Source code for gui.core.regressionMethods.BayesianRidge

from PyQt5 import QtWidgets
from sklearn.linear_model import BayesianRidge

from gui.ui.BayesianRidge import Ui_Form
from gui.util.Modules import Modules



[docs]
class Ui_Form(Ui_Form, BayesianRidge, Modules):

[docs]
    def setupUi(self, Form):
        super().setupUi(Form)
        self.checkMinAndMax()
        self.connectWidgets()



[docs]
    def get_widget(self):
        return self.formGroupBox



[docs]
    def setHidden(self, bool):
        self.get_widget().setHidden(bool)



[docs]
    def toggle_params(self, widgets, state):
        for w in widgets:
            if state:
                w.setHidden(True)
            else:
                w.setHidden(False)



[docs]
    def connectWidgets(self):
        self.alpha_checkbox.setChecked(True)
        alphawidgets = [
            self.alphalabel,
            self.alphadoubleSpinBox,
            self.alpha1Label,
            self.alpha1DoubleSpinBox,
            self.alpha2Label,
            self.alpha2DoubleSpinBox,
        ]
        self.toggle_params(alphawidgets, self.alpha_checkbox.isChecked())
        self.lambda_checkbox.setChecked(True)
        lambdawidgets = [
            self.lambdaLabel,
            self.lambdaDoubleSpinBox,
            self.L1label,
            self.L1doubleSpinBox,
            self.L2label,
            self.L2doubleSpinBox,
        ]
        self.toggle_params(lambdawidgets, self.lambda_checkbox.isChecked())
        self.alpha_checkbox.stateChanged.connect(
            lambda: self.toggle_params(alphawidgets, self.alpha_checkbox.isChecked())
        )
        self.lambda_checkbox.stateChanged.connect(
            lambda: self.toggle_params(lambdawidgets, self.lambda_checkbox.isChecked())
        )



[docs]
    def run(self):
        if self.alpha_checkbox.isChecked() is True:
            alpha_init = None
        else:
            alpha_init = self.alphadoubleSpinBox.value()

        if self.lambda_checkbox.isChecked() is True:
            lambda_init = None
        else:
            lambda_init = self.lambdaDoubleSpinBox.value()

        params = {
            "n_iter": self.numOfIterationsSpinBox.value(),
            "tol": self.toleranceDoubleSpinBox.value(),
            "alpha_init": alpha_init,
            "alpha_1": self.alpha1DoubleSpinBox.value(),
            "alpha_2": self.alpha2DoubleSpinBox.value(),
            "lambda_init": lambda_init,
            "lambda_1": self.lambdaDoubleSpinBox.value(),
            "lambda_2": self.lambdaDoubleSpinBox.value(),
            "fit_intercept": self.fitInterceptCheckBox.isChecked(),
            "normalize": self.normalizeCheckBox.isChecked(),
        }
        return params, self.getChangedValues(params, BayesianRidge())




if __name__ == "__main__":
    import sys

    app = QtWidgets.QApplication(sys.argv)
    Form = QtWidgets.QWidget()
    ui = Ui_Form()
    ui.setupUi(Form)
    Form.show()
    sys.exit(app.exec_())