fmt: formatting changes

kalpa/config.py

@@ -14,6 +14,7 @@ class MeasurementTypeEnum(Enum):
 	POTENTIAL = "electric-potential"
 	X_ELECTRIC_FIELD = "x-electric-field"
 
+
 class SkipToStage(IntEnum):
 	# shouldn't need this lol
 	STAGE_01 = 0
@@ -30,7 +31,9 @@ class GeneralConfig:
 	dots_json_name: str = "dots.json"
 	indexes_json_name: str = "indexes.json"
 	out_dir_name: str = "out"
-	log_pattern: str = "%(asctime)s | %(process)d | %(levelname)-7s | %(name)s:%(lineno)d | %(message)s"
+	log_pattern: str = (
+		"%(asctime)s | %(process)d | %(levelname)-7s | %(name)s:%(lineno)d | %(message)s"
+	)
 	measurement_type: MeasurementTypeEnum = MeasurementTypeEnum.X_ELECTRIC_FIELD
 	root_directory: pathlib.Path = pathlib.Path.cwd()
 
@@ -64,14 +67,14 @@ class GenerationConfig:
 	num_replicas: int = 3
 
 	# the above three can be overrided with manually specified configurations
-	override_dipole_configs: typing.Optional[typing.Mapping[str, typing.Sequence[tantri.dipoles.types.DipoleTO]]] = None
+	override_dipole_configs: typing.Optional[
+		typing.Mapping[str, typing.Sequence[tantri.dipoles.types.DipoleTO]]
+	] = None
 
 	tantri_configs: typing.Sequence[TantriConfig] = field(
 		default_factory=lambda: [TantriConfig()]
 	)
 
-
-
 	num_bin_time_series: int = 25
 	bin_log_width: float = 0.25
 

kalpa/inference_coalesce/coalescer.py

@@ -93,11 +93,10 @@ class Coalescer:
 				for model_key, val in subdict[str(gen)].items():
 					val["coalesced_prob"] = (
 						float(val["prob"])
-						* float(subdict[str(gen-1)][model_key]["coalesced_prob"])
+						* float(subdict[str(gen - 1)][model_key]["coalesced_prob"])
 						/ generation_weight
 					)
 
-
 	def coalesce_all(self):
 		for actual_key in self.actual_dict.keys():
 			for dot_key in self.actual_dict[actual_key].keys():

kalpa/read_bin_csv.py

@@ -70,7 +70,10 @@ class StDevUsingCostFunction:
 
 		self.use_log_noise = log_noise
 		self.log_actual = numpy.log(self.actual_measurement_array)
-		self.log_denom2 = (numpy.log(self.actual_stdev_array + self.actual_measurement_array) - numpy.log(self.actual_measurement_array))**2
+		self.log_denom2 = (
+			numpy.log(self.actual_stdev_array + self.actual_measurement_array)
+			- numpy.log(self.actual_measurement_array)
+		) ** 2
 		# if self.use_log_noise:
 		# 	_logger.debug("remove these debugs later")
 		# 	_logger.debug(self.actual_measurement_array)
@@ -89,9 +92,11 @@ class StDevUsingCostFunction:
 			)
 
 		if self.use_log_noise:
-			diffs = ((numpy.log(vals) - self.log_actual) **2) / self.log_denom2
+			diffs = ((numpy.log(vals) - self.log_actual) ** 2) / self.log_denom2
 		else:
-			diffs = ((vals - self.actual_measurement_array) ** 2) / self.actual_stdev_array2
+			diffs = (
+				(vals - self.actual_measurement_array) ** 2
+			) / self.actual_stdev_array2
 
 		return numpy.sqrt(diffs.mean(axis=-1))
 

kalpa/stages/__init__.py

@@ -35,11 +35,10 @@ class Runner:
 
 			start = int(self.config.general_config.skip_to_stage)
 			_logger.info(f"Received instruction to start at stage {start + 1}")
-			for i, stage in enumerate(stages[start: 4]):
+			for i, stage in enumerate(stages[start:4]):
 				_logger.info(f"*** Running stage {i + start + 1}")
 				stage.run()
 
-
 		else:
 			# standard run, can keep old
 
@@ -74,7 +73,8 @@ def parse_args():
 	)
 
 	parser.add_argument(
-		"-s", "--skip-to-stage",
+		"-s",
+		"--skip-to-stage",
 		type=int,
 		help="Skip to stage, if provided. 1 means stages 1-4 will run, 4 means only stage 4 will run.",
 		default=None,
@@ -91,7 +91,6 @@ def main():
 		# kalpa.TantriConfig(1234, 50, 0.0005, 10000),
 	]
 
-
 	override_config = {
 		# "test1": [
 		# 	tantri.dipoles.types.DipoleTO(
@@ -102,38 +101,28 @@ def main():
 		# ],
 		"two_dipole_connors_geom": [
 			tantri.dipoles.types.DipoleTO(
-				numpy.array([0, 0, 100]),
-				numpy.array([-2, -2, 5.75]),
-				0.0005
+				numpy.array([0, 0, 100]), numpy.array([-2, -2, 5.75]), 0.0005
 			),
 			tantri.dipoles.types.DipoleTO(
-				numpy.array([0, 0, 100]),
-				numpy.array([6, 2, 5.75]),
-				0.05
-			)
+				numpy.array([0, 0, 100]), numpy.array([6, 2, 5.75]), 0.05
+			),
 		],
 		"two_dipole_connors_geom_omegaswap": [
 			tantri.dipoles.types.DipoleTO(
-				numpy.array([0, 0, 100]),
-				numpy.array([-2, -2, 5.75]),
-				0.05
+				numpy.array([0, 0, 100]), numpy.array([-2, -2, 5.75]), 0.05
 			),
 			tantri.dipoles.types.DipoleTO(
-				numpy.array([0, 0, 100]),
-				numpy.array([6, 2, 5.75]),
-				0.0005
-			)
-		]
+				numpy.array([0, 0, 100]), numpy.array([6, 2, 5.75]), 0.0005
+			),
+		],
 	}
 
 	generation_config = kalpa.GenerationConfig(
 		tantri_configs=tantri_configs,
 		counts=[3, 31],
 		num_replicas=5,
-
 		# let's test this out
 		# override_dipole_configs=override_config,
-
 		orientations=[tantri.dipoles.types.Orientation.Z],
 		num_bin_time_series=25,
 	)
@@ -150,13 +139,12 @@ def main():
 		else:
 			skip = kalpa.config.SkipToStage(args.skip_to_stage - 1)
 	else:
-			skip = None
-
+		skip = None
 
 	general_config = kalpa.GeneralConfig(
 		measurement_type=kalpa.MeasurementTypeEnum.POTENTIAL,
 		out_dir_name=str(root / "out"),
-		skip_to_stage=skip
+		skip_to_stage=skip,
 	)
 
 	# kalpa.GeneralConfig

kalpa/stages/stage01.py

@@ -116,9 +116,7 @@ class Stage01Runner:
 		for tantri_index, tantri_config in enumerate(
 			self.config.generation_config.tantri_configs
 		):
-			output_csv = directory / kalpa.common.tantri_full_output_name(
-				tantri_index
-			)
+			output_csv = directory / kalpa.common.tantri_full_output_name(tantri_index)
 			binned_csv = directory / kalpa.common.tantri_binned_output_name(
 				tantri_index
 			)
@@ -140,7 +138,10 @@ class Stage01Runner:
 	# deliberately bad to get it done.
 	# here we're going to be manually specifying dipoles as we have from our config
 	def generate_override_dipole(
-		self, seed: int, override_name: str, override_dipoles: typing.Sequence[tantri.dipoles.types.DipoleTO]
+		self,
+		seed: int,
+		override_name: str,
+		override_dipoles: typing.Sequence[tantri.dipoles.types.DipoleTO],
 	):
 		"""
 		create a directory, populate it with stuff.
@@ -178,7 +179,7 @@ class Stage01Runner:
 			dipole_out.write(
 				json.dumps(
 					[dip.as_dict() for dip in override_dipoles],
-					cls=tantri.cli.input_files.write_dipoles.NumpyEncoder
+					cls=tantri.cli.input_files.write_dipoles.NumpyEncoder,
 				)
 			)
 
