From 53c58b2bbb7cb3db58e877fdab3083daa855c72d Mon Sep 17 00:00:00 2001
From: Dominik Demuth <dominik.demuth@physik.tu-darmstadt.de>
Date: Wed, 6 Sep 2023 17:45:57 +0200
Subject: [PATCH] disable validators

---
 src/gui_qt/fit/fit_forms.py     | 15 ++++++++-------
 src/gui_qt/fit/fit_parameter.py | 11 +++++++----
 src/nmreval/fit/minimizer.py    |  2 ++
 3 files changed, 17 insertions(+), 11 deletions(-)

diff --git a/src/gui_qt/fit/fit_forms.py b/src/gui_qt/fit/fit_forms.py
index f0f63f7..983a0db 100644
--- a/src/gui_qt/fit/fit_forms.py
+++ b/src/gui_qt/fit/fit_forms.py
@@ -19,9 +19,9 @@ class FitModelWidget(QtWidgets.QWidget, Ui_FitParameter):
 
         self.parametername.setText(label + ' ')
 
-        validator = QtGui.QDoubleValidator()
-        validator.setDecimals(9)
-        self.parameter_line.setValidator(validator)
+        # validator = QtGui.QDoubleValidator()
+        # validator.setDecimals(9)
+        # self.parameter_line.setValidator(validator)
         self.parameter_line.setText('1')
         self.parameter_line.setMaximumWidth(60)
         self.lineEdit.setMaximumWidth(60)
@@ -97,10 +97,11 @@ class FitModelWidget(QtWidgets.QWidget, Ui_FitParameter):
             try:
                 p = float(self.parameter_line.text().replace(',', '.'))
             except ValueError:
-                _ = QtWidgets.QMessageBox().warning(self, 'Invalid value',
-                                                    f'{self.parametername.text()} contains invalid values',
-                                                    QtWidgets.QMessageBox.Cancel)
-                return None
+                p = self.parameter_line.text().replace(',', '.')
+                # _ = QtWidgets.QMessageBox().warning(self, 'Invalid value',
+                #                                     f'{self.parametername.text()} contains invalid values',
+                #                                     QtWidgets.QMessageBox.Cancel)
+                # return None
 
         if self.checkBox.isChecked():
             try:
diff --git a/src/gui_qt/fit/fit_parameter.py b/src/gui_qt/fit/fit_parameter.py
index 292c220..b461d23 100644
--- a/src/gui_qt/fit/fit_parameter.py
+++ b/src/gui_qt/fit/fit_parameter.py
@@ -124,10 +124,12 @@ class QFitParameterWidget(QtWidgets.QWidget, Ui_FormFit):
         if idx is None:
             idx = self.global_parameter.index(self.sender())
 
-        self.glob_values[idx] = float(value)
+        # self.glob_values[idx] = float(value)
+        self.glob_values[idx] = value
         if self.data_values[self.comboBox.currentData()][idx] is None:
             self.data_parameter[idx].blockSignals(True)
-            self.data_parameter[idx].value = float(value)
+            # self.data_parameter[idx].value = float(value)
+            self.data_parameter[idx].value = value
             self.data_parameter[idx].blockSignals(False)
 
     @QtCore.pyqtSlot(str, object)
@@ -300,7 +302,7 @@ class ParameterSingleWidget(QtWidgets.QWidget):
         self.label.setText(convert(name))
         self.label.setToolTip('IIf this is bold then this parameter is only for this data. otherwise the general parameter is used and displayed')
 
-        self.value_line.setValidator(QtGui.QDoubleValidator())
+        # self.value_line.setValidator(QtGui.QDoubleValidator())
         self.value_line.textChanged.connect(lambda: self.valueChanged.emit(self.value) if self.value is not None else 0)
         self.reset_button.clicked.connect(lambda x: self.removeSingleValue.emit())
 
@@ -334,7 +336,8 @@ class ParameterSingleWidget(QtWidgets.QWidget):
 
     @value.setter
     def value(self, val):
-        self.value_line.setText(f'{float(val):.5g}')
+        # self.value_line.setText(f'{float(val):.5g}')
+        self.value_line.setText(f'{val}')
 
     def show_as_local_parameter(self, is_local):
         if is_local:
diff --git a/src/nmreval/fit/minimizer.py b/src/nmreval/fit/minimizer.py
index b9dec07..355769d 100644
--- a/src/nmreval/fit/minimizer.py
+++ b/src/nmreval/fit/minimizer.py
@@ -223,6 +223,8 @@ class FitRoutine(object):
     def run(self, mode: str = 'lsq'):
         self._abort = False
 
+        print('run')
+
         fit_groups, linked_parameter = self.prepare_links()
         for data_groups in fit_groups:
             if len(data_groups) == 1 and not self.linked: