本文整理汇总了Python中scipy.sparse.linalg.gmres方法的典型用法代码示例。如果您正苦于以下问题：Python linalg.gmres方法的具体用法？Python linalg.gmres怎么用？Python linalg.gmres使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在模块scipy.sparse.linalg的用法示例。

在下文中一共展示了linalg.gmres方法的16个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Python代码示例。

示例1: __init__

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def __init__(self, A, M, sigma, ifunc=gmres, tol=0):

if tol <= 0:

# when tol=0, ARPACK uses machine tolerance as calculated

# by LAPACK's _LAMCH function. We should match this

tol = 2 * np.finfo(A.dtype).eps

self.A = A

self.M = M

self.sigma = sigma

self.ifunc = ifunc

self.tol = tol

x = np.zeros(A.shape[1])

if M is None:

dtype = self.mult_func_M_None(x).dtype

self.OP = LinearOperator(self.A.shape,

self.mult_func_M_None,

dtype=dtype)

else:

dtype = self.mult_func(x).dtype

self.OP = LinearOperator(self.A.shape,

self.mult_func,

dtype=dtype)

LinearOperator.__init__(self, A.shape, self._matvec, dtype=dtype)

开发者ID:ktraunmueller，项目名称:Computable，代码行数:25，

示例2: solve_system

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def solve_system(self,rhs,factor,u0,t):

"""

Simple linear solver for (I-dtA)u = rhs

Args:

rhs: right-hand side for the nonlinear system

factor: abbrev. for the node-to-node stepsize (or any other factor required)

u0: initial guess for the iterative solver (not used here so far)

t: current time (e.g. for time-dependent BCs)

Returns:

solution as mesh

"""

b = rhs.values.flatten()

# NOTE: A = -M, therefore solve Id + factor*M here

sol, info = LA.gmres( self.Id + factor*self.c_s*self.M, b, x0=u0.values.flatten(), tol=1e-13, restart=10, maxiter=20)

me = mesh(self.nvars)

me.values = unflatten(sol, 3, self.N[0], self.N[1])

return me

开发者ID:Parallel-in-Time，项目名称:pySDC，代码行数:23，

示例3: solve_system

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def solve_system(self, rhs, factor, u0, t):

"""

Simple linear solver for (I-factor*A)u = rhs

Args:

rhs (dtype_f): right-hand side for the linear system

factor (float): abbrev. for the local stepsize (or any other factor required)

u0 (dtype_u): initial guess for the iterative solver

t (float): current time (e.g. for time-dependent BCs)

Returns:

dtype_u: solution as mesh

"""

me = self.dtype_u(self.init)

if self.params.direct_solver:

me.values = spsolve(self.Id - factor * self.A, rhs.values.flatten())

else:

me.values = gmres(self.Id - factor * self.A, rhs.values.flatten(), x0=u0.values.flatten(),

tol=self.params.lintol, maxiter=self.params.liniter)[0]

me.values = me.values.reshape(self.params.nvars)

return me

开发者ID:Parallel-in-Time，项目名称:pySDC，代码行数:25，

示例4: __init__

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def __init__(self, M, ifunc=gmres, tol=0):

if tol <= 0:

# when tol=0, ARPACK uses machine tolerance as calculated

# by LAPACK's _LAMCH function. We should match this

tol = 2 * np.finfo(M.dtype).eps

self.M = M

self.ifunc = ifunc

self.tol = tol

if hasattr(M, 'dtype'):

self.dtype = M.dtype

else:

x = np.zeros(M.shape[1])

self.dtype = (M * x).dtype

self.shape = M.shape

开发者ID:ryfeus，项目名称:lambda-packs，代码行数:16，

示例5: SetSolver

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def SetSolver(self,linear_solver="direct", linear_solver_type="umfpack",

apply_preconditioner=False, preconditioner="amg_smoothed_aggregation",

iterative_solver_tolerance=1.0e-12, reduce_matrix_bandwidth=False,

geometric_discretisation=None):

"""

input:

linear_solver: [str] type of solver either "direct",

"iterative", "petsc" or "amg"

linear_solver_type [str] type of direct or linear solver to

use, for instance "umfpack", "superlu" or

"mumps" for direct solvers, or "cg", "gmres"

etc for iterative solvers or "amg" for algebraic

multigrid solver. See WhichSolvers method for

the complete set of available linear solvers

preconditioner: [str] either "smoothed_aggregation",

or "ruge_stuben" or "rootnode" for

a preconditioner based on algebraic multigrid

or "ilu" for scipy's spilu linear

operator

geometric_discretisation:

[str] type of geometric discretisation used, for

instance for FEM discretisations this would correspond

to "tri", "quad", "tet", "hex" etc

"""

self.solver_type = linear_solver

self.solver_subtype = "umfpack"

self.iterative_solver_tolerance = iterative_solver_tolerance

self.apply_preconditioner = apply_preconditioner

self.requires_cuthill_mckee = reduce_matrix_bandwidth

self.geometric_discretisation = geometric_discretisation

开发者ID:romeric，项目名称:florence，代码行数:38，

示例6: WhichLinearSolvers

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def WhichLinearSolvers(self):

return {"direct":["superlu", "umfpack", "mumps", "pardiso"],

"iterative":["cg", "bicg", "cgstab", "bicgstab", "gmres", "lgmres"],

"amg":["cg", "bicg", "cgstab", "bicgstab", "gmres", "lgmres"],

"petsc":["cg", "bicgstab", "gmres"]}

开发者ID:romeric，项目名称:florence，代码行数:7，

示例7: gmres_loose

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def gmres_loose(A, b, tol):

"""

gmres with looser termination condition.

"""

b = np.asarray(b)

min_tol = 1000 * np.sqrt(b.size) * np.finfo(b.dtype).eps

return gmres(A, b, tol=max(tol, min_tol), atol=0)

开发者ID:Relph1119，项目名称:GraphicDesignPatternByPython，代码行数:9，

示例8: solve_system

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def solve_system(self, rhs, factor, u0, t):

"""

Simple linear solver for (I-dtA)u = rhs using GMRES

Args:

rhs (dtype_f): right-hand side for the nonlinear system

factor (float): abbrev. for the node-to-node stepsize (or any other factor required)

u0 (dtype_u): initial guess for the iterative solver (not used here so far)

t (float): current time (e.g. for time-dependent BCs)

Returns:

dtype_u: solution as mesh

"""

b = rhs.values.flatten()

cb = Callback()

sol, info = gmres(self.Id - factor * self.M, b, x0=u0.values.flatten(), tol=self.params.gmres_tol_limit,

restart=self.params.gmres_restart, maxiter=self.params.gmres_maxiter, callback=cb)

# If this is a dummy call with factor==0.0, do not log because it should not be counted as a solver call

if factor != 0.0:

self.gmres_logger.add(cb.getcounter())

me = self.dtype_u(self.init)

me.values = unflatten(sol, 4, self.N[0], self.N[1])

return me

开发者ID:Parallel-in-Time，项目名称:pySDC，代码行数:28，

示例9: f_fast_solve

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def f_fast_solve(self, rhs, alpha, u0):

cb = Callback()

sol, info = gmres(self.problem.Id - alpha * self.problem.M, rhs, x0=u0,

tol=self.problem.params.gmres_tol_limit, restart=self.problem.params.gmres_restart,

maxiter=self.problem.params.gmres_maxiter, callback=cb)

if alpha != 0.0:

self.logger.add(cb.getcounter())

return sol

#

# Trapezoidal rule

#

开发者ID:Parallel-in-Time，项目名称:pySDC，代码行数:15，

示例10: f_solve

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def f_solve(self, b, alpha, u0):

cb = Callback()

sol, info = gmres(self.problem.Id - alpha * (self.problem.D_upwind + self.problem.M), b, x0=u0,

tol=self.problem.params.gmres_tol_limit, restart=self.problem.params.gmres_restart,

maxiter=self.problem.params.gmres_maxiter, callback=cb)

if alpha != 0.0:

self.logger.add(cb.getcounter())

return sol

#

# Split-Explicit method

#

开发者ID:Parallel-in-Time，项目名称:pySDC，代码行数:15，

示例11: __init__

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def __init__(self,

A,

drop_tol=0.005,

fill_factor=2.0,

normalize_inplace=False):

# the spilu and gmres functions are most efficient with csc sparse. If the

# matrix is already csc then this will do nothing

A = sp.csc_matrix(A)

n = row_norms(A)

if normalize_inplace:

divide_rows(A, n, inplace=True)

else:

A = divide_rows(A, n, inplace=False).tocsc()

LOGGER.debug(

'computing the ILU decomposition of a %s by %s sparse matrix with %s '

'nonzeros ' % (A.shape + (A.nnz,)))

ilu = spla.spilu(

A,

drop_rule='basic',

drop_tol=drop_tol,

fill_factor=fill_factor)

LOGGER.debug('done')

M = spla.LinearOperator(A.shape, ilu.solve)

self.A = A

self.M = M

self.n = n

开发者ID:treverhines，项目名称:RBF，代码行数:29，

示例12: solve

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def solve(self, b, tol=1.0e-10):

'''

Solve `Ax = b` for `x`

Parameters

----------

b : (n,) array

tol : float, optional

Returns

-------

(n,) array

'''

# solve the system using GMRES and define the callback function to

# print info for each iteration

def callback(res, _itr=[0]):

l2 = np.linalg.norm(res)

LOGGER.debug('GMRES error on iteration %s: %s' % (_itr[0], l2))

_itr[0] += 1

LOGGER.debug('solving the system with GMRES')

x, info = spla.gmres(

self.A,

b/self.n,

tol=tol,

M=self.M,

callback=callback)

LOGGER.debug('finished GMRES with info %s' % info)

return x

开发者ID:treverhines，项目名称:RBF，代码行数:33，

示例13: krylovMethod

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def krylovMethod(self,tol=1e-8):

"""

We obtain ``pi`` by using the :func:``gmres`` solver for the system of linear equations.

It searches in Krylov subspace for a vector with minimal residual. The result is stored in the class attribute ``pi``.

Example

-------

>>> P = np.array([[0.5,0.5],[0.6,0.4]])

>>> mc = markovChain(P)

>>> mc.krylovMethod()

>>> print(mc.pi)

[ 0.54545455 0.45454545]

Parameters

----------

tol : float, optional(default=1e-8)

Tolerance level for the precision of the end result. A lower tolerance leads to more accurate estimate of ``pi``.

Remarks

-------

For large state spaces, this method may not always give a solution.

Code due to http://stackoverflow.com/questions/21308848/

"""

P = self.getIrreducibleTransitionMatrix()

#if P consists of one element, then set self.pi = 1.0

if P.shape == (1, 1):

self.pi = np.array([1.0])

return

size = P.shape[0]

dP = P - eye(size)

#Replace the first equation by the normalizing condition.

A = vstack([np.ones(size), dP.T[1:,:]]).tocsr()

rhs = np.zeros((size,))

rhs[0] = 1

pi, info = gmres(A, rhs, tol=tol)

if info != 0:

raise RuntimeError("gmres did not converge")

self.pi = pi

开发者ID:gvanderheide，项目名称:discreteMarkovChain，代码行数:43，

示例14: gmres_linsolve

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def gmres_linsolve(A, b):

"""

:param A:

:param b:

:return:

"""

x, info = gmres(A, b)

return x

开发者ID:SanPen，项目名称:GridCal，代码行数:11，

示例15: solve_gmres

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def solve_gmres(A, b):

LOG.debug(f"Solve with GMRES for {A}.")

if LOG.isEnabledFor(logging.DEBUG):

counter = Counter()

x, info = ssl.gmres(A, b, atol=1e-6, callback=counter)

LOG.debug(f"End of GMRES after {counter.nb_iter} iterations.")

else:

x, info = ssl.gmres(A, b, atol=1e-6)

if info != 0:

LOG.warning(f"No convergence of the GMRES. Error code: {info}")

return x

开发者ID:mancellin，项目名称:capytaine，代码行数:17，

示例16: gmres_no_fft

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# 需要导入模块: from scipy.sparse import linalg [as 别名]

# 或者: from scipy.sparse.linalg import gmres [as 别名]

def gmres_no_fft(A, b):

LOG.debug(f"Solve with GMRES for {A} without using FFT.")

x, info = ssl.gmres(A.no_toeplitz() if isinstance(A, BlockMatrix) else A, b, atol=1e-6)

if info != 0:

LOG.warning(f"No convergence of the GMRES. Error code: {info}")

return x

开发者ID:mancellin，项目名称:capytaine，代码行数:11，

注：本文中的scipy.sparse.linalg.gmres方法示例整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。