Make formatting consistent

.github/workflows/autoblack.yml

@@ -0,0 +1,15 @@
+name: Black Format Check
+
+on: [pull_request]
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - uses: psf/black@stable
+        with:
+          options: "--check --line-length 100"
+          src: "."
+          jupyter: false
+          version: "23.3.0"

examples/Constellation_example/constellation_example_utils.py

@@ -18,7 +18,6 @@ def get_closest_entry(df, t, id):
 
 
 def get_analysis_df(df, timestep=60, orbital_period=1):
-
     t = np.round(np.linspace(0, df.Time.max(), int(df.Time.max() // timestep)))
     sats = df.ID.unique()
     df["known_actors"] = pd.Categorical(df.known_actors)

examples/Learning_example/simple_neural_network.py

@@ -57,9 +57,7 @@ def __len__(self):
 
         # Instantiate training and test data
         X, y = make_circles(n_samples=10000, noise=0.05, random_state=26)
-        X_train, X_test, y_train, y_test = train_test_split(
-            X, y, test_size=0.33, random_state=26
-        )
+        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=26)
 
         # divide the training set so none of the peers have the same data
         if self.node_id == 1:
@@ -75,12 +73,8 @@ def __len__(self):
         # Create dataloaders
         train_data = Data(X_train, y_train)
         test_data = Data(X_test, y_test)
-        self.train_dataloader = DataLoader(
-            dataset=train_data, batch_size=64, shuffle=True
-        )
-        self.test_dataloader = DataLoader(
-            dataset=test_data, batch_size=64, shuffle=True
-        )
+        self.train_dataloader = DataLoader(dataset=train_data, batch_size=64, shuffle=True)
+        self.test_dataloader = DataLoader(dataset=test_data, batch_size=64, shuffle=True)
 
     def forward(self, x):
         """Do inference on model

examples/Learning_example/simple_node.py

@@ -13,13 +13,10 @@ class Node:
     """
 
     def __init__(self, node_id, pos_and_vel, paseos_cfg, power_consumption_in_watt):
-
         # Create PASEOS instance to node
         earth = pk.planet.jpl_lp("earth")
         self.node_id = node_id
-        sat = ActorBuilder.get_actor_scaffold(
-            f"sat{node_id}", SpacecraftActor, pk.epoch(0)
-        )
+        sat = ActorBuilder.get_actor_scaffold(f"sat{node_id}", SpacecraftActor, pk.epoch(0))
         ActorBuilder.set_orbit(sat, pos_and_vel[0], pos_and_vel[1], pk.epoch(0), earth)
         ActorBuilder.set_power_devices(
             actor=sat,
@@ -37,8 +34,7 @@ def __init__(self, node_id, pos_and_vel, paseos_cfg, power_consumption_in_watt):
 
         transmit_bits = self.model_size()
         self.transmit_duration = transmit_bits / (
-            1000
-            * self.paseos.local_actor.communication_devices["link"].bandwidth_in_kbps
+            1000 * self.paseos.local_actor.communication_devices["link"].bandwidth_in_kbps
         )
 
         self.current_activity = "train"
@@ -70,9 +66,7 @@ def model_size(self):
         # Return model parameters as a list of NumPy ndarrays
         bytestream = b""  # Empty byte represenation
         for _, val in self.model.state_dict().items():  # go over each layer
-            bytestream += (
-                val.cpu().numpy().tobytes()
-            )  # convert layer to bytes and concatenate
+            bytestream += val.cpu().numpy().tobytes()  # convert layer to bytes and concatenate
         return len(bytestream) * 8
 
     def local_time(self):
@@ -112,9 +106,7 @@ def transmission_is_feasible(self, target_node):
         target_actor = target_node.paseos.local_actor
         local_actor = self.paseos.local_actor
 
-        transmit_end = pk.epoch(
-            self.local_time().mjd2000 + self.transmit_duration * pk.SEC2DAY
-        )
+        transmit_end = pk.epoch(self.local_time().mjd2000 + self.transmit_duration * pk.SEC2DAY)
         los_end = local_actor.is_in_line_of_sight(target_actor, transmit_end)
         return los_end
 

examples/MPI_example/mpi_example.py

@@ -26,9 +26,7 @@
 try:
     from mpi4py import MPI
 except:
-    print(
-        "This example requires mpi4py. Please install with conda install mpi4py -c conda-forge"
-    )
+    print("This example requires mpi4py. Please install with conda install mpi4py -c conda-forge")
 
 import pykep as pk
 import paseos
@@ -44,9 +42,7 @@
 # Now we will initialize MPI, for more details please refer to the mpi4py docs.
 # In MPI "rank" indicates the index of the compute node (so 0-3 in our example).
 comm = MPI.COMM_WORLD
-assert (
-    comm.Get_size() == 4
-), "Please run the example with mpiexec -n 4 python mpi_example.py"
+assert comm.Get_size() == 4, "Please run the example with mpiexec -n 4 python mpi_example.py"
 rank = comm.Get_rank()
 other_ranks = [x for x in range(4) if x != rank]
 print(f"Started rank {rank}, other ranks are {other_ranks}")
@@ -65,9 +61,7 @@
 planet_list, sats_pos_and_v, _ = get_constellation(
     altitude, inclination, nSats, nPlanes, t0, verbose=False
 )
-print(
-    f"Rank {rank} set up its orbit with altitude={altitude}m and inclination={inclination}deg"
-)
+print(f"Rank {rank} set up its orbit with altitude={altitude}m and inclination={inclination}deg")
 
 ############ PASEOS INIT #############
 # We will now initialize the PASEOS instance on each rank
@@ -78,9 +72,7 @@
 local_actor = ActorBuilder.get_actor_scaffold(
     name="Sat_" + str(rank), actor_type=SpacecraftActor, epoch=t0
 )
-ActorBuilder.set_orbit(
-    actor=local_actor, position=pos, velocity=v, epoch=t0, central_body=earth
-)
+ActorBuilder.set_orbit(actor=local_actor, position=pos, velocity=v, epoch=t0, central_body=earth)
 
 paseos_instance = paseos.init_sim(local_actor=local_actor)
 print(f"Rank {rank} set up its PASEOS instance for its local actor {local_actor}")
@@ -97,6 +89,7 @@
 # Let's define the variable to track the actors we see
 total_seen_actors = 0
 
+
 # We will (ab)use PASEOS constraint function to track all the actors
 # we see in an evaluation window (see timestep below).
 # Turn on SHOW_ALL_WINDOWS if you want to see each window
@@ -135,7 +128,6 @@ def constraint_func(verbose=SHOW_ALL_WINDOWS):
 
 # Run until end of simulation
 while t <= simulation_time:
-
     # Advance the simulation state of this rank
     # Note how we pass the "constraint_func" to tell paseos
     # to track windows
@@ -147,9 +139,7 @@ def constraint_func(verbose=SHOW_ALL_WINDOWS):
     sys.stdout.flush()  # update prints to better see parallelism
 
     # Exchange actors between all ranks
-    exchange_actors(
-        comm, paseos_instance, local_actor, other_ranks, rank, verbose=SHOW_ALL_COMMS
-    )
+    exchange_actors(comm, paseos_instance, local_actor, other_ranks, rank, verbose=SHOW_ALL_COMMS)
 
 # Wait until all ranks finished
 print(f"Rank {rank} finished the simulation. Waiting for all to finish.")

examples/MPI_example/mpi_utility_func.py

@@ -48,9 +48,7 @@ def _parse_actor_data(actor_data):
     return actor
 
 
-def exchange_actors(
-    comm, paseos_instance, local_actor, other_ranks, rank, verbose=False
-):
+def exchange_actors(comm, paseos_instance, local_actor, other_ranks, rank, verbose=False):
     """This function exchanges the states of various actors among all MPI ranks.
 
     Args:
@@ -69,9 +67,7 @@ def exchange_actors(
     # Send local actor to other ranks
     for i in other_ranks:
         actor_data = _encode_actor(local_actor)
-        send_requests.append(
-            comm.isend(actor_data, dest=i, tag=int(str(rank) + str(i)))
-        )
+        send_requests.append(comm.isend(actor_data, dest=i, tag=int(str(rank) + str(i))))
 
     # Receive from other ranks
     for i in other_ranks:

examples/Sentinel_2_example_notebook/utils.py

@@ -96,12 +96,8 @@ def get_thresholds(
     alpha = np.logical_and(
         np.where(sentinel_img[:, :, 2] >= alpha_thr[2], 1, 0),
         np.logical_and(
-            np.where(
-                sentinel_img[:, :, 2] / sentinel_img[:, :, 1] >= alpha_thr[0], 1, 0
-            ),
-            np.where(
-                sentinel_img[:, :, 2] / sentinel_img[:, :, 0] >= alpha_thr[1], 1, 0
-            ),
+            np.where(sentinel_img[:, :, 2] / sentinel_img[:, :, 1] >= alpha_thr[0], 1, 0),
+            np.where(sentinel_img[:, :, 2] / sentinel_img[:, :, 0] >= alpha_thr[1], 1, 0),
         ),
     )
     beta = np.logical_and(
@@ -159,9 +155,7 @@ def get_alert_matrix_and_thresholds(
         numpy.array: gamma threshold map.
     """
 
-    alpha, beta, S, gamma = get_thresholds(
-        sentinel_img, alpha_thr, beta_thr, S_thr, gamma_thr
-    )
+    alpha, beta, S, gamma = get_thresholds(sentinel_img, alpha_thr, beta_thr, S_thr, gamma_thr)
     alert_matrix = np.logical_or(np.logical_or(np.logical_or(alpha, beta), gamma), S)
     return alert_matrix, alpha, beta, S, gamma
 

paseos/__init__.py

@@ -21,9 +21,7 @@
 logger.debug("Loaded module.")
 
 
-def init_sim(
-    local_actor: BaseActor, cfg: DotMap = None, starting_epoch: pk.epoch = None
-):
+def init_sim(local_actor: BaseActor, cfg: DotMap = None, starting_epoch: pk.epoch = None):
     """Initializes PASEOS
 
     Args:

paseos/activities/activity_manager.py

@@ -43,9 +43,7 @@ def remove_activity(self, name: str):
             name (str): Name of the activity.
         """
         if name not in self._activities.keys():
-            raise ValueError(
-                "Trying to remove non-existing activity with name: " + name
-            )
+            raise ValueError("Trying to remove non-existing activity with name: " + name)
         else:
             del self._activities[name]
 

paseos/activities/activity_processor.py

@@ -89,9 +89,7 @@ async def _update(self, elapsed_time: float):
         logger.debug(f"Time since last update: {elapsed_time}s")
         logger.trace(f"Applying time multiplier of {self._time_multiplier}")
         elapsed_time *= self._time_multiplier
-        self._paseos_instance.advance_time(
-            elapsed_time, self._power_consumption_in_watt
-        )
+        self._paseos_instance.advance_time(elapsed_time, self._power_consumption_in_watt)
 
     async def _run(self):
         """Main processor loop. Will track time, update paseos and check constraints of the activity."""