Fix spelling issues

smart_control/environment/environment.py

@@ -240,7 +240,7 @@ def compute_action_regularization_cost(
     Returns the L2 Norm of the actions as a penalty term for large changes.
 
   Args:
-    action_history: Seqential array of actions taken in the episode.
+    action_history: Sequential array of actions taken in the episode.
 
   Returns:
     A smoothing cost applied to the reward function for applying big changes.
@@ -986,7 +986,7 @@ def _normalized_observation_response_to_observation_map_single_timeseries(
       continuous_value = single_observation_response.continuous_value
 
       if not single_observation_response.observation_valid:
-        logging.warn(
+        logging.warning(
             "Invalid observation reported %s %s %f",
             device_id,
             measurement_name,

smart_control/environment/environment_test.py

@@ -66,13 +66,13 @@ class EnvironmentTest(parameterized.TestCase, tf.test.TestCase):
           2.236067,
       ),
   )
-  def test_comput_actions_regularization_cost_valid(
+  def test_compute_actions_regularization_cost_valid(
       self, action_history, expected
   ):
     cost = environment.compute_action_regularization_cost(action_history)
     self.assertAlmostEqual(expected, cost, places=3)
 
-  def test_comput_actions_regularization_cost_invalid(self):
+  def test_compute_actions_regularization_cost_invalid(self):
     action_history = [np.array([1, 0]), np.array([1, 0, 1])]
     with self.assertRaises(ValueError):
       _ = environment.compute_action_regularization_cost(action_history)

smart_control/environment/environment_test_utils.py

@@ -1,4 +1,4 @@
-"""Shared test utiltiles for environment tests."""
+"""Shared test utilities for environment tests."""
 
 import collections
 from typing import Sequence

smart_control/models/base_building.py

@@ -47,7 +47,7 @@ def wait_time(self) -> None:
 
   @abc.abstractmethod
   def reset(self) -> None:
-    """Resets the building, throwing an RuntimeError if this is impossible."""
+    """Resets the building, throwing a RuntimeError if this is impossible."""
 
   @property
   @abc.abstractmethod

smart_control/models/base_energy_cost.py

@@ -38,7 +38,7 @@ def carbon(
     """Returns the mass of carbon emitted from the energy consumption.
 
     The energy-to-carbon emission is source specific. Assuming a constant
-    rate of energy consumption (W) of the time interval bounded by
+    rate of energy consumption (W) over the time interval bounded by
     start_time and end_time, we can estimate total energy use (J). The type
     of source will convert energy into carbon mass (kg).
 

smart_control/reinforcement_learning/scripts/populate_starter_buffer.py

@@ -70,7 +70,7 @@ def populate_replay_buffer(
         'This buffer path already exists. This would override the existing'
         ' buffer. Please use another name'
     )
-    raise FileExistsError('Buffer name already exists, would be overriden') from err  # pylint: disable=line-too-long
+    raise FileExistsError('Buffer name already exists, would be overridden') from err  # pylint: disable=line-too-long
 
   # Load environment
   logger.info('Loading environment from standard config')

smart_control/reinforcement_learning/scripts/train.py

@@ -244,7 +244,7 @@ def train_agent(
   for i in range(train_iterations):
     # Get current training step value before operations
     current_step = train_step.numpy()
-    logger.exception(
+    logger.info(
         'Starting training loop iteration %d (step %d)', i, current_step
     )
 

smart_control/reinforcement_learning/utils/config.py

@@ -30,7 +30,7 @@
 
 # pylint: enable=unused-import
 
-# Relative filepaths. Consider moving to reinforcement_learning/constants.py
+# Relative file paths. Consider moving to reinforcement_learning/constants.py
 # fmt: off
 # pylint: disable=line-too-long
 DATA_PATH = os.path.join(ROOT_DIR, "smart_control", "configs", "resources", "sb1")

smart_control/reward/base_setpoint_energy_carbon_reward.py

@@ -155,7 +155,7 @@ def _sum_electricity_energy_rate(
   def _sum_natural_gas_energy_rate(
       self, energy_reward_info: smart_control_reward_pb2.RewardInfo
   ) -> float:
-    """Returns the sum of nat gas energy rate over the interval in W."""
+    """Returns the sum of natural gas energy rate over the interval in W."""
 