@@ -188,9 +189,7 @@ class Stage01Runner:
 		for tantri_index, tantri_config in enumerate(
 			self.config.generation_config.tantri_configs
 		):
-			output_csv = directory / kalpa.common.tantri_full_output_name(
-				tantri_index
-			)
+			output_csv = directory / kalpa.common.tantri_full_output_name(tantri_index)
 			binned_csv = directory / kalpa.common.tantri_binned_output_name(
 				tantri_index
 			)
@@ -219,12 +218,21 @@ class Stage01Runner:
 						_logger.info(
 							f"Generating for {seed_index=}: [{count=}, {orientation=}, {replica=}"
 						)
-						self.generate_single_subdir(seed_index, count, orientation, replica)
+						self.generate_single_subdir(
+							seed_index, count, orientation, replica
+						)
 						seed_index += 1
 		else:
-			_logger.debug(f"Dipole generation override received: {self.config.generation_config.override_dipole_configs}")
-			for override_name, override_dipoles in self.config.generation_config.override_dipole_configs.items():
-				self.generate_override_dipole(seed_index, override_name, override_dipoles)
+			_logger.debug(
+				f"Dipole generation override received: {self.config.generation_config.override_dipole_configs}"
+			)
+			for (
+				override_name,
+				override_dipoles,
+			) in self.config.generation_config.override_dipole_configs.items():
+				self.generate_override_dipole(
+					seed_index, override_name, override_dipoles
+				)
 
 
 def parse_args():

kalpa/stages/stage02.py

@@ -216,7 +216,10 @@ class Stage02Runner:
 		_logger.info(f"{deepdog_config=}")
 
 		stdev_cost_function_filters = [
-			b.stdev_cost_function_filter(dot_names, cost, self.config.deepdog_config.use_log_noise) for b in binned_datas
+			b.stdev_cost_function_filter(
+				dot_names, cost, self.config.deepdog_config.use_log_noise
+			)
+			for b in binned_datas
 		]
 
 		_logger.debug(f"{stdev_cost_function_filters=}")

kalpa/stages/stage04.py

@@ -145,7 +145,6 @@ class Stage04Runner:
 				out_list.append(row)
 			return out_list
 
-
 	def run(self):
 		megamerged_path = (
 			self.config.get_out_dir_path() / self.config.general_config.mega_merged_name
@@ -156,12 +155,13 @@ class Stage04Runner:
 			writer = csv.DictWriter(outfile, MERGED_OUT_FIELDNAMES)
 			writer.writeheader()
 
-
 			if self.config.generation_config.override_dipole_configs is None:
 
 				for count in self.config.generation_config.counts:
 					for orientation in self.config.generation_config.orientations:
-						for replica in range(self.config.generation_config.num_replicas):
+						for replica in range(
+							self.config.generation_config.num_replicas
+						):
 							_logger.info(f"Reading {count=} {orientation=} {replica=}")
 							rows = self.read_merged_coalesced_csv(
 								orientation, count, replica
@@ -170,16 +170,17 @@ class Stage04Runner:
 								writer.writerow(row)
 
 			else:
-				_logger.debug(f"We had overridden dipole config, using override {self.config.generation_config.override_dipole_configs}")
-				for override_name in self.config.generation_config.override_dipole_configs.keys():
+				_logger.debug(
+					f"We had overridden dipole config, using override {self.config.generation_config.override_dipole_configs}"
+				)
+				for (
+					override_name
+				) in self.config.generation_config.override_dipole_configs.keys():
 					_logger.info(f"Working for subdir {override_name}")
-					rows = self.read_merged_coalesced_csv_override(
-						override_name
-					)
+					rows = self.read_merged_coalesced_csv_override(override_name)
 					for row in rows:
 						writer.writerow(row)
 
-
 		# merge with inference
 
 		if self.config.generation_config.override_dipole_configs is None:
@@ -204,7 +205,9 @@ class Stage04Runner:
 					/ self.config.general_config.mega_merged_inferenced_name
 				)
 				with inferenced_path.open(mode="w", newline="") as outfile:
-					writer = csv.DictWriter(outfile, fieldnames=INFERENCED_OUT_FIELDNAMES)
+					writer = csv.DictWriter(
+						outfile, fieldnames=INFERENCED_OUT_FIELDNAMES
+					)
 					writer.writeheader()
 					for val in coalesced.values():
 						for dots in val.values():
@@ -212,7 +215,10 @@ class Stage04Runner:
 								for row in generation.values():
 									writer.writerow(row)
 		else:
-			_logger.info("skipping inference metamerge, overridden dipole config specified")
+			_logger.info(
+				"skipping inference metamerge, overridden dipole config specified"
+			)
+
 
 def parse_args():