def run_userfcn(userfcn, stage, *args):
"""Runs the userfcn callbacks for a given stage.
Example::
ppc = om.get_mpc()
om = run_userfcn(ppc['userfcn'], 'formulation', om)
@param userfcn: the 'userfcn' field of ppc, populated by L{add_userfcn}
@param stage: the name of the callback stage begin executed
(additional arguments) some stages require additional arguments.
@see: L{add_userfcn}, L{remove_userfcn}, L{toggle_reserves},
L{toggle_iflims}, L{runopf_w_res}.
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
rv = args[0]
if (len(userfcn) > 0) and (stage in userfcn):
for k in range(len(userfcn[stage])):
if 'args' in userfcn[stage][k]:
args = userfcn[stage][k]['args']
else:
args = []
if stage in ['ext2int', 'formulation', 'int2ext']:
# ppc = userfcn_*_ext2int(ppc, args)
# om = userfcn_*_formulation(om, args)
# results = userfcn_*_int2ext(results, args)
rv = userfcn[stage][k]['fcn'](rv, args)
elif stage in ['printpf', 'savecase']:
# results = userfcn_*_printpf(results, fd, ppopt, args)
# ppc = userfcn_*_savecase(mpc, fd, prefix, args)
rv = feval(userfcn[stage][k]['fcn'], rv, args[1], args[2], args)
return rv
def run_userfcn(userfcn, stage, *args):
"""Runs the userfcn callbacks for a given stage.
Example::
ppc = om.get_mpc()
om = run_userfcn(ppc['userfcn'], 'formulation', om)
@param userfcn: the 'userfcn' field of ppc, populated by L{add_userfcn}
@param stage: the name of the callback stage begin executed
(additional arguments) some stages require additional arguments.
@see: L{add_userfcn}, L{remove_userfcn}, L{toggle_reserves},
L{toggle_iflims}, L{runopf_w_res}.
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
rv = args[0]
if (len(userfcn) > 0) and (stage in userfcn):
for k in range(len(userfcn[stage])):
if 'args' in userfcn[stage][k]:
args = userfcn[stage][k]['args']
else:
args = []
if stage in ['ext2int', 'formulation', 'int2ext']:
# ppc = userfcn_*_ext2int(ppc, args)
# om = userfcn_*_formulation(om, args)
# results = userfcn_*_int2ext(results, args)
rv = userfcn[stage][k]['fcn'](rv, args)
elif stage in ['printpf', 'savecase']:
# results = userfcn_*_printpf(results, fd, ppopt, args)
# ppc = userfcn_*_savecase(mpc, fd, prefix, args)
rv = feval(userfcn[stage][k]['fcn'], rv, args[1], args[2], args)
return rv
def mosek_options(overrides=None, ppopt=None):
"""Sets options for MOSEK.
Inputs are all optional, second argument must be either a string
(C{fname}) or a dict (C{ppopt}):
- C{overrides}
- dict containing values to override the defaults
- C{fname} name of user-supplied function called after default
options are set to modify them. Calling syntax is::
modified_opt = fname(default_opt)
- C{ppopt} PYPOWER options vector, uses the following entries:
- C{OPF_VIOLATION} used to set opt.MSK_DPAR_INTPNT_TOL_PFEAS
- C{VERBOSE} not currently used here
- C{MOSEK_LP_ALG} - used to set opt.MSK_IPAR_OPTIMIZER
- C{MOSEK_MAX_IT} used to set opt.MSK_IPAR_INTPNT_MAX_ITERATIONS
- C{MOSEK_GAP_TOL} used to set opt.MSK_DPAR_INTPNT_TOL_REL_GAP
- C{MOSEK_MAX_TIME} used to set opt.MSK_DPAR_OPTIMIZER_MAX_TIME
- C{MOSEK_NUM_THREADS} used to set opt.MSK_IPAR_INTPNT_NUM_THREADS
- C{MOSEK_OPT} user option file, if ppopt['MOSEK_OPT'] is non-zero
it is appended to 'mosek_user_options_' to form
the name of a user-supplied function used as C{fname}
described above, except with calling syntax::
modified_opt = fname(default_opt, ppopt)
Output is a param dict to pass to MOSEKOPT.
Example:
If PPOPT['MOSEK_OPT'] = 3, then after setting the default MOSEK options,
L{mosek_options} will execute the following user-defined function
to allow option overrides::
opt = mosek_user_options_3(opt, ppopt)
The contents of mosek_user_options_3.py, could be something like::
def mosek_user_options_3(opt, ppopt):
opt = {}
opt.MSK_DPAR_INTPNT_TOL_DFEAS = 1e-9
opt.MSK_IPAR_SIM_MAX_ITERATIONS = 5000000
return opt
See the Parameters reference in Appix E of "The MOSEK
optimization toolbox for MATLAB manaul" for
details on the available options.
U{http://www.mosek.com/documentation/}
@see: C{mosekopt}, L{ppoption}.
