SuiteSparseMatrix¶
-
class
probnum.problems.zoo.linalg.
SuiteSparseMatrix
(matid, group, name, nnz, is2d3d, isspd, psym, nsym, kind)¶ Bases:
probnum.linops.Matrix
SuiteSparse Matrix.
Sparse matrix from the SuiteSparse Matrix Collection. 1 2
- Parameters
matid (
str
) – Unique identifier for the matrix in the database.group (
str
) – Group this matrix belongs to.name (
str
) – Name of this matrix.nnz (
int
) – Number of non-zero elements.is2d3d (
bool
) – Does this matrix come from a 2D or 3D discretization?isspd (
bool
) – Is this matrix symmetric, positive definite?psym (
float
) – Degree of symmetry of the matrix pattern.nsym (
float
) – Degree of numerical symmetry of the matrix.kind (
str
) – Information of the problem domain this matrix arises from.
References
- 1
Davis, TA and Hu, Y. The University of Florida sparse matrix collection. ACM Transactions on Mathematical Software (TOMS) 38.1 ( 2011): 1-25.
- 2
Kolodziej, Scott P., et al. The SuiteSparse matrix collection website interface. Journal of Open Source Software 4.35 (2019): 1244.
Attributes Summary
- rtype
- rtype
- rtype
- rtype
- rtype
Methods Summary
__call__
(x[, axis])Call self as a function.
adjoint
()- rtype
astype
(dtype[, order, casting, subok, copy])- rtype
broadcast_matmat
(matmat)broadcast_matvec
(matvec)broadcast_rmatmat
(rmatmat)broadcast_rmatvec
(rmatvec)cond
([p])Compute the condition number of the linear operator.
conj
()- rtype
- rtype
det
()Determinant of the linear operator.
eigvals
()Eigenvalue spectrum of the linear operator.
from_database_entry
(database_entry)Create a SuiteSparseMatrix object from an entry of the database index.
inv
()Inverse of the linear operator.
Log absolute determinant of the linear operator.
rank
()Rank of the linear operator.
todense
([cache])Dense matrix representation of the linear operator.
trace
()Trace of the linear operator.
Transpose this linear operator.
Attributes Documentation
-
H
¶ - Return type
-
T
¶ - Return type
Methods Documentation
-
adjoint
()¶ - Return type
-
astype
(dtype, order='K', casting='unsafe', subok=True, copy=True)¶ - Return type
-
cond
(p=None)¶ Compute the condition number of the linear operator.
The condition number of the linear operator with respect to the
p
norm. It measures how much the solution \(x\) of the linear system \(Ax=b\) changes with respect to small changes in \(b\).- Parameters
p ({None, 1, , 2, , inf, 'fro'}, optional) –
Order of the norm:
p
norm for matrices
None
2-norm, computed directly via singular value decomposition
’fro’
Frobenius norm
np.inf
max(sum(abs(x), axis=1))
1
max(sum(abs(x), axis=0))
2
2-norm (largest sing. value)
- Returns
The condition number of the linear operator. May be infinite.
- Return type
cond
-
conj
()¶ - Return type
-
conjugate
()¶ - Return type
-
classmethod
from_database_entry
(database_entry)[source]¶ Create a SuiteSparseMatrix object from an entry of the database index.
- Parameters
database_entry (
Dict
) – Dictionary representing one entry from the SuiteSparse database index.- Return type
-
inv
()¶ Inverse of the linear operator.
- Return type
-
rank
()¶ Rank of the linear operator.
- Return type
int64
-
todense
(cache=True)¶ Dense matrix representation of the linear operator.
This method can be computationally very costly depending on the shape of the linear operator. Use with caution.
- Returns
matrix – Matrix representation of the linear operator.
- Return type
np.ndarray
-
trace
()¶ Trace of the linear operator.
Computes the trace of a square linear operator \(\text{tr}(A) = \sum_{i-1}^n A_ii\).
- Returns
trace – Trace of the linear operator.
- Return type
:raises LinAlgError : If
trace()
is called on a non-square matrix.:
-
transpose
()¶ Transpose this linear operator.
Can be abbreviated self.T instead of self.transpose().
- Return type