1/p bounds in ui

src/gui_qt/fit/fit_forms.py

@@ -86,15 +86,21 @@ class FitModelWidget(QtWidgets.QWidget, Ui_FitParameter):
             p = self.parameter_line.text().replace(',', '.')
 
         if self.checkBox.isChecked():
-            try:
-                lb = float(self.lineEdit.text().replace(',', '.'))
-            except ValueError:
-                lb = None
+            lb_text = self.lineEdit.text()
+            lb = None
+            if lb_text:
+                try:
+                    lb = float(lb_text.replace(',', '.'))
+                except ValueError:
+                    lb = lb_text
 
-            try:
-                rb = float(self.lineEdit_2.text().replace(',', '.'))
-            except ValueError:
-                rb = None
+            ub_text = self.lineEdit_2.text()
+            rb = None
+            if ub_text:
+                try:
+                    rb = float(ub_text.replace(',', '.'))
+                except ValueError:
+                    rb = ub_text
         else:
             lb = rb = None
 

src/nmreval/fit/minimizer.py

@@ -278,10 +278,12 @@ class FitRoutine(object):
             data._model = self.fit_model
             self._no_own_model.append(data)
 
+        data.parameter.prepare_bounds()
+
         return self._prep_parameter(data.parameter)
 
     @staticmethod
-    def _prep_parameter(parameter):
+    def _prep_parameter(parameter: Parameters):
         vals = []
         var_pars = []
         for p_k, v_k in parameter.items():
@@ -293,7 +295,8 @@ class FitRoutine(object):
 
         return pp, lb, ub, var_pars
 
-    def _prep_global(self, data_group, linked):
+    @staticmethod
+    def _prep_global(data_group: list[Data], linked):
         p0 = []
         lb = []
         ub = []
@@ -306,6 +309,8 @@ class FitRoutine(object):
             for k, v in data.model.parameter.items():
                 data.replace_parameter(k, v)
 
+            data.parameter.prepare_bounds()
+
             actual_pars = []
             for i, p_k in enumerate(data.para_keys):
                 p_k_used = p_k

src/nmreval/fit/parameter.py

@@ -102,10 +102,12 @@ class Parameters(dict):
                 p._expr = expression
 
     def prepare_bounds(self):
+        print('prepare_bounds')
         original_values = list(self.values())
         for param in original_values:
             already_with_expression = False
             for mode, value in (('lower', param.lb), ('upper', param.ub)):
+                print(mode, value)
                 if already_with_expression:
                     raise ValueError('Only one boundary can be an expression')
                 already_with_expression = self.parse(param, value, bnd=mode)