def HGdebugSolve(ph,options,ScenarioList):
print("HGdebugSolve prints attributes after solving")
SolStat, Lagrangian = lagrUtil.solve_ph_code(ph, options)
IndVarName = options.indicator_var_name
for scenario in ScenarioList:
sname = scenario[0]
instance = ph._instances[sname]
if getattr(instance,IndVarName).fixed: stat = "fixed"
else: stat = "free"
lambdaval = getattr(instance, options.lambda_parm_name).value
#print IndVarName+"("+sname+") =",getattr(instance,IndVarName).value, stat, "\tlambda =",lambdaval
b = Compute_ExpectationforVariable(ph, IndVarName, options.stage_num)
z = Lagrangian + lambdaval*b
#print "L = ",z," - ",lambdaval,"x",b
return SolStat, Lagrangian
def HGdebugSolve(ph, options, ScenarioList):
print("HGdebugSolve prints attributes after solving")
SolStat, Lagrangian = lagrUtil.solve_ph_code(ph, options)
IndVarName = options.indicator_var_name
for scenario in ScenarioList:
sname = scenario[0]
instance = ph._instances[sname]
if getattr(instance, IndVarName).fixed: stat = "fixed"
else: stat = "free"
lambdaval = getattr(instance, options.lambda_parm_name).value
#print IndVarName+"("+sname+") =",getattr(instance,IndVarName).value, stat, "\tlambda =",lambdaval
b = Compute_ExpectationforVariable(ph, IndVarName, options.stage_num)
z = Lagrangian + lambdaval * b
#print "L = ",z," - ",lambdaval,"x",b
return SolStat, Lagrangian
def LagrangeParametric(args=None):
class Object(object): pass
Result = Object()
Result.status = 'LagrangeParam begins '+ datetime_string() + '...running new ph'
ph = None
blanks = " " # used for formatting print statements
# options used
betaMin = options.beta_min
betaMax = options.beta_max
betaTol = options.beta_tol
gapTol = options.Lagrange_gap
minProb = options.min_prob
maxIntervals = options.max_intervals
maxTime = options.max_time
IndVarName = options.indicator_var_name
multName = options.lambda_parm_name
CCStageNum = options.stage_num
csvPrefix = options.csvPrefix
verbosity = options.verbosity
verbosity = 2 # override for debug (= 3 to get super-debug)
HGdebug = 0 # special debug (not public)
# local...may become option
optTol = gapTol
####################################################################
STARTTIME = time.time()
Result.status = "options set"
if verbosity > 1:
print("From LagrangeParametric, status = %s\tSTARTTIME = %s" \
% (str(getattr(Result,'status')), str(STARTTIME)))
ph = PHFromScratch(options)
Result.ph = ph
rootnode = ph._scenario_tree._stages[0]._tree_nodes[0] # use rootnode to loop over scenarios
ReferenceInstance = ph._instances[rootnode._scenarios[0]._name] # arbitrary scenario
if find_active_objective(ph._scenario_tree._scenarios[0]._instance,safety_checks=True).is_minimizing():
sense = 'min'
else:
sense = 'max'
scenario_count = len(full_scenario_tree._stages[-1]._tree_nodes)
if options.verbosity > 0: print("%s %s scenarios" % (str(sense),str(scenario_count)))
# initialize
Result.status = 'starting at '+datetime_string()
if verbosity > 0:
print(Result.status)
ScenarioList = []
lambdaval = 0.
lagrUtil.Set_ParmValue(ph, multName,lambdaval)
# IMPORTANT: Preprocess the scenario instances
# before fixing variables, otherwise they
# will be preprocessed out of the expressions
# and the output_fixed_variable_bounds option
# will have no effect when we update the
# fixed variable values (and then assume we
# do not need to preprocess again because
# of this option).
ph._preprocess_scenario_instances()
sumprob = 0.
minprob = 1.
maxprob = 0.
# fixed = 0 to get PR point at b=0
lagrUtil.FixAllIndicatorVariables(ph, IndVarName, 0)
for scenario in rootnode._scenarios:
instance = ph._instances[scenario._name]
sname = scenario._name
sprob = scenario._probability
sumprob = sumprob + sprob
minprob = min(minprob,sprob)
maxprob = max(maxprob,sprob)
ScenarioList.append([sname,sprob])
ScenarioList.sort(key=operator.itemgetter(1)) # sorts from min to max probability
if verbosity > 0:
print("probabilities sum to %f range: %f to %f" % (sumprob,minprob,maxprob))
Result.ScenarioList = ScenarioList
# Write ScenarioList = name, probability in csv file sorted by probability
outName = csvPrefix + 'ScenarioList.csv'
print("writing to %s" % outName)
with open(outName,'w') as outFile:
for scenario in ScenarioList:
outFile.write(scenario[0]+", "+str(scenario[1])+'\n')
Result.ScenarioList = ScenarioList
addstatus = 'Scenario List written to ' + csvPrefix+'ScenarioList.csv'
Result.status = Result.status + '\n' + addstatus
if verbosity > 0:
print(addstatus)
if verbosity > 0:
print("solve begins %s" % datetime_string())
print("\t- lambda = %f" % lambdaval)
SolStat, zL = lagrUtil.solve_ph_code(ph, options)
if verbosity > 0:
print("solve ends %s" % datetime_string())
print("\t- status = %s" % str(SolStat))
print("\t- zL = %s" % str(zL))
bL = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
if bL > 0:
print("** bL = %s > 0 (all %s = 0)" % (str(bL), str(IndVarName)))
return Result
if verbosity > 0: print("Initial optimal obj = %s for bL = %s" % (str(zL), str(bL)))
# fixed = 1 to get PR point at b=1
lagrUtil.FixAllIndicatorVariables(ph, IndVarName, 1)
if verbosity > 0:
print("solve begins %s" % datetime_string())
print("\t- lambda = %s" % str(lambdaval))
SolStat, zU = lagrUtil.solve_ph_code(ph, options)
if verbosity > 0:
print("solve ends %s" % datetime_string())
print("\t- status = %s" % str(SolStat))
print("\t- zU = %s" % str(zU))
if not SolStat[0:2] == 'ok':
print(str(SolStat[0:3])+" is not 'ok'")
addstatus = "** Solution is non-optimal...aborting"
print(addstatus)
Result.status = Result.status + "\n" + addstatus
return Result
bU = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
if bU < 1.- betaTol and verbosity > 0:
print("** Warning: bU = %s < 1" % str(bU))
### enumerate points in PR space (all but one scenario)
# Result.lbz = [ [0,bL,zL], [None,bU,zU] ]
# for scenario in rootnode._scenarios:
# sname = scenario._name
# instance = ph._instances[sname]
# print "excluding scenario",sname
# getattr(instance,IndVarName).value = 0
# print sname,"value =",getattr(instance,IndVarName).value,getattr(instance,IndVarName).fixed
# SolStat, z = lagrUtil.solve_ph_code(ph, options)
# b = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
# print "solve ends with status =",SolStat,"(b, z) =",b,z
# getattr(instance,IndVarName).value = 1
# Result.lbz.append([None,b,z])
# for t in instance.TimePeriods:
# print "Global at",t,"=",instance.posGlobalLoadGenerateMismatch[t].value, \
# '-',instance.negGlobalLoadGenerateMismatch[t].value,"=",\
# instance.GlobalLoadGenerateMismatch[t].value,\
# "\tDemand =",instance.TotalDemand[t].value, ",",\
# "Reserve =",instance.ReserveRequirement[t].value
#
# PrintPRpoints(Result.lbz)
# return Result
#### end enumeration
########################################################################
if verbosity > 1:
print("We have bU = %s ...about to free all %s for %d scenarios" % \
(str(bU), str(IndVarName), len(ScenarioList)))
# free scenario selection variable
lagrUtil.FreeAllIndicatorVariables(ph, IndVarName)
if verbosity > 1:
print("\tall %s freed; elapsed time = %f" % (str(IndVarName), time.time() - STARTTIME))
# initialize with the two endpoints
Result.lbz = [ [0.,bL,zL], [None,bU,zU] ]
Result.selections = [[], ScenarioList]
NumIntervals = 1
if verbosity > 0:
print("Initial relative Lagrangian gap = %f maxIntervals = %d" % (1-zL/zU, maxIntervals))
if verbosity > 1:
print("entering while loop %s" % datetime_string())
print("\n")
############ main loop to search intervals #############
########################################################
while NumIntervals < maxIntervals:
lapsedTime = time.time() - STARTTIME
if lapsedTime > maxTime:
addstatus = '** max time reached ' + str(lapsedTime)
print(addstatus)
Result.status = Result.status + '\n' + addstatus
break
if verbosity > 1:
print("Top of while with %d intervals elapsed time = %f" % (NumIntervals, lapsedTime))
PrintPRpoints(Result.lbz)
lambdaval = None
### loop over PR points to find first unfathomed interval to search ###
for PRpoint in range(1,len(Result.lbz)):
if Result.lbz[PRpoint][0] == None:
# multiplier = None means interval with upper endpoint at PRpoint not fathomed
bL = Result.lbz[PRpoint-1][1]
zL = Result.lbz[PRpoint-1][2]
bU = Result.lbz[PRpoint][1]
zU = Result.lbz[PRpoint][2]
lambdaval = (zU - zL) / (bU - bL)
break
#############################
# Exited from the for loop
if verbosity > 1:
print("exited for loop with PRpoint = %s ...lambdaval = %s" % (PRpoint, lambdaval))
if lambdaval == None: break # all intervals are fathomed
if verbosity > 1: PrintPRpoints(Result.lbz)
if verbosity > 0:
print("Searching for b in [%s, %s] with %s = %f" % (str(round(bL,4)), str(round(bU,4)), multName, lambdaval))
# search interval (bL,bU)
lagrUtil.Set_ParmValue(ph, multName,lambdaval)
if verbosity > 0:
print("solve begins %s" % datetime_string())
print("\t- %s = %f" % (multName, lambdaval))
#########################################################
SolStat, Lagrangian = lagrUtil.solve_ph_code(ph, options)
#########################################################
if not SolStat[0:2] == 'ok':
addstatus = "** Solution status " + SolStat + " is not optimal"
print(addstatus)
Result.status = Result.status + "\n" + addstatus
return Result
b = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
z = Lagrangian + lambdaval*b
if verbosity > 0:
print("solve ends %s" % datetime_string())
print("\t- Lagrangian = %f" % Lagrangian)
print("\t- b = %s" % str(b))
print("\t- z = %s" % str(z))
print("\n")
# We have PR point (b,z), which may be new or one of the endpoints
##################################################################
######### Begin tolerance tests ##########
# Test that b is in [bL,bU]
if verbosity > 1: print("\ttesting b")
if b < bL - betaTol or b > bU + betaTol:
addstatus = "** fatal error: probability (= " + str(b) + \
") is outside interval, (" + str(bL) + ", " + str(bU) + ")"
addstatus = addstatus + "\n\t(tolerance = " + str(betaTol) + ")"
print(addstatus+'\n')
Result.status = Result.status + addstatus
return Result
# Test that z is in [zL,zU]
if verbosity > 1: print("\ttesting z")
# using optTol as absolute tolerance (not relative)
# ...if we reconsider, need to allow negative z-values
if z < zL - optTol or z > zU + optTol:
addstatus = "** fatal error: obj (= " + str(z) + \
") is outside interval, (" + str(zL) + ", " + str(zU) + ")"
print(addstatus+'\n')
Result.status = Result.status + addstatus
return Result
# Ok, we have (b,z) in [(bL,zL), (bU,zU)], at least within tolerances
oldLagrangian = zL - lambdaval*bL
# ensure lambdaval set such that endpoints have same Lagrangian value
# (this is probably unnecessary, but check anyway)
if abs(oldLagrangian - (zU - lambdaval*bU)) > optTol*abs(oldLagrangian):
addstatus = "** fatal error: Lagrangian at (bL,zL) = " + \
str(oldLagrangian) + " not= " + str(zU-lambdaval*bU) + \
"\n\t(optTol = " + str(optTol) + ")"
Result.status = Result.status + addstatus
return Result
# no more fatal error tests...need to know if (b,z) is endpoint or new
if verbosity > 1: print("No anomalies...testing if b = bL or bU")
# Test if endpoint is an alternative optimum of Lagrangian
# ...using optTol as *relative* tolerance
# (could use other reference values -- eg, avg or max of old and new Lagrangian values)
refValue = max( min( abs(oldLagrangian), abs(Lagrangian) ), 1.)
alternativeOpt = abs( oldLagrangian - Lagrangian ) <= optTol*refValue
# alternativeOpt = True means we computed point (b,z) is alternative optimum such that:
# case 1: (b,z) = endpoint, in which case we simply fathom [bL,bU] by setting PRpoint
# to [lambdaval,bU,zU] (the numeric value of multiplier means fathomed)
# case 2: (b,z) is new PR point on line segment, in which case we split into
# [bL,b] and [b,bU], with both fathomed
if verbosity > 1:
print("oldLagrangian = %s" % str(oldLagrangian))
if alternativeOpt: print(":= Lagrangian = %s" % str(Lagrangian ))
else: print("> Lagrangian = %s" % str(Lagrangian))
if alternativeOpt:
# setting multiplier of (bU,zU) to a numeric fathoms the interval [bL,bU]
Result.lbz[PRpoint][0] = lambdaval
# test if (b,z) is an endpoint
newPRpoint = abs(b-bL) > betaTol and abs(b-bU) > betaTol
if not newPRpoint:
# ...(b,z) is NOT an endpoint (or sufficiently close), so split and fathom
if verbosity > 1:
print("\tnot an endpoint\tlbz = %s" % str(Result.lbz[PRpoint]))
if verbosity > 0:
print("Lagangian solution is new PR point on line segment of (" \
+ str(bL) + ", " + str(bU) +")")
print("\tsplitting (bL,bU) into (bL,b) and (b,bU), both fathomed")
# note: else ==> b = bL or bU, so we do nothing, having already fathomed [bL,bU]
# (b,z) is new PR point, so split interval (still in while loop)
##########################################
# alternative optimum ==> split & fathom: (bL,b), (b,bU)
if verbosity > 1:
print("\talternativeOpt %s newPRpoint = %s" % (alternativeOpt, newPRpoint))
if newPRpoint:
NumIntervals += 1
if alternativeOpt:
if verbosity > 1: print("\tInsert [lambdaval,b,z] at %f" % PRpoint)
Result.lbz = Insert([lambdaval,b,z],PRpoint,Result.lbz)
addstatus = "Added PR point on line segment of envelope"
if verbosity > 0: print(addstatus+'\n')
else:
if verbosity > 1: print("\tInsert [None,b,z] at %f" % PRpoint)
Result.lbz = Insert([None,b,z],PRpoint,Result.lbz)
addstatus = "new envelope extreme point added (interval split, not fathomed)"
Result.status = Result.status + "\n" + addstatus
if verbosity > 1:
print("...after insertion:")
PrintPRpoints(Result.lbz)
# get the selections of new point (ie, scenarios for which delta=1)
Selections = []
for scenario in ScenarioList:
instance = ph._instances[scenario[0]]
if getattr(instance,IndVarName).value == 1:
Selections.append(scenario)
Result.selections = Insert(Selections,PRpoint,Result.selections)
if verbosity > 0:
print("Interval "+str(PRpoint)+", ["+str(bL)+", "+str(bU)+ \
"] split at ("+str(b)+", "+str(z)+")")
print("\tnew PR point has "+str(len(Selections))+" selections")
if verbosity > 1: print("test that selections list aligned with lbz")
if not len(Result.lbz) == len(Result.selections):
print("** fatal error: lbz not= selections")
PrintPRpoints(Result.lbz)
print("Result.selections:")
for i in range(Result.selections): print("%d %f" % (i,Result.selections[i]))
return Result
# ok, we have split and/or fathomed interval
if NumIntervals >= maxIntervals:
# we are about to leave while loop due to...
addstatus = "** terminating because number of intervals = " + \
str(NumIntervals) + " >= max = " + str(maxIntervals)
if verbosity > 0: print(addstatus+'\n')
Result.status = Result.status + "\n" + addstatus
# while loop continues
if verbosity > 1:
print("bottom of while loop")
PrintPRpoints(Result.lbz)
###################################################
# end while NumIntervals < maxIntervals:
# ^ this is indentation of while loop
################ end while loop ###################
if verbosity > 1: print("\nend while loop...setting multipliers")
for i in range(1,len(Result.lbz)):
db = Result.lbz[i][1] - Result.lbz[i-1][1]
dz = Result.lbz[i][2] - Result.lbz[i-1][2]
if dz > 0:
Result.lbz[i][0] = dz/db
else:
#print "dz =",dz," at ",i,": ",Result.lbz[i]," -",Result.lbz[i-1]
Result.lbz[i][0] = 0
if verbosity > 0: PrintPRpoints(Result.lbz)
addstatus = '\nLagrange multiplier search ends'+datetime_string()
if verbosity > 0:
print(addstatus+'\n')
Result.status = Result.status + addstatus
outName = csvPrefix + "PRoptimal.csv"
with open(outName,'w') as outFile:
if verbosity > 0:
print("writing PR points to "+outName+'\n')
for lbz in Result.lbz:
outFile.write(str(lbz[1])+ ", " +str(lbz[2])+'\n')
outName = csvPrefix + "OptimalSelections.csv"
with open(outName,'w') as outFile:
if verbosity > 0:
print("writing optimal selections for each PR point to "+csvPrefix+'PRoptimal.csv\n')
for selections in Result.selections:
char = ""
thisSelection = ""
for slist in selections:
if slist:
thisSelection = thisSelection + char + slist[0]
char = ","
outFile.write(thisSelection+'\n')
if verbosity > 0:
print("\nReturning status:\n %s \n=======================" % Result.status)
################################
if verbosity > 2:
print("\nAbout to return...Result attributes: %d" % len(inspect.getmembers(Result)))
for attr in inspect.getmembers(Result): print(attr[0])
print("\n===========================================")
# LagrangeParametric ends here
return Result
def partialLagrangeParametric(args=None):
print("lagrangeParam begins ")
blanks = " " # used for formatting print statements
class Object(object):
pass
Result = Object()
# options used
IndVarName = options.indicator_var_name
CCStageNum = options.stage_num
alphaTol = options.alpha_tol
MaxMorePR = options.MaxMorePR # option to include up to this many PR points above F^* with all delta fixed
outputFilePrefix = options.outputFilePrefix
# We write ScenarioList = name, probability
# PRoptimal = probability, min-cost, [selections]
# PRmore = probability, min-cost, [selections]
# ================ sorted by probability ========================
#
# These can be read to avoid re-computing points
ph = PHFromScratch(options)
Result.ph = ph
rootnode = ph._scenario_tree._stages[0]._tree_nodes[
0] # use rootnode to loop over scenarios
if find_active_objective(ph._scenario_tree._scenarios[0]._instance,
safety_checks=True).is_minimizing():
print("We are solving a MINIMIZATION problem.\n")
else:
print("We are solving a MAXIMIZATION problem.\n")
# initialize
ScenarioList = []
lambdaval = 0.
lagrUtil.Set_ParmValue(ph, options.lambda_parm_name, lambdaval)
# IMPORTANT: Preprocess the scenario instances
# before fixing variables, otherwise they
# will be preprocessed out of the expressions
# and the output_fixed_variable_bounds option
# will have no effect when we update the
# fixed variable values (and then assume we
# do not need to preprocess again because
# of this option).
ph._preprocess_scenario_instances()
lagrUtil.FixAllIndicatorVariables(ph, IndVarName, 0)
for scenario in rootnode._scenarios:
ScenarioList.append((scenario._name, scenario._probability))
# sorts from min to max probability
ScenarioList.sort(key=operator.itemgetter(1))
with open(outputFilePrefix + 'ScenarioList.csv', 'w') as outFile:
for scenario in ScenarioList:
outFile.write(scenario[0] + ", " + str(scenario[1]) + "\n")
Result.ScenarioList = ScenarioList
print("lambda= " + str(lambdaval) + " ...run begins " +
str(len(ScenarioList)) + " scenarios")
SolStat, zL = lagrUtil.solve_ph_code(ph, options)
print("\t...ends")
bL = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
if bL > 0:
print("** bL = " + str(bL) + " > 0")
return Result
print("Initial cost = " + str(zL) + " for bL = " + str(bL))
lagrUtil.FixAllIndicatorVariables(ph, IndVarName, 1)
print("lambda= " + str(lambdaval) + " ...run begins")
SolStat, zU = lagrUtil.solve_ph_code(ph, options)
print("\t...ends")
bU = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
if bU < 1:
print("** bU = " + str(bU) + " < 1")
lagrUtil.FreeAllIndicatorVariables(ph, IndVarName)
Result.lbz = [[0, bL, zL], [None, bU, zU]]
Result.selections = [[], ScenarioList]
NumIntervals = 1
print("initial gap = " + str(1 - zL / zU) + " \n")
print("End of test; this is only a test.")
return Result
def LagrangeParametric(args=None):
class Object(object):
pass
Result = Object()
Result.status = 'LagrangeParam begins ' + datetime_string(
) + '...running new ph'
ph = None
blanks = " " # used for formatting print statements
# options used
betaMin = options.beta_min
betaMax = options.beta_max
betaTol = options.beta_tol
gapTol = options.Lagrange_gap
minProb = options.min_prob
maxIntervals = options.max_intervals
maxTime = options.max_time
IndVarName = options.indicator_var_name
multName = options.lambda_parm_name
CCStageNum = options.stage_num
csvPrefix = options.csvPrefix
verbosity = options.verbosity
verbosity = 2 # override for debug (= 3 to get super-debug)
HGdebug = 0 # special debug (not public)
# local...may become option
optTol = gapTol
####################################################################
STARTTIME = time.time()
Result.status = "options set"
if verbosity > 1:
print("From LagrangeParametric, status = %s\tSTARTTIME = %s" \
% (str(getattr(Result,'status')), str(STARTTIME)))
ph = PHFromScratch(options)
Result.ph = ph
rootnode = ph._scenario_tree._stages[0]._tree_nodes[
0] # use rootnode to loop over scenarios
ReferenceInstance = ph._instances[
rootnode._scenarios[0]._name] # arbitrary scenario
if find_active_objective(ph._scenario_tree._scenarios[0]._instance,
safety_checks=True).is_minimizing():
sense = 'min'
else:
sense = 'max'
scenario_count = len(full_scenario_tree._stages[-1]._tree_nodes)
if options.verbosity > 0:
print("%s %s scenarios" % (str(sense), str(scenario_count)))
# initialize
Result.status = 'starting at ' + datetime_string()
if verbosity > 0:
print(Result.status)
ScenarioList = []
lambdaval = 0.
lagrUtil.Set_ParmValue(ph, multName, lambdaval)
# IMPORTANT: Preprocess the scenario instances
# before fixing variables, otherwise they
# will be preprocessed out of the expressions
# and the output_fixed_variable_bounds option
# will have no effect when we update the
# fixed variable values (and then assume we
# do not need to preprocess again because
# of this option).
ph._preprocess_scenario_instances()
sumprob = 0.
minprob = 1.
maxprob = 0.
# fixed = 0 to get PR point at b=0
lagrUtil.FixAllIndicatorVariables(ph, IndVarName, 0)
for scenario in rootnode._scenarios:
instance = ph._instances[scenario._name]
sname = scenario._name
sprob = scenario._probability
sumprob = sumprob + sprob
minprob = min(minprob, sprob)
maxprob = max(maxprob, sprob)
ScenarioList.append([sname, sprob])
ScenarioList.sort(
key=operator.itemgetter(1)) # sorts from min to max probability
if verbosity > 0:
print("probabilities sum to %f range: %f to %f" %
(sumprob, minprob, maxprob))
Result.ScenarioList = ScenarioList
# Write ScenarioList = name, probability in csv file sorted by probability
outName = csvPrefix + 'ScenarioList.csv'
print("writing to %s" % outName)
with open(outName, 'w') as outFile:
for scenario in ScenarioList:
outFile.write(scenario[0] + ", " + str(scenario[1]) + '\n')
Result.ScenarioList = ScenarioList
addstatus = 'Scenario List written to ' + csvPrefix + 'ScenarioList.csv'
Result.status = Result.status + '\n' + addstatus
if verbosity > 0:
print(addstatus)
if verbosity > 0:
print("solve begins %s" % datetime_string())
print("\t- lambda = %f" % lambdaval)
SolStat, zL = lagrUtil.solve_ph_code(ph, options)
if verbosity > 0:
print("solve ends %s" % datetime_string())
print("\t- status = %s" % str(SolStat))
print("\t- zL = %s" % str(zL))
bL = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
if bL > 0:
print("** bL = %s > 0 (all %s = 0)" % (str(bL), str(IndVarName)))
return Result
if verbosity > 0:
print("Initial optimal obj = %s for bL = %s" % (str(zL), str(bL)))
# fixed = 1 to get PR point at b=1
lagrUtil.FixAllIndicatorVariables(ph, IndVarName, 1)
if verbosity > 0:
print("solve begins %s" % datetime_string())
print("\t- lambda = %s" % str(lambdaval))
SolStat, zU = lagrUtil.solve_ph_code(ph, options)
if verbosity > 0:
print("solve ends %s" % datetime_string())
print("\t- status = %s" % str(SolStat))
print("\t- zU = %s" % str(zU))
if not SolStat[0:2] == 'ok':
print(str(SolStat[0:3]) + " is not 'ok'")
addstatus = "** Solution is non-optimal...aborting"
print(addstatus)
Result.status = Result.status + "\n" + addstatus
return Result
bU = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
if bU < 1. - betaTol and verbosity > 0:
print("** Warning: bU = %s < 1" % str(bU))
### enumerate points in PR space (all but one scenario)
# Result.lbz = [ [0,bL,zL], [None,bU,zU] ]
# for scenario in rootnode._scenarios:
# sname = scenario._name
# instance = ph._instances[sname]
# print "excluding scenario",sname
# getattr(instance,IndVarName).value = 0
# print sname,"value =",getattr(instance,IndVarName).value,getattr(instance,IndVarName).fixed
# SolStat, z = lagrUtil.solve_ph_code(ph, options)
# b = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
# print "solve ends with status =",SolStat,"(b, z) =",b,z
# getattr(instance,IndVarName).value = 1
# Result.lbz.append([None,b,z])
# for t in instance.TimePeriods:
# print "Global at",t,"=",instance.posGlobalLoadGenerateMismatch[t].value, \
# '-',instance.negGlobalLoadGenerateMismatch[t].value,"=",\
# instance.GlobalLoadGenerateMismatch[t].value,\
# "\tDemand =",instance.TotalDemand[t].value, ",",\
# "Reserve =",instance.ReserveRequirement[t].value
#
# PrintPRpoints(Result.lbz)
# return Result
#### end enumeration
########################################################################
if verbosity > 1:
print("We have bU = %s ...about to free all %s for %d scenarios" % \
(str(bU), str(IndVarName), len(ScenarioList)))
# free scenario selection variable
lagrUtil.FreeAllIndicatorVariables(ph, IndVarName)
if verbosity > 1:
print("\tall %s freed; elapsed time = %f" %
(str(IndVarName), time.time() - STARTTIME))
# initialize with the two endpoints
Result.lbz = [[0., bL, zL], [None, bU, zU]]
Result.selections = [[], ScenarioList]
NumIntervals = 1
if verbosity > 0:
print("Initial relative Lagrangian gap = %f maxIntervals = %d" %
(1 - zL / zU, maxIntervals))
if verbosity > 1:
print("entering while loop %s" % datetime_string())
print("\n")
############ main loop to search intervals #############
########################################################
while NumIntervals < maxIntervals:
lapsedTime = time.time() - STARTTIME
if lapsedTime > maxTime:
addstatus = '** max time reached ' + str(lapsedTime)
print(addstatus)
Result.status = Result.status + '\n' + addstatus
break
if verbosity > 1:
print("Top of while with %d intervals elapsed time = %f" %
(NumIntervals, lapsedTime))
PrintPRpoints(Result.lbz)
lambdaval = None
### loop over PR points to find first unfathomed interval to search ###
for PRpoint in range(1, len(Result.lbz)):
if Result.lbz[PRpoint][0] == None:
# multiplier = None means interval with upper endpoint at PRpoint not fathomed
bL = Result.lbz[PRpoint - 1][1]
zL = Result.lbz[PRpoint - 1][2]
bU = Result.lbz[PRpoint][1]
zU = Result.lbz[PRpoint][2]
lambdaval = (zU - zL) / (bU - bL)
break
#############################
# Exited from the for loop
if verbosity > 1:
print("exited for loop with PRpoint = %s ...lambdaval = %s" %
(PRpoint, lambdaval))
if lambdaval == None: break # all intervals are fathomed
if verbosity > 1: PrintPRpoints(Result.lbz)
if verbosity > 0:
print("Searching for b in [%s, %s] with %s = %f" % (str(
round(bL, 4)), str(round(bU, 4)), multName, lambdaval))
# search interval (bL,bU)
lagrUtil.Set_ParmValue(ph, multName, lambdaval)
if verbosity > 0:
print("solve begins %s" % datetime_string())
print("\t- %s = %f" % (multName, lambdaval))
#########################################################
SolStat, Lagrangian = lagrUtil.solve_ph_code(ph, options)
#########################################################
if not SolStat[0:2] == 'ok':
addstatus = "** Solution status " + SolStat + " is not optimal"
print(addstatus)
Result.status = Result.status + "\n" + addstatus
return Result
b = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
z = Lagrangian + lambdaval * b
if verbosity > 0:
print("solve ends %s" % datetime_string())
print("\t- Lagrangian = %f" % Lagrangian)
print("\t- b = %s" % str(b))
print("\t- z = %s" % str(z))
print("\n")
# We have PR point (b,z), which may be new or one of the endpoints
##################################################################
######### Begin tolerance tests ##########
# Test that b is in [bL,bU]
if verbosity > 1: print("\ttesting b")
if b < bL - betaTol or b > bU + betaTol:
addstatus = "** fatal error: probability (= " + str(b) + \
") is outside interval, (" + str(bL) + ", " + str(bU) + ")"
addstatus = addstatus + "\n\t(tolerance = " + str(
betaTol) + ")"
print(addstatus + '\n')
Result.status = Result.status + addstatus
return Result
# Test that z is in [zL,zU]
if verbosity > 1: print("\ttesting z")
# using optTol as absolute tolerance (not relative)
# ...if we reconsider, need to allow negative z-values
if z < zL - optTol or z > zU + optTol:
addstatus = "** fatal error: obj (= " + str(z) + \
") is outside interval, (" + str(zL) + ", " + str(zU) + ")"
print(addstatus + '\n')
Result.status = Result.status + addstatus
return Result
# Ok, we have (b,z) in [(bL,zL), (bU,zU)], at least within tolerances
oldLagrangian = zL - lambdaval * bL
# ensure lambdaval set such that endpoints have same Lagrangian value
# (this is probably unnecessary, but check anyway)
if abs(oldLagrangian -
(zU - lambdaval * bU)) > optTol * abs(oldLagrangian):
addstatus = "** fatal error: Lagrangian at (bL,zL) = " + \
str(oldLagrangian) + " not= " + str(zU-lambdaval*bU) + \
"\n\t(optTol = " + str(optTol) + ")"
Result.status = Result.status + addstatus
return Result
# no more fatal error tests...need to know if (b,z) is endpoint or new
if verbosity > 1: print("No anomalies...testing if b = bL or bU")
# Test if endpoint is an alternative optimum of Lagrangian
# ...using optTol as *relative* tolerance
# (could use other reference values -- eg, avg or max of old and new Lagrangian values)
refValue = max(min(abs(oldLagrangian), abs(Lagrangian)), 1.)
