def create_aspfile(FnameCSV, FnameASP, TemplateClassifier, TemplateObjective):
params_classifier = interfaces.templates.read_classifier(
TemplateClassifier)
params_objective = interfaces.templates.read_objective(TemplateObjective)
CLASSIFIER_SCRIPT.csv2asp(
FnameCSV=FnameCSV,
FnameASP=FnameASP,
LowerBoundInputs=params_classifier['LowerBoundInputs'],
UpperBoundInputs=params_classifier['UpperBoundInputs'],
LowerBoundGates=params_classifier['LowerBoundGates'],
UpperBoundGates=params_classifier['UpperBoundGates'],
GateTypes=params_classifier['GateTypes'],
EfficiencyConstraint=params_objective['EfficiencyConstraint'],
OptimizationStrategy=params_objective['OptimizationStrategy'],
BreakSymmetries=params_objective['BreakSymmetries'],
Silent=True,
UniquenessConstraint=params_objective['UniquenessConstraint'],
PerfectClassifier=params_objective['PerfectClassifier'],
UpperBoundFalsePos=params_objective['UpperBoundFalsePos'],
UpperBoundFalseNeg=params_objective['UpperBoundFalseNeg'])
def create_asp_prog(input_file, config_file_name):
"""
Function to create ASP program.
Parameters
----------
input_file : str
name of input train data file
config_file_name : str
name of constraint file
Returns
-------
instance : str
ASP instance
program : str
ASP program
"""
config_file = configparser.ConfigParser()
config_file.read(config_file_name)
FnameCSV = input_file
FnameASP = input_file.replace(".csv", ".asp")
GateTypes = []
GateType1 = {
"LowerBoundPos":
int(config_file['GATE SPECIFICATION']['GateType1_LowerBoundPos']),
"LowerBoundNeg":
int(config_file['GATE SPECIFICATION']['GateType1_LowerBoundNeg']),
"UpperBoundPos":
int(config_file['GATE SPECIFICATION']['GateType1_UpperBoundPos']),
"UpperBoundNeg":
int(config_file['GATE SPECIFICATION']['GateType1_UpperBoundNeg']),
"UpperBoundOcc":
int(config_file['GATE SPECIFICATION']['GateType1_UpperBoundOcc']),
}
GateType2 = {
"LowerBoundPos":
int(config_file['GATE SPECIFICATION']['GateType2_LowerBoundPos']),
"LowerBoundNeg":
int(config_file['GATE SPECIFICATION']['GateType2_LowerBoundNeg']),
"UpperBoundPos":
int(config_file['GATE SPECIFICATION']['GateType2_UpperBoundPos']),
"UpperBoundNeg":
int(config_file['GATE SPECIFICATION']['GateType2_UpperBoundNeg']),
"UpperBoundOcc":
int(config_file['GATE SPECIFICATION']['GateType2_UpperBoundOcc']),
}
GateTypes = [GateType1, GateType2]
instance, program = \
classifier.csv2asp(fname_csv=FnameCSV,
fname_asp=FnameASP,
lower_bound_inputs=int(config_file['CLASSIFIER CONSTRAINTS']['LowerBoundInputs']),
upper_bound_inputs=int(config_file['CLASSIFIER CONSTRAINTS']['UpperBoundInputs']),
lower_bound_gates=int(config_file['CLASSIFIER CONSTRAINTS']['LowerBoundGates']),
upper_bound_gates=int(config_file['CLASSIFIER CONSTRAINTS']['UpperBoundGates']),
gate_types=GateTypes,
efficiency_constraint=config_file.getboolean('OPTIONAL', 'EfficiencyConstraint'),
optimization_strategy=int(config_file['OPTIMIZATION']['OptimizationStrategy']),
break_symmetries=config_file.getboolean('OPTIONAL', 'BreakSymmetries'),
silent=config_file.getboolean('OPTIONAL', 'Silent'),
uniqueness_constraint=config_file.getboolean('CLASSIFIER CONSTRAINTS', 'UniquenessConstraint'),
boolean_function_form=int(config_file['CLASSIFIER CONSTRAINTS']['BooleanFunctionForm']),
perfect_classifier=config_file.getboolean('ERROR CONSTRAINTS', 'PerfectClassifier'),
add_bounds_on_errors=config_file.getboolean('ERROR CONSTRAINTS', 'AddBoundsOnErrors'),
upper_bound_false_pos=int(config_file['ERROR CONSTRAINTS']['UpperBoundFalsePos']),
upper_bound_false_neg=int(config_file['ERROR CONSTRAINTS']['UpperBoundFalseNeg']))
instance = "\n".join(instance)
program = "\n".join(program)
return instance, program
import sys
sys.path = ["../"] + sys.path
import classifier
if __name__=="__main__":
if 0 :
classifier.check_csv(FnameCSV)
classifier.csv2asp(FnameCSV,
FnameASP,
LowerBoundInputs,
UpperBoundInputs,
LowerBoundGates,
UpperBoundGates,
GateTypes,
EfficiencyConstraint,
OptimizationStrategy,
BreakSymmetries,
Silent,
UniquenessConstraint,
PerfectClassifier,
UpperBoundFalsePos,
UpperBoundFalseNeg
)
if 1 :
# basel classifier
GateInputs = "gate_input(1,negative,g7) gate_input(2,negative,g6) gate_input(3,negative,g4) gate_input(4,negative,g3) "
GateInputs+= "gate_input(5,positive,g1) gate_input(5,positive,g2) gate_input(5,positive,g8) "
GateInputs+= "gate_input(6,positive,g1) gate_input(6,positive,g5) gate_input(6,positive,g8)"
classifier.check_classifier(FnameCSV, GateInputs)
OptimizationStrategy = 1
BreakSymmetries = True
import sys
sys.path = ["../"] + sys.path
import classifier
if __name__=="__main__":
if 1 :
classifier.csv2asp(
FnameCSV,
FnameASP,
LowerBoundInputs,
UpperBoundInputs,
LowerBoundGates,
UpperBoundGates,
GateTypes,
EfficiencyConstraint,
OptimizationStrategy,
BreakSymmetries)
if 1 :
GateInputs = "gate_input(1,negative,g5) gate_input(2,negative,g4) gate_input(3,negative,g3) gate_input(4,negative,g2) "
GateInputs+= "gate_input(5,positive,g1) gate_input(5,positive,g6) "
GateInputs+= "gate_input(6,positive,g1) gate_input(6,positive,g7)"
classifier.check_classifier(FnameCSV, GateInputs)
if 0 :
GateInputs = "gate_input(2,positive,g2) gate_input(1,negative,g1)"
FnamePDF = "toy_classifier.pdf"
"LowerBoundNeg": 0,
"UpperBoundNeg": 1,
"UpperBoundOcc": 4
}]
EfficiencyConstraint = True
OptimizationStrategy = 1
BreakSymmetries = True
import sys
sys.path = ["../"] + sys.path
import classifier
if __name__ == "__main__":
if 1:
classifier.csv2asp(FnameCSV, FnameASP, LowerBoundInputs,
UpperBoundInputs, LowerBoundGates, UpperBoundGates,
GateTypes, EfficiencyConstraint,
OptimizationStrategy, BreakSymmetries)
if 1:
GateInputs = "gate_input(1,negative,g8) gate_input(2,negative,g7) gate_input(3,negative,g6) gate_input(4,negative,g6) "
GateInputs += "gate_input(5,positive,g1) gate_input(5,positive,g2) gate_input(5,positive,g3) "
GateInputs += "gate_input(6,positive,g1) gate_input(6,positive,g3) gate_input(6,positive,g4)"
classifier.check_classifier(FnameCSV, GateInputs)
if 0:
GateInputs = "gate_input(2,positive,g2) gate_input(1,negative,g1)"
FnamePDF = "toy_classifier.pdf"
classifier.gateinputs2pdf(FnamePDF, GateInputs)
if 0:
FnameMAT = "casestudy01.mat"
UpperBoundFalseNeg = 0
import classifier
if __name__=="__main__":
if 1:
classifier.csv2asp(
FnameCSV,
FnameASP,
LowerBoundInputs,
UpperBoundInputs,
LowerBoundGates,
UpperBoundGates,
GateTypes,
EfficiencyConstraint,
OptimizationStrategy,
BreakSymmetries,
Silent,
UniquenessConstraint,
PerfectClassifier,
UpperBoundFalsePos,
UpperBoundFalseNeg)
if 1:
GateInputs = "gate_input(1,positive,g2) gate_input(2,positive,g3) gate_input(2,negative,g1)"
classifier.check_classifier(FnameCSV, GateInputs)
if 1:
GateInputs = "gate_input(1,positive,g2) gate_input(2,positive,g3) gate_input(2,negative,g1)"
Fname = "toy.pdf"