def __init__(self):
QMainWindow.__init__(self)
loadUi("../ui/Prediction.ui", self)
self.setWindowTitle("Wavelet Transform Data Analyzer Tool")
self.setWindowIcon(QtGui.QIcon('../icon/icon.png'))
Features.center(self)
list_tables = Database.get_table_names(Database.database_name)
Features.list_db_tables(self, list_tables)
for i in range(2, 21):
self.comboBox_kfold.addItem(str(i), i)
self.selected_table_name = ""
self.checkBox_knn.setChecked(True)
self.checkBox_randomForest.setChecked(True)
self.checkBox_svcLinear.setChecked(True)
self.checkBox_svcPoly.setChecked(True) # prediction page checks
self.checkBox_gaussianNB.setChecked(True)
self.checkBox_svcRBF.setChecked(True)
self.pushButton.clicked.connect(self.analyze_signal)
self.dbTables_listWidget.itemSelectionChanged.connect(self.selectionChanged)
def run(self):
wave_types = pywt.wavelist(kind='discrete')
levels = [1, 2, 3]
signals = []
self.average, self.entropy, self.kurtosis, self.max_v, self.median, self.min_v, self.skewness, self.standart_dev = Features.check_statistics(
self)
table_names = Database.get_table_names(Database.database_name)
for wave_func in wave_types:
if wave_func.find("sym") == -1:
for level in levels:
self.wavelet_level = level
self.wavelet_type = wave_func
col, self.header, self.db_header = Features.init_table(
self, len(self.all_signals))
self.db_matrix = np.zeros(
(len(self.all_signals), 8 * (self.wavelet_level + 1)))
if not any("Db_GTZAN_function_" + str(wave_func) +
"_Degree_" + str(level) in s
for s in table_names):
for iter in range(0, len(self.all_signals)):
self.signals.clear()
self.audio, self.sample = librosa.load(
self.all_signals[iter])
self.signals.append(self.audio)
self.time = np.arange(0, len(
self.audio)) / self.sample
coeffs = pywt.wavedec(
self.audio,
self.wavelet_type,
level=self.wavelet_level) # wavelet analyze
for i in range(0, self.wavelet_level + 1):
self.signals.append(
coeffs[i]
) # adding signals array to coeffs
self.db_matrix[iter] = Features.insertTable(
self, iter, col
) # level = 3 ise signals içinde 5 (4 analiz edilmiş + 1 kaynak)
w_name = str(wave_func)
table_name = "Db_GTZAN_function_" + w_name + "_Degree_" + str(
level)
Database.create_table(Database.database_name,
table_name, self.db_header, "")
for index in range(0, len(self.all_signals)):
name = self.all_signals[index].split(
sep='/') # name of signal
Database.delete_row(Database.database_name,
table_name, name[-1], "")
Database.add_values_to_table(
Database.database_name, table_name, name[-1],
self.db_header, self.db_matrix[index],
"") # adding db to values
print(table_name)
else:
print("Db_GTZAN_function_" + str(wave_func) +
"_Degree_" + str(level) + ' passed')
else:
print(wave_func + " passed")
def analyze_all_continuous(self):
list_tables = Database.get_table_names(Database.database_name)
iter = 0
func_names = {}
for table in list_tables:
if (table.split('_')[0] != 'Comp'):
func_name = table.split('_')[3]
if (func_names.get(func_name, -1) == -1):
func_names[str(func_name)] = iter
iter += 1
acc_matrix = [['' for x in range(7)] for x in range(iter)]
rec_matrix = [['' for x in range(7)] for x in range(iter)]
prec_matrix = [['' for x in range(7)] for x in range(iter)]
iter = -1
x = 0
for table in list_tables:
print(table)
if (table.split('_')[0] != 'Comp'):
func_name = table.split('_')[3]
result = ClassifyMusic.run(table, 5, [1, 2, 3, 4, 5, 6], False)
string = acc_matrix[func_names.get(func_name)]
array = [func_name, result[0][2], result[1][2], result[2][2], result[3][2], result[4][2], result[5][2]]
if (string[0] == ''):
acc_matrix[func_names.get(func_name)] = array
else:
arr = [a + '-' + b for a, b in zip(string, array)]
acc_matrix[func_names.get(func_name)] = arr
array = [func_name, result[0][3], result[1][3], result[2][3], result[3][3], result[4][3], result[5][3]]
if (string[0] == ''):
prec_matrix[func_names.get(func_name)] = array
else:
arr = [a + '-' + b for a, b in zip(string, array)]
prec_matrix[func_names.get(func_name)] = arr
array = [func_name, result[0][4], result[1][4], result[2][4], result[3][4], result[4][4], result[5][4]]
if (string[0] == ''):
rec_matrix[func_names.get(func_name)] = array
else:
arr = [a + '-' + b for a, b in zip(string, array)]
rec_matrix[func_names.get(func_name)] = arr
avg_acc_matrix = cont_create_tables(acc_matrix)
avg_rec_matrix = cont_create_tables(rec_matrix)
avg_prec_matrix = cont_create_tables(prec_matrix)
print('-------------------------------------------------------------------')
print('------------------------------------acc matrix---------------------')
print(tabulate(avg_acc_matrix, tablefmt="latex_raw",
headers=['Type', 'Random Forest', 'KNN', 'SVC Poly', 'GaussianNB', 'SVC Linear', 'SVC RBF']))
print(
'----------------------------------------------------------------------------')
print(
'-----------------------------------acc matrix--------------------------------')
print(
'-------------------------------------------------------------------------------')
print(
'----------------------------------------rec matrix-----------------------------')
print(tabulate(avg_rec_matrix, tablefmt="latex_raw",
headers=['Type', 'Random Forest', 'KNN', 'SVC Poly', 'GaussianNB', 'SVC Linear', 'SVC RBF']))
print(
'-----------------------------------------------------------------------------------')
print(
'-----------------------------rec matrix--------------------------------------------')
print(
'----------------------------------------------------------------')
print(
'-------------------------prec matrix-----------------------------')
print(tabulate(avg_prec_matrix, tablefmt="latex_raw",
headers=['Type', 'Random Forest', 'KNN', 'SVC Poly', 'GaussianNB', 'SVC Linear', 'SVC RBF']))
print(
'-------------------------------------------------------------------------------')
print(
'-----------------------------------------prec matrix---------------------------')
