def __init__(self, conf, problem, **kwargs):
NonlinearSolver.__init__(self, conf, **kwargs)
conf = self.conf
log = get_logging_conf(conf)
conf.log = log = Struct(name='log_conf', **log)
conf.is_any_log = (log.text is not None) or (log.plot is not None)
conf.problem = problem
conf = self.conf
if conf.is_any_log:
self.log = Log([[r'$||r||$'], ['iteration'],
[r'$\gamma$', r'$\max(\delta)$', r'$\max(\tau)$']],
xlabels=['', '', 'all iterations'],
ylabels=[r'$||r||$', 'iteration', 'stabilization'],
yscales=['log', 'linear', 'log'],
is_plot=conf.log.plot is not None,
log_filename=conf.log.text,
formats=[['%.8e'], ['%d'],
['%.8e', '%.8e', '%.8e']])
else:
self.log = None
def __init__(self, conf, context=None, **kwargs):
NonlinearSolver.__init__(self, conf, context=context, **kwargs)
conf = self.conf
log = get_logging_conf(conf)
conf.log = log = Struct(name='log_conf', **log)
conf.is_any_log = (log.text is not None) or (log.plot is not None)
conf.problem = context
conf = self.conf
if conf.is_any_log:
self.log = Log([[r'$||r||$'], ['iteration'],
[r'$\gamma$', r'$\max(\delta)$', r'$\max(\tau)$']],
xlabels=['', '', 'all iterations'],
ylabels=[r'$||r||$', 'iteration', 'stabilization'],
yscales=['log', 'linear', 'log'],
is_plot=conf.log.plot is not None,
log_filename=conf.log.text,
formats=[['%.8e'], ['%d'], ['%.8e', '%.8e',
'%.8e']])
else:
self.log = None
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):
"""
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 ):
"""
Missing items are set to default values.
Example configuration, all items::
solver_1 = {
'name' : 'oseen',
'kind' : 'nls.oseen',
'needs_problem_instance' : True,
'stabilization_hook' : 'create_stabil_mat',
'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).
'is_plot' : False,
'log' : {'text' : 'oseen_log.txt',
'plot' : 'oseen_log.png'},
}
"""
get = conf.get_default_attr
# 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)
stabilization_hook = get('stabilization_hook', None,
'missing "stabilization_hook" in options!')
# With defaults.
adimensionalize = get( 'adimensionalize', False )
check_navier_stokes_rezidual = get( 'check_navier_stokes_rezidual',
False )
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 )
is_plot = get( 'is_plot', 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)
common = NonlinearSolver.process_conf( conf )
return Struct( **locals() ) + 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 ):
"""
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).
'ls_red' : 0.1,
'ls_red_warp' : 0.001,
'ls_on' : 0.99999,
'ls_min' : 1e-5,
'check' : 0,
'delta' : 1e-6,
'is_plot' : False,
'log' : None,
# 'nonlinear' or 'linear' (ignore i_max)
'problem' : 'nonlinear',
}
"""
get = conf.get_default_attr
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 )
check = get( 'check', 0 )
delta = get( 'delta', 1e-6)
is_plot = get( 'is_plot', False )
problem = get( 'problem', 'nonlinear' )
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)
common = NonlinearSolver.process_conf( conf )
return Struct( **locals() ) + common
def process_conf(conf):
"""
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 = conf.get_default_attr
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 = {'regular' : get('ls_red_reg', 0.1),
'steepest_descent' : get('ls_red_alt', 0.01)}
ls_red_warp = get('ls_red_warp', 0.001)
ls_on = get('ls_on', 0.99999)
ls_min = get('ls_min', 1e-5)
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)
common = NonlinearSolver.process_conf(conf)
return Struct(**locals()) + 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_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 __init__(self, conf, **kwargs):
OptimizationSolver.__init__(self, conf, **kwargs)
conf = self.conf
log = get_logging_conf(conf)
conf.log = log = Struct(name='log_conf', **log)
conf.is_any_log = (log.text is not None) or (log.plot is not None)
if conf.is_any_log:
self.log = Log([[r'$||\Psi||$'], [r'$||\nabla \Psi||$'],
[r'$\alpha$'], ['iteration']],
xlabels=['', '', 'all iterations', 'all iterations'],
yscales=conf.yscales,
is_plot=conf.log.plot is not None,
log_filename=conf.log.text,
formats=[['%.8e'], ['%.3e'], ['%.3e'], ['%d']])
else:
self.log = None
def __init__(self, conf, **kwargs):
NonlinearSolver.__init__(self, conf, **kwargs)
conf = self.conf
log = get_logging_conf(conf)
conf.log = log = Struct(name='log_conf', **log)
conf.is_any_log = (log.text is not None) or (log.plot is not None)
if conf.is_any_log:
self.log = Log([[r'$||r||$'], ['iteration']],
xlabels=['', 'all iterations'],
ylabels=[r'$||r||$', 'iteration'],
yscales=['log', 'linear'],
is_plot=conf.log.plot is not None,
log_filename=conf.log.text,
formats=[['%.8e'], ['%d']])
else:
self.log = None
def __init__(self, conf, **kwargs):
NonlinearSolver.__init__(self, conf, **kwargs)
conf = self.conf
log = get_logging_conf(conf)
conf.log = log = Struct(name='log_conf', **log)
conf.is_any_log = (log.text is not None) or (log.plot is not None)
if conf.is_any_log:
self.log = Log([[r'$||r||$'], ['iteration']],
xlabels=['', 'all iterations'],
ylabels=[r'$||r||$', 'iteration'],
yscales=['log', 'linear'],
is_plot=conf.log.plot is not None,
log_filename=conf.log.text,
formats=[['%.8e'], ['%d']])
else:
self.log = None
def __init__(self, conf, **kwargs):
OptimizationSolver.__init__(self, conf, **kwargs)
conf = self.conf
log = get_logging_conf(conf)
conf.log = log = Struct(name='log_conf', **log)
conf.is_any_log = (log.text is not None) or (log.plot is not None)
if conf.is_any_log:
self.log = Log(
[[r'$||\Psi||$'], [r'$||\nabla \Psi||$'], [r'$\alpha$'],
['iteration']],
xlabels=['', '', 'all iterations', 'all iterations'],
yscales=conf.yscales,
is_plot=conf.log.plot is not None,
log_filename=conf.log.text,
formats=[['%.8e'], ['%.3e'], ['%.3e'], ['%d']])
else:
self.log = None
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