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
##----- initialization and arg handling -----
## defaults
verbose = 2
gaptol = 0
fname = ''
## get symbolic constant names
r, res = mosekopt('symbcon echo(0)')
sc = res['symbcon']
## second argument
if ppopt == None:
if isinstance(ppopt, basestring): ## 2nd arg is FNAME (string)
fname = ppopt
have_ppopt = False
else: ## 2nd arg is ppopt (MATPOWER options vector)
have_ppopt = True
verbose = ppopt['VERBOSE']
if ppopt['MOSEK_OPT']:
fname = 'mosek_user_options_#d' # ppopt['MOSEK_OPT']
else:
have_ppopt = False
opt = {}
##----- set default options for MOSEK -----
## solution algorithm
if have_ppopt:
alg = ppopt['MOSEK_LP_ALG']
if alg == sc['MSK_OPTIMIZER_FREE'] or \
alg == sc['MSK_OPTIMIZER_INTPNT'] or \
alg == sc['MSK_OPTIMIZER_PRIMAL_SIMPLEX'] or \
alg == sc['MSK_OPTIMIZER_DUAL_SIMPLEX'] or \
alg == sc['MSK_OPTIMIZER_PRIMAL_DUAL_SIMPLEX'] or \
alg == sc['MSK_OPTIMIZER_FREE_SIMPLEX'] or \
alg == sc['MSK_OPTIMIZER_CONCURRENT']:
opt['MSK_IPAR_OPTIMIZER'] = alg
else:
opt['MSK_IPAR_OPTIMIZER'] = sc['MSK_OPTIMIZER_FREE'];
## (make default OPF_VIOLATION correspond to default MSK_DPAR_INTPNT_TOL_PFEAS)
opt['MSK_DPAR_INTPNT_TOL_PFEAS'] = ppopt['OPF_VIOLATION'] / 500
if ppopt['MOSEK_MAX_IT']:
opt['MSK_IPAR_INTPNT_MAX_ITERATIONS'] = ppopt['MOSEK_MAX_IT']
if ppopt['MOSEK_GAP_TOL']:
opt['MSK_DPAR_INTPNT_TOL_REL_GAP'] = ppopt['MOSEK_GAP_TOL']
if ppopt['MOSEK_MAX_TIME']:
opt['MSK_DPAR_OPTIMIZER_MAX_TIME'] = ppopt['MOSEK_MAX_TIME']
if ppopt['MOSEK_NUM_THREADS']:
opt['MSK_IPAR_INTPNT_NUM_THREADS'] = ppopt['MOSEK_NUM_THREADS']
else:
opt['MSK_IPAR_OPTIMIZER'] = sc['MSK_OPTIMIZER_FREE']
# opt['MSK_DPAR_INTPNT_TOL_PFEAS'] = 1e-8 ## primal feasibility tol
# opt['MSK_DPAR_INTPNT_TOL_DFEAS'] = 1e-8 ## dual feasibility tol
# opt['MSK_DPAR_INTPNT_TOL_MU_RED'] = 1e-16 ## relative complementarity gap tol
# opt['MSK_DPAR_INTPNT_TOL_REL_GAP'] = 1e-8 ## relative gap termination tol
# opt['MSK_IPAR_INTPNT_MAX_ITERATIONS'] = 400 ## max iterations for int point
# opt['MSK_IPAR_SIM_MAX_ITERATIONS'] = 10000000 ## max iterations for simplex
# opt['MSK_DPAR_OPTIMIZER_MAX_TIME'] = -1 ## max time allowed (< 0 --> Inf)
# opt['MSK_IPAR_INTPNT_NUM_THREADS'] = 1 ## number of threads
# opt['MSK_IPAR_PRESOLVE_USE'] = sc['MSK_PRESOLVE_MODE_OFF']
# if verbose == 0:
# opt['MSK_IPAR_LOG'] = 0
#
##----- call user function to modify defaults -----
if len(fname) > 0:
if have_ppopt:
opt = feval(fname, opt, ppopt)
else:
opt = feval(fname, opt)
##----- apply overrides -----
if overrides is not None:
names = overrides.keys()
for k in range(len(names)):
opt[names[k]] = overrides[names[k]]
def cplex_options(overrides=None, ppopt=None):
"""Sets options for CPLEX.
Sets the values for the options dict normally passed to
C{cplexoptimset}.
Inputs are all optional, second argument must be either a string
(C{fname}) or a dict (C{ppopt}):
Output is an options dict to pass to C{cplexoptimset}.
