def printScoresFromCollectionFile(feExFun, clf, lt, collFi, out_file,
labelsHierarchy):
"""
clf : classifier
le : label encoder (object)
collfi : annotated wav collection (*.txt)
out_file : out file (*.txt)
"""
coll = fex.readCols(
collFi,
colIndexes=(0, 1)) # np.loadtxt(collFi, delimiter='\t', dtype='|S')
printScoresFromCollection(feExFun, clf, lt, coll, out_file,
labelsHierarchy)
Tpipe = fex.makeTransformationsPipeline(T_settings)
## clf settings
clfStr = 'cv{}-'.format(cv)
settingsStr = "{}-{}".format(Tpipe.string, clfStr)
settingsStr += '-labsHierarchy_' + '_'.join(labsHierarchy)
## write in out file
out_file = open(out_fN, 'a')
out_file.write("#WSD1\n###--------- {} ---------###\n".format(
time.strftime("%Y.%m.%d\t\t%H:%M:%S")))
out_file.write("#" + settingsStr + '\n')
out_file.close()
## load collections
train_coll = fex.readCols(collFi_train, colIndexes=(0, 1))
test_coll = np.genfromtxt(collFi_test, dtype=object)
lt = myML.labelTransformer(clf_labs)
def runWSD2Experiment(train_coll,
test_coll,
lt,
T_settings,
labsHierarchy,
cv,
out_fN,
testColl_scoreClassLabels,
readSections,
param=None,