put set attribute method in abstract

whobpyt/datatypes/AbstractParams.py

@@ -4,32 +4,15 @@
 class AbstractParams:
     # This class stores the parameters used by a model. The parameters may be for the Neural Mass Model and/or Neuroimaging Modality.
     # It should be useable by both the pytorch model for training and a numpy model for parameter verification. 
-
+    params ={}
     def __init__(self, **kwargs):
         # Define the parameters using the par data structure
-        pass
-
-    def getFittedNames(self):
+
+        for var in kwargs:
+            self.params[var] = kwargs[var]
+    def setParamsAsattr(self):
         # Returns a named list of paramters that are being fitted
         # Assumes the par datastructure is being used for parameters
 
-        fp = []
-        vars_names = [a for a in dir(self) if not a.startswith('__')]
-        for var_name in vars_names:
-            var = getattr(model.param, var_name)
-            if (type(var) == whobpyt.datatypes.parameter.par):
-                if (var.fit_par == True):
-                    fp.append(var_name)
-                if (var.fit_hyper == True):
-                    fp.append(var_name + "_m")
-                    fp.append(var_name + "_v_inv")
-        return fp
-
-    def to(self, device):
-        # Moves all parameters between CPU and GPU
-
-        vars_names = [a for a in dir(self) if not a.startswith('__')]
-        for var_name in vars_names:
-            var = getattr(self, var_name)
-            if (type(var) == par):
-                var.to(device)
+        for var in self.params:
+            setattr(self, var, self.params[var])