Correct many ruff issues

pyproject.toml

@@ -110,5 +110,9 @@ extend-exclude = ["examples"]
 ignore = [
     "RET504",  # Subjective but, naming the returned value often seems to help readability.
     "SIM108",  # Subjective but, ternary operators are often too confusing.
+    # We don't expect use cases of the frame to need to worry about security issues.
+    "S608",
+    "S301",
+    "S311",
 ]
 isort.known-first-party = ["qusi", "ramjet"]

src/ramjet/logging/wandb_logger.py

@@ -4,13 +4,13 @@
 from __future__ import annotations
 
 import math
+import multiprocessing
 import queue
 from abc import ABC, abstractmethod
 
 import plotly
 import plotly.graph_objects as go
 from plotly.subplots import make_subplots
-import multiprocessing
 
 import wandb
 from ramjet.photometric_database.light_curve import LightCurve

src/ramjet/photometric_database/derived/tess_two_minute_cadence_light_curve_collection.py

@@ -1,21 +1,30 @@
 """
 Code for a light curve collection of the TESS two minute cadence data.
 """
-from pathlib import Path
-from typing import Union
+from __future__ import annotations
 
-import numpy as np
-from peewee import Select
+from pathlib import Path
+from typing import TYPE_CHECKING
 
-from ramjet.data_interface.metadatabase import MetadatabaseModel
-from ramjet.data_interface.tess_data_interface import TessDataInterface, TessFluxType
+from ramjet.data_interface.tess_data_interface import (
+    TessDataInterface,
+    TessFluxType,
+    download_two_minute_cadence_light_curves,
+    load_fluxes_and_times_from_fits_file,
+)
 from ramjet.data_interface.tess_target_metadata_manager import TessTargetMetadata
 from ramjet.data_interface.tess_two_minute_cadence_light_curve_metadata_manager import (
     TessTwoMinuteCadenceLightCurveMetadata,
     TessTwoMinuteCadenceLightCurveMetadataManger,
 )
 from ramjet.photometric_database.sql_metadata_light_curve_collection import SqlMetadataLightCurveCollection
 
+if TYPE_CHECKING:
+    import numpy as np
+    from peewee import Select
+
+    from ramjet.data_interface.metadatabase import MetadatabaseModel
+
 
 class TessTwoMinuteCadenceLightCurveCollection(SqlMetadataLightCurveCollection):
     """
@@ -24,11 +33,11 @@ class TessTwoMinuteCadenceLightCurveCollection(SqlMetadataLightCurveCollection):
     tess_data_interface = TessDataInterface()
     tess_two_minute_cadence_light_curve_metadata_manger = TessTwoMinuteCadenceLightCurveMetadataManger()
 
-    def __init__(self, dataset_splits: Union[list[int], None] = None, flux_type: TessFluxType = TessFluxType.PDCSAP):
+    def __init__(self, dataset_splits: list[int] | None = None, flux_type: TessFluxType = TessFluxType.PDCSAP):
         super().__init__()
         self.data_directory: Path = Path('data/tess_two_minute_cadence_light_curves')
         self.label = 0
-        self.dataset_splits: Union[list[int], None] = dataset_splits
+        self.dataset_splits: list[int] | None = dataset_splits
         self.flux_type: TessFluxType = flux_type
 
     def get_sql_query(self) -> Select:

src/ramjet/photometric_database/derived/tess_two_minute_cadence_transit_light_curve_collections.py

@@ -1,9 +1,9 @@
 """
 Code representing the collection of TESS two minute cadence light curves containing transits.
 """
-from typing import Union
+from __future__ import annotations
 
-from peewee import Select
+from typing import TYPE_CHECKING
 
 from ramjet.data_interface.tess_transit_metadata_manager import Disposition, TessTransitMetadata
 from ramjet.data_interface.tess_two_minute_cadence_light_curve_metadata_manager import (
@@ -13,13 +13,16 @@
     TessTwoMinuteCadenceTargetDatasetSplitLightCurveCollection,
 )
 
+if TYPE_CHECKING:
+    from peewee import Select
+
 
 class TessTwoMinuteCadenceConfirmedTransitLightCurveCollection(
     TessTwoMinuteCadenceTargetDatasetSplitLightCurveCollection):
     """
     A class representing the collection of TESS two minute cadence light curves containing transits.
     """
-    def __init__(self, dataset_splits: Union[list[int], None] = None):
+    def __init__(self, dataset_splits: list[int] | None = None):
         super().__init__(dataset_splits=dataset_splits)
         self.label = 1
 
@@ -41,7 +44,7 @@ class TessTwoMinuteCadenceConfirmedAndCandidateTransitLightCurveCollection(
     """
     A class representing the collection of TESS two minute cadence light curves containing transits.
     """
-    def __init__(self, dataset_splits: Union[list[int], None] = None):
+    def __init__(self, dataset_splits: list[int] | None = None):
         super().__init__(dataset_splits=dataset_splits)
         self.label = 1
 
@@ -63,7 +66,7 @@ class TessTwoMinuteCadenceNonTransitLightCurveCollection(TessTwoMinuteCadenceTar
     """
     A class representing the collection of TESS two minute cadence light curves containing transits.
     """
-    def __init__(self, dataset_splits: Union[list[int], None] = None):
+    def __init__(self, dataset_splits: list[int] | None = None):
         super().__init__(dataset_splits=dataset_splits)
         self.label = 0
 

src/ramjet/photometric_database/derived/toy_database.py

@@ -27,6 +27,7 @@ def __init__(self):
             ToySineWaveLightCurveCollection(),
         ]
 
+
 class ToyRamjetDatabaseWithAuxiliary(StandardAndInjectedLightCurveDatabase):
     def __init__(self):
         super().__init__()
@@ -36,8 +37,10 @@ def __init__(self):
         self.number_of_auxiliary_values = 2
         flat_collection = ToyFlatLightCurveCollection()
         sine_wave_collection = ToySineWaveLightCurveCollection()
-        flat_collection.load_auxiliary_information_for_path = lambda path: np.array([0, 0], dtype=np.float32)
-        sine_wave_collection.load_auxiliary_information_for_path = lambda path: np.array([1, 1], dtype=np.float32)
+        flat_collection.load_auxiliary_information_for_path = (
+            lambda path: np.array([0, 0], dtype=np.float32))  # noqa ARG002
+        sine_wave_collection.load_auxiliary_information_for_path = (
+            lambda path: np.array([1, 1], dtype=np.float32))  # noqa ARG002
         self.training_standard_light_curve_collections = [
             flat_collection,
             sine_wave_collection,

src/ramjet/photometric_database/derived/toy_light_curve_collection.py

@@ -1,12 +1,16 @@
-from collections.abc import Iterable
+from __future__ import annotations
+
 from pathlib import Path
-from typing import Union
+from typing import TYPE_CHECKING
 
 import numpy as np
 
 from ramjet.photometric_database.light_curve import LightCurve
 from ramjet.photometric_database.light_curve_collection import LightCurveCollection
 
+if TYPE_CHECKING:
+    from collections.abc import Iterable
+
 
 class ToyLightCurveCollection(LightCurveCollection):
     """
@@ -26,7 +30,7 @@ def __init__(self):
         super().__init__()
         self.label = 0
 
-    def load_times_and_fluxes_from_path(self, path: Path) -> (np.ndarray, np.ndarray):
+    def load_times_and_fluxes_from_path(self, path: Path) -> (np.ndarray, np.ndarray):  # noqa ARG002
         light_curve = ToyLightCurve.flat()
         return light_curve.times, light_curve.fluxes
 
@@ -43,7 +47,7 @@ def load_times_and_fluxes_from_path(self, path: Path) -> (np.ndarray, np.ndarray
         light_curve = ToyLightCurve.flat(float(path.name))
         return light_curve.times, light_curve.fluxes
 
-    def load_label_from_path(self, path: Path) -> Union[float, np.ndarray]:
+    def load_label_from_path(self, path: Path) -> float | np.ndarray:
         label = float(path.name)
         return label
 
@@ -53,7 +57,7 @@ def __init__(self):
         super().__init__()
         self.label = 1
 
-    def load_times_and_fluxes_from_path(self, path: Path) -> (np.ndarray, np.ndarray):
+    def load_times_and_fluxes_from_path(self, path: Path) -> (np.ndarray, np.ndarray):  # noqa ARG002
         light_curve = ToyLightCurve.sine_wave()
         return light_curve.times, light_curve.fluxes
 

src/ramjet/photometric_database/light_curve.py

@@ -3,19 +3,18 @@
 """
 from __future__ import annotations
 
-from abc import ABC
-
 import lightkurve.lightcurve
 import numpy as np
 import pandas as pd
 from lightkurve.periodogram import LombScarglePeriodogram
 
 
-class LightCurve(ABC):
+class LightCurve:
     """
     A class to represent a light curve. A light curve is a collection of data which may includes times, fluxes,
     flux errors, and related values.
     """
+
     def __init__(self):
         self.data_frame: pd.DataFrame = pd.DataFrame()
         self.flux_column_names: list[str] = []
@@ -59,7 +58,7 @@ def times(self, value: np.ndarray):
     def folded_times(self):
         if self.folded_times_column_name not in self.data_frame.columns:
             error_message = 'Light curve has not been folded.'
-            raise MissingFoldedTimes(error_message)
+            raise MissingFoldedTimesError(error_message)
         return self.data_frame[self.folded_times_column_name].values
 
     @folded_times.setter
@@ -114,7 +113,11 @@ def to_lightkurve(self) -> lightkurve.lightcurve.LightCurve:
     def get_variability_phase_folding_parameters(
             self, minimum_period: float | None = None, maximum_period: float | None = None
     ) -> (float, float, float, float, float):
-        fold_period, fold_epoch, time_bin_size, minimum_bin_phase, maximum_bin_phase, inlier_lightkurve_light_curve, periodogram, folded_lightkurve_light_curve = self.get_variability_phase_folding_parameters_and_folding_lightkurve_light_curves(minimum_period=minimum_period, maximum_period=maximum_period)
+        (
+            fold_period, fold_epoch, time_bin_size, minimum_bin_phase, maximum_bin_phase, inlier_lightkurve_light_curve,
+            periodogram, folded_lightkurve_light_curve
+        ) = self.get_variability_phase_folding_parameters_and_folding_lightkurve_light_curves(
+            minimum_period=minimum_period, maximum_period=maximum_period)
         self._variability_period = fold_period
         self._variability_period_epoch = fold_epoch
         return fold_period, fold_epoch, time_bin_size, minimum_bin_phase, maximum_bin_phase
@@ -138,11 +141,14 @@ def get_variability_phase_folding_parameters_and_folding_lightkurve_light_curves
         minimum_bin_phase = binned_folded_lightkurve_light_curve.phase.value[minimum_bin_index]
         maximum_bin_phase = binned_folded_lightkurve_light_curve.phase.value[maximum_bin_index]
         fold_epoch = inlier_lightkurve_light_curve.time.value[0]
-        return fold_period, fold_epoch, time_bin_size, minimum_bin_phase, maximum_bin_phase, inlier_lightkurve_light_curve, periodogram, folded_lightkurve_light_curve
+        return (
+            fold_period, fold_epoch, time_bin_size, minimum_bin_phase, maximum_bin_phase, inlier_lightkurve_light_curve,
+            periodogram, folded_lightkurve_light_curve
+        )
 
     def fold(self, period: float, epoch: float) -> None:
         self.folded_times = (self.times - epoch) % period
 
