def __init__(self):
super(GUI, self).__init__()
self.ui = Ui_MainWindow()
self.ui.setupUi(self)
# Default parameters
self.ui.tabs.setCurrentIndex(0)
def __init__(self, parent=None):
super().__init__(parent)
self.ui = Ui_MainWindow()
self.ui.setupUi(self)
self.ui.Exit.clicked.connect(self.onExit)
self.ui.Open_Pat.clicked.connect(self.onOpenPat)
self.setWindowTitle("Heilpraktiker Software Version 1.0.0")
def __init__(self, settings):
# mandatory
QMainWindow.__init__(self)
Ui_MainWindow.__init__(self)
self.trading_session_state = "TBD"
self.est = timezone('US/Eastern')
self.settingsWindow = SettingsWindow()
self.setupUi(self)
self.settings = settings
self.ibkrworker = IBKRWorker(self.settings)
self.threadpool = QThreadPool()
self.setWindowTitle("Algo Traider v 2.0")
sys.stderr = open('LOG/errorLog.txt', 'w')
self.create_open_positions_grid()
# setting a timer for Worker
self.uiTimer = QTimer()
self.uiTimer.timeout.connect(self.update_ui)
self.workerTimer = QTimer()
self.workerTimer.timeout.connect(self.run_worker)
self.server_timer = QTimer()
self.server_timer.timeout.connect(self.report_to_server)
self.server_timer.start(int(self.settings.INTERVALSERVER) * 1000)
# connecting a buttons
self.chbxProcess.stateChanged.connect(self.process_checked)
self.btnSettings.pressed.connect(self.show_settings)
self.statusbar.showMessage("Ready")
stock_names = [o.ticker for o in self.settings.CANDIDATES]
self.ibkrworker.stocks_data_from_server = get_market_data_from_server(
self.settings, stock_names)
self.update_console("Market data for " + str(len(stock_names)) +
" Candidates received from Server")
self.start_updating_candidates_and_connect()
StyleSheet = '''
#lcdPNLgreen {
border: 3px solid green;
}
#lcdPNLred {
border: 3px solid red;
}
'''
self.setStyleSheet(StyleSheet)
def __init__(self, settings):
# mandatory
QMainWindow.__init__(self)
Ui_MainWindow.__init__(self)
self.settingsWindow = SettingsWindow()
self.setupUi(self)
self.settings = settings
self.ibkrworker = IBKRWorker(self.settings)
self.threadpool = QThreadPool()
self.setWindowTitle("Algo Traider v 2.0")
sys.stderr = open('LOG/errorLog.txt', 'w')
self.create_open_positions_grid()
# # redirecting Cosole to UI and Log
# sys.stdout = OutLog(self.consoleOut, sys.stdout)
# sys.stderr = OutLog(self.consoleOut, sys.stderr)
# setting a timer for Worker
self.uiTimer = QTimer()
self.uiTimer.timeout.connect(self.update_ui)
self.workerTimer = QTimer()
self.workerTimer.timeout.connect(self.run_worker)
# connecting a buttons
self.chbxProcess.stateChanged.connect(self.process_checked)
self.btnSettings.pressed.connect(self.show_settings)
self.statusbar.showMessage("Ready")
# self.update_session_state()
# self.connect_to_ibkr()
if not self.settings.UIDEBUG:
self.connect_to_ibkr()
else:
self.btnSettings.setEnabled(True)
StyleSheet = '''
#lcdPNLgreen {
border: 3px solid green;
}
#lcdPNLred {
border: 3px solid red;
}
'''
self.setStyleSheet(StyleSheet)
class GUI(QtWidgets.QMainWindow):
def __init__(self):
super(GUI, self).__init__()
self.ui = Ui_MainWindow()
self.ui.setupUi(self)
# Default parameters
self.ui.tabs.setCurrentIndex(0)
def set_weight(self, weight, unit):
w = str(weight)
self.ui.weightL.setText()
def set_sleep_time(self, hours, unit):
h = str(hours)
self.ui.sleepTimeL.setText("{} {}".format(h, unit))
class MainWindow(QtWidgets.QMainWindow):
def __init__(self, parent=None):
super().__init__(parent)
self.ui = Ui_MainWindow()
self.ui.setupUi(self)
self.ui.Exit.clicked.connect(self.onExit)
self.ui.Open_Pat.clicked.connect(self.onOpenPat)
self.setWindowTitle("Heilpraktiker Software Version 1.0.0")
def onOpenPat(self):
self.pat = PatVerWindow()
self.pat.show()
window.hide()
def onExit(self):
PatientenVerwaltung.listespeichern()
sys.exit()
def __init__(self):
super(mywindow, self).__init__()
self.ui = Ui_MainWindow()
self.ui.setupUi(self)
self.ui.tabWidget.setCurrentIndex(0)
# ===init classifiers==============
classifier.load_params()
# ===1==================
self.ui.btn_select_input_data.clicked.connect(
self.btn_select_input_data_clicked)
self.ui.btn_load_data.clicked.connect(self.btn_load_data_clicked)
self.ui.btn_fit.clicked.connect(self.btn_fit_clicked)
self.ui.btn_open_path_to_data.clicked.connect(
self.btn_open_path_to_data_clicked)
self.ui.btn_fit.setDisabled(True)
self.ui.preprocess_type.setCurrentIndex(1)
for m in classifier.classifiers:
self.ui.classifier_type.addItem(str(m))
# ===2============================
self.ui.tabWidget.currentChanged.connect(self.tab_changed)
self.ui.btn_select_path_to_test_data.clicked.connect(
self.btn_select_path_to_test_data_clicked)
self.ui.btn_open_path_to_test_data.clicked.connect(
self.btn_open_path_to_test_data_clicked)
self.ui.selector_model.currentIndexChanged.connect(
self.set_preprocess_type_test)
self.ui.btn_load_test_data.clicked.connect(
self.btn_load_test_data_clicked)
self.ui.btn_test.clicked.connect(self.btn_test_clicked)
self.ui.btn_test.setDisabled(True)
# ===3================================
self.ui.btn_choose_input_data_path.clicked.connect(
self.btn_choose_input_data_path_clicked)
self.ui.btn_choose_output_bmp_data_path.clicked.connect(
self.btn_choose_output_bmp_data_path_clicked)
self.ui.btn_choose_output_png_data_path.clicked.connect(
self.btn_choose_output_png_data_path_clicked)
self.ui.btn_start_devider.clicked.connect(
self.btn_start_devider_clicked)
self.ui.btn_open_input_data_path.clicked.connect(
self.btn_open_input_data_path_clicked)
self.ui.btn_open_output_bmp_data_path.clicked.connect(
self.btn_open_output_bmp_data_path_clicked)
self.ui.btn_open_output_png_data_path.clicked.connect(
self.btn_open_output_png_data_path_clicked)
# ===4================================
self.ui.btn_choose_neiron_train_data_path.clicked.connect(
self.btn_choose_neiron_train_data_path_clicked)
self.ui.btn_choose_neiron_test_data_path.clicked.connect(
self.btn_choose_neiron_test_data_path_clicked)
self.ui.btn_open_neiron_train_data_path.clicked.connect(
self.btn_open_neiron_train_data_path_clicked)
self.ui.btn_open_neiron_test_data_path.clicked.connect(
self.btn_open_neiron_test_data_path_clicked)
self.ui.btn_open_neiron_weights_path.clicked.connect(
self.btn_open_neiron_weights_path_clicked)
self.ui.btn_start_neiron_train.clicked.connect(
self.btn_start_neiron_train_clicked)
self.ui.btn_neiron_test.clicked.connect(self.btn_neiron_test_clicked)
self.ui.btn_neiron_additional_train.clicked.connect(
self.btn_neiron_additional_train_clicked)
class mywindow(QtWidgets.QMainWindow):
X = []
y = []
y_unic = []
# начальная инициализация формы
def __init__(self):
super(mywindow, self).__init__()
self.ui = Ui_MainWindow()
self.ui.setupUi(self)
self.ui.tabWidget.setCurrentIndex(0)
# ===init classifiers==============
classifier.load_params()
# ===1==================
self.ui.btn_select_input_data.clicked.connect(
self.btn_select_input_data_clicked)
self.ui.btn_load_data.clicked.connect(self.btn_load_data_clicked)
self.ui.btn_fit.clicked.connect(self.btn_fit_clicked)
self.ui.btn_open_path_to_data.clicked.connect(
self.btn_open_path_to_data_clicked)
self.ui.btn_fit.setDisabled(True)
self.ui.preprocess_type.setCurrentIndex(1)
for m in classifier.classifiers:
