Sparse rational matrices#
AUTHORS:
William Stein (2007-02-21)
Soroosh Yazdani (2007-02-21)
- class sage.matrix.matrix_rational_sparse.Matrix_rational_sparse#
Bases:
Matrix_sparse
Create a sparse matrix over the rational numbers.
INPUT:
parent
– a matrix space overQQ
entries
– seematrix()
copy
– ignored (for backwards compatibility)coerce
– if False, assume without checking that the entries are of typeRational
.
- add_to_entry(i, j, elt)#
Add
elt
to the entry at position(i, j)
.EXAMPLES:
sage: m = matrix(QQ, 2, 2, sparse=True) sage: m.add_to_entry(0, 0, -1/3) sage: m [-1/3 0] [ 0 0] sage: m.add_to_entry(0, 0, 1/3) sage: m [0 0] [0 0] sage: m.nonzero_positions() []
- denominator()#
Return the denominator of this matrix.
OUTPUT:
– Sage Integer
EXAMPLES:
sage: b = matrix(QQ,2,range(6)); b[0,0]=-5007/293; b [-5007/293 1 2] [ 3 4 5] sage: b.denominator() 293
- dense_matrix()#
Return dense version of this matrix.
EXAMPLES:
sage: a = matrix(QQ,2,[1..4],sparse=True); type(a) <class 'sage.matrix.matrix_rational_sparse.Matrix_rational_sparse'> sage: type(a.dense_matrix()) <class 'sage.matrix.matrix_rational_dense.Matrix_rational_dense'> sage: a.dense_matrix() [1 2] [3 4]
Check that subdivisions are preserved when converting between dense and sparse matrices:
sage: a.subdivide([1,1], [2]) sage: b = a.dense_matrix().sparse_matrix().dense_matrix() sage: b.subdivisions() == a.subdivisions() True
- echelon_form(algorithm='default', height_guess=None, proof=True, **kwds)#
INPUT:
height_guess
,proof
,**kwds
– all passed to the multimodular algorithm; ignored by the p-adic algorithm.OUTPUT:
self is no in reduced row echelon form.
EXAMPLES:
sage: a = matrix(QQ, 4, range(16), sparse=True); a[0,0] = 1/19; a[0,1] = 1/5; a [1/19 1/5 2 3] [ 4 5 6 7] [ 8 9 10 11] [ 12 13 14 15] sage: a.echelon_form() [ 1 0 0 -76/157] [ 0 1 0 -5/157] [ 0 0 1 238/157] [ 0 0 0 0]
- echelonize(height_guess=None, proof=True, **kwds)#
Transform the matrix
self
into reduced row echelon form in place.INPUT:
height_guess
,proof
,**kwds
– all passed to the multimodular algorithm; ignored by the p-adic algorithm.OUTPUT:
Nothing. The matrix
self
is transformed into reduced row echelon form in place.ALGORITHM: a multimodular algorithm.
EXAMPLES:
sage: a = matrix(QQ, 4, range(16), sparse=True); a[0,0] = 1/19; a[0,1] = 1/5; a [1/19 1/5 2 3] [ 4 5 6 7] [ 8 9 10 11] [ 12 13 14 15] sage: a.echelonize(); a [ 1 0 0 -76/157] [ 0 1 0 -5/157] [ 0 0 1 238/157] [ 0 0 0 0]
trac ticket #10319 has been fixed:
sage: m = Matrix(QQ, [1], sparse=True); m.echelonize() sage: m = Matrix(QQ, [1], sparse=True); m.echelonize(); m [1]
- height()#
Return the height of this matrix, which is the least common multiple of all numerators and denominators of elements of this matrix.
OUTPUT:
– Integer
EXAMPLES:
sage: b = matrix(QQ,2,range(6), sparse=True); b[0,0]=-5007/293; b [-5007/293 1 2] [ 3 4 5] sage: b.height() 5007
- set_row_to_multiple_of_row(i, j, s)#
Set row i equal to s times row j.
EXAMPLES:
sage: a = matrix(QQ,2,3,range(6), sparse=True); a [0 1 2] [3 4 5] sage: a.set_row_to_multiple_of_row(1,0,-3) sage: a [ 0 1 2] [ 0 -3 -6]