def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_2 = {
'name' : 'lobpcg',
'kind' : 'eig.scipy_lobpcg',
'i_max' : 20,
'n_eigs' : 5,
'eps_a' : None,
'largest' : True,
'precond' : None,
'verbosity' : 0,
}
"""
get = make_get_conf(conf, kwargs)
common = EigenvalueSolver.process_conf(conf)
return Struct(i_max=get('i_max', 20),
n_eigs=get('n_eigs', None),
eps_a=get('eps_a', None),
largest=get('largest', True),
precond=get('precond', None),
verbosity=get('verbosity', 0)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_120 = {
'name' : 'ls120',
'kind' : 'ls.petsc',
'method' : 'cg', # ksp_type
'precond' : 'icc', # pc_type
'precond_side' : 'left', # ksp_pc_side
'eps_a' : 1e-12, # abstol
'eps_r' : 1e-12, # rtol
'eps_d' : 1e5, # divtol
'i_max' : 1000, # maxits
}
"""
get = make_get_conf(conf, kwargs)
common = LinearSolver.process_conf(conf)
return Struct(method=get('method', 'cg'),
precond=get('precond', 'icc'),
precond_side=get('precond_side', None),
i_max=get('i_max', 100),
eps_a=get('eps_a', 1e-8),
eps_r=get('eps_r', 1e-8),
eps_d=get('eps_d', 1e5)) + common
def process_conf(conf, kwargs):
"""
Setup solver configuration options.
Example configuration::
solvers = {
'ls': ('ls.schur_generalized',
{'blocks':
{'u': ['displacement1', 'displacement2'],
'v': ['velocity1', 'velocity2'],
'w': ['pressure1', 'pressure2'],
},
'function': my_schur,
'needs_problem_instance': True,
})
}
"""
get = make_get_conf(conf, kwargs)
common = ScipyDirect.process_conf(conf, kwargs)
return Struct(blocks=get('blocks', None,
'missing "blocks" in options!'),
function=get('function', None,
'missing "function" in options!'),
needs_problem_instance=True) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_1 = {
'name' : 'ls',
'kind' : 'ls.petsc_parallel',
'log_dir' : '.', # Store logs here.
'n_proc' : 5, # Number of processes to run.
'method' : 'cg', # ksp_type
'precond' : 'bjacobi', # pc_type
'sub_precond' : 'icc', # sub_pc_type
'eps_a' : 1e-12, # abstol
'eps_r' : 1e-12, # rtol
'eps_d' : 1e5, # divtol
'i_max' : 1000, # maxits
}
"""
get = make_get_conf(conf, kwargs)
common = PETScKrylovSolver.process_conf(conf, kwargs)
return Struct(log_dir=get('log_dir', '.'),
n_proc=get('n_proc', 1),
sub_precond=get('sub_precond', 'icc')) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_2 = {
'name' : 'lobpcg',
'kind' : 'eig.scipy_lobpcg',
'i_max' : 20,
'n_eigs' : 5,
'eps_a' : None,
'largest' : True,
'precond' : None,
'verbosity' : 0,
}
"""
get = make_get_conf(conf, kwargs)
common = EigenvalueSolver.process_conf(conf)
return Struct(i_max=get('i_max', 20),
n_eigs=get('n_eigs', None),
eps_a=get('eps_a', None),
largest=get('largest', True),
precond=get('precond', None),
verbosity=get('verbosity', 0)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_2 = {
'name' : 'eigen1',
'kind' : 'eig.pysparse',
'i_max' : 150,
'eps_a' : 1e-5,
'tau' : -10.0,
'method' : 'qmrs',
'verbosity' : 0,
'strategy' : 1,
}
"""
get = make_get_conf(conf, kwargs)
common = EigenvalueSolver.process_conf(conf)
return Struct(i_max=get('i_max', 100),
n_eigs=get('n_eigs', 5),
eps_a=get('eps_a', 1e-5),
tau=get('tau', 0.0),
method=get('method', 'qmrs'),
verbosity=get('verbosity', 0),
strategy=get('strategy', 1)) + common
def process_conf(conf, kwargs):
"""
Missing items are left to scipy defaults. Unused options are ignored.