self.ui.classifier_type.addItem(str(m))
# ===2============================
self.ui.tabWidget.currentChanged.connect(self.tab_changed)
self.ui.btn_select_path_to_test_data.clicked.connect(
self.btn_select_path_to_test_data_clicked)
self.ui.btn_open_path_to_test_data.clicked.connect(
self.btn_open_path_to_test_data_clicked)
self.ui.selector_model.currentIndexChanged.connect(
self.set_preprocess_type_test)
self.ui.btn_load_test_data.clicked.connect(
self.btn_load_test_data_clicked)
self.ui.btn_test.clicked.connect(self.btn_test_clicked)
self.ui.btn_test.setDisabled(True)
# ===3================================
self.ui.btn_choose_input_data_path.clicked.connect(
self.btn_choose_input_data_path_clicked)
self.ui.btn_choose_output_bmp_data_path.clicked.connect(
self.btn_choose_output_bmp_data_path_clicked)
self.ui.btn_choose_output_png_data_path.clicked.connect(
self.btn_choose_output_png_data_path_clicked)
self.ui.btn_start_devider.clicked.connect(
self.btn_start_devider_clicked)
self.ui.btn_open_input_data_path.clicked.connect(
self.btn_open_input_data_path_clicked)
self.ui.btn_open_output_bmp_data_path.clicked.connect(
self.btn_open_output_bmp_data_path_clicked)
self.ui.btn_open_output_png_data_path.clicked.connect(
self.btn_open_output_png_data_path_clicked)
# ===4================================
self.ui.btn_choose_neiron_train_data_path.clicked.connect(
self.btn_choose_neiron_train_data_path_clicked)
self.ui.btn_choose_neiron_test_data_path.clicked.connect(
self.btn_choose_neiron_test_data_path_clicked)
self.ui.btn_open_neiron_train_data_path.clicked.connect(
self.btn_open_neiron_train_data_path_clicked)
self.ui.btn_open_neiron_test_data_path.clicked.connect(
self.btn_open_neiron_test_data_path_clicked)
self.ui.btn_open_neiron_weights_path.clicked.connect(
self.btn_open_neiron_weights_path_clicked)
self.ui.btn_start_neiron_train.clicked.connect(
self.btn_start_neiron_train_clicked)
self.ui.btn_neiron_test.clicked.connect(self.btn_neiron_test_clicked)
self.ui.btn_neiron_additional_train.clicked.connect(
self.btn_neiron_additional_train_clicked)
# ===5=======================================================
# ====Управление первой вкладкой====================================================
def btn_open_path_to_data_clicked(self):
path = self.ui.path_to_data.text()
path = '\\'.join(path.split('\\')[:-1])
path = os.path.realpath(path)
os.startfile(path)
def btn_fit_clicked(self):
expected, predicted = classifier.control_classifiers(
self.X, self.y, self.ui.classifier_type.currentIndex(),
self.ui.preprocess_type.currentText())
self.ui.label_4.setText(
metrics.classification_report(expected, predicted,
zero_division=0))
self.load_train_predictions_matrix_table(
metrics.confusion_matrix(expected, predicted))
def btn_select_input_data_clicked(self):
file_path = QFileDialog.getOpenFileName(self,
"Выберите файл",
filter="*.csv")
self.ui.path_to_data.setText(file_path[0])
def btn_load_data_clicked(self):
if self.ui.preprocess_type.currentText() == "Стандартизация":
preprocess_type = 2
status_text = "стандартизованны"
else:
preprocess_type = 1
status_text = "нормализованны"
self.ui.btn_fit.setDisabled(False)
self.X, self.y = classifier.load_and_preprocess_data(
self.ui.path_to_data.text(), preprocess_type)
self.load_info_table(classifier.get_load_file_stats(self.y))
self.ui.status.setText("Статус загрузки данных: данные загружены и " +
status_text)
def load_train_predictions_matrix_table(self, data):
self.ui.train_predictions_matrix.setColumnCount(len(self.y_unic))
self.ui.train_predictions_matrix.setRowCount(len(self.y_unic))