Example:
If C{ppopt['CPLEX_OPT'] = 3}, then after setting the default CPLEX options,
CPLEX_OPTIONS will execute the following user-defined function
to allow option overrides::
opt = cplex_user_options_3(opt, ppopt)
The contents of cplex_user_options_3.py, could be something like::
def cplex_user_options_3(opt, ppopt):
opt = {}
opt['threads'] = 2
opt['simplex']['refactor'] = 1
opt['timelimit'] = 10000
return opt
For details on the available options, see the I{"Parameters Reference
Manual"} section of the CPLEX documentation at:
U{http://publib.boulder.ibm.com/infocenter/cosinfoc/v12r2/}
@param overrides:
- dict containing values to override the defaults
- fname: name of user-supplied function called after default
options are set to modify them. Calling syntax is::
modified_opt = fname(default_opt)
@param ppopt: PYPOWER options vector, uses the following entries:
- OPF_VIOLATION - used to set opt.simplex.tolerances.feasibility
- VERBOSE - used to set opt.barrier.display,
opt.conflict.display, opt.mip.display, opt.sifting.display,
opt.simplex.display, opt.tune.display
- CPLEX_LPMETHOD - used to set opt.lpmethod
- CPLEX_QPMETHOD - used to set opt.qpmethod
- CPLEX_OPT - user option file, if ppopt['CPLEX_OPT'] is
non-zero it is appended to 'cplex_user_options_' to form
the name of a user-supplied function used as C{fname}
described above, except with calling syntax::
modified_opt = fname(default_opt, ppopt)
@see: C{cplexlp}, C{cplexqp}, L{ppoption}.
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
##----- initialization and arg handling -----
## defaults
verbose = 1
feastol = 1e-6
fname = ''
## second argument
if ppopt != None:
if isinstance(ppopt, basestring): ## 2nd arg is FNAME (string)
fname = ppopt
have_ppopt = False
else: ## 2nd arg is ppopt (MATPOWER options vector)
have_ppopt = True
## (make default OPF_VIOLATION correspond to default CPLEX feastol)
feastol = ppopt['OPF_VIOLATION'] / 5
verbose = ppopt['VERBOSE']
lpmethod = ppopt['CPLEX_LPMETHOD']
qpmethod = ppopt['CPLEX_QPMETHOD']
if ppopt['CPLEX_OPT']:
fname = 'cplex_user_options_#d' % ppopt['CPLEX_OPT']
else:
have_ppopt = False
##----- set default options for CPLEX -----
opt = cplexoptimset('cplex')
opt['simplex']['tolerances']['feasibility'] = feastol
## printing
vrb = max([0, verbose - 1])
opt['barrier']['display'] = vrb
opt['conflict']['display'] = vrb
opt['mip']['display'] = vrb
opt['sifting']['display'] = vrb
opt['simplex']['display'] = vrb
opt['tune']['display'] = vrb
## solution algorithm
if have_ppopt:
opt['lpmethod'] = lpmethod
opt['qpmethod'] = qpmethod
#else:
# opt['lpmethod'] = 2
# opt['qpmethod'] = 2
##----- call user function to modify defaults -----
if len(fname) > 0:
if have_ppopt:
opt = feval(fname, opt, ppopt)
else:
opt = feval(fname, opt)
##----- apply overrides -----
if overrides is not None:
names = overrides.keys()
for k in range(len(names)):
if isinstance(overrides[names[k]], dict):
names2 = overrides[names[k]].keys()
for k2 in range(len(names2)):
if isinstance(overrides[names[k]][names2[k2]], dict):
names3 = overrides[names[k]][names2[k2]].keys()
for k3 in range(len(names3)):
opt[names[k]][names2[k2]][names3[k3]] = overrides[names[k]][names2[k2]][names3[k3]]
else:
opt[names[k]][names2[k2]] = overrides[names[k]][names2[k2]]
else:
opt[names[k]] = overrides[names[k]]
return opt
def gurobi_options(overrides=None, ppopt=None):
"""Sets options for GUROBI.
Sets the values for the options dict normally passed to GUROBI_MEX.
Inputs are all optional, second argument must be either a string
(fname) or a vector (ppopt):
overrides - dict containing values to override the defaults
fname - name of user-supplied function called after default
options are set to modify them. Calling syntax is:
modified_opt = fname(default_opt)
ppopt - PYPOWER options vector, uses the following entries:
OPF_VIOLATION (16) - used to set opt.FeasibilityTol
VERBOSE (31) - used to set opt.DisplayInterval, opt.Display
GRB_METHOD (121) - used to set opt.Method
GRB_TIMELIMIT (122) - used to set opt.TimeLimit (seconds)
GRB_THREADS (123) - used to set opt.Threads
GRB_OPT (124) - user option file, if PPOPT(124) is non-zero
it is appended to 'gurobi_user_options_' to form the name of a
user-supplied function used as C{fname} described above, except
with calling syntax:
modified_opt = fname(default_opt, mpopt)
Output is an options struct to pass to GUROBI_MEX.
Example:
If ppopt['GRB_OPT'] = 3, then after setting the default GUROBI options,
GUROBI_OPTIONS will execute the following user-defined function
to allow option overrides:
opt = gurobi_user_options_3(opt, ppopt)
The contents of gurobi_user_options_3.py, could be something like:
def gurobi_user_options_3(opt, ppopt):
opt = {}
opt['OptimalityTol'] = 1e-9
opt['IterationLimit'] = 3000
opt['BarIterLimit'] = 200
opt['Crossover'] = 0
opt['Presolve'] = 0
return opt
For details on the available options, see the "Parameters" section
of the "Gurobi Optimizer Reference Manual" at:
http://www.gurobi.com/doc/45/refman/
@see: L{gurobi_mex}, L{ppoption}.