alternativeOpt = abs(oldLagrangian -
Lagrangian) <= optTol * refValue
# alternativeOpt = True means we computed point (b,z) is alternative optimum such that:
# case 1: (b,z) = endpoint, in which case we simply fathom [bL,bU] by setting PRpoint
# to [lambdaval,bU,zU] (the numeric value of multiplier means fathomed)
# case 2: (b,z) is new PR point on line segment, in which case we split into
# [bL,b] and [b,bU], with both fathomed
if verbosity > 1:
print("oldLagrangian = %s" % str(oldLagrangian))
if alternativeOpt:
print(":= Lagrangian = %s" % str(Lagrangian))
else:
print("> Lagrangian = %s" % str(Lagrangian))
if alternativeOpt:
# setting multiplier of (bU,zU) to a numeric fathoms the interval [bL,bU]
Result.lbz[PRpoint][0] = lambdaval
# test if (b,z) is an endpoint
newPRpoint = abs(b - bL) > betaTol and abs(b - bU) > betaTol
if not newPRpoint:
# ...(b,z) is NOT an endpoint (or sufficiently close), so split and fathom
if verbosity > 1:
print("\tnot an endpoint\tlbz = %s" %
str(Result.lbz[PRpoint]))
if verbosity > 0:
print("Lagangian solution is new PR point on line segment of (" \
+ str(bL) + ", " + str(bU) +")")
print(
"\tsplitting (bL,bU) into (bL,b) and (b,bU), both fathomed"
)
# note: else ==> b = bL or bU, so we do nothing, having already fathomed [bL,bU]
# (b,z) is new PR point, so split interval (still in while loop)
##########################################
# alternative optimum ==> split & fathom: (bL,b), (b,bU)
if verbosity > 1:
print("\talternativeOpt %s newPRpoint = %s" %
(alternativeOpt, newPRpoint))
if newPRpoint:
NumIntervals += 1
if alternativeOpt:
if verbosity > 1:
print("\tInsert [lambdaval,b,z] at %f" % PRpoint)
Result.lbz = Insert([lambdaval, b, z], PRpoint, Result.lbz)
addstatus = "Added PR point on line segment of envelope"
if verbosity > 0: print(addstatus + '\n')
else:
if verbosity > 1:
print("\tInsert [None,b,z] at %f" % PRpoint)
Result.lbz = Insert([None, b, z], PRpoint, Result.lbz)
addstatus = "new envelope extreme point added (interval split, not fathomed)"
Result.status = Result.status + "\n" + addstatus
if verbosity > 1:
print("...after insertion:")
PrintPRpoints(Result.lbz)
# get the selections of new point (ie, scenarios for which delta=1)
Selections = []
for scenario in ScenarioList:
instance = ph._instances[scenario[0]]
if getattr(instance, IndVarName).value == 1:
Selections.append(scenario)
Result.selections = Insert(Selections, PRpoint,
Result.selections)
if verbosity > 0:
print("Interval "+str(PRpoint)+", ["+str(bL)+", "+str(bU)+ \
"] split at ("+str(b)+", "+str(z)+")")
print("\tnew PR point has " + str(len(Selections)) +
" selections")
if verbosity > 1:
print("test that selections list aligned with lbz")
if not len(Result.lbz) == len(Result.selections):
print("** fatal error: lbz not= selections")
PrintPRpoints(Result.lbz)
print("Result.selections:")
for i in range(Result.selections):
print("%d %f" % (i, Result.selections[i]))
return Result
# ok, we have split and/or fathomed interval
if NumIntervals >= maxIntervals:
# we are about to leave while loop due to...
addstatus = "** terminating because number of intervals = " + \
str(NumIntervals) + " >= max = " + str(maxIntervals)
if verbosity > 0: print(addstatus + '\n')
Result.status = Result.status + "\n" + addstatus
# while loop continues
if verbosity > 1:
print("bottom of while loop")
PrintPRpoints(Result.lbz)
###################################################
# end while NumIntervals < maxIntervals:
# ^ this is indentation of while loop
################ end while loop ###################
if verbosity > 1: print("\nend while loop...setting multipliers")
for i in range(1, len(Result.lbz)):
db = Result.lbz[i][1] - Result.lbz[i - 1][1]
dz = Result.lbz[i][2] - Result.lbz[i - 1][2]
if dz > 0:
Result.lbz[i][0] = dz / db
else:
#print "dz =",dz," at ",i,": ",Result.lbz[i]," -",Result.lbz[i-1]
Result.lbz[i][0] = 0
if verbosity > 0: PrintPRpoints(Result.lbz)
addstatus = '\nLagrange multiplier search ends' + datetime_string()
if verbosity > 0:
print(addstatus + '\n')
Result.status = Result.status + addstatus
outName = csvPrefix + "PRoptimal.csv"
with open(outName, 'w') as outFile:
if verbosity > 0:
print("writing PR points to " + outName + '\n')
for lbz in Result.lbz:
outFile.write(str(lbz[1]) + ", " + str(lbz[2]) + '\n')
outName = csvPrefix + "OptimalSelections.csv"
with open(outName, 'w') as outFile:
if verbosity > 0:
print("writing optimal selections for each PR point to " +
csvPrefix + 'PRoptimal.csv\n')
for selections in Result.selections:
char = ""
thisSelection = ""
for slist in selections:
if slist:
thisSelection = thisSelection + char + slist[0]
char = ","
outFile.write(thisSelection + '\n')
if verbosity > 0:
print("\nReturning status:\n %s \n=======================" %
Result.status)
################################
if verbosity > 2:
print("\nAbout to return...Result attributes: %d" %
len(inspect.getmembers(Result)))
for attr in inspect.getmembers(Result):
print(attr[0])
print("\n===========================================")
# LagrangeParametric ends here
return Result
def LagrangeMorePR(args=None):
print("lagrangeMorePR begins %s" % datetime_string())
blanks = " " # used for formatting print statements
class Object(object): pass
Result = Object()
# options used
betaTol = options.beta_tol # tolerance used to separate b-values
IndVarName = options.indicator_var_name
multName = options.lambda_parm_name
CCStageNum = options.stage_num
MaxMorePR = options.max_number # max PR points to be generated (above F^* with all delta fixed)
MaxTime = options.max_time # max time before terminate
csvPrefix = options.csvPrefix # input filename prefix (eg, case name)
probFileName = options.probFileName # name of file containing probabilities
##HG override
# options.verbosity = 2
verbosity = options.verbosity
Result.status = 'starting '+datetime_string()
STARTTIME = time.time()
ph = PHFromScratch(options)
rootnode = ph._scenario_tree._stages[0]._tree_nodes[0] # use rootnode to loop over scenarios
if find_active_objective(ph._scenario_tree._scenarios[0]._instance,safety_checks=True).is_minimizing():
print("We are solving a MINIMIZATION problem.")
else:
print("We are solving a MAXIMIZATION problem.")
# initialize
ScenarioList = []
with open(csvPrefix+"ScenarioList.csv",'r') as inputFile:
for line in inputFile.readlines():
L = line.split(',')
ScenarioList.append([L[0],float(L[1])])
addstatus = str(len(ScenarioList))+' scenarios read from file: ' + csvPrefix+'ScenarioList.csv'
if verbosity > 0: print(addstatus)
Result.status = Result.status + '\n' + addstatus
PRoptimal = []
with open(csvPrefix+"PRoptimal.csv",'r') as inputFile:
for line in inputFile.readlines():
bzS = line.split(',')
PRoptimal.append( [None, float(bzS[0]), float(bzS[1])] )
addstatus = str(len(PRoptimal))+' PR points read from file: '+ csvPrefix+'PRoptimal.csv (envelope function)'
if verbosity > 0:
print(addstatus)
Result.status = Result.status + '\n' + addstatus
# ensure PR points on envelope function are sorted by probability
PRoptimal.sort(key=operator.itemgetter(1))
PRoptimal[0][0] = 0 # initial lambda (for b=0)
for p in range(1,len(PRoptimal)):
dz = PRoptimal[p][2] - PRoptimal[p-1][2]
db = PRoptimal[p][1] - PRoptimal[p-1][1]
PRoptimal[p][0] = dz/db
if verbosity > 0:
PrintPRpoints(PRoptimal)
Result.PRoptimal = PRoptimal
lambdaval = 0.
lagrUtil.Set_ParmValue(ph, options.lambda_parm_name,lambdaval)
# IMPORTANT: Preprocess the scenario instances
# before fixing variables, otherwise they
# will be preprocessed out of the expressions
# and the output_fixed_variable_bounds option
# will have no effect when we update the
# fixed variable values (and then assume we
# do not need to preprocess again because
# of this option).
ph._preprocess_scenario_instances()
## read scenarios to select for each PR point on envelope function
with open(csvPrefix+"OptimalSelections.csv",'r') as inputFile:
OptimalSelections = []
for line in inputFile.readlines():
if len(line) == 0: break # eof
selections = line.split(',')
L = len(selections)
Ls = len(selections[L-1])
selections[L-1] = selections[L-1][0:Ls-1]
if verbosity > 1:
print(str(selections))
OptimalSelections.append(selections)
Result.OptimalSelections = OptimalSelections
addstatus = str(len(OptimalSelections)) + ' Optimal selections read from file: ' \
+ csvPrefix + 'OptimalSelections.csv'
Result.status = Result.status + '\n' + addstatus
if len(OptimalSelections) == len(PRoptimal):
if verbosity > 0:
print(addstatus)
else:
addstatus = addstatus + '\n** Number of selections not equal to number of PR points'
print(addstatus)
Result.status = Result.status + '\n' + addstatus
print(str(OptimalSelections))
print((PRoptimal))
return Result
#####################################################################################
# get probabilities
if probFileName is None:
# ...generate from widest gap regions
PRlist = FindPRpoints(options, PRoptimal)
else:
# ...read probabilities
probList = []
with open(probFileName,'r') as inputFile:
if verbosity > 0:
print("reading from probList = "+probFileName)
for line in inputFile.readlines(): # 1 probability per line
if len(line) == 0:
break
prob = float(line)
probList.append(prob)
if verbosity > 0:
print("\t "+str(len(probList))+" probabilities")
if verbosity > 1:
print(str(probList))
PRlist = GetPoints(options, PRoptimal, probList)
if verbosity > 1:
print("PRlist:")
for interval in PRlist:
print(str(interval))
# We now have PRlist = [[i, b], ...], where b is in PRoptimal interval (i-1,i)
addstatus = str(len(PRlist)) + ' probabilities'
if verbosity > 0:
print(addstatus)
Result.status = Result.status + '\n' + addstatus
#####################################################################################
lapsedTime = time.time() - STARTTIME
addstatus = 'Initialize complete...lapsed time = ' + str(lapsedTime)
if verbosity > 1:
print(addstatus)
Result.status = Result.status + '\n' + addstatus
#####################################################################################
if verbosity > 1:
print("\nlooping over Intervals to generate PR points by flipping heuristic")
Result.morePR = []
for interval in PRlist:
lapsedTime = time.time() - STARTTIME
if lapsedTime > MaxTime:
addstatus = '** lapsed time = ' + str(lapsedTime) + ' > max time = ' + str(MaxTime)
if verbosity > 0: print(addstatus)
Result.status = Result.status + '\n' + addstatus
break
i = interval[0] # = PR point index
b = interval[1] # = target probability to reach by flipping from upper endpoint
bU = PRoptimal[i][1] # = upper endpoint
bL = PRoptimal[i-1][1] # = lower endpoint
if verbosity > 1:
print( "target probability = "+str(b)+" < bU = PRoptimal[" + str(i) + "][1]" \
" and > bL = PRoptimal["+str(i-1)+"][1]")
if b < bL or b > bU:
addstatus = '** probability = '+str(b) + ', not in gap interval: (' \
+ str(bL) + ', ' + str(bU) + ')'
print(addstatus)
print(str(PRoptimal))
print(str(PRlist))
Result.status = Result.status + '\n' + addstatus
return Result
if verbosity > 1:
print( "i = "+str(i)+" : Starting with bU = "+str(bU)+" having "+ \
str(len(OptimalSelections[i]))+ " selections:")
print(str(OptimalSelections[i]))
# first fix all scenarios = 0
for sname, sprob in ScenarioList:
scenario = ph._scenario_tree.get_scenario(sname)
lagrUtil.FixIndicatorVariableOneScenario(ph,
scenario,
IndVarName,
0)
# now fix optimal selections = 1
for sname in OptimalSelections[i]:
scenario = ph._scenario_tree.get_scenario(sname)
lagrUtil.FixIndicatorVariableOneScenario(ph,
scenario,
IndVarName,
1)
# flip scenario selections from bU until we reach b (target probability)
bNew = bU
for sname, sprob in ScenarioList:
scenario = ph._scenario_tree.get_scenario(sname)
if bNew - sprob < b:
continue
instance = ph._instances[sname]
if getattr(instance, IndVarName).value == 0:
continue
bNew = bNew - sprob
# flipped scenario selection
lagrUtil.FixIndicatorVariableOneScenario(ph,
scenario,
IndVarName,
0)
if verbosity > 1:
print("\tflipped "+sname+" with prob = "+str(sprob)+" ...bNew = "+str(bNew))
if verbosity > 1:
print("\tflipped selections reach "+str(bNew)+" >= target = "+str(b)+" (bL = "+str(bL)+")")
if bNew <= bL + betaTol or bNew >= bU - betaTol:
if verbosity > 0:
print("\tNot generating PR point...flipping from bU failed")
continue # to next interval in list
# ready to solve to get cost for fixed scenario selections associated with probability = bNew
if verbosity > 1:
# check that scenarios are fixed as they should be
totalprob = 0.
