AnalyticFunction: Support functions with separate param and arg arguments

1 files changed, 8 insertions, 4 deletions

diff --git a/lib/dfatool.py b/lib/dfatool.py
index 30ffbd5..896dc12 100755
--- a/lib/dfatool.py
+++ b/lib/dfatool.py
@@ -466,7 +466,7 @@ class ParamFunction:
 
 class AnalyticFunction:
 
-    def __init__(self, function_str, parameters, num_args, verbose = True, regression_args = None, function_lambda = None):
+    def __init__(self, function_str, parameters, num_args, verbose = True, regression_args = None):
         self._parameter_names = parameters
         self._num_args = num_args
         self._model_str = function_str
@@ -490,15 +490,17 @@ class AnalyticFunction:
                 rawfunction = rawfunction.replace('regression_arg({:d})'.format(i), 'reg_param[{:d}]'.format(i))
             self._function_str = rawfunction
             self._function = eval('lambda reg_param, model_param: ' + rawfunction)
-        elif type(function_str) == function:
+        else:
             self._function_str = 'raise ValueError'
             self._function = function_str
 
         if regression_args:
             self._regression_args = regression_args.copy()
             self._fit_success = True
-        else:
+        elif type(function_str) == str:
             self._regression_args = list(np.ones((num_vars)))
+        else:
+            self._regression_args = None
 
     def get_fit_data(self, by_param, state_or_tran, model_attribute):
         dimension = len(self._parameter_names) + self._num_args
@@ -553,7 +555,9 @@ class AnalyticFunction:
                 return False
         return True
 
-    def eval(self, param_list):
+    def eval(self, param_list, arg_list = []):
+        if self._regression_args == None:
+            return self._function(param_list, arg_list)
         return self._function(self._regression_args, param_list)
 
 class analytic: