can accept a mechanism config with at least a single state

engine/configProcessor.py

@@ -2,14 +2,12 @@ import pandas as pd
 from functools import partial, reduce
 
 def state_identity(k):
-    def identity(step, sL, s, _input):
-        return (k, s[k])
-    return identity
+    return lambda step, sL, s, _input: (k, s[k])
 
+def b_identity(step, sL, s):
+    return 0
 def behavior_identity(k):
-    def identity(step, sL, s):
-        return 0
-    return identity
+    return b_identity
 
 def key_filter(mechanisms, keyname):
     return [ v[keyname] for k, v in mechanisms.items() ]
@@ -27,10 +25,24 @@ def create_matrix_field(mechanisms, key):
         identity = behavior_identity
     df = pd.DataFrame(key_filter(mechanisms, key))
     col_list = apply_identity_funcs(identity, df, list(df.columns))
-    return reduce((lambda x, y: pd.concat([x, y], axis=1)), col_list)
+    if len(col_list) != 0:
+        return reduce((lambda x, y: pd.concat([x, y], axis=1)), col_list)
+    else:
+        return pd.DataFrame({'empty' : []})
+
 
 def generate_config(mechanisms, env_poc):
-    bdf = create_matrix_field(mechanisms,'behaviors')
-    sdf = create_matrix_field(mechanisms,'states')
-    zipped_list = list(zip(sdf.values.tolist(), bdf.values.tolist()))
+    def no_behavior_handler(bdf, sdf):
+        if bdf.empty == False:
+            sdf_values, bdf_values = sdf.values.tolist(), bdf.values.tolist()
+        else:
+            sdf_values = sdf.values.tolist()
+            bdf_values = [[b_identity] * len(sdf_values)]
+        return sdf_values, bdf_values
+
+    bdf = create_matrix_field(mechanisms, 'behaviors')
+    sdf = create_matrix_field(mechanisms, 'states')
+    sdf_values, bdf_values = no_behavior_handler(bdf, sdf)
+    zipped_list = list(zip(sdf_values, bdf_values))
+
     return list(map(lambda x: (x[0] + env_poc, x[1]), zipped_list))

engine/mechanismExecutor.py

@@ -45,7 +45,11 @@ def mech_step(m_step, sL, state_funcs, behavior_funcs, env_processes, t_step):
 
 def block_gen(states_list, configs, env_processes, t_step):
     m_step = 0
+    print("states_list")
+    print(states_list)
     states_list_copy = deepcopy(states_list)
+    print("states_list_copy")
+    print(states_list_copy)
     genesis_states = states_list_copy[-1]
     genesis_states['mech_step'], genesis_states['time_step'] = m_step, t_step
     states_list = [genesis_states]
@@ -54,7 +58,7 @@ def block_gen(states_list, configs, env_processes, t_step):
     for config in configs:
         s_conf, b_conf = config[0], config[1]
         states_list = mech_step(m_step, states_list, s_conf, b_conf, env_processes, t_step)
-        print(b_conf)
+        # print(b_conf)
         m_step += 1
 
     t_step += 1

ui/config.py

@@ -105,34 +105,34 @@ env_processes = {
 mechanisms = {
     "m1": {
         "behaviors": {
-            "b1": b1m1, # lambda step, sL, s: s['s1'] + 1,
+            # "b1": b1m1, # lambda step, sL, s: s['s1'] + 1,
             "b2": b2m1
         },
         "states": { # exclude only. TypeError: reduce() of empty sequence with no initial value
-            "s1": s1m1,
-            "s2": s2m1
+            # "s1": s1m1,
+            # "s2": s2m1
         }
     },
-    "m2": {
-        "behaviors": {
-            "b1": b1m2,
-            "b2": b2m2
-        },
-        "states": {
-            "s1": s1m2,
-            "s2": s2m2
-        }
-    },
-    "m3": {
-        "behaviors": {
-            "b1": b1m3,
-            "b2": b2m3 #toggle for error
-        },
-        "states": {
-            "s1": s1m3,
-            "s2": s2m3
-        }
-    }
+    # "m2": {
+    #     "behaviors": {
+    #         "b1": b1m2,
+    #         "b2": b2m2
+    #     },
+    #     "states": {
+    #         "s1": s1m2,
+    #         "s2": s2m2
+    #     }
+    # },
+    # "m3": {
+    #     "behaviors": {
+    #         "b1": b1m3,
+    #         "b2": b2m3 #toggle for error
+    #     },
+    #     "states": {
+    #         "s1": s1m3,
+    #         "s2": s2m3
+    #     }
+    # }
 }
 
 sim_config = {