def _setup_gui(self):
     self.ui.topologyDimensionsBox.hide()
     self.ui.topologySelector.addItems(TopologyUtil.registered_topologies())
     self.ui.topologySelector.setCurrentIndex(self.ui.topologySelector.findText(TopologyUtil.default_topology()))
     self.ui.neighbourhoodFunctionSelector.addItems(NeighbourhoodUtil.registered_neighbourhoods())
     self.ui.neighbourhoodFunctionSelector.setCurrentIndex(
         self.ui.neighbourhoodFunctionSelector.findText(NeighbourhoodUtil.default_neighbourhood()))
     self.ui.metricSelector.addItems(MetricUtil.registered_metrics())
     self.ui.metricSelector.setCurrentIndex(self.ui.metricSelector.findText(MetricUtil.default_metric()))
     self.ui.learningFactorSelector.addItems(LearningFactorUtil.registered_factors())
     self.ui.learningFactorSelector.setCurrentIndex(
         self.ui.learningFactorSelector.findText(LearningFactorUtil.default_factor()))
    def on_runButton_clicked(self):
        if self.ui.neighbourhoodEnabled.isChecked():
            neighbourhood = NeighbourhoodUtil.get_neighbourhood(
                str(self.ui.neighbourhoodFunctionSelector.currentText())
            )()
            topology = TopologyUtil.get_topology(
                str(self.ui.topologySelector.currentText()),
                neighbourhood,
                int(self.ui.initialNeighbourhoodRadius.text()),
                int(self.ui.topologyRowsValue.text()),
                int(self.ui.topologyColsValue.text()),
            )
        else:
            topology = NoTopology()
        self.metric = MetricUtil.get_metric(str(self.ui.metricSelector.currentText()))()
        learning_factor = LearningFactorUtil.get_factor(
            str(self.ui.kohonenLearningFactorSelector.currentText()),
            float(self.ui.kohonenLearningFactorInitialValue.text()),
            int(self.ui.kohonenLearningIterations.text()),
        )

        conscience_threshold = (
            float(self.ui.conscienceThresholdValue.text()) if self.ui.conscienceEnabled.isChecked() else 0
        )
        kohonen_learning_iterations = int(self.ui.kohonenLearningIterations.text())
        kohonen_learning = CounterPropagationKohonenLearning(
            self.network_layer, topology, self.metric, learning_factor, conscience_threshold
        )
        learning_data = self.input_view.get_data()

        grossberg_learning_rule = RulesUtil.get_rule(self.ui.learningRuleSelector.currentText())

        grossberg_learning_factor = LearningFactorUtil.get_factor(
            str(self.ui.grossbergLearningFactorSelector.currentText()),
            float(self.ui.grossbergLearningFactorInitialValue.text()),
            int(self.ui.grossbergLearningIterations.text()),
        )

        grossberg_learning_iterations = int(self.ui.grossbergLearningIterations.text())
        cp_learning = CounterPropagationLearning(
            self.network, grossberg_learning_rule, grossberg_learning_factor, kohonen_learning
        )
        cp_learning.learn(kohonen_learning_iterations, grossberg_learning_iterations, learning_data)
        self.accept()
 def _setup_gui(self):
     self.ui.topologyDimensionsBox.hide()
     self.ui.topologySelector.addItems(TopologyUtil.registered_topologies())
     self.ui.topologySelector.setCurrentIndex(self.ui.topologySelector.findText(TopologyUtil.default_topology()))
     self.ui.neighbourhoodFunctionSelector.addItems(NeighbourhoodUtil.registered_neighbourhoods())
     self.ui.neighbourhoodFunctionSelector.setCurrentIndex(
         self.ui.neighbourhoodFunctionSelector.findText(NeighbourhoodUtil.default_neighbourhood())
     )
     self.ui.metricSelector.addItems(MetricUtil.registered_metrics())
     self.ui.metricSelector.setCurrentIndex(self.ui.metricSelector.findText(MetricUtil.default_metric()))
     self.ui.kohonenLearningFactorSelector.addItems(LearningFactorUtil.registered_factors())
     self.ui.kohonenLearningFactorSelector.setCurrentIndex(
         self.ui.kohonenLearningFactorSelector.findText(LearningFactorUtil.default_factor())
     )
     self.ui.grossbergLearningFactorSelector.addItems(LearningFactorUtil.registered_factors())
     self.ui.grossbergLearningFactorSelector.setCurrentIndex(
         self.ui.grossbergLearningFactorSelector.findText(LearningFactorUtil.default_factor())
     )
     self.ui.learningRuleSelector.addItems(RulesUtil.rules())
     self.ui.learningRuleSelector.setCurrentIndex(self.ui.learningRuleSelector.findText(RulesUtil.default_layer()))
     self.ui.conscienceThresholdValue.setText(str(1 - round(float(1.0 / self.network.inputs_count()), 2) - 0.01))
    def on_runButton_clicked(self):
        if self.ui.neighbourhoodEnabled.isChecked():
            neighbourhood = NeighbourhoodUtil.get_neighbourhood(
                str(self.ui.neighbourhoodFunctionSelector.currentText()))()
            topology = TopologyUtil.get_topology(str(self.ui.topologySelector.currentText()),
                neighbourhood, int(self.ui.initialNeighbourhoodRadius.text()),
                int(self.ui.topologyRowsValue.text()), int(self.ui.topologyColsValue.text()))
        else:
            topology = NoTopology()
        self.metric = MetricUtil.get_metric(str(self.ui.metricSelector.currentText()))()
        learning_factor = LearningFactorUtil.get_factor(str(self.ui.learningFactorSelector.currentText()),
            float(self.ui.learningFactorInitialValue.text()), int(self.ui.learningIterations.text()))

        conscience_threshold =\
        float(self.ui.conscienceThresholdValue.text()) if self.ui.conscienceEnabled.isChecked() else 0
        learning_iterations = int(self.ui.learningIterations.text())
        learning = KohonenLearning(self.network_layer, topology, self.metric, learning_factor,
            conscience_threshold)
        learning.learn(DataNormalizer.normalize(self.input_view.get_data()), learning_iterations)
        self.accept()