 
-class MissingFoldedTimes(Exception):
+class MissingFoldedTimesError(Exception):
     pass

src/ramjet/photometric_database/light_curve_collection.py

@@ -1,12 +1,16 @@
 """
 Code for representing a collection of light curves.
 """
-from collections.abc import Iterable
+from __future__ import annotations
+
 from pathlib import Path
-from typing import Union
+from typing import TYPE_CHECKING
 
 import numpy as np
 
+if TYPE_CHECKING:
+    from collections.abc import Iterable
+
 
 class LightCurveCollectionMethodNotImplementedError(RuntimeError):
     """
@@ -25,8 +29,8 @@ class LightCurveCollection:
     :ivar paths: The default list of paths to be used if the `get_paths` method is not overridden.
     """
     def __init__(self):
-        self.label: Union[float, list[float], np.ndarray, None] = None
-        self.paths: Union[list[Path], None] = None
+        self.label: float | list[float] | np.ndarray | None = None
+        self.paths: list[Path] | None = None
 
     def get_paths(self) -> Iterable[Path]:
         """
@@ -36,7 +40,7 @@ def get_paths(self) -> Iterable[Path]:
         """
         return self.paths
 
-    def load_times_and_fluxes_from_path(self, path: Path) -> (np.ndarray, np.ndarray):
+    def load_times_and_fluxes_from_path(self, path: Path) -> (np.ndarray, np.ndarray):  # noqa ARG002
         """
         Loads the times and fluxes from a given light curve path.
 
@@ -45,7 +49,7 @@ def load_times_and_fluxes_from_path(self, path: Path) -> (np.ndarray, np.ndarray
         """
         raise LightCurveCollectionMethodNotImplementedError
 
-    def load_times_and_magnifications_from_path(self, path: Path) -> (np.ndarray, np.ndarray):
+    def load_times_and_magnifications_from_path(self, path: Path) -> (np.ndarray, np.ndarray):  # noqa ARG002
         """
         Loads the times and magnifications from a given path as an injectable signal.
 
@@ -69,7 +73,7 @@ def generate_synthetic_signal_from_real_data(fluxes: np.ndarray, times: np.ndarr
         relative_times = times - np.min(times)
         return normalized_fluxes, relative_times
 
-    def load_label_from_path(self, path: Path) -> Union[float, np.ndarray]:
+    def load_label_from_path(self, path: Path) -> float | np.ndarray:  # noqa ARG002
         """
         Loads the label of an example from a corresponding path.
 
@@ -101,7 +105,7 @@ def shuffle_and_split_paths(paths: list[Path], dataset_splits: list[int], number
         return dataset_split_paths
 
     def load_times_fluxes_and_flux_errors_from_path(self, path: Path
-                                                    ) -> (np.ndarray, np.ndarray, Union[np.ndarray, None]):
+                                                    ) -> (np.ndarray, np.ndarray, np.ndarray | None):
         """
         Loads the times, fluxes, and flux errors of a light curve from a path to the data.
         Unless overridden, defaults to using the method to load only the times and fluxes, and returns None for errors.
@@ -114,7 +118,7 @@ def load_times_fluxes_and_flux_errors_from_path(self, path: Path
         return times, fluxes, flux_errors
 
     def load_times_magnifications_and_magnification_errors_from_path(
-            self, path: Path) -> (np.ndarray, np.ndarray, Union[np.ndarray, None]):
+            self, path: Path) -> (np.ndarray, np.ndarray, np.ndarray | None):
         """
         Loads the times, magnifications, and magnification_errors of a light curve from a path to the data.
         Unless overridden, defaults to using the method to load only the times and magnifications,
@@ -127,7 +131,7 @@ def load_times_magnifications_and_magnification_errors_from_path(
         flux_errors = None
         return times, fluxes, flux_errors
 
-    def load_auxiliary_information_for_path(self, path: Path) -> np.ndarray:
+    def load_auxiliary_information_for_path(self, path: Path) -> np.ndarray:  # noqa ARG002
         """
         Loads auxiliary information for the given path.