def full_test():
# CREATE CHAR_NUM CHARACTERISTICS
console.write_header("Creating Characteristics")
characteristics = []
data.generate_characteristic(characteristics)
# CREATE CLASS_NUM SYMBOL CLASSES
console.write_header(" Creating Symbol Classes")
symbolClasses = []
data.generate_symbol_classes(symbolClasses, characteristics)
console.write_header("Computing Homogeneous Distortion")
Distorter().create_homogeneus_cloud(symbolClasses)
for c in range(0, util.global_variables.CLASS_NUM):
console.write_header("Computing Cluster Evaluation")
best_k = ps.cluster_evaluation(util.global_variables.MAX_K_CLUS_EVALUATION, symbolClasses[c:c+1])
util.global_variables.K = best_k[0]
console.write_header("Computing Clusters with K:", str(util.global_variables.K))
Clusterer().computeClusters(symbolClasses[c:c+1])
console.write_header("Creating Non Homogeneous Foreign")
foreignClassesNonHomo = f_creator.create_non_homogeneous_foreign(symbolClasses)
console.write_header("Creating Homogeneous Foreign")
foreignClassesHomo = f_creator.create_homogeneous_foreign(symbolClasses, characteristics)
console.write_header(" Synthetic Data Calculations")
synth_calc.ambiguity_for_different_radiuses(symbolClasses[:], foreignClassesHomo, foreignClassesNonHomo)
def grouping_assessment():
# CREATE CHAR_NUM CHARACTERISTICS
console.write_header("Creating Characteristics")
characteristics = []
data.generate_characteristic(characteristics)
# CREATE CLASS_NUM SYMBOL CLASSES
console.write_header(" Creating Symbol Classes")
symbolClasses = []
data.generate_symbol_classes(symbolClasses, characteristics)
console.write_header("Computing K cloud Distortion")
#Distorter().create_k_clouds(util.global_variables.K_CLOUD_DISTORTION,symbolClasses)
Distorter().create_non_homogeneus_cloud(symbolClasses)
console.write_header("Computing Cluster Evaluation")
ps.cluster_evaluation(util.global_variables.MAX_K_CLUS_EVALUATION,symbolClasses)
def synthetic_test_paper_2_old():
# CREATE CHAR_NUM CHARACTERISTICS
console.write_header("Creating Characteristics")
characteristics = []
data.generate_characteristic(characteristics)
# CREATE CLASS_NUM SYMBOL CLASSES
console.write_header(" Creating Symbol Classes")
symbolClasses = []
data.generate_symbol_classes(symbolClasses, characteristics)
# CREATE CLOUD DISTORTION IN NATIVE SET
console.write_header("Computing K cloud Distortion")
Distorter().create_cluster_assessment_cloud(util.global_variables.K_CLOUD_DISTORTION,symbolClasses)
#Distorter().create_k_clouds(util.global_variables.K_CLOUD_DISTORTION,symbolClasses)
Clusterer().computeClusters(symbolClasses[:])
Plot3D().renderPlot(symbolClasses)
# COMPUTE CLUSTER EVALUATION
console.write_header("Computing Cluster Evaluation")
ps.cluster_evaluation(util.global_variables.MAX_K_CLUS_EVALUATION,symbolClasses)
def real_data():
console.write_header("Loading Native symbols")
symbolClasses = loader.load_native_xls()
console.write_header("Loading Foreign symbols")
foreignClasses = loader.load_foreign_xls()
util.global_variables.CLASS_NUM = len(symbolClasses)
util.global_variables.CHAR_NUM = len(symbolClasses[0].learning_set[0].characteristicsValues)
for c in range(0, util.global_variables.CLASS_NUM):
console.write_header("Computing Cluster Evaluation")
best_k = ps.cluster_evaluation(util.global_variables.MAX_K_CLUS_EVALUATION, symbolClasses[c:c+1])
util.global_variables.K = best_k[0]
console.write_header("Computing Clusters with K:", str(util.global_variables.K))
Clusterer().computeClusters(symbolClasses[c:c+1])
console.write_header(" Synthetic Data Calculations")
synth_calc.ambiguity_for_different_radiuses_real_data(symbolClasses[:], foreignClasses)
def semisynthetic_test_paper_2():
console.write_header("Loading Native symbols")
symbolClasses = loader.load_native_xls()
console.write_header("Loading Foreign symbols")
foreignClasses = loader.load_foreign_xls()
util.global_variables.CLASS_NUM = len(symbolClasses)
util.global_variables.CHAR_NUM = len(symbolClasses[0].learning_set[0].characteristicsValues)
# COMPUTE CLUSTER EVALUATION
for c in range(0, util.global_variables.CLASS_NUM):
console.write_header("Computing Cluster Evaluation")
best_k = ps.cluster_evaluation(util.global_variables.MAX_K_CLUS_EVALUATION, symbolClasses[c:c+1])
util.global_variables.K = best_k[0]
console.write_header("Computing Clusters with K:", str(util.global_variables.K))
Clusterer().computeClusters(symbolClasses[c:c+1])
paper2.compute(symbolClasses, foreignClasses)
