slepc4py.SLEPc.DS#

class slepc4py.SLEPc.DS#

Bases: Object

Direct Solver (or Dense System).

The DS package provides auxiliary routines that are internally used by the different slepc4py solvers. It is used to represent low-dimensional eigenproblems that must be solved within iterative solvers with direct methods. It can be seen as a structured wrapper to LAPACK functionality.

Enumerations

MatType

To refer to one of the matrices stored internally in DS.

ParallelType

Indicates the parallel mode that the direct solver will use.

StateType

DS state types.

Type

DS type.

Methods Summary

allocate(ld)

Allocate memory for internal storage or matrices in DS.

appendOptionsPrefix([prefix])

Append to the prefix used for searching for all DS options in the database.

cond()

Compute the inf-norm condition number of the first matrix.

create([comm])

Create the DS object.

destroy()

Destroy the DS object.

duplicate()

Duplicate the DS object with the same type and dimensions.

getArray(matname)

Return the array where the data is stored.

getBlockSize()

Get the block size.

getCompact()

Get the compact storage flag.

getDimensions()

Get the current dimensions.

getExtraRow()

Get the extra row flag.

getGSVDDimensions()

Get the number of columns and rows of a DS of type GSVD.

getHSVDDimensions()

Get the number of columns of a DS of type HSVD.

getLeadingDimension()

Get the leading dimension of the allocated matrices.

getMat(matname)

Get the requested matrix as a sequential dense Mat object.

getMethod()

Get the method currently used in the DS.

getOptionsPrefix()

Get the prefix used for searching for all DS options in the database.

getPEPCoefficients()

Get the polynomial basis coefficients of a DS of type PEP.

getPEPDegree()

Get the polynomial degree of a DS of type PEP.

getParallel()

Get the mode of operation in parallel runs.

getRefined()

Get the refined vectors flag.

getSVDDimensions()

Get the number of columns of a DS of type SVD.

getState()

Get the current state.

getType()

Get the DS type of this object.

reset()

Reset the DS object.

restoreMat(matname, mat)

Restore the previously seized matrix.

setBlockSize(bs)

Set the block size.

setCompact(comp)

Set the compact flag for storage of matrices.

setDimensions([n, l, k])

Set the matrix sizes in the DS object.

setExtraRow(ext)

Set a flag to indicate that the matrix has one extra row.

setFromOptions()

Set DS options from the options database.

setGSVDDimensions(m, p)

Set the number of columns and rows of a DS of type GSVD.

setHSVDDimensions(m)

Set the number of columns of a DS of type HSVD.

setIdentity(matname)

Set the identity on the active part of a matrix.

setMethod(meth)

Set the method to be used to solve the problem.

setOptionsPrefix([prefix])

Set the prefix used for searching for all DS options in the database.

setPEPCoefficients(pbc)

Set the polynomial basis coefficients of a DS of type PEP.

setPEPDegree(deg)

Set the polynomial degree of a DS of type PEP.

setParallel(pmode)

Set the mode of operation in parallel runs.

setRefined(ref)

Set a flag to indicate that refined vectors must be computed.

setSVDDimensions(m)

Set the number of columns of a DS of type SVD.

setState(state)

Set the state of the DS object.

setType(ds_type)

Set the type for the DS object.

solve()

Solve the problem.

truncate(n[, trim])

Truncate the system represented in the DS object.

updateExtraRow()

Ensure that the extra row gets up-to-date after a call to DS.solve().

vectors([matname])

Compute vectors associated to the dense system such as eigenvectors.

view([viewer])

Print the DS data structure.

Attributes Summary

block_size

The block size.

compact

Compact storage of matrices.

extra_row

If the matrix has one extra row.

method

The method to be used to solve the problem.

parallel

The mode of operation in parallel runs.

refined

If refined vectors must be computed.

state

The state of the DS object.

Methods Documentation

allocate(ld)#

Allocate memory for internal storage or matrices in DS.

Logically collective.

Parameters:

ld (int) – Leading dimension (maximum allowed dimension for the matrices, including the extra row if present).

Return type:

None

Notes

If the leading dimension is different from a previously set value, then all matrices are destroyed with reset().

Source code at slepc4py/SLEPc/DS.pyx:338

appendOptionsPrefix(prefix=None)#

Append to the prefix used for searching for all DS options in the database.

Logically collective.

Parameters:

prefix (str | None) – The prefix string to prepend to all DS option requests.

Return type:

None

Source code at slepc4py/SLEPc/DS.pyx:256

cond()#

Compute the inf-norm condition number of the first matrix.

Logically collective.

Returns:

Condition number.

Return type:

float

See also

DSCond

Source code at slepc4py/SLEPc/DS.pyx:905

create(comm=None)#

Create the DS object.

Collective.

Parameters:

comm (Comm | None) – MPI communicator; if not provided, it defaults to all processes.

Return type:

Self

See also

duplicate, DSCreate

Source code at slepc4py/SLEPc/DS.pyx:172

destroy()#

Destroy the DS object.

Collective.

See also

DSDestroy

Source code at slepc4py/SLEPc/DS.pyx:146

Return type:

Self

duplicate()#

Duplicate the DS object with the same type and dimensions.

Collective.

Returns:

The new object.

Return type:

DS

Notes

This method does not copy the matrices, and the new object does not even have internal arrays allocated. Use allocate() to use the new DS.

Source code at slepc4py/SLEPc/DS.pyx:311

getArray(matname)#

Return the array where the data is stored.

Not collective.

Parameters:

matname (MatType) – The selected matrix.

Returns:

The array.

Return type:

ArrayScalar

See also

DSGetArray

Source code at slepc4py/SLEPc/DS.pyx:845

getBlockSize()#

Get the block size.

Not collective.

Returns:

The block size.

Return type:

int

Source code at slepc4py/SLEPc/DS.pyx:555

getCompact()#

Get the compact storage flag.

Not collective.

Returns:

The flag.

Return type:

bool

Source code at slepc4py/SLEPc/DS.pyx:639

getDimensions()#

Get the current dimensions.

Not collective.

Returns:

  • n (int) – The new size.

  • l (int) – Number of locked (inactive) leading columns.

  • k (int) – Intermediate dimension (e.g., position of arrow).

  • t (int) – Truncated length.

Return type:

tuple[int, int, int, int]

Notes

The t value makes sense only if truncate() has been called. Otherwise it is equal to n.

Source code at slepc4py/SLEPc/DS.pyx:504

getExtraRow()#

Get the extra row flag.

Not collective.

Returns:

The flag.

Return type:

bool

Source code at slepc4py/SLEPc/DS.pyx:686

getGSVDDimensions()#

Get the number of columns and rows of a DS of type GSVD.

Not collective.

Returns:

  • m (int) – The number of columns.

  • p (int) – The number of rows for the second matrix.

Return type:

tuple[int, int]

Source code at slepc4py/SLEPc/DS.pyx:1082

getHSVDDimensions()#

Get the number of columns of a DS of type HSVD.

Not collective.

Returns:

The number of columns.

Return type:

int

Source code at slepc4py/SLEPc/DS.pyx:1037

getLeadingDimension()#

Get the leading dimension of the allocated matrices.

Not collective.

Returns:

Leading dimension (maximum allowed dimension for the matrices).

Return type:

int

Source code at slepc4py/SLEPc/DS.pyx:362

getMat(matname)#

Get the requested matrix as a sequential dense Mat object.

Not collective.

Parameters:

matname (MatType) – The requested matrix.

Returns:

The matrix.

Return type:

petsc4py.PETSc.Mat

Notes

The returned matrix has sizes equal to the current DS dimensions (see setDimensions()), and contains the values that would be obtained with getArray(). If the DS was truncated, then the number of rows is equal to the dimension prior to truncation, see truncate().

When no longer needed the user must call restoreMat().

Source code at slepc4py/SLEPc/DS.pyx:789

getMethod()#

Get the method currently used in the DS.

Not collective.

Returns:

Identifier of the method.

Return type:

int

Source code at slepc4py/SLEPc/DS.pyx:592

getOptionsPrefix()#

Get the prefix used for searching for all DS options in the database.

Not collective.

Returns:

The prefix string set for this DS object.

Return type:

str

Source code at slepc4py/SLEPc/DS.pyx:275

getPEPCoefficients()#

Get the polynomial basis coefficients of a DS of type PEP.

Not collective.

Returns:

Coefficients.

Return type:

ArrayReal

Source code at slepc4py/SLEPc/DS.pyx:1176

getPEPDegree()#

Get the polynomial degree of a DS of type PEP.

Not collective.

Returns:

The polynomial degree.

Return type:

int

Source code at slepc4py/SLEPc/DS.pyx:1122

getParallel()#

Get the mode of operation in parallel runs.

Not collective.

Returns:

The parallel mode.

Return type:

ParallelType

Source code at slepc4py/SLEPc/DS.pyx:450

getRefined()#

Get the refined vectors flag.

Not collective.

Returns:

The flag.

Return type:

bool

Source code at slepc4py/SLEPc/DS.pyx:734

getSVDDimensions()#

Get the number of columns of a DS of type SVD.

Not collective.

Returns:

The number of columns.

Return type:

int

Source code at slepc4py/SLEPc/DS.pyx:995

getState()#

Get the current state.

Not collective.

Returns:

The current state.

Return type:

StateType

See also

setState, DSGetState

Source code at slepc4py/SLEPc/DS.pyx:413

getType()#

Get the DS type of this object.

Not collective.

Returns:

The direct solver type currently being used.

Return type:

str

See also

setType, DSGetType

Source code at slepc4py/SLEPc/DS.pyx:212

reset()#

Reset the DS object.

Collective.

See also

allocate, DSReset

Source code at slepc4py/SLEPc/DS.pyx:160

Return type:

None

restoreMat(matname, mat)#

Restore the previously seized matrix.

Not collective.

Parameters:
Return type:

None

See also

getMat, DSRestoreMat

Source code at slepc4py/SLEPc/DS.pyx:824

setBlockSize(bs)#

Set the block size.

Logically collective.

Parameters:

bs (int) – The block size.

Return type:

None

Source code at slepc4py/SLEPc/DS.pyx:537

setCompact(comp)#

Set the compact flag for storage of matrices.

Logically collective.

Parameters:

comp (bool) – True means compact storage.

Return type:

None

Notes

Compact storage is used in some DS types such as DS.Type.HEP when the matrix is tridiagonal. This flag can be used to indicate whether the user provides the matrix entries via the compact form (the tridiagonal DS.MatType.T) or the non-compact one (DS.MatType.A).

The default is False.

Source code at slepc4py/SLEPc/DS.pyx:611

setDimensions(n=None, l=None, k=None)#

Set the matrix sizes in the DS object.

Logically collective.

Parameters:
  • n (int | None) – The new size.

  • l (int | None) – Number of locked (inactive) leading columns.

  • k (int | None) – Intermediate dimension (e.g., position of arrow).

Return type:

None

Notes

The internal arrays are not reallocated.

Some DS types have additional dimensions, e.g., the number of columns in DS.Type.SVD. For these, you should call a specific interface function.

Source code at slepc4py/SLEPc/DS.pyx:469

setExtraRow(ext)#

Set a flag to indicate that the matrix has one extra row.

Logically collective.

Parameters:

ext (bool) – True if the matrix has extra row.

Return type:

None

Notes

In Krylov methods it is useful that the matrix representing the direct solver has one extra row, i.e., has \((n+1)\) rows and \((n+1)\) columns. If this flag is activated, all transformations applied to the right of the matrix also affect this additional row. In that case, \((n+1)\) must be less or equal than the leading dimension.

The default is False.

Source code at slepc4py/SLEPc/DS.pyx:658

setFromOptions()#

Set DS options from the options database.

Collective.

Notes

To see all options, run your program with the -help option.

Source code at slepc4py/SLEPc/DS.pyx:294

Return type:

None

setGSVDDimensions(m, p)#

Set the number of columns and rows of a DS of type GSVD.

Logically collective.

Parameters:
  • m (int) – The number of columns.

  • p (int) – The number of rows for the second matrix.

Return type:

None

Notes

This call is complementary to setDimensions(), to provide dimensions that are specific to this DS.Type.

Source code at slepc4py/SLEPc/DS.pyx:1056

setHSVDDimensions(m)#

Set the number of columns of a DS of type HSVD.

Logically collective.

Parameters:

m (int) – The number of columns.

Return type:

None

Notes

This call is complementary to setDimensions(), to provide a dimension that is specific to this DS.Type.

Source code at slepc4py/SLEPc/DS.pyx:1014

setIdentity(matname)#

Set the identity on the active part of a matrix.

Logically collective.

Parameters:

matname (MatType) – The matrix to be changed.

Return type:

None

See also

DSSetIdentity

Source code at slepc4py/SLEPc/DS.pyx:885

setMethod(meth)#

Set the method to be used to solve the problem.

Logically collective.

Parameters:

meth (int) – An index identifying the method.

Return type:

None

Source code at slepc4py/SLEPc/DS.pyx:574

setOptionsPrefix(prefix=None)#

Set the prefix used for searching for all DS options in the database.

Logically collective.

Parameters:

prefix (str | None) – The prefix string to prepend to all DS option requests.

Return type:

None

Notes

A hyphen (-) must NOT be given at the beginning of the prefix name. The first character of all runtime options is AUTOMATICALLY the hyphen.

Source code at slepc4py/SLEPc/DS.pyx:231

setPEPCoefficients(pbc)#

Set the polynomial basis coefficients of a DS of type PEP.

Logically collective.

Parameters:

pbc (Sequence[float]) – Coefficients.

Return type:

None

Notes

This function is required only in the case of a polynomial specified in a non-monomial basis, to provide the coefficients that will be used during the linearization, multiplying the identity blocks on the three main diagonal blocks. Depending on the polynomial basis (Chebyshev, Legendre, …) the coefficients must be different.

There must be a total of \(3(d+1)\) coefficients, where \(d\) is the degree of the polynomial. The coefficients are arranged in three groups, \(a_i, b_i, c_i\), according to the definition of the three-term recurrence. In the case of the monomial basis, \(a_i=1\) and \(b_i=c_i=0\), in which case it is not necessary to invoke this function.

Source code at slepc4py/SLEPc/DS.pyx:1141

setPEPDegree(deg)#

Set the polynomial degree of a DS of type PEP.

Logically collective.

Parameters:

deg (int) – The polynomial degree.

Return type:

None

Source code at slepc4py/SLEPc/DS.pyx:1104

setParallel(pmode)#

Set the mode of operation in parallel runs.

Logically collective.

Parameters:

pmode (ParallelType) – The parallel mode.

Return type:

None

Source code at slepc4py/SLEPc/DS.pyx:432

setRefined(ref)#

Set a flag to indicate that refined vectors must be computed.

Logically collective.

Parameters:

ref (bool) – True if refined vectors must be used.

Return type:

None

Notes

Normally the vectors returned in DS.MatType.X are eigenvectors of the projected matrix. With this flag activated, vectors() will return the right singular vector of the smallest singular value of matrix \(\hat A - \eta I\), where \(\hat A\) is the extended matrix (with extra row) and \(\eta\) is the Ritz value. This is used in the refined Ritz approximation.

The default is False.

Source code at slepc4py/SLEPc/DS.pyx:705

setSVDDimensions(m)#

Set the number of columns of a DS of type SVD.

Logically collective.

Parameters:

m (int) – The number of columns.

Return type:

None

Notes

This call is complementary to setDimensions(), to provide a dimension that is specific to this DS.Type.

Source code at slepc4py/SLEPc/DS.pyx:972

setState(state)#

Set the state of the DS object.

Logically collective.

Parameters:

state (StateType) – The new state.

Return type:

None

Notes

The state indicates that the dense system is in an initial state (raw), in an intermediate state (such as tridiagonal, Hessenberg or Hessenberg-triangular), in a condensed state (such as diagonal, Schur or generalized Schur), or in a truncated state.

The state is automatically changed in functions such as solve() or truncate(). This function is normally used to return to the raw state when the condensed structure is destroyed, or to indicate that solve() must start with a problem that already has an intermediate form.

Source code at slepc4py/SLEPc/DS.pyx:381

setType(ds_type)#

Set the type for the DS object.

Logically collective.

Parameters:

ds_type (Type | str) – The direct solver type to be used.

Return type:

None

See also

getType, DSSetType

Source code at slepc4py/SLEPc/DS.pyx:193

solve()#

Solve the problem.

Logically collective.

Returns:

Eigenvalues or singular values.

Return type:

ArrayScalar

See also

DSSolve

Source code at slepc4py/SLEPc/DS.pyx:924

truncate(n, trim=False)#

Truncate the system represented in the DS object.

Logically collective.

Parameters:
  • n (int) – The new size.

  • trim (bool) – A flag to indicate if the factorization must be trimmed.

Return type:

None

Source code at slepc4py/SLEPc/DS.pyx:753

updateExtraRow()#

Ensure that the extra row gets up-to-date after a call to DS.solve().

Logically collective.

Perform all necessary operations so that the extra row gets up-to-date after a call to DS.solve().

See also

DSUpdateExtraRow

Source code at slepc4py/SLEPc/DS.pyx:774

Return type:

None

vectors(matname=X)#

Compute vectors associated to the dense system such as eigenvectors.

Logically collective.

Parameters:

matname – The matrix, used to indicate which vectors are required.

Return type:

None

See also

DSVectors

Source code at slepc4py/SLEPc/DS.pyx:952

view(viewer=None)#

Print the DS data structure.

Collective.

Parameters:

viewer (Viewer | None) – Visualization context; if not provided, the standard output is used.

Return type:

None

See also

DSView

Source code at slepc4py/SLEPc/DS.pyx:127

Attributes Documentation

block_size#

The block size.

Source code at slepc4py/SLEPc/DS.pyx:1218

compact#

Compact storage of matrices.

Source code at slepc4py/SLEPc/DS.pyx:1232

extra_row#

If the matrix has one extra row.

Source code at slepc4py/SLEPc/DS.pyx:1239

method#

The method to be used to solve the problem.

Source code at slepc4py/SLEPc/DS.pyx:1225

parallel#

The mode of operation in parallel runs.

Source code at slepc4py/SLEPc/DS.pyx:1211

refined#

If refined vectors must be computed.

Source code at slepc4py/SLEPc/DS.pyx:1246

state#

The state of the DS object.

Source code at slepc4py/SLEPc/DS.pyx:1204