Source code for gui.core.crossValidateMethods.cv_BayesianRidge

from PyQt5 import QtWidgets
from sklearn.linear_model import BayesianRidge

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




class Ui_Form(Ui_Form, BayesianRidge, Modules):


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




    def get_widget(self):
        return self.formGroupBox




    def setHidden(self, bool):
        self.get_widget().setHidden(bool)




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




    def connectWidgets(self):
        self.alpha_checkbox.setChecked(True)
        alphawidgets = [
            self.alpha_label,
            self.alpha_lineEdit,
            self.alpha1Label,
            self.alpha1LineEdit,
            self.alpha2Label,
            self.alpha2LineEdit,
        ]
        self.toggle_params(alphawidgets, self.alpha_checkbox.isChecked())
        self.lambda_checkbox.setChecked(True)
        lambdawidgets = [
            self.lambda_label,
            self.lambda_lineEdit,
            self.lambda1Label,
            self.lambda1LineEdit,
            self.lambda2_label,
            self.lambda2LineEdit,
        ]
        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())
        )




    def run(self):
        fit_intercept_items = [
            i.text() == "True" for i in self.fitIntercept_List.selectedItems()
        ]
        normalize_items = [
            i.text() == "True" for i in self.normalize_List.selectedItems()
        ]
        if self.alpha_checkbox.isChecked() is True:
            alpha_init = [None]
        else:
            alpha_init = [float(i) for i in self.alpha_lineEdit.text().split(",")]

        if self.lambda_checkbox.isChecked() is True:
            lambda_init = [None]
        else:
            lambda_init = [float(i) for i in self.lambda_lineEdit.text().split(",")]

        params = {
            "n_iter": [int(i) for i in self.numOfIterationsLineEdit.text().split(",")],
            "tol": [float(i) for i in self.toleranceLineEdit.text().split(",")],
            "alpha_init": alpha_init,
            "alpha_1": [float(i) for i in self.alpha1LineEdit.text().split(",")],
            "alpha_2": [float(i) for i in self.alpha2LineEdit.text().split(",")],
            "lambda_init": lambda_init,
            "lambda_1": [float(i) for i in self.lambda1LineEdit.text().split(",")],
            "lambda_2": [float(i) for i in self.lambda2LineEdit.text().split(",")],
            "compute_score": [False],
            "fit_intercept": fit_intercept_items,
            "normalize": normalize_items,
            "copy_X": [True],
            "verbose": [True],
        }

        return params




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_())