def semisynthetic_test_paper_1():
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)
# CREATE ELLIPSOIDS AND CUBOIDS FOR EACH LEARNING SET
console.write_header("Generating Convex and Compact Sets")
membership = BasicMembership(symbolClasses, False)
membership.shrink_objects(0) # just to write to he file
for i in range(0,5):
# Check native
membership.check_natives_ellipsoid_proper(symbolClasses[:],"foreign_REAL","foreign_REAL")
membership.check_natives_cuboid_proper(symbolClasses[:],"foreign_REAL","foreign_REAL")
# Check foreign
membership.check_foreign_ellipsoid(foreignClasses, "foreign_REAL")
membership.check_foreign_cuboids(foreignClasses, "foreign_REAL")
# Shrink
if i != 4:
membership.shrink_objects(5)
def static_k_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)
Clusterer().computeClusters(symbolClasses)
paper2.compute(symbolClasses, foreignClasses)
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)
def __serialize():
logger.log_header("Serializing")
nativeElements = loader.load_native_xls()
loader.serialize_chosen_elements(nativeElements)
