1118 updated dakota_interface

dakota_interface.py

@@ -25,8 +25,27 @@ def interface(fn_json_args):
         interface_args = json.load(fo)
 
 
+    # Load data processing module
+    if 'data_process_functions_file' in interface_args.keys():
+        fn_dpf = interface_args['data_process_functions_file']
+        if fn_dpf != '':
+            import_str = 'import {0} as dpf'.format(fn_dpf)
+            exec(import_str)
+
+
     # Read parameters
     params, results = di.read_parameters_file(sys.argv[-2], sys.argv[-1])
+
+
+    # Pre-processing of parameters
+    if 'pre_process' in interface_args.keys():
+        funcs = interface_args['pre_process']
+        if len(funcs) > 0:
+            for func in funcs:
+                eval('dpf.{0}'.format(func))(params)
+
+
+    # Substitute templates
     for fn_t, fn_i in interface_args['template_output'].items():
         di.dprepro(template=fn_t, parameters=params, output=fn_i)
 
@@ -37,12 +56,6 @@ def interface(fn_json_args):
     ))
 
 
-    # Processing of parameters
-
-
-    # study = interface_args['study']
-
-
     try:
         # preVABS/VABS
         print('  - running cross-sectional analysis...')
@@ -53,26 +66,21 @@ def interface(fn_json_args):
         ms = sga.solve(fn_main, analysis, ppcmd, solver, False)
 
 
-        # Collect beam properties
-        # responses = interface_args['beam_props']
-        # for k, v in responses.items():
-        #     if k == 'stiffness_refined':
-        #         for label, index in v.items():
-        #             results[label].function = ms.stiffness_refined[index[0]][index[1]]
-
-
         # Calculate actual responses
-        is_post_funcs_imported = False
-        for k, v in interface_args['post_functions'].items():
+        # is_post_funcs_imported = False
+        for k, v in interface_args['post_process'].items():
+            # print('')
+            # print('label:', v[0])
             bp = ms.getBeamProperty(v[0])
+            # print('bp:', bp)
             if v[1] == 'self':
                 r = bp
             elif v[1] == 'abs_rel_diff':
                 r = np.abs((bp - v[2]) / v[2])
             else:
-                if not is_post_funcs_imported:
-                    import post_funcs
-                    is_post_funcs_imported = True
+                # if not is_post_funcs_imported:
+                #     import post_funcs
+                #     is_post_funcs_imported = True
                 # eval('from post_funcs import {0}'.format(v[1]))
                 # r = eval(v[1])(bp, v[2])
                 r = eval('post_funcs.{0}'.format(v[1]))(bp, v[2])