"""
##----- initialization and arg handling -----
## defaults
verbose = True
fname = ''
## second argument
if ppopt != None:
if isinstance(ppopt, basestring): ## 2nd arg is FNAME (string)
fname = ppopt
have_ppopt = False
else: ## 2nd arg is MPOPT (MATPOWER options vector)
have_ppopt = True
verbose = ppopt['VERBOSE']
if ppopt['GRB_OPT']:
fname = 'gurobi_user_options_%d', ppopt['GRB_OPT']
else:
have_ppopt = False
##----- set default options for CPLEX -----
opt = {}
# opt['OptimalityTol'] = 1e-6
## -1 - auto, 0 - no, 1 - conserv, 2 - aggressive=
# opt['Presolve'] = -1
# opt['LogFile'] = 'qps_gurobi.log'
if have_ppopt:
## (make default OPF_VIOLATION correspond to default FeasibilityTol)
opt['FeasibilityTol'] = ppopt['OPF_VIOLATION'] / 5
opt['Method'] = ppopt['GRB_METHOD']
opt['TimeLimit'] = ppopt['GRB_TIMELIMIT']
opt['Threads'] = ppopt['GRB_THREADS']
else:
opt['Method'] = 1 ## dual simplex
opt['Display'] = min(verbose, 3)
if verbose:
opt['DisplayInterval'] = 1
else:
opt['DisplayInterval'] = Inf
##----- call user function to modify defaults -----
if len(fname) > 0:
if have_ppopt:
opt = feval(fname, opt, ppopt)
else:
opt = feval(fname, opt)
##----- apply overrides -----
if overrides is not None:
names = overrides.keys()
for k in range(len(names)):
opt[names[k]] = overrides[names[k]]
return opt
def mosek_options(overrides=None, ppopt=None):
"""Sets options for MOSEK.
Inputs are all optional, second argument must be either a string
(C{fname}) or a dict (C{ppopt}):
- C{overrides}
- dict containing values to override the defaults
- C{fname} name of user-supplied function called after default
options are set to modify them. Calling syntax is::
modified_opt = fname(default_opt)
- C{ppopt} PYPOWER options vector, uses the following entries:
- C{OPF_VIOLATION} used to set opt.MSK_DPAR_INTPNT_TOL_PFEAS
- C{VERBOSE} not currently used here
- C{MOSEK_LP_ALG} - used to set opt.MSK_IPAR_OPTIMIZER
- C{MOSEK_MAX_IT} used to set opt.MSK_IPAR_INTPNT_MAX_ITERATIONS
- C{MOSEK_GAP_TOL} used to set opt.MSK_DPAR_INTPNT_TOL_REL_GAP
- C{MOSEK_MAX_TIME} used to set opt.MSK_DPAR_OPTIMIZER_MAX_TIME
- C{MOSEK_NUM_THREADS} used to set opt.MSK_IPAR_INTPNT_NUM_THREADS
- C{MOSEK_OPT} user option file, if ppopt['MOSEK_OPT'] is non-zero
it is appended to 'mosek_user_options_' to form
the name of a user-supplied function used as C{fname}
described above, except with calling syntax::
modified_opt = fname(default_opt, ppopt)
Output is a param dict to pass to MOSEKOPT.
Example:
If PPOPT['MOSEK_OPT'] = 3, then after setting the default MOSEK options,
L{mosek_options} will execute the following user-defined function
to allow option overrides::
opt = mosek_user_options_3(opt, ppopt)
The contents of mosek_user_options_3.py, could be something like::
def mosek_user_options_3(opt, ppopt):
opt = {}
opt.MSK_DPAR_INTPNT_TOL_DFEAS = 1e-9
opt.MSK_IPAR_SIM_MAX_ITERATIONS = 5000000
return opt
See the Parameters reference in Appix E of "The MOSEK
optimization toolbox for MATLAB manaul" for
details on the available options.
U{http://www.mosek.com/documentation/}
@see: C{mosekopt}, L{ppoption}.
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
##----- initialization and arg handling -----
## defaults
verbose = 2
gaptol = 0
fname = ''
## get symbolic constant names
r, res = mosekopt('symbcon echo(0)')
sc = res['symbcon']
## second argument
if ppopt == None:
if isinstance(ppopt, basestring): ## 2nd arg is FNAME (string)
fname = ppopt
have_ppopt = False
else: ## 2nd arg is ppopt (MATPOWER options vector)
have_ppopt = True
verbose = ppopt['VERBOSE']
if ppopt['MOSEK_OPT']:
fname = 'mosek_user_options_#d' # ppopt['MOSEK_OPT']
else:
have_ppopt = False
opt = {}
##----- set default options for MOSEK -----
## solution algorithm
if have_ppopt:
alg = ppopt['MOSEK_LP_ALG']
if alg == sc['MSK_OPTIMIZER_FREE'] or \
alg == sc['MSK_OPTIMIZER_INTPNT'] or \
alg == sc['MSK_OPTIMIZER_PRIMAL_SIMPLEX'] or \
alg == sc['MSK_OPTIMIZER_DUAL_SIMPLEX'] or \
alg == sc['MSK_OPTIMIZER_PRIMAL_DUAL_SIMPLEX'] or \
alg == sc['MSK_OPTIMIZER_FREE_SIMPLEX'] or \
alg == sc['MSK_OPTIMIZER_CONCURRENT']:
opt['MSK_IPAR_OPTIMIZER'] = alg
else:
opt['MSK_IPAR_OPTIMIZER'] = sc['MSK_OPTIMIZER_FREE']
## (make default OPF_VIOLATION correspond to default MSK_DPAR_INTPNT_TOL_PFEAS)
opt['MSK_DPAR_INTPNT_TOL_PFEAS'] = ppopt['OPF_VIOLATION'] / 500
if ppopt['MOSEK_MAX_IT']:
opt['MSK_IPAR_INTPNT_MAX_ITERATIONS'] = ppopt['MOSEK_MAX_IT']
if ppopt['MOSEK_GAP_TOL']:
opt['MSK_DPAR_INTPNT_TOL_REL_GAP'] = ppopt['MOSEK_GAP_TOL']
if ppopt['MOSEK_MAX_TIME']:
opt['MSK_DPAR_OPTIMIZER_MAX_TIME'] = ppopt['MOSEK_MAX_TIME']
if ppopt['MOSEK_NUM_THREADS']:
opt['MSK_IPAR_INTPNT_NUM_THREADS'] = ppopt['MOSEK_NUM_THREADS']
else:
opt['MSK_IPAR_OPTIMIZER'] = sc['MSK_OPTIMIZER_FREE']
# opt['MSK_DPAR_INTPNT_TOL_PFEAS'] = 1e-8 ## primal feasibility tol
# opt['MSK_DPAR_INTPNT_TOL_DFEAS'] = 1e-8 ## dual feasibility tol
# opt['MSK_DPAR_INTPNT_TOL_MU_RED'] = 1e-16 ## relative complementarity gap tol
# opt['MSK_DPAR_INTPNT_TOL_REL_GAP'] = 1e-8 ## relative gap termination tol
# opt['MSK_IPAR_INTPNT_MAX_ITERATIONS'] = 400 ## max iterations for int point
# opt['MSK_IPAR_SIM_MAX_ITERATIONS'] = 10000000 ## max iterations for simplex
# opt['MSK_DPAR_OPTIMIZER_MAX_TIME'] = -1 ## max time allowed (< 0 --> Inf)
# opt['MSK_IPAR_INTPNT_NUM_THREADS'] = 1 ## number of threads
# opt['MSK_IPAR_PRESOLVE_USE'] = sc['MSK_PRESOLVE_MODE_OFF']
# if verbose == 0:
# opt['MSK_IPAR_LOG'] = 0
#
##----- call user function to modify defaults -----
if len(fname) > 0:
if have_ppopt:
opt = feval(fname, opt, ppopt)
else:
opt = feval(fname, opt)
##----- apply overrides -----
if overrides is not None:
names = overrides.keys()
for k in range(len(names)):
opt[names[k]] = overrides[names[k]]
def cplex_options(overrides=None, ppopt=None):
"""Sets options for CPLEX.
Sets the values for the options dict normally passed to
C{cplexoptimset}.
Inputs are all optional, second argument must be either a string
(C{fname}) or a dict (C{ppopt}):
Output is an options dict to pass to C{cplexoptimset}.
Example:
If C{ppopt['CPLEX_OPT'] = 3}, then after setting the default CPLEX options,
CPLEX_OPTIONS will execute the following user-defined function
to allow option overrides::
opt = cplex_user_options_3(opt, ppopt)
The contents of cplex_user_options_3.py, could be something like::
def cplex_user_options_3(opt, ppopt):
opt = {}
opt['threads'] = 2
opt['simplex']['refactor'] = 1
opt['timelimit'] = 10000
return opt
For details on the available options, see the I{"Parameters Reference
Manual"} section of the CPLEX documentation at:
U{http://publib.boulder.ibm.com/infocenter/cosinfoc/v12r2/}
@param overrides:
- dict containing values to override the defaults
- fname: name of user-supplied function called after default
options are set to modify them. Calling syntax is::
modified_opt = fname(default_opt)
@param ppopt: PYPOWER options vector, uses the following entries:
- OPF_VIOLATION - used to set opt.simplex.tolerances.feasibility
- VERBOSE - used to set opt.barrier.display,
opt.conflict.display, opt.mip.display, opt.sifting.display,
opt.simplex.display, opt.tune.display
- CPLEX_LPMETHOD - used to set opt.lpmethod
- CPLEX_QPMETHOD - used to set opt.qpmethod
- CPLEX_OPT - user option file, if ppopt['CPLEX_OPT'] is
non-zero it is appended to 'cplex_user_options_' to form
the name of a user-supplied function used as C{fname}
described above, except with calling syntax::
modified_opt = fname(default_opt, ppopt)
@see: C{cplexlp}, C{cplexqp}, L{ppoption}.
@author: Ray Zimmerman (PSERC Cornell)
"""
##----- initialization and arg handling -----
## defaults
verbose = 1
feastol = 1e-6
fname = ''
## second argument
if ppopt != None:
if isinstance(ppopt, basestring): ## 2nd arg is FNAME (string)
fname = ppopt
have_ppopt = False
else: ## 2nd arg is ppopt (MATPOWER options vector)
have_ppopt = True
## (make default OPF_VIOLATION correspond to default CPLEX feastol)
feastol = ppopt['OPF_VIOLATION'] / 5
verbose = ppopt['VERBOSE']
lpmethod = ppopt['CPLEX_LPMETHOD']
qpmethod = ppopt['CPLEX_QPMETHOD']
if ppopt['CPLEX_OPT']:
fname = 'cplex_user_options_#d' % ppopt['CPLEX_OPT']
else:
have_ppopt = False
##----- set default options for CPLEX -----
opt = cplexoptimset('cplex')
opt['simplex']['tolerances']['feasibility'] = feastol
## printing
vrb = max([0, verbose - 1])
opt['barrier']['display'] = vrb
opt['conflict']['display'] = vrb
opt['mip']['display'] = vrb
opt['sifting']['display'] = vrb
opt['simplex']['display'] = vrb
opt['tune']['display'] = vrb
## solution algorithm
if have_ppopt:
opt['lpmethod'] = lpmethod
opt['qpmethod'] = qpmethod
#else:
# opt['lpmethod'] = 2
# opt['qpmethod'] = 2
##----- call user function to modify defaults -----
if len(fname) > 0:
if have_ppopt:
opt = feval(fname, opt, ppopt)
else:
opt = feval(fname, opt)
##----- apply overrides -----
if overrides is not None:
names = overrides.keys()
for k in range(len(names)):
if isinstance(overrides[names[k]], dict):
names2 = overrides[names[k]].keys()
for k2 in range(len(names2)):
if isinstance(overrides[names[k]][names2[k2]], dict):
names3 = overrides[names[k]][names2[k2]].keys()
for k3 in range(len(names3)):
opt[names[k]][names2[k2]][names3[k3]] = overrides[
names[k]][names2[k2]][names3[k3]]
else:
opt[names[k]][names2[k2]] = overrides[names[k]][
names2[k2]]
else:
opt[names[k]] = overrides[names[k]]
return opt
def cplex_options(overrides=None, ppopt=None):
"""Sets options for CPLEX.
Sets the values for the options dict normally passed to
C{cplexoptimset}.
Inputs are all optional, second argument must be either a string
(C{fname}) or a dict (C{ppopt}):
Output is an options dict to pass to C{cplexoptimset}.
Example:
If C{ppopt['CPLEX_OPT'] = 3}, then after setting the default CPLEX options,
CPLEX_OPTIONS will execute the following user-defined function
to allow option overrides::
opt = cplex_user_options_3(opt, ppopt)
The contents of cplex_user_options_3.py, could be something like::
def cplex_user_options_3(opt, ppopt):
opt = {}
opt['threads'] = 2
opt['simplex']['refactor'] = 1
opt['timelimit'] = 10000
return opt
For details on the available options, see the I{"Parameters Reference
Manual"} section of the CPLEX documentation at:
U{http://publib.boulder.ibm.com/infocenter/cosinfoc/v12r2/}
@param overrides:
- dict containing values to override the defaults
- fname: name of user-supplied function called after default
options are set to modify them. Calling syntax is::
modified_opt = fname(default_opt)
@param ppopt: PYPOWER options vector, uses the following entries:
- OPF_VIOLATION - used to set opt.simplex.tolerances.feasibility
- VERBOSE - used to set opt.barrier.display,
opt.conflict.display, opt.mip.display, opt.sifting.display,
opt.simplex.display, opt.tune.display
- CPLEX_LPMETHOD - used to set opt.lpmethod
- CPLEX_QPMETHOD - used to set opt.qpmethod
- CPLEX_OPT - user option file, if ppopt['CPLEX_OPT'] is
non-zero it is appended to 'cplex_user_options_' to form
the name of a user-supplied function used as C{fname}
described above, except with calling syntax::
modified_opt = fname(default_opt, ppopt)
@see: C{cplexlp}, C{cplexqp}, L{ppoption}.