Example configuration, all items::
solver_1 = {
'name' : 'broyden',
'kind' : 'nls.scipy_broyden_like',
'method' : 'broyden3',
'i_max' : 10,
'alpha' : 0.9,
'M' : 5,
'w0' : 0.1,
'verbose' : True,
}
"""
get = make_get_conf(conf, kwargs)
common = NonlinearSolver.process_conf(conf)
return Struct(method=get('method', 'broyden3'),
i_max=get('i_max', 10),
alpha=get('alpha', 0.9),
M=get('M', 5),
w0=get('w0', 0.1),
verbose=get('verbose', False)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_1 = {
'name' : 'ls',
'kind' : 'ls.petsc_parallel',
'n_proc' : 5, # Number of processes to run.
'method' : 'cg', # ksp_type
'precond' : 'bjacobi', # pc_type
'sub_precond' : 'icc', # sub_pc_type
'eps_a' : 1e-12, # abstol
'eps_r' : 1e-12, # rtol
'eps_d' : 1e5, # divtol
'i_max' : 1000, # maxits
}
"""
get = make_get_conf(conf, kwargs)
common = PETScKrylovSolver.process_conf(conf, kwargs)
return Struct(n_proc=get('n_proc', 1),
sub_precond=get('sub_precond', 'icc')) + common
def process_conf(conf, kwargs):
"""
Setup solver configuration options.
Example configuration::
solvers = {
'ls': ('ls.cm_pb',
{'others': ['acoustic_subproblem.py'],
'coupling_variables': ['g'],
'needs_problem_instance': True,
})
}
"""
get = make_get_conf(conf, kwargs)
common = ScipyDirect.process_conf(conf, kwargs)
return (
Struct(
others=get("others", None, 'missing "others" in options!'),
coupling_variables=get("coupling_variables", None, 'missing "coupling_variables"!'),
needs_problem_instance=True,
)
+ common
)
def process_conf(conf, kwargs):
"""
Setup solver configuration options.
Example configuration::
solvers = {
'ls': ('ls.schur_generalized',
{'blocks':
{'u': ['displacement1', 'displacement2'],
'v': ['velocity1', 'velocity2'],
'w': ['pressure1', 'pressure2'],
},
'function': my_schur,
'needs_problem_instance': True,
})
}
"""
get = make_get_conf(conf, kwargs)
common = ScipyDirect.process_conf(conf, kwargs)
return Struct(
blocks=get('blocks', None, 'missing "blocks" in options!'),
function=get('function', None, 'missing "function" in options!'),
needs_problem_instance=True) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_110 = {
'name' : 'ls110',
'kind' : 'ls.scipy_iterative',
'method' : 'cg',
'precond' : None,
'callback' : None,
'i_max' : 1000,
'eps_r' : 1e-12,
}
"""
get = make_get_conf(conf, kwargs)
common = LinearSolver.process_conf(conf)
return Struct(method=get('method', 'cg'),
precond=get('precond', None),
callback=get('callback', None),
i_max=get('i_max', 100),
eps_a=None,
eps_r=get('eps_r', 1e-8)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_102 = {
'name' : 'ls102',
'kind' : 'ls.pyamg',
'method' : 'smoothed_aggregation_solver',
'accel' : 'cg'
'eps_r' : 1e-12,
}
"""
get = make_get_conf(conf, kwargs)
common = LinearSolver.process_conf(conf)
return (
Struct(
method=get("method", "smoothed_aggregation_solver"),
accel=get("accel", None),
i_max=None,
eps_a=None,
eps_r=get("eps_r", 1e-8),
)
+ common
)
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_1100 = {
'name' : 'dls1100',
'kind' : 'ls.scipy_direct',
'method' : 'superlu',
'presolve' : False,
'warn' : True,
}
"""
get = make_get_conf(conf, kwargs)
common = LinearSolver.process_conf(conf)
return (
Struct(
method=get("method", "auto"),
presolve=get("presolve", False),
warn=get("warn", True),
i_max=None,
eps_a=None,
eps_r=None,
)
+ common
)
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_2 = {
'name' : 'eigen1',
'kind' : 'eig.pysparse',
'i_max' : 150,
'eps_a' : 1e-5,
'tau' : -10.0,
'method' : 'qmrs',
'verbosity' : 0,
'strategy' : 1,
}
"""
get = make_get_conf(conf, kwargs)
common = EigenvalueSolver.process_conf(conf)
return Struct(i_max=get('i_max', 100),
eps_a=get('eps_a', 1e-5),
tau=get('tau', 0.0),
method=get('method', 'qmrs'),
verbosity=get('verbosity', 0),
strategy=get('strategy', 1)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_110 = {
'name' : 'ls110',
'kind' : 'ls.scipy_iterative',
'method' : 'cg',
'precond' : None,
'callback' : None,
'i_max' : 1000,
'eps_r' : 1e-12,
}
"""
get = make_get_conf(conf, kwargs)
common = LinearSolver.process_conf(conf)
return Struct(method=get('method', 'cg'),
precond=get('precond', None),
callback=get('callback', None),
i_max=get('i_max', 100),
eps_a=None,
eps_r=get('eps_r', 1e-8)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_120 = {
'name' : 'ls120',
'kind' : 'ls.petsc',
'method' : 'cg', # ksp_type
'precond' : 'icc', # pc_type
'precond_side' : 'left', # ksp_pc_side
'eps_a' : 1e-12, # abstol
'eps_r' : 1e-12, # rtol
'eps_d' : 1e5, # divtol
'i_max' : 1000, # maxits
}
"""
get = make_get_conf(conf, kwargs)
common = LinearSolver.process_conf(conf)
return Struct(method=get('method', 'cg'),
precond=get('precond', 'icc'),
precond_side=get('precond_side', None),
i_max=get('i_max', 100),
eps_a=get('eps_a', 1e-8),
eps_r=get('eps_r', 1e-8),
eps_d=get('eps_d', 1e5)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_1 = {
'name' : 'oseen',
'kind' : 'nls.oseen',
'needs_problem_instance' : True,
'stabil_mat' : 'stabil',
'adimensionalize' : False,
'check_navier_stokes_rezidual' : False,
'i_max' : 10,
'eps_a' : 1e-8,
'eps_r' : 1.0,
'macheps' : 1e-16,
'lin_red' : 1e-2, # Linear system error < (eps_a * lin_red).
'log' : {'text' : 'oseen_log.txt',
'plot' : 'oseen_log.png'},
}
"""
get = make_get_conf(conf, kwargs)
common = NonlinearSolver.process_conf(conf)
# Compulsory.
needs_problem_instance = get('needs_problem_instance', True)
if not needs_problem_instance:
msg = 'set solver option "needs_problem_instance" to True!'
raise ValueError(msg)
stabil_mat = get('stabil_mat', None, 'missing "stabil_mat" in options!')
# With defaults.
adimensionalize = get('adimensionalize', False)
if adimensionalize:
raise NotImplementedError
check = get('check_navier_stokes_rezidual', False)
log = get_logging_conf(conf)
log = Struct(name='log_conf', **log)
is_any_log = (log.text is not None) or (log.plot is not None)
return Struct(needs_problem_instance=needs_problem_instance,
stabil_mat=stabil_mat,
adimensionalize=adimensionalize,
check_navier_stokes_rezidual=check,
i_max=get('i_max', 1),
eps_a=get('eps_a', 1e-10),
eps_r=get('eps_r', 1.0),
macheps=get('macheps', nm.finfo(nm.float64).eps),
lin_red=get('lin_red', 1.0),
lin_precision=get('lin_precision', None),
log=log,
is_any_log=is_any_log) + common
def process_conf(conf, kwargs):
"""
Process configuration options.