# заголовки для столбцов.
self.ui.train_predictions_matrix.setHorizontalHeaderLabels(self.y_unic)
# заголовки для строк.
self.ui.train_predictions_matrix.setVerticalHeaderLabels(self.y_unic)
row = 0
for tup in data:
col = 0
for item in tup:
cellinfo = QTableWidgetItem(str(item))
# Только для чтения
cellinfo.setFlags(PyQt5.QtCore.Qt.ItemIsSelectable
| PyQt5.QtCore.Qt.ItemIsEnabled)
self.ui.train_predictions_matrix.setItem(row, col, cellinfo)
col += 1
row += 1
def load_info_table(self, data):
self.y_unic.clear()
self.ui.table_file_info.setColumnCount(2)
self.ui.table_file_info.setRowCount(len(data))
# заголовки для столбцов.
self.ui.table_file_info.setHorizontalHeaderLabels(
('Клетка', 'Количество'))
row = 0
for tup in data:
col = 0
for item in tup:
cellinfo = QTableWidgetItem(item)
# Только для чтения
cellinfo.setFlags(PyQt5.QtCore.Qt.ItemIsSelectable
| PyQt5.QtCore.Qt.ItemIsEnabled)
self.ui.table_file_info.setItem(row, col, cellinfo)
if col == 0:
self.y_unic.append(item)
col += 1
row += 1
# ====Управление второй вкладкой=================================================
def tab_changed(self):
if self.ui.tabWidget.currentIndex() == 1:
path = "ProjectData/Weights/Classic/"
path = pathlib.Path(path)
all_model_paths = list(path.glob('*'))
# self.ui.selector_model.clear()
# self.ui.selector_model.clear()
for x in all_model_paths:
self.ui.selector_model.addItem(str(x))
def set_preprocess_type_test(self):
type = self.ui.selector_model.currentText().split("_")
type = type[len(type) - 1]
type = type.split(".")
type = type[0]
print(type)
if type == "Стандартизация":
self.ui.preprocess_type_test.setCurrentIndex(0)
self.ui.preprocess_type_test.setEnabled(False)
else:
self.ui.preprocess_type_test.setCurrentIndex(1)
self.ui.preprocess_type_test.setEnabled(False)
def btn_load_test_data_clicked(self):
if self.ui.preprocess_type_test.currentText() == "Стандартизация":
preprocess_type = 2
status_text = "стандартизованны"
else:
preprocess_type = 1
status_text = "нормализованны"
self.ui.btn_test.setDisabled(False)
self.X, self.y = classifier.load_and_preprocess_data(
self.ui.path_to_test_data.text(), preprocess_type)
self.load_test_info_table(classifier.get_load_file_stats(self.y))
self.ui.status_2.setText(
"Статус загрузки данных: данные загружены и " + status_text)
def load_test_info_table(self, data):
self.y_unic.clear()
self.ui.table_file_info_2.setColumnCount(2)
self.ui.table_file_info_2.setRowCount(len(data))
# заголовки для столбцов.
self.ui.table_file_info_2.setHorizontalHeaderLabels(
('Клетка', 'Количество'))
row = 0
for tup in data:
col = 0
for item in tup:
cellinfo = QTableWidgetItem(item)
# Только для чтения
cellinfo.setFlags(PyQt5.QtCore.Qt.ItemIsSelectable
| PyQt5.QtCore.Qt.ItemIsEnabled)
self.ui.table_file_info_2.setItem(row, col, cellinfo)
if col == 0:
self.y_unic.append(item)
col += 1
row += 1
def btn_test_clicked(self):
expected, predicted = classifier.test_model(
self.X, self.y, self.ui.selector_model.currentText())
print("!")
if self.ui.preprocess_type_test.currentText() == "Стандартизация":
preprocess_type = 2
else:
preprocess_type = 1
classifier.generate_test_report(self.ui.path_to_test_data.text(),
self.ui.selector_model.currentText(),
preprocess_type)
self.ui.label_20.setText(
metrics.classification_report(expected, predicted,
zero_division=0))
# print(metrics.confusion_matrix(expected, predicted))
self.load_test_predictions_matrix(
metrics.confusion_matrix(expected, predicted))
def load_test_predictions_matrix(self, data):
print(len(self.y_unic))
self.ui.test_predictions_matrix.setColumnCount(len(self.y_unic))
self.ui.test_predictions_matrix.setRowCount(len(self.y_unic))
# заголовки для столбцов.
self.ui.test_predictions_matrix.setHorizontalHeaderLabels(self.y_unic)
# заголовки для строк.
self.ui.test_predictions_matrix.setVerticalHeaderLabels(self.y_unic)
row = 0
for tup in data:
col = 0
for item in tup:
cellinfo = QTableWidgetItem(str(item))
# Только для чтения
cellinfo.setFlags(PyQt5.QtCore.Qt.ItemIsSelectable
| PyQt5.QtCore.Qt.ItemIsEnabled)
self.ui.test_predictions_matrix.setItem(row, col, cellinfo)
col += 1
row += 1
def btn_select_path_to_test_data_clicked(self):
file_path = QFileDialog.getOpenFileName(self,
"Выберите файл",
filter="*.csv")
self.ui.path_to_test_data.setText(file_path[0])
def btn_open_path_to_test_data_clicked(self):
path = self.ui.path_to_test_data.text()
path = '\\'.join(path.split('\\')[:-1])
path = os.path.realpath(path)
os.startfile(path)
# ====Управление третьей вкладкой===================================================
def btn_open_input_data_path_clicked(self):
path = self.ui.input_data_path.text()
path = os.path.realpath(path)
os.startfile(path)
def btn_open_output_bmp_data_path_clicked(self):
path = self.ui.output_bmp_data_path.text()
path = os.path.realpath(path)
os.startfile(path)
def btn_open_output_png_data_path_clicked(self):
path = self.ui.output_png_data_path.text()
path = os.path.realpath(path)
os.startfile(path)
def btn_choose_input_data_path_clicked(self):
file_path = QFileDialog.getExistingDirectory(
self, "Выберите папку с изображениями в формате BMP")
self.ui.input_data_path.setText(file_path)
self.load_table(
self.ui.table_input_info,
data_prep.get_folder_stats(self.ui.input_data_path.text()))
def btn_choose_output_bmp_data_path_clicked(self):
file_path = QFileDialog.getExistingDirectory(
self, "Выберите папку для сохранения данных в формате BMP")
self.ui.output_bmp_data_path.setText(file_path)
def btn_choose_output_png_data_path_clicked(self):
file_path = QFileDialog.getExistingDirectory(
self, "Выберите папку для сохранения данных в формате PNG")
self.ui.output_png_data_path.setText(file_path)
def btn_start_devider_clicked(self):
data_prep.devide_data(self.ui.input_data_path.text(),
self.ui.output_bmp_data_path.text(),
self.ui.output_png_data_path.text(),
self.ui.checkBox_convert_png.isChecked(),
int(self.ui.spinBox.value()),
self.ui.progressBar)
self.load_table(
self.ui.table_input_info,
data_prep.get_folder_stats(self.ui.input_data_path.text()))
self.load_table(
self.ui.table_test_info,
data_prep.get_folder_stats(self.ui.output_bmp_data_path.text() +
"\\" + data_prep.TEST_FOLDER))
self.load_table(
self.ui.table_train_info,
data_prep.get_folder_stats(self.ui.output_bmp_data_path.text() +
"\\" + data_prep.TRAIN_FOLDER))
def load_table(self, table, data):
table.setColumnCount(2)
table.setRowCount(len(data))