     # Sum up the power in Watts for the total power.
     gas_energy_rate = 0.0

smart_control/reward/electricity_energy_cost_test.py

@@ -96,7 +96,7 @@ def test_cost(self, start_time, end_time, energy_rate, expected_cost):
           0.4410,
       ),
   ])
-  def test_carbon_emisison(
+  def test_carbon_emission(
       self, start_time, end_time, energy_rate, expected_carbon
   ):
     cost = electricity_energy_cost.ElectricityEnergyCost()

smart_control/reward/natural_gas_energy_cost_test.py

@@ -40,7 +40,7 @@ def test_energy_cost(self, month, expected_cost):
     cost_estimate = cost.cost(start_time, end_time, energy_rate)
     self.assertAlmostEqual(expected_cost, cost_estimate, 2)
 
-  def test_carbon_emisison(self):
+  def test_carbon_emission(self):
     # Source:
     # https://www.eia.gov/environment/emissions/co2_vol_mass.php
     # 1 million BTUs nat gas generate 53.1 kg C02.

smart_control/reward/setpoint_energy_carbon_regret.py

@@ -8,7 +8,7 @@
 For this pilot there are three principal factors that contribute to the
 reward function:
   * Setpoint: Maintaining the zone temperatures within heating and cooling
-  setpoints  results in a positive reward, and any temperature outside of
+  setpoints results in a positive reward, and any temperature outside of
   setpoints may also result in a negative reward (i.e., penalty).
   * Cost: The cost of electricity and natural gas is a negative reward (cost).
   Then by minimizing negative rewards/maximizing positive reward, the agent

smart_control/reward/setpoint_energy_carbon_reward.py

@@ -24,7 +24,7 @@
   s(setpoint) is the reward for maintaining setpoint
   f(cost) is the cost of consuming electrical and natural gas energy
   g(carbon) is the cost of emitting carbon,
-  and u, w are weighing factors for cost and carbon depending on the policy.
+  and u, w are weighting factors for cost and carbon depending on the policy.
 
 The fundamental metric unit of energy is the Joule (J), and the unit of energy
 applied over a fixed time interval (energy rate) is power measured in J/sec or

smart_control/simulator/air_handler.py

@@ -13,7 +13,8 @@
 
 @gin.configurable
 class AirHandler(smart_device.SmartDevice):
-  """Models an air hander with heating/cooling, input/exhaust and recirculation.
+  """
+  Models an air handler with heating/cooling, input/exhaust and recirculation.
 
   Attributes:
     recirculation: Proportion of air recirculated.
@@ -45,7 +46,7 @@ def __init__(
   ):
     if cooling_air_temp_setpoint <= heating_air_temp_setpoint:
       raise ValueError(
-          'cooling_air_temp_setpoint must greater than'
+          'cooling_air_temp_setpoint must be greater than'
           ' heating_air_temp_setpoint'
       )
 

smart_control/simulator/air_handler_test.py

@@ -106,7 +106,7 @@ def test_get_mixed_air_temp(
   ):
     """Calculates the mixed air temperature.
 
-    This function is calculated by muliplying the recirculation_temp by
+    This function is calculated by multiplying the recirculation_temp by
     the recirculation factor, and the ambient_temp
     by 1 minus the recirculation factor, and adding the two.
 
@@ -129,7 +129,7 @@ def test_get_mixed_air_temp(
 
   @parameterized.named_parameters(
       ('below setpoint window case 1', 0.3, 280, 240, 270),
-      ('below setpount window case 2', 0.6, 244, 270, 270),
+      ('below setpoint window case 2', 0.6, 244, 270, 270),
       ('above setpoint window case 1', 0.1, 210, 316, 288),
       ('above setpoint window case 2', 0.4, 250, 316, 288),
       ('in setpoint window case 1', 0.4, 286, 266, 0.4 * 286 + 0.6 * 266),

smart_control/simulator/boiler.py

@@ -263,11 +263,11 @@ def compute_thermal_dissipation_rate(
   ) -> float:
     """Returns the amount of thermal loss in W from a boiler tank.
 
-    Thermal dissipation is the loss of heat due from the tank to the environment
+    Thermal dissipation is the loss of heat from the tank to the environment
     due to imperfect insulation, measured in Watts.
 
     The tank is assumed to be a cylindrical annulus, with an internal radius
-    internal length, and an insulation thickness. Heat is dissapated only
+    internal length, and an insulation thickness. Heat is dissipated only
     through the cylinder walls, and no heat is lost through the ends/caps.
 
     The equation is computed by applying an energy balance of:

smart_control/simulator/building.py

@@ -259,7 +259,7 @@ def _construct_cv_type_array(
 ) -> np.ndarray:
   """Fills once the CV type matrix and save it.
 
-  In the original imlementation,
+  In the original implementation,
       the sweep() function would call the get_cv_type() function every time,
       repeating logic that only needed to be computed once and saved.
 
@@ -390,7 +390,7 @@ class Building(BaseSimulatorBuilding):
       length of the building.
     temp: The current temp in K of each control volume.
     conductivity: Thermal conductivity in of each control volume W/m/K.
-    heat_capacity: Thermal heat cpacity of each control volume in J/kg/K.
+    heat_capacity: Thermal heat capacity of each control volume in J/kg/K.
     density: Material density in kg/m3 of each control volume.
     input_q: Heat energy applied (sign indicates heating/cooling) at the CV in W
       (J/s).

smart_control/simulator/building_test.py

@@ -807,7 +807,7 @@ def test_enlarge_exterior_walls(self):
         [0, 0, 0, 0, 0, 0, 0],
     ])
 
-    expexted_interior_output = np.array([
+    expected_interior_output = np.array([
         [0, 0, 0, 0, 0, 0, 0],
         [0, 0, 0, 0, 0, 0, 0],
         [0, 0, 0, 0, 0, 0, 0],
@@ -823,7 +823,7 @@ def test_enlarge_exterior_walls(self):
     with self.subTest("exterior_output"):
       np.testing.assert_array_equal(exterior_output, expected_exterior_output)
     with self.subTest("interior_output"):
-      np.testing.assert_array_equal(interior_output, expexted_interior_output)
+      np.testing.assert_array_equal(interior_output, expected_interior_output)
 
   def test_interior_air_values(self):
     initial_temp = 292.0
@@ -1691,7 +1691,7 @@ def test_stochastic_convection_simulator_shuffle_max_dist(
           continue
         self.assertEqual(b.temp[i][j], 292.0)
 
-    # lets reset and try again, to make sure the chache works
+    # lets reset and try again, to make sure the cache works
     # now lets change the temps in a room
     b.temp[2][2] = 1
     b.temp[2][3] = 2

smart_control/simulator/building_utils.py

@@ -129,7 +129,7 @@ def save_images_to_cns_for_debugging(
 def guarantee_air_padding_in_frame(
     floor_plan: FileInputFloorPlan,
 ) -> FileInputFloorPlan:
-  """Adds a row or column of air if a building is abuts its frame edge.
+  """Adds a row or column of air if a building abuts its frame edge.
 
   Future computation relies on buildings being surrounded by at least one
     layer of air CVs between them and the edge of the floor plan frame.
@@ -175,7 +175,7 @@ def determine_row_size_of_exterior_space_to_add() -> np.ndarray:
     )
 
   def determine_column_size_of_exterior_space_to_add() -> np.ndarray:
-    """A helper function to recompute a columns row to add from floor plan dim.
+    """A helper function to recompute a column row to add from floor plan dim.
 
     Returns:
       a column of constants.EXTERIOR_SPACE_VALUE_IN_FILE_INPUT's to concat if
@@ -283,7 +283,7 @@ def _set_exterior_space_neg(
   """Modifies the connections array so that exterior space is negative.
 
   Encoding the exterior space as negative is important in the connections array
-  as it will encode an aribtrarily large number of rooms as positive integers.
+  as it will encode an arbitrarily large number of rooms as positive integers.
   Thus, setting the exterior space as negative ensures that we will always be
   able to deal with it as its own category of space.
 

smart_control/simulator/constants.py

@@ -34,13 +34,13 @@
 # that designates exterior space in the file input.
 EXTERIOR_SPACE_VALUE_IN_FILE_INPUT = 2
 
-# Here we designate a specific placeholder to help use demarcate which CVs
+# Here we designate a specific placeholder to help us demarcate which CVs
 # are for exterior space once processed in the function. It is intentionally
 # set to -1 so that the connectedComponent function can have access to all
 # nonzero integers to count upwards in an unbounded way.
 EXTERIOR_SPACE_VALUE_IN_FUNCTION = -1
 
-# Here we designate a specific placeholder to help use demarcate which CVs
+# Here we designate a specific placeholder to help us demarcate which CVs
 # are for exterior space are noted in the component. It is intentionally
 # set to -1 so that the connectedComponent function can have access to all
 # nonzero integers to count upwards in an unbounded way.
@@ -52,7 +52,7 @@
 
 # Here we pick out a specific value that we know will code for interior space
 # after connectedComponents() processes it. We know this because we have ensured
-# that the CV at index (0,0) will always be an "space" CV when ready for
+# that the CV at index (0,0) will always be a "space" CV when ready for
 # input to connectedComponents, but we previously index the exterior space CVs
 # in their own data array. Thus, after overwriting the exterior space CVs to
 # the value _EXTERIOR_SPACE_VALUE_IN_FUNCTION, all connectedComponents of
@@ -82,17 +82,11 @@
 # returning expanded exterior walls when calling enlarge_component()
 WALLS_AND_EXPANDED_BOOLS = 2
 
-# Here we wish to specifically set exterior space as indistinguishable
-# from exterior walls, as we wish to perform connectedComponents only on
-# connected groups of interior space. Thus, we set exterior space to a generic
-# space value, i.e. 0.
-GENERIC_SPACE_VALUE_IN_CONNECTION_INPUT = 0
-
 # Here we use a specific placeholder value, matching with the file input schema,
 # that designates interior space in the file input.
 INTERIOR_WALL_VALUE_IN_FILE_INPUT = 1
 
-# Here we designate a specific placeholder to help use demarcate which CVs
+# Here we designate a specific placeholder to help us demarcate which CVs
 # are for interior walls once processed in the function. It is intentionally
 # set to -3 so that the connectedComponent function can have access to all
 # nonzero integers to count upwards in an unbounded way.

smart_control/simulator/hvac.py

@@ -44,7 +44,7 @@ def __init__(
 
     Args:
       zone_coordinates: List of 2-tuple containing zone coordinates to service.
-      air_handler: the air handler for hte HVAC
+      air_handler: the air handler for the HVAC
       boiler: the boiler for the HVAC
       schedule: the setpoint_schedule for the thermostats
       vav_max_air_flow_rate: the max airflow rate for the vavs

smart_control/simulator/hvac_test.py

@@ -199,7 +199,7 @@ def test_vav_device_ids(self):
 
     self.assertListEqual(vav_ids, expected_vav_ids)
 
-  def test_id_comfort_mode(self):
+  def test_is_comfort_mode(self):
     zone_coordinates = [(0, 0), (1, 0), (1, 1), (0, 1)]
     handler = _get_default_air_handler()
     b = _get_default_boiler()

smart_control/simulator/randomized_arrival_departure_occupancy.py

@@ -28,8 +28,8 @@ class ZoneOccupant:
   """Represents a single occupant in a zone.
 
   Attributes:
-    earliest_expected_arrival_hour: earliest arrivel, 0 - 22
-    latest_expected_arrival_hour: latest arrivel, 1 - 23
+    earliest_expected_arrival_hour: earliest arrival, 0 - 22
+    latest_expected_arrival_hour: latest arrival, 1 - 23
     earliest_expected_departure_hour: earliest departure, 0 - 22
     latest_expected_departure_hour: latest departure, 1 - 23
     random_state: random state used to generate events
@@ -82,16 +82,16 @@ def _get_event_probability(self, start_hour, end_hour):
     # The halfway point is the firts half of the trials.
     n_halfway = window / self._step_size / 2.0
     # We'd like to return the probability of event happening in a single time-
-    # step. This follow a geometric distribution, where E[X] = 1/p, where
-    # E[x] is the expected number of events before the first success. If
+    # step. This follows a geometric distribution, where E[X] = 1/p, where
+    # E[X] is the expected number of events before the first success. If
     # E[X] is the halfway point, then p = 1 / n_halfway.
     return 1.0 / n_halfway
 
   def _occupant_arrived(self, timestamp):
     """Makes a random draw to determine whether occupant arrives."""
 
     local_timestamp = self._to_local_time(timestamp)
-    # TODO(sipple): Consider effects when time crosses DST>
+    # TODO(sipple): Consider effects when time crosses DST.
     if (
         local_timestamp.hour < self._earliest_expected_arrival_hour
         or local_timestamp.hour > self._latest_expected_arrival_hour
@@ -138,8 +138,8 @@ class RandomizedArrivalDepartureOccupancy(BaseOccupancy):
 
   Attributes:
     zone_assignment: number of occupants in a zone
-    earliest_expected_arrival_hour: earliest arrivel, 0 - 22
-    latest_expected_arrival_hour: latest arrivel, 1 - 23
+    earliest_expected_arrival_hour: earliest arrival, 0 - 22
+    latest_expected_arrival_hour: latest arrival, 1 - 23
     earliest_expected_departure_hour: earliest departure, 0 - 22
     latest_expected_departure_hour: latest departure, 1 - 23
     seed: integer used to set the random state for repeatability

smart_control/simulator/rejection_simulator_building.py

@@ -17,7 +17,7 @@
 
 @gin.configurable
 class RejectionSimulatorBuilding(BaseBuilding):
-  """A Building that throws exception while agent is awaiting authorization."""
+  """A Building that throws exceptions while agent is awaiting authorization."""
 
   def __init__(
       self, base_building: BaseBuilding, initial_rejection_count: int = 0