"""
get = make_get_conf(conf, kwargs)
common = SimpleTimeSteppingSolver.process_conf(conf, kwargs)
return Struct(mass=get('mass', None, 'missing "mass" in options!'),
lumped=get('lumped', False)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values for a linear problem.
Example configuration, all items::
solver_1 = {
'name' : 'newton',
'kind' : 'nls.newton',
'i_max' : 2,
'eps_a' : 1e-8,
'eps_r' : 1e-2,
'macheps' : 1e-16,
'lin_red' : 1e-2, # Linear system error < (eps_a * lin_red).
'lin_precision' : None,
'ls_red' : 0.1,
'ls_red_warp' : 0.001,
'ls_on' : 0.99999,
'ls_min' : 1e-5,
'give_up_warp' : False,
'check' : 0,
'delta' : 1e-6,
'is_plot' : False,
'log' : None, # 'nonlinear' or 'linear' (ignore i_max)
'problem' : 'nonlinear',
}
"""
get = make_get_conf(conf, kwargs)
common = NonlinearSolver.process_conf(conf)
log = get_logging_conf(conf)
log = Struct(name="log_conf", **log)
is_any_log = (log.text is not None) or (log.plot is not None)
return (
Struct(
i_max=get("i_max", 1),
eps_a=get("eps_a", 1e-10),
eps_r=get("eps_r", 1.0),
macheps=get("macheps", nm.finfo(nm.float64).eps),
lin_red=get("lin_red", 1.0),
lin_precision=get("lin_precision", None),
ls_red=get("ls_red", 0.1),
ls_red_warp=get("ls_red_warp", 0.001),
ls_on=get("ls_on", 0.99999),
ls_min=get("ls_min", 1e-5),
give_up_warp=get("give_up_warp", False),
check=get("check", 0),
delta=get("delta", 1e-6),
is_plot=get("is_plot", False),
problem=get("problem", "nonlinear"),
log=log,
is_any_log=is_any_log,
)
+ common
)
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_0 = {
'name' : 'fmin_sd',
'kind' : 'opt.fmin_sd',
'i_max' : 10,
'eps_rd' : 1e-5, # Relative delta of objective function
'eps_of' : 1e-4,
'eps_ofg' : 1e-8,
'norm' : nm.Inf,
'ls' : True, # Linesearch.
'ls_method' : 'backtracking', # 'backtracking' or 'full'
'ls0' : 0.25,
'ls_red' : 0.5,
'ls_red_warp' : 0.1,
'ls_on' : 0.99999,
'ls_min' : 1e-5,
'check' : 0,
'delta' : 1e-6,
'output' : None, # 'itc'
'log' : {'text' : 'output/log.txt',
'plot' : 'output/log.png'},
'yscales' : ['linear', 'log', 'log', 'linear'],
}
"""
get = make_get_conf(conf, kwargs)
common = OptimizationSolver.process_conf(conf)
log = get_logging_conf(conf)
log = Struct(name='log_conf', **log)
is_any_log = (log.text is not None) or (log.plot is not None)
return Struct(i_max=get('i_max', 10),
eps_rd=get('eps_rd', 1e-5),
eps_of=get('eps_of', 1e-4),
eps_ofg=get('eps_ofg', 1e-8),
norm=get('norm', nm.Inf),
ls=get('ls', True),
ls_method=get('ls_method', 'backtracking'),
ls0=get('ls0', 0.25),
ls_red=get('ls_red', 0.5),
ls_red_warp=get('ls_red_warp', 0.1),
ls_on=get('ls_on', 0.99999),
ls_min=get('ls_min', 1e-5),
check=get('check', 0),
delta=get('delta', 1e-6),
output=get('output', None),
yscales=get('yscales',
['linear', 'log', 'log', 'linear']),
log=log,
is_any_log=is_any_log) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_0 = {
'name' : 'fmin_sd',
'kind' : 'opt.fmin_sd',
'i_max' : 10,
'eps_rd' : 1e-5, # Relative delta of objective function
'eps_of' : 1e-4,
'eps_ofg' : 1e-8,
'norm' : nm.Inf,
'ls' : True, # Linesearch.
'ls_method' : 'backtracking', # 'backtracking' or 'full'
'ls0' : 0.25,
'ls_red' : 0.5,
'ls_red_warp' : 0.1,
'ls_on' : 0.99999,
'ls_min' : 1e-5,
'check' : 0,
'delta' : 1e-6,
'output' : None, # 'itc'
'log' : {'text' : 'output/log.txt',
'plot' : 'output/log.png'},
'yscales' : ['linear', 'log', 'log', 'linear'],
}
"""
get = make_get_conf(conf, kwargs)
common = OptimizationSolver.process_conf(conf)
log = get_logging_conf(conf)
log = Struct(name='log_conf', **log)
is_any_log = (log.text is not None) or (log.plot is not None)
return Struct(i_max=get('i_max', 10),
eps_rd=get('eps_rd', 1e-5),
eps_of=get('eps_of', 1e-4),
eps_ofg=get('eps_ofg', 1e-8),
norm=get('norm', nm.Inf),
ls=get('ls', True),
ls_method=get('ls_method', 'backtracking'),
ls0=get('ls0', 0.25),
ls_red=get('ls_red', 0.5),
ls_red_warp=get('ls_red_warp', 0.1),
ls_on=get('ls_on', 0.99999),
ls_min=get('ls_min', 1e-5),
check=get('check', 0),
delta=get('delta', 1e-6),
output=get('output', None),
yscales=get('yscales',
['linear', 'log', 'log', 'linear']),
log=log,
is_any_log=is_any_log) + common
def process_conf(conf, kwargs):
"""
Process configuration options.
"""
get = make_get_conf(conf, kwargs)
common = SimpleTimeSteppingSolver.process_conf(conf, kwargs)
return Struct(mass=get('mass', None,
'missing "mass" in options!'),
lumped=get('lumped', False)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values for a linear problem.
Example configuration, all items::
solver_1 = {
'name' : 'newton',
'kind' : 'nls.newton',
'i_max' : 2,
'eps_a' : 1e-8,
'eps_r' : 1e-2,
'eps_mode' : 'or',
'macheps' : 1e-16,
'lin_red' : 1e-2, # Linear system error < (eps_a * lin_red).
'lin_precision' : None,
'ls_on' : 0.99999,
'ls_red' : 0.1,
'ls_red_warp' : 0.001,
'ls_min' : 1e-5,
'give_up_warp' : False,
'check' : 0,
'delta' : 1e-6,
'log' : None, # 'nonlinear' or 'linear' (ignore i_max)
'problem' : 'nonlinear',
}
"""
get = make_get_conf(conf, kwargs)
common = NonlinearSolver.process_conf(conf)
log = get_logging_conf(conf)
log = Struct(name='log_conf', **log)
is_any_log = (log.text is not None) or (log.plot is not None)
return Struct(i_max=get('i_max', 1),
eps_a=get('eps_a', 1e-10),
eps_r=get('eps_r', 1.0),
eps_mode=get('eps_mode', 'and'),
macheps=get('macheps',
nm.finfo(nm.float64).eps),
lin_red=get('lin_red', 1.0),
lin_precision=get('lin_precision', None),
ls_red=get('ls_red', 0.1),
ls_red_warp=get('ls_red_warp', 0.001),
ls_on=get('ls_on', 0.99999),
ls_min=get('ls_min', 1e-5),
give_up_warp=get('give_up_warp', False),
check=get('check', 0),
delta=get('delta', 1e-6),
problem=get('problem', 'nonlinear'),
log=log,
is_any_log=is_any_log) + common
def process_conf(conf, kwargs):
"""
Process configuration options.