# заголовки для столбцов.
table.setHorizontalHeaderLabels(('Клетка', 'Количество'))
row = 0
for tup in data:
col = 0
for item in tup:
cellinfo = QTableWidgetItem(item)
# Только для чтения
cellinfo.setFlags(PyQt5.QtCore.Qt.ItemIsSelectable
| PyQt5.QtCore.Qt.ItemIsEnabled)
table.setItem(row, col, cellinfo)
col += 1
row += 1
# ======================================4===========================================
def btn_choose_neiron_train_data_path_clicked(self):
file_path = QFileDialog.getExistingDirectory(self, "Выберите папку")
self.ui.neiron_train_data_path.setText(file_path)
def btn_choose_neiron_test_data_path_clicked(self):
file_path = QFileDialog.getExistingDirectory(self, "Выберите папку")
self.ui.neiron_test_data_path.setText(file_path)
def btn_open_neiron_train_data_path_clicked(self):
path = self.ui.neiron_train_data_path.text()
path = os.path.realpath(path)
os.startfile(path)
def btn_open_neiron_test_data_path_clicked(self):
path = self.ui.neiron_test_data_path.text()
path = os.path.realpath(path)
os.startfile(path)
def btn_open_neiron_weights_path_clicked(self):
path = "ProjectData//Weights//Neiron"
path = os.path.realpath(path)
os.startfile(path)
def btn_start_neiron_train_clicked(self):
print("!!")
neiron.start_train(self.ui.neiron_train_data_path.text(),
self.ui.use_gpu.isChecked(), self.ui.epoch.value())
def btn_neiron_test_clicked(self):
neiron.test_model(self.ui.neiron_test_data_path.text(),
self.ui.use_gpu.isChecked(),
"ProjectData//Weights/Neiron//cp.ckpt")
def btn_neiron_additional_train_clicked(self):
pass
def __init__(self):
QMainWindow.__init__(self)
Ui_MainWindow.__init__(self)
self.setupUi(self)
self.resize(600, 600)
# define the Bin Information
self.bin_info_dict = {}
# define the Sort bin map
self.bin_map_dict = {}
# define bin data
self.bin_data = pd.DataFrame()
# define the ucs map and initial the map and ucs_info
self.ucs_map = pd.DataFrame()
self.ucs_info = pd.DataFrame()
# Initialize scene and graphicView setting
self.scene = QGraphicsScene()
self.scene_text_item = None
self.graphicsView.setScene(self.scene)
# self.graphicsView.scale(1.5, 1.5)
# self.scene.setSceneRect(-200, -200, 400, 400)
# self.graphicsView.setScene(self.scene)
self.graphicsView_save_path = os.path.abspath(".")
# define the graphic item dictionary to store each plot item data
self.graphics_item_dict = {}
self.scene_text_item = None
# create the dialog for wafer setting
self.wafer_setting_dialog = ShowWaferSettingDialog()
self.wafer_setting_dialog.wafer_layout_changed.connect(self.updateWaferLayoutSetting)
self.wafer_setting_dialog.wafer_title_changed.connect(self.updateWaferTitleSetting)
self.wafer_setting_dialog.die_props_changed.connect(self.updateDieSetting)
# create the dialog for wafer selection
self.wafer_select_dialog = ShowWaferItemDialog()
self.wafer_select_dialog.select_item.connect(self.updateWaferSortMap)
# create the ink dialog for wafer ink off process
self.wafer_ink_dialog = ShowInkDialog()
# self.wafer_select_dialog.select_bin.connect(self.updateWaferSortMap)
# initial ink off setting in QGraphic View
# self.graphicsView.ink_off_color = QColor(self.comboBox_inkoff_color.currentText())
# self.die_edge_color = QColor(0, 0, 0, 90)
# action button
self.action_Map_Setting.triggered.connect(self.showWaferSettingDialog)
self.action_Lot_Dialog.triggered.connect(self.showWaferSelectDialog)
self.sort_map = SortMap(ucs_map_df=self.ucs_map, scene=self.scene)
self.action_Zoom_In.triggered.connect(lambda : self.graphicsView.zoomMap(factor=1.1))
self.action_Zoom_Out.triggered.connect(lambda : self.graphicsView.zoomMap(factor=0.9))
self.action_Rotation_Left.triggered.connect(lambda : self.graphicsView.rotateMap(angle=-15))
self.action_Rotation_Right.triggered.connect(lambda : self.graphicsView.rotateMap(angle=15))
self.action_Ink_Off.triggered.connect(self.showInkDialog)
# create the sort map class
self.testGraphicPlot()
self.testLotTableWidget()