for scenario in ScenarioList:
sname = scenario[0]
sprob = scenario[1]
instance = ph._instances[sname]
print("fix "+sname+" = "+str(getattr(instance,IndVarName).value)+\
" is "+str(getattr(instance,IndVarName).fixed)+" probability = "+str(sprob))
if getattr(instance,IndVarName).value == 1:
totalprob = totalprob + sprob
lambdaval = getattr(instance, multName).value
print("\ttotal probability = %f" % totalprob)
# solve (all delta fixed); lambda=0, so z = Lagrangian
if verbosity > 0:
print("solve begins %s" % datetime_string())
print("\t- lambda = %f" % lambdaval)
SolStat, z = lagrUtil.solve_ph_code(ph, options)
b = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
if verbosity > 0:
print("solve ends %s" % datetime_string())
print("\t- SolStat = %s" % str(SolStat))
print("\t- b = %s" % str(b))
print("\t- z = %s" % str(z))
print("(adding to more PR points)")
Result.morePR.append([None,b,z])
if verbosity > 1:
PrintPRpoints(Result.morePR)
######################################################
# end loop over target probabilities
with open(csvPrefix+"PRmore.csv",'w') as outFile:
for point in Result.morePR:
outFile.write(str(point[1])+','+str(point[2]))
addstatus = str(len(Result.morePR)) + ' PR points written to file: '+ csvPrefix + 'PRmore.csv'
if verbosity > 0: print(addstatus)
Result.status = Result.status + '\n' + addstatus
addstatus = 'lapsed time = ' + putcommas(time.time() - STARTTIME)
if verbosity > 0: print(addstatus)
Result.status = Result.status + '\n' + addstatus
return Result
def LagrangeMorePR(args=None):
print("lagrangeMorePR begins %s" % datetime_string())
blanks = " " # used for formatting print statements
class Object(object): pass
Result = Object()
# options used
betaTol = options.beta_tol # tolerance used to separate b-values
IndVarName = options.indicator_var_name
multName = options.lambda_parm_name
CCStageNum = options.stage_num
MaxMorePR = options.max_number # max PR points to be generated (above F^* with all delta fixed)
MaxTime = options.max_time # max time before terminate
csvPrefix = options.csvPrefix # input filename prefix (eg, case name)
probFileName = options.probFileName # name of file containing probabilities
##HG override
# options.verbosity = 2
verbosity = options.verbosity
Result.status = 'starting '+datetime_string()
STARTTIME = time.time()
ph = PHFromScratch(options)
rootnode = ph._scenario_tree._stages[0]._tree_nodes[0] # use rootnode to loop over scenarios
if find_active_objective(ph._scenario_tree._scenarios[0]._instance,safety_checks=True).is_minimizing():
print("We are solving a MINIMIZATION problem.")
else:
print("We are solving a MAXIMIZATION problem.")
# initialize
ScenarioList = []
with open(csvPrefix+"ScenarioList.csv",'r') as inputFile:
for line in inputFile.readlines():
L = line.split(',')
ScenarioList.append([L[0],float(L[1])])
addstatus = str(len(ScenarioList))+' scenarios read from file: ' + csvPrefix+'ScenarioList.csv'
if verbosity > 0: print(addstatus)
Result.status = Result.status + '\n' + addstatus
PRoptimal = []
with open(csvPrefix+"PRoptimal.csv",'r') as inputFile:
for line in inputFile.readlines():
bzS = line.split(',')
PRoptimal.append( [None, float(bzS[0]), float(bzS[1])] )
addstatus = str(len(PRoptimal))+' PR points read from file: '+ csvPrefix+'PRoptimal.csv (envelope function)'
if verbosity > 0:
print(addstatus)
Result.status = Result.status + '\n' + addstatus
# ensure PR points on envelope function are sorted by probability
PRoptimal.sort(key=operator.itemgetter(1))
PRoptimal[0][0] = 0 # initial lambda (for b=0)
for p in range(1,len(PRoptimal)):
dz = PRoptimal[p][2] - PRoptimal[p-1][2]
db = PRoptimal[p][1] - PRoptimal[p-1][1]
PRoptimal[p][0] = dz/db
if verbosity > 0:
PrintPRpoints(PRoptimal)
Result.PRoptimal = PRoptimal
lambdaval = 0.
lagrUtil.Set_ParmValue(ph, options.lambda_parm_name,lambdaval)
# IMPORTANT: Preprocess the scenario instances
# before fixing variables, otherwise they
# will be preprocessed out of the expressions
# and the output_fixed_variable_bounds option
# will have no effect when we update the
# fixed variable values (and then assume we
# do not need to preprocess again because
# of this option).
ph._preprocess_scenario_instances()
## read scenarios to select for each PR point on envelope function
with open(csvPrefix+"OptimalSelections.csv",'r') as inputFile:
OptimalSelections = []
for line in inputFile.readlines():
if len(line) == 0: break # eof
selections = line.split(',')
L = len(selections)
Ls = len(selections[L-1])
selections[L-1] = selections[L-1][0:Ls-1]
if verbosity > 1:
print(str(selections))
OptimalSelections.append(selections)
Result.OptimalSelections = OptimalSelections
addstatus = str(len(OptimalSelections)) + ' Optimal selections read from file: ' \
+ csvPrefix + 'OptimalSelections.csv'
Result.status = Result.status + '\n' + addstatus
if len(OptimalSelections) == len(PRoptimal):
if verbosity > 0:
print(addstatus)
else:
addstatus = addstatus + '\n** Number of selections not equal to number of PR points'
print(addstatus)
Result.status = Result.status + '\n' + addstatus
print(str(OptimalSelections))
print((PRoptimal))
return Result
#####################################################################################
# get probabilities
if probFileName is None:
# ...generate from widest gap regions
PRlist = FindPRpoints(options, PRoptimal)
else:
# ...read probabilities
probList = []
with open(probFileName,'r') as inputFile:
if verbosity > 0:
print("reading from probList = "+probFileName)
for line in inputFile.readlines(): # 1 probability per line
if len(line) == 0:
break
prob = float(line)
probList.append(prob)
if verbosity > 0:
print("\t "+str(len(probList))+" probabilities")
if verbosity > 1:
print(str(probList))
PRlist = GetPoints(options, PRoptimal, probList)
if verbosity > 1:
print("PRlist:")
for interval in PRlist:
print(str(interval))
# We now have PRlist = [[i, b], ...], where b is in PRoptimal interval (i-1,i)
addstatus = str(len(PRlist)) + ' probabilities'
if verbosity > 0:
print(addstatus)
Result.status = Result.status + '\n' + addstatus
#####################################################################################
lapsedTime = time.time() - STARTTIME
addstatus = 'Initialize complete...lapsed time = ' + str(lapsedTime)
if verbosity > 1:
print(addstatus)
Result.status = Result.status + '\n' + addstatus
#####################################################################################
if verbosity > 1:
print("\nlooping over Intervals to generate PR points by flipping heuristic")
Result.morePR = []
for interval in PRlist:
lapsedTime = time.time() - STARTTIME