"""
get = make_get_conf(conf, kwargs)
common = TimeSteppingSolver.process_conf(conf)
return Struct(t0=get('t0', 0.0),
t1=get('t1', 1.0),
dt=get('dt', None),
n_step=get('n_step', 10),
quasistatic=get('quasistatic', False)) + common
def process_conf(conf, kwargs):
"""
Process configuration options.
"""
get = make_get_conf(conf, kwargs)
common = TimeSteppingSolver.process_conf(conf)
return Struct(t0=get('t0', 0.0),
t1=get('t1', 1.0),
dt=get('dt', None),
n_step=get('n_step', 10),
quasistatic=get('quasistatic', False)) + common
def process_conf(conf, kwargs):
"""
Process configuration options.
"""
get = make_get_conf(conf, kwargs)
common = SimpleTimeSteppingSolver.process_conf(conf, kwargs)
adt = Struct(red_factor=get('dt_red_factor', 0.2),
red_max=get('dt_red_max', 1e-3),
inc_factor=get('dt_inc_factor', 1.25),
inc_on_iter=get('dt_inc_on_iter', 4),
inc_wait=get('dt_inc_wait', 5),
red=1.0, wait=0, dt0=0.0)
return Struct(adapt_fun=get('adapt_fun', adapt_time_step),
adt=adt) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_20 = {
'name' : 'eigen2',
'kind' : 'eig.sgscipy',
'force_n_eigs' : True,
}
"""
get = make_get_conf(conf, kwargs)
common = EigenvalueSolver.process_conf(conf)
return Struct(force_n_eigs=get('force_n_eigs', False)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_20 = {
'name' : 'eigen2',
'kind' : 'eig.sgscipy',
'force_n_eigs' : True,
}
"""
get = make_get_conf(conf, kwargs)
common = EigenvalueSolver.process_conf(conf)
return Struct(force_n_eigs=get('force_n_eigs', False)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_1 = {
'name' : 'semismooth_newton',
'kind' : 'nls.semismooth_newton',
'semismooth' : True,
'i_max' : 10,
'eps_a' : 1e-8,
'eps_r' : 1e-2,
'macheps' : 1e-16,
'lin_red' : 1e-2, # Linear system error < (eps_a * lin_red).
'ls_red_reg' : 0.1,
'ls_red_alt' : 0.01,
'ls_red_warp' : 0.001,
'ls_on' : 0.9,
'ls_min' : 1e-10,
'log' : {'plot' : 'convergence.png'},
}
"""
get = make_get_conf(conf, kwargs)
common = NonlinearSolver.process_conf(conf)
log = get_logging_conf(conf)
log = Struct(name='log_conf', **log)
is_any_log = (log.text is not None) or (log.plot is not None)
return Struct(semismooth=get('semismooth', True),
i_max=get('i_max', 1),
eps_a=get('eps_a', 1e-10),
eps_r=get('eps_r', 1.0),
macheps=get('macheps',
nm.finfo(nm.float64).eps),
lin_red=get('lin_red', 1.0),
ls_red=get('ls_red', 0.1),
ls_red_warp=get('ls_red_warp', 0.001),
ls_on=get('ls_on', 0.99999),
ls_min=get('ls_min', 1e-5),
log=log,
is_any_log=is_any_log) + common
def process_conf(conf, kwargs):
"""
Process configuration options.
"""
get = make_get_conf(conf, kwargs)
common = SimpleTimeSteppingSolver.process_conf(conf, kwargs)
adt = Struct(red_factor=get('dt_red_factor', 0.2),
red_max=get('dt_red_max', 1e-3),
inc_factor=get('dt_inc_factor', 1.25),
inc_on_iter=get('dt_inc_on_iter', 4),
inc_wait=get('dt_inc_wait', 5),
red=1.0,
wait=0,
dt0=0.0)
return Struct(adapt_fun=get('adapt_fun', adapt_time_step),
adt=adt) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_1 = {
'name' : 'semismooth_newton',
'kind' : 'nls.semismooth_newton',
'semismooth' : True,
'i_max' : 10,
'eps_a' : 1e-8,
'eps_r' : 1e-2,
'macheps' : 1e-16,
'lin_red' : 1e-2, # Linear system error < (eps_a * lin_red).
'ls_red_reg' : 0.1,
'ls_red_alt' : 0.01,
'ls_red_warp' : 0.001,
'ls_on' : 0.9,
'ls_min' : 1e-10,
'log' : {'plot' : 'convergence.png'},
}
"""
get = make_get_conf(conf, kwargs)
common = NonlinearSolver.process_conf(conf)
log = get_logging_conf(conf)
log = Struct(name='log_conf', **log)
is_any_log = (log.text is not None) or (log.plot is not None)
return Struct(semismooth=get('semismooth', True),
i_max=get('i_max', 1),
eps_a=get('eps_a', 1e-10),
eps_r=get('eps_r', 1.0),
macheps=get('macheps', nm.finfo(nm.float64).eps),
lin_red=get('lin_red', 1.0),
ls_red=get('ls_red', 0.1),
ls_red_warp=get('ls_red_warp', 0.001),
ls_on=get('ls_on', 0.99999),
ls_min=get('ls_min', 1e-5),
log=log,
is_any_log=is_any_log) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_102 = {
'name' : 'ls102',
'kind' : 'ls.pyamg',
'method' : 'smoothed_aggregation_solver',
'accel' : 'cg'
'eps_r' : 1e-12,
}
"""
get = make_get_conf(conf, kwargs)
common = LinearSolver.process_conf(conf)
return Struct(method=get('method', 'smoothed_aggregation_solver'),
accel = get('accel', None),
i_max=None, eps_a=None,
eps_r=get('eps_r', 1e-8)) + common
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_1100 = {
'name' : 'dls1100',
'kind' : 'ls.scipy_direct',
'method' : 'superlu',
'presolve' : False,
'warn' : True,
}
"""
get = make_get_conf(conf, kwargs)
common = LinearSolver.process_conf(conf)
return Struct(method=get('method', 'auto'),
presolve=get('presolve', False),
warn=get('warn', True),
i_max=None, eps_a=None, eps_r=None) + common
def process_conf(conf, kwargs):
"""
Setup solver configuration options.
Example configuration::
solvers = {
'ls': ('ls.cm_pb',
{'others': ['acoustic_subproblem.py'],
'coupling_variables': ['g'],
'needs_problem_instance': True,
})
}
"""
get = make_get_conf(conf, kwargs)
common = ScipyDirect.process_conf(conf, kwargs)
return Struct(others=get('others', None,
'missing "others" in options!'),
coupling_variables=get('coupling_variables', None,
'missing "coupling_variables"!'),
needs_problem_instance=True) + common
def process_conf(conf, kwargs):
"""
Setup solver configuration options.
Example configuration::
solvers = {
'ls': ('ls.schur_complement',
{'eliminate': ['displacement'],
'keep': ['pressure'],
'needs_problem_instance': True,
})
}
"""
get = make_get_conf(conf, kwargs)
conf.blocks = {'1': get('eliminate', None,
'missing "eliminate" in options!'),
'2': get('keep', None,
'missing "keep" in options!'),}
conf.function = SchurComplement.schur_fun
common = SchurGeneralized.process_conf(conf, kwargs)
return common
def process_conf(conf, kwargs):
"""
Setup solver configuration options.