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
##----- initialization and arg handling -----
## defaults
verbose = 1
feastol = 1e-6
fname = ''
## second argument
if ppopt != None:
if isinstance(ppopt, basestring): ## 2nd arg is FNAME (string)
fname = ppopt
have_ppopt = False
else: ## 2nd arg is ppopt (MATPOWER options vector)
have_ppopt = True
## (make default OPF_VIOLATION correspond to default CPLEX feastol)
feastol = ppopt['OPF_VIOLATION'] / 5
verbose = ppopt['VERBOSE']
lpmethod = ppopt['CPLEX_LPMETHOD']
qpmethod = ppopt['CPLEX_QPMETHOD']
if ppopt['CPLEX_OPT']:
fname = 'cplex_user_options_#d' % ppopt['CPLEX_OPT']
else:
have_ppopt = False
##----- set default options for CPLEX -----
opt = cplexoptimset('cplex')
opt['simplex']['tolerances']['feasibility'] = feastol
## printing
vrb = max([0, verbose - 1])
opt['barrier']['display'] = vrb
opt['conflict']['display'] = vrb
opt['mip']['display'] = vrb
opt['sifting']['display'] = vrb
opt['simplex']['display'] = vrb
opt['tune']['display'] = vrb
## solution algorithm
if have_ppopt:
opt['lpmethod'] = lpmethod
opt['qpmethod'] = qpmethod
#else:
# opt['lpmethod'] = 2
# opt['qpmethod'] = 2
##----- call user function to modify defaults -----
if len(fname) > 0:
if have_ppopt:
opt = feval(fname, opt, ppopt)
else:
opt = feval(fname, opt)
##----- apply overrides -----
if overrides is not None:
names = overrides.keys()
for k in range(len(names)):
if isinstance(overrides[names[k]], dict):
names2 = overrides[names[k]].keys()
for k2 in range(len(names2)):
if isinstance(overrides[names[k]][names2[k2]], dict):
names3 = overrides[names[k]][names2[k2]].keys()
for k3 in range(len(names3)):
opt[names[k]][names2[k2]][names3[k3]] = overrides[names[k]][names2[k2]][names3[k3]]
else:
opt[names[k]][names2[k2]] = overrides[names[k]][names2[k2]]
else:
opt[names[k]] = overrides[names[k]]
return opt
#-------------------------- Default Options Struct --------------------------
# as returned by ...
# >> opt = cplexoptimset('cplex')
#
# opt =
# advance: 1
# barrier: [1x1 struct]
# algorithm: 0
# colnonzeros: 0
# convergetol: 1.0000e-08
# crossover: 0
# display: 1
# limits: [1x1 struct]
# corrections: -1
# growth: 1.0000e+12
# iteration: 9.2234e+18
# objrange: 1.0000e+20
# ordering: 0
# qcpconvergetol: 1.0000e-07
# startalg: 1
# clocktype: 2
# conflict: [1x1 struct]
# display: 1
# diagnostics: 'off'
# emphasis: [1x1 struct]
# memory: 0
# mip: 0
# numerical: 0
# exportmodel: ''
# feasopt: [1x1 struct]
# mode: 0
# tolerance: 1.0000e-06
# lpmethod: 0
# mip: [1x1 struct]
# cuts: [1x1 struct]
# cliques: 0
# covers: 0
# disjunctive: 0
# flowcovers: 0
# gomory: 0
# gubcovers: 0
# implied: 0
# mcfcut: 0
# mircut: 0
# pathcut: 0
# zerohalfcut: 0
# display: 2
# interval: 0
# limits: [1x1 struct]
# aggforcut: 3
# auxrootthreads: 0
# cutpasses: 0
# cutsfactor: 4
# eachcutlimit: 2.1000e+09
# gomorycand: 200
# gomorypass: 0
# nodes: 9.2234e+18
# polishtime: 0
# populate: 20
# probetime: 1.0000e+75
# repairtries: 0
# solutions: 9.2234e+18
# strongcand: 10
# strongit: 0
# submipnodelim: 500
# treememory: 1.0000e+75
# ordertype: 0
# polishafter: [1x1 struct]
# absmipgap: 0
# mipgap: 0
# nodes: 9.2234e+18
# solutions: 9.2234e+18
# time: 1.0000e+75
# pool: [1x1 struct]
# absgap: 1.0000e+75
# capacity: 2.1000e+09
# intensity: 0
# relgap: 1.0000e+75
# replace: 0
# strategy: [1x1 struct]
# backtrack: 0.9999
# bbinterval: 7
# branch: 0
# dive: 0
# file: 1
# fpheur: 0
# heuristicfreq: 0
# kappastats: 0
# lbheur: 0
# miqcpstrat: 0
# nodeselect: 1
# order: 1
# presolvenode: 0
# probe: 0
# rinsheur: 0
# search: 0
# startalgorithm: 0
# subalgorithm: 0
# variableselect: 0
# tolerances: [1x1 struct]
# absmipgap: 1.0000e-06
# integrality: 1.0000e-05
# lowercutoff: -1.0000e+75
# mipgap: 1.0000e-04
# objdifference: 0
# relobjdifference: 0
# uppercutoff: 1.0000e+75
# output: [1x1 struct]
# clonelog: 1
# intsolfileprefix: ''
# mpslong: 1
# writelevel: 0
# parallel: 0
# preprocessing: [1x1 struct]
# aggregator: -1
# boundstrength: -1
# coeffreduce: -1
# depency: -1
# dual: 0
# fill: 10
# linear: 1
# numpass: -1
# presolve: 1
# qpmakepsd: 1
# reduce: 3
# relax: -1
# repeatpresolve: -1
# symmetry: -1
# qpmethod: 0
# read: [1x1 struct]
# apiencoding: ''
# constraints: 30000
# datacheck: 0
# fileencoding: 'ISO-8859-1'
# nonzeros: 250000
# qpnonzeros: 5000
# scale: 0
# variables: 60000
# sifting: [1x1 struct]
# algorithm: 0
# display: 1
# iterations: 9.2234e+18
# simplex: [1x1 struct]
# crash: 1
# dgradient: 0
# display: 1
# limits: [1x1 struct]
# iterations: 9.2234e+18
# lowerobj: -1.0000e+75
# perturbation: 0
# singularity: 10
# upperobj: 1.0000e+75
# perturbation: [1x1 struct]
# indicator: 0
# constant: 1.0000e-06
# pgradient: 0
# pricing: 0
# refactor: 0
# tolerances: [1x1 struct]
# feasibility: 1.0000e-06
# markowitz: 0.0100
# optimality: 1.0000e-06
# solutiontarget: 0
# threads: 0
# timelimit: 1.0000e+75
# tune: [1x1 struct]
# display: 1
# measure: 1
# repeat: 1
# timelimit: 10000
# workdir: '.'
# workmem: 128
def gurobi_options(overrides=None, ppopt=None):
"""Sets options for GUROBI.
Sets the values for the options dict normally passed to GUROBI_MEX.
Inputs are all optional, second argument must be either a string
(fname) or a vector (ppopt):
overrides - dict containing values to override the defaults
fname - name of user-supplied function called after default
options are set to modify them. Calling syntax is:
modified_opt = fname(default_opt)
ppopt - PYPOWER options vector, uses the following entries:
OPF_VIOLATION (16) - used to set opt.FeasibilityTol
VERBOSE (31) - used to set opt.DisplayInterval, opt.Display
GRB_METHOD (121) - used to set opt.Method
GRB_TIMELIMIT (122) - used to set opt.TimeLimit (seconds)
GRB_THREADS (123) - used to set opt.Threads
GRB_OPT (124) - user option file, if PPOPT(124) is non-zero
it is appended to 'gurobi_user_options_' to form the name of a
user-supplied function used as C{fname} described above, except
with calling syntax:
modified_opt = fname(default_opt, mpopt)
Output is an options struct to pass to GUROBI_MEX.
Example:
If ppopt['GRB_OPT'] = 3, then after setting the default GUROBI options,
GUROBI_OPTIONS will execute the following user-defined function
to allow option overrides:
opt = gurobi_user_options_3(opt, ppopt)
The contents of gurobi_user_options_3.py, could be something like:
def gurobi_user_options_3(opt, ppopt):
opt = {}
opt['OptimalityTol'] = 1e-9
opt['IterationLimit'] = 3000
opt['BarIterLimit'] = 200
opt['Crossover'] = 0
opt['Presolve'] = 0
return opt
For details on the available options, see the "Parameters" section
of the "Gurobi Optimizer Reference Manual" at:
http://www.gurobi.com/doc/45/refman/
@see: L{gurobi_mex}, L{ppoption}.
"""
##----- initialization and arg handling -----
## defaults
verbose = True
fname = ''
## second argument
if ppopt != None:
if isinstance(ppopt, str): ## 2nd arg is FNAME (string)
fname = ppopt
have_ppopt = False
else: ## 2nd arg is MPOPT (MATPOWER options vector)
have_ppopt = True
verbose = ppopt['VERBOSE']
if ppopt['GRB_OPT']:
fname = 'gurobi_user_options_%d', ppopt['GRB_OPT']
else:
have_ppopt = False
##----- set default options for CPLEX -----
opt = {}
# opt['OptimalityTol'] = 1e-6
## -1 - auto, 0 - no, 1 - conserv, 2 - aggressive=
# opt['Presolve'] = -1
# opt['LogFile'] = 'qps_gurobi.log'
if have_ppopt:
## (make default OPF_VIOLATION correspond to default FeasibilityTol)
opt['FeasibilityTol'] = ppopt['OPF_VIOLATION'] / 5
opt['Method'] = ppopt['GRB_METHOD']
opt['TimeLimit'] = ppopt['GRB_TIMELIMIT']
opt['Threads'] = ppopt['GRB_THREADS']
else:
opt['Method'] = 1 ## dual simplex
opt['Display'] = min(verbose, 3)
if verbose:
opt['DisplayInterval'] = 1
else:
opt['DisplayInterval'] = Inf
##----- call user function to modify defaults -----
if len(fname) > 0:
if have_ppopt:
opt = feval(fname, opt, ppopt)
else:
opt = feval(fname, opt)
##----- apply overrides -----
if overrides is not None:
names = list(overrides.keys())
for k in range(len(names)):
opt[names[k]] = overrides[names[k]]
return opt