if lapsedTime > MaxTime:
addstatus = '** lapsed time = ' + str(lapsedTime) + ' > max time = ' + str(MaxTime)
if verbosity > 0: print(addstatus)
Result.status = Result.status + '\n' + addstatus
break
i = interval[0] # = PR point index
b = interval[1] # = target probability to reach by flipping from upper endpoint
bU = PRoptimal[i][1] # = upper endpoint
bL = PRoptimal[i-1][1] # = lower endpoint
if verbosity > 1:
print( "target probability = "+str(b)+" < bU = PRoptimal[" + str(i) + "][1]" \
" and > bL = PRoptimal["+str(i-1)+"][1]")
if b < bL or b > bU:
addstatus = '** probability = '+str(b) + ', not in gap interval: (' \
+ str(bL) + ', ' + str(bU) + ')'
print(addstatus)
print(str(PRoptimal))
print(str(PRlist))
Result.status = Result.status + '\n' + addstatus
return Result
if verbosity > 1:
print( "i = "+str(i)+" : Starting with bU = "+str(bU)+" having "+ \
str(len(OptimalSelections[i]))+ " selections:")
print(str(OptimalSelections[i]))
# first fix all scenarios = 0
for sname, sprob in ScenarioList:
scenario = ph._scenario_tree.get_scenario(sname)
lagrUtil.FixIndicatorVariableOneScenario(ph,
scenario,
IndVarName,
0)
# now fix optimal selections = 1
for sname in OptimalSelections[i]:
scenario = ph._scenario_tree.get_scenario(sname)
lagrUtil.FixIndicatorVariableOneScenario(ph,
scenario,
IndVarName,
1)
# flip scenario selections from bU until we reach b (target probability)
bNew = bU
for sname, sprob in ScenarioList:
scenario = ph._scenario_tree.get_scenario(sname)
if bNew - sprob < b:
continue
instance = ph._instances[sname]
if getattr(instance, IndVarName).value == 0:
continue
bNew = bNew - sprob
# flipped scenario selection
lagrUtil.FixIndicatorVariableOneScenario(ph,
scenario,
IndVarName,
0)
if verbosity > 1:
print("\tflipped "+sname+" with prob = "+str(sprob)+" ...bNew = "+str(bNew))
if verbosity > 1:
print("\tflipped selections reach "+str(bNew)+" >= target = "+str(b)+" (bL = "+str(bL)+")")
if bNew <= bL + betaTol or bNew >= bU - betaTol:
if verbosity > 0:
print("\tNot generating PR point...flipping from bU failed")
continue # to next interval in list
# ready to solve to get cost for fixed scenario selections associated with probability = bNew
if verbosity > 1:
# check that scenarios are fixed as they should be
totalprob = 0.
for scenario in ScenarioList:
sname = scenario[0]
sprob = scenario[1]
instance = ph._instances[sname]
print("fix "+sname+" = "+str(getattr(instance,IndVarName).value)+\
" is "+str(getattr(instance,IndVarName).fixed)+" probability = "+str(sprob))
if getattr(instance,IndVarName).value == 1:
totalprob = totalprob + sprob
lambdaval = getattr(instance, multName).value
print("\ttotal probability = %f" % totalprob)
# solve (all delta fixed); lambda=0, so z = Lagrangian
if verbosity > 0:
print("solve begins %s" % datetime_string())
print("\t- lambda = %f" % lambdaval)
SolStat, z = lagrUtil.solve_ph_code(ph, options)
b = Compute_ExpectationforVariable(ph, IndVarName, CCStageNum)
if verbosity > 0:
print("solve ends %s" % datetime_string())
print("\t- SolStat = %s" % str(SolStat))
print("\t- b = %s" % str(b))
print("\t- z = %s" % str(z))
print("(adding to more PR points)")
Result.morePR.append([None,b,z])
if verbosity > 1:
PrintPRpoints(Result.morePR)
######################################################
# end loop over target probabilities
with open(csvPrefix+"PRmore.csv",'w') as outFile:
for point in Result.morePR:
outFile.write(str(point[1])+','+str(point[2]))
addstatus = str(len(Result.morePR)) + ' PR points written to file: '+ csvPrefix + 'PRmore.csv'
if verbosity > 0: print(addstatus)
Result.status = Result.status + '\n' + addstatus
addstatus = 'lapsed time = ' + putcommas(time.time() - STARTTIME)
if verbosity > 0: print(addstatus)
Result.status = Result.status + '\n' + addstatus
return Result
def partialLagrangeParametric(args=None):
print("lagrangeParam begins ")
blanks = " " # used for formatting print statements
class Object(object): pass
Result = Object()
# options used
IndVarName = options.indicator_var_name
CCStageNum = options.stage_num
alphaTol = options.alpha_tol
MaxMorePR = options.MaxMorePR # option to include up to this many PR points above F^* with all delta fixed
outputFilePrefix = options.outputFilePrefix
# We write ScenarioList = name, probability
# PRoptimal = probability, min-cost, [selections]
# PRmore = probability, min-cost, [selections]
# ================ sorted by probability ========================
#
# These can be read to avoid re-computing points
ph = PHFromScratch(options)
Result.ph = ph
rootnode = ph._scenario_tree._stages[0]._tree_nodes[0] # use rootnode to loop over scenarios
if find_active_objective(ph._scenario_tree._scenarios[0]._instance,safety_checks=True).is_minimizing():
print("We are solving a MINIMIZATION problem.\n")
else:
print("We are solving a MAXIMIZATION problem.\n")
# initialize
ScenarioList = []
lambdaval = 0.
lagrUtil.Set_ParmValue(ph,
options.lambda_parm_name,
lambdaval)
# IMPORTANT: Preprocess the scenario instances
# before fixing variables, otherwise they
# will be preprocessed out of the expressions
# and the output_fixed_variable_bounds option
# will have no effect when we update the
# fixed variable values (and then assume we
# do not need to preprocess again because
# of this option).
ph._preprocess_scenario_instances()
lagrUtil.FixAllIndicatorVariables(ph, IndVarName, 0)
for scenario in rootnode._scenarios:
ScenarioList.append((scenario._name,
scenario._probability))
# sorts from min to max probability
ScenarioList.sort(key=operator.itemgetter(1))
with open(outputFilePrefix+'ScenarioList.csv','w') as outFile:
for scenario in ScenarioList:
outFile.write(scenario[0]+ ", " +str(scenario[1])+"\n")
Result.ScenarioList = ScenarioList
print("lambda= "+str(lambdaval)+" ...run begins "+str(len(ScenarioList))+" scenarios")
SolStat, zL = lagrUtil.solve_ph_code(ph, options)
print("\t...ends")
bL = Compute_ExpectationforVariable(ph,
IndVarName,
CCStageNum)
if bL > 0:
print("** bL = "+str(bL)+" > 0")
return Result
print("Initial cost = "+str(zL)+" for bL = "+str(bL))
lagrUtil.FixAllIndicatorVariables(ph, IndVarName, 1)
print("lambda= "+str(lambdaval)+" ...run begins")
SolStat, zU = lagrUtil.solve_ph_code(ph, options)
print("\t...ends")
bU = Compute_ExpectationforVariable(ph,
IndVarName,
CCStageNum)
if bU < 1:
print("** bU = "+str(bU)+" < 1")
lagrUtil.FreeAllIndicatorVariables(ph, IndVarName)
Result.lbz = [ [0,bL,zL], [None,bU,zU] ]
Result.selections = [[], ScenarioList]
NumIntervals = 1
print("initial gap = "+str(1-zL/zU)+" \n")
print("End of test; this is only a test.")
return Result
