fit with expression works with single fit

src/nmreval/fit/parameter.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 from numbers import Number
 from itertools import count
+from re import sub
 
 import numpy as np
 
@@ -69,6 +70,9 @@ class Parameters(dict):
             name = par.name
         else:
             par = Parameter(name=name, value=value, var=var, lb=lb, ub=ub)
+
+        name = _prepare_namespace_string(name)
+
         self[name] = par
         par.eval_allowed = False
         self._namespace[name] = par.value
@@ -114,6 +118,7 @@ class Parameter:
         self._expr = None
 
         if isinstance(value, str):
+            value = _prepare_namespace_string(value)
             self._expr = value
             self.var = False
 
@@ -171,9 +176,7 @@ class Parameter:
     @property
     def value(self) -> float:
         if self._expr is not None and self.eval_allowed:
-            print(self._expr, self.namespace)
-            print(eval(self._expr, self.namespace))
-            return eval(self._expr, self.namespace)
+            return eval(self._expr, {}, self.namespace)
         elif self._value is not None:
             return self._value
 
@@ -216,3 +219,7 @@ class Parameter:
         para_copy = Parameter(name=self.name, value=val, var=self.var, lb=self.lb, ub=self.ub)
 
         return para_copy
+
+
+def _prepare_namespace_string(expr: str) -> str:
+    return sub('[\(\)\{.\}\\\]', '_', expr)

src/nmreval/models/spectrum.py

@@ -56,7 +56,7 @@ class Lorentzian:
             off (float): baseline
 
         """
-        print('Lorentzian', a, mu, sigma, off)
+        # print('Lorentzian', a, mu, sigma, off)
         return (a/np.pi) * 2*sigma / (4*(x-mu)**2 + sigma**2) + off