Example configuration::
solvers = {
'ls': ('ls.schur_complement',
{'eliminate': ['displacement'],
'keep': ['pressure'],
'needs_problem_instance': True,
})
}
"""
get = make_get_conf(conf, kwargs)
conf.blocks = {
'1': get('eliminate', None, 'missing "eliminate" in options!'),
'2': get('keep', None, 'missing "keep" in options!'),
}
conf.function = SchurComplement.schur_fun
common = SchurGeneralized.process_conf(conf, kwargs)
return common
def process_conf(conf, kwargs):
"""
Missing items are left to SciPy defaults. Unused options are ignored.
Besides 'i_max', use option names according to scipy.optimize
function arguments. The 'i_max' translates either to 'maxiter'
or 'maxfun' as available.
Example configuration::
solver_1 = {
'name' : 'fmin',
'kind' : 'nls.scipy_fmin_like',
'method' : 'bfgs',
'i_max' : 10,
'verbose' : True,
'gtol' : 1e-7
}
"""
get = make_get_conf(conf, kwargs)
common = OptimizationSolver.process_conf(conf)
opts = Struct(method=get('method', 'fmin'),
i_max=get('i_max', 10),
verbose=get('verbose', False)) + common
other = {}
keys = opts.to_dict().keys()
for key, val in conf.to_dict().iteritems():
if key not in keys:
other[key] = val
return opts + Struct(**other)
def process_conf(conf, kwargs):
"""
Missing items are left to SciPy defaults. Unused options are ignored.
Besides 'i_max', use option names according to scipy.optimize
function arguments. The 'i_max' translates either to 'maxiter'
or 'maxfun' as available.
Example configuration::
solver_1 = {
'name' : 'fmin',
'kind' : 'nls.scipy_fmin_like',
'method' : 'bfgs',
'i_max' : 10,
'verbose' : True,
'gtol' : 1e-7
}
"""
get = make_get_conf(conf, kwargs)
common = OptimizationSolver.process_conf(conf)
opts = Struct(method=get('method', 'fmin'),
i_max=get('i_max', 10),
verbose=get('verbose', False)) + common
other = {}
keys = opts.to_dict().keys()
for key, val in conf.to_dict().iteritems():
if key not in keys:
other[key] = val
return opts + Struct(**other)
def process_conf(conf, kwargs):
"""
Missing items are set to default values.
Example configuration, all items::
solver_1 = {
'name' : 'oseen',
'kind' : 'nls.oseen',
'needs_problem_instance' : True,
'stabil_mat' : 'stabil',
'adimensionalize' : False,
'check_navier_stokes_rezidual' : False,
'i_max' : 10,
'eps_a' : 1e-8,
'eps_r' : 1.0,
'macheps' : 1e-16,
'lin_red' : 1e-2, # Linear system error < (eps_a * lin_red).
'log' : {'text' : 'oseen_log.txt',
'plot' : 'oseen_log.png'},
}
"""
get = make_get_conf(conf, kwargs)
common = NonlinearSolver.process_conf(conf)
# Compulsory.
needs_problem_instance = get('needs_problem_instance', True)
if not needs_problem_instance:
msg = 'set solver option "needs_problem_instance" to True!'
raise ValueError(msg)
stabil_mat = get('stabil_mat', None,
'missing "stabil_mat" in options!')
# With defaults.
adimensionalize = get('adimensionalize', False)
if adimensionalize:
raise NotImplementedError
check = get('check_navier_stokes_rezidual', False)
log = get_logging_conf(conf)
log = Struct(name='log_conf', **log)
is_any_log = (log.text is not None) or (log.plot is not None)
return Struct(needs_problem_instance=needs_problem_instance,
stabil_mat=stabil_mat,
adimensionalize=adimensionalize,
check_navier_stokes_rezidual=check,
i_max=get('i_max', 1),
eps_a=get('eps_a', 1e-10),
eps_r=get('eps_r', 1.0),
macheps=get('macheps',
nm.finfo(nm.float64).eps),
lin_red=get('lin_red', 1.0),
lin_precision=get('lin_precision', None),
log=log,
is_any_log=is_any_log) + common
