automata: .states -> .state (it's a dict)

2 files changed, 15 insertions, 15 deletions

diff --git a/bin/test_automata.py b/bin/test_automata.py
index 3b64783..c117c56 100755
--- a/bin/test_automata.py
+++ b/bin/test_automata.py
@@ -6,7 +6,7 @@ import unittest
 example_json_1 = {
     'parameters' : ['datarate', 'txbytes', 'txpower'],
     'initial_param_values' : [None, None],
-    'states' : {
+    'state' : {
         'IDLE' : {
             'power' : {
                 'static' : 5,
@@ -107,9 +107,9 @@ class TestPTA(unittest.TestCase):
     def test_from_json(self):
         pta = PTA.from_json(example_json_1)
         self.assertEqual(pta.parameters, ['datarate', 'txbytes', 'txpower'])
-        self.assertEqual(pta.states['UNINITIALIZED'].name, 'UNINITIALIZED')
-        self.assertEqual(pta.states['IDLE'].name, 'IDLE')
-        self.assertEqual(pta.states['TX'].name, 'TX')
+        self.assertEqual(pta.state['UNINITIALIZED'].name, 'UNINITIALIZED')
+        self.assertEqual(pta.state['IDLE'].name, 'IDLE')
+        self.assertEqual(pta.state['TX'].name, 'TX')
         self.assertEqual(len(pta.transitions), 5)
         self.assertEqual(pta.transitions[0].name, 'init')
         self.assertEqual(pta.transitions[1].name, 'init')
@@ -123,7 +123,7 @@ class TestPTA(unittest.TestCase):
 
     def test_from_json_function(self):
         pta = PTA.from_json(example_json_1)
-        self.assertEqual(pta.states['TX'].get_energy(1000, {'datarate' : 10, 'txbytes' : 6, 'txpower' : 10 }), 1000 * (100 + 2 * 10))
+        self.assertEqual(pta.state['TX'].get_energy(1000, {'datarate' : 10, 'txbytes' : 6, 'txpower' : 10 }), 1000 * (100 + 2 * 10))
         self.assertEqual(pta.transitions[4].get_timeout({'datarate' : 10, 'txbytes' : 6, 'txpower' : 10 }), 500 + 16 * 6)
 
     def test_simulation(self):
diff --git a/lib/automata.py b/lib/automata.py
index 3913670..fbfaf36 100755
--- a/lib/automata.py
+++ b/lib/automata.py
@@ -249,7 +249,7 @@ class PTA:
         parameters -- names of PTA parameters
         initial_param_values -- initial value for each parameter
         """
-        self.states = dict([[state_name, State(state_name)] for state_name in state_names])
+        self.state = dict([[state_name, State(state_name)] for state_name in state_names])
         self.parameters = parameters.copy()
         if initial_param_values:
             self.initial_param_values = initial_param_values.copy()
@@ -258,7 +258,7 @@ class PTA:
         self.transitions = []
 
         if not 'UNINITIALIZED' in state_names:
-            self.states['UNINITIALIZED'] = State('UNINITIALIZED')
+            self.state['UNINITIALIZED'] = State('UNINITIALIZED')
 
     @classmethod
     def from_json(cls, json_input: dict):
@@ -272,7 +272,7 @@ class PTA:
             if key in json_input:
                 kwargs[key] = json_input[key]
         pta = cls(**kwargs)
-        for name, state in json_input['states'].items():
+        for name, state in json_input['state'].items():
             power_function = _json_function_to_analytic_function(state, 'power', pta.parameters)
             pta.add_state(name, power = _json_get_static(state, 'power'), power_function = power_function)
         for transition in json_input['transitions']:
@@ -308,7 +308,7 @@ class PTA:
         ret = {
             'parameters' : self.parameters,
             'initial_param_values' : self.initial_param_values,
-            'states' : dict([[state.name, state.to_json()] for state in self.states.values()]),
+            'state' : dict([[state.name, state.to_json()] for state in self.state.values()]),
             'transitions' : [trans.to_json() for trans in self.transitions]
         }
         return ret
@@ -322,7 +322,7 @@ class PTA:
         if 'power_function' in kwargs and type(kwargs['power_function']) != AnalyticFunction:
             kwargs['power_function'] = AnalyticFunction(kwargs['power_function'],
                 self.parameters, 0)
-        self.states[state_name] = State(state_name, **kwargs)
+        self.state[state_name] = State(state_name, **kwargs)
 
     def add_transition(self, orig_state: str, dest_state: str, function_name: str, **kwargs):
         """
@@ -334,8 +334,8 @@ class PTA:
         function_name -- function name
         kwargs -- see Transition() documentation
         """
-        orig_state = self.states[orig_state]
-        dest_state = self.states[dest_state]
+        orig_state = self.state[orig_state]
+        dest_state = self.state[dest_state]
         for key in ('duration_function', 'energy_function', 'timeout_function'):
             if key in kwargs and type(kwargs[key]) != AnalyticFunction:
                 kwargs[key] = AnalyticFunction(kwargs[key], self.parameters, 0)
@@ -352,12 +352,12 @@ class PTA:
         depth -- search depth
         orig_state -- initial state for depth-first search
         """
-        return self.states[orig_state].dfs(depth, **kwargs)
+        return self.state[orig_state].dfs(depth, **kwargs)
 
     def simulate(self, trace: list, orig_state: str = 'UNINITIALIZED'):
         total_duration = 0.
         total_energy = 0.
-        state = self.states[orig_state]
+        state = self.state[orig_state]
         param_dict = dict([[self.parameters[i], self.initial_param_values[i]] for i in range(len(self.parameters))])
         for function in trace:
             function_name = function[0]
@@ -383,7 +383,7 @@ class PTA:
         return total_energy, total_duration, state, param_dict
 
     def update(self, static_model, param_model):
-        for state in self.states.values():
+        for state in self.state.values():
             if state.name != 'UNINITIALIZED':
                 state.power = static_model(state.name, 'power')
                 if param_model(state.name, 'power'):