.

SparseMatrix __setitem__ can now translate an integer to a key
S[1] = 42 will figure out the i,j location of position 1

simplified toMatrix by using the tolist method

gave SparseMatrix its own tolist method since S.mat is a dictionary
and using the default parent class tolist method did not work for
SparseMatrix

Add an efficient negation of a SparseMatrix

simplified the add method for SparseMatrix
spaces after commas added
smarter multiply and other SparseMatrix methods added

These are some of the methods that Sherjil worked on in PR #456.
The _lil_row_major is modified from what he presented there. In addition
col_join was added, too, for SparseMatrix.
matrices: add normalize and sort options to diagonalize
matrices: SparseMatrix mat -> smat

[regarding mat -> smat, see below]

minor edits

put a temporary as_int in place until this is merged with 0.7.2

MUTABLEMATRIX

since _cholesky is a parent-class function, make sure it returns
the same type as was received. (SparseMatrix doesn't have a _new
method so either one has to be added or -- as here -- the general
instantiation using the type of self must be used.)

elaborate the _handle_creation_inputs docstring and reorganize
code so there is only one error message location at the end of the
if-blocks.

__setitem__ and __getitem__ are now defined in MutableMatrix and
overridden in SparseMatrix

SPARSEMATRIX

refactored the __init__ code for SparseMatrix and removed the TODO
since it appears that the only things left to process are the
numpy array and the flat list...and I don't see any sparse-smarts
that can be applied to those.

copy is put here to override the MutableMatrix version because...
** smat ** rather than mat is used to store the sparse matrix dict;
if SparseMatrix shares the name 'mat' with MutableMatrix, it is
possible to call methods on Sparse that are only defined to work
in Mutable -- methods that operate on mat. Now, at least, an error
will be raised signaling the need to write a sparse routine for the
desired method.

TODO: change indexing and mat storage so __getitem__ always works
quickly with M[(i, j)] and then perhaps smat can be changed back to
mat.

rowdecomp is such a low-level activity that it is simply inlined
where it is needed.

a duplicate multiply was removed and _lil_row_major removed (and the
row_list is now used in-place in multiply)

all other changes involve changing mat to smat or removing obsolete tests
and editing whitespace.
Sparse gets C, T, H, D methods; upgrade reshape+copyin_matrix
add solve methods to SparseMatrix
corrections to SparseMatrix solve methods
matrices: misc changes
matrices: make norm more flexible
un-XFAIL sparse matrix tests
matrices: increase coverage
fix blockmatrix.transpose