pre-commit fix

imap_processing/cdf/utils.py

@@ -57,7 +57,9 @@ def met_to_j2000ns(
     time_array = (np.asarray(met, dtype=float) * 1e9).astype(np.int64)
     # Calculate the time difference between our reference system and J2000
     if isinstance(reference_epoch, np.datetime64):
-        place_holder: np.timedelta64 = (reference_epoch - J2000_EPOCH).astype("timedelta64[ns]")
+        place_holder: np.timedelta64 = (reference_epoch - J2000_EPOCH).astype(
+            "timedelta64[ns]"
+        )
         j2000_offset: np.int64 = place_holder.astype(np.int64)
         return j2000_offset + time_array
 

imap_processing/codice/codice_l1a.py

@@ -412,7 +412,9 @@ def process_codice_l1a(file_path: Path, data_version: str) -> xr.Dataset:
             apid = CODICEAPID.COD_HI_SECT_SPECIES_COUNTS
             table_id, plan_id, plan_step, view_id = (1, 0, 0, 6)
 
-        met0: np.timedelta64 = (np.datetime64("2024-04-29T00:00") - IMAP_EPOCH).astype("timedelta64[s]")
+        met0: np.timedelta64 = (np.datetime64("2024-04-29T00:00") - IMAP_EPOCH).astype(
+            "timedelta64[s]"
+        )
         met0 = met0.astype(np.int64)
         met = [met0, met0 + 1]  # Using this to match the other data products
         science_values = ""  # Currently don't have simulated data for this

imap_processing/glows/l1b/glows_l1b_data.py

@@ -4,8 +4,8 @@
 import dataclasses
 import json
 from dataclasses import InitVar, dataclass, field
-from typing import Optional
 from pathlib import Path
+from typing import Optional
 
 import numpy as np
 

imap_processing/lo/l0/data_classes/science_direct_events.py

@@ -179,8 +179,8 @@ def _decompress_data(self) -> None:
 
             # Case decoder indicates which parts of the data
             # are transmitted for each case.
-            case_decoder = CASE_DECODER[(case_number, self.MODE[de_idx])] #type: ignore[index]
-            #Todo Mypy Error: Invalid index type "tuple[int, ndarray[Any, Any]]" for
+            case_decoder = CASE_DECODER[(case_number, self.MODE[de_idx])]  # type: ignore[index]
+            # Todo Mypy Error: Invalid index type "tuple[int, ndarray[Any, Any]]" for
             # "dict[tuple[int, int], TOFFields]"; expected type "tuple[int, int]"
 
             # Check the case decoder to see if the TOF field was

imap_processing/mag/l0/mag_l0_data.py

@@ -109,9 +109,9 @@ def __post_init__(self) -> None:
         # Convert string output from space_packet_parser to numpy array of
         # big-endian bytes
         self.VECTORS = np.frombuffer(
-            int(self.VECTORS, 2).to_bytes(len(self.VECTORS) // 8, "big"), #type: ignore[arg-type]
-            #MYPY Error: Argument 1 to "int" has incompatible type
-            #"Union[ndarray[Any, Any], str]"; expected "Union[str, bytes, bytearray]"
+            int(self.VECTORS, 2).to_bytes(len(self.VECTORS) // 8, "big"),  # type: ignore[arg-type]
+            # MYPY Error: Argument 1 to "int" has incompatible type
+            # "Union[ndarray[Any, Any], str]"; expected "Union[str, bytes, bytearray]"
             dtype=np.dtype(">b"),
         )
 

imap_processing/swapi/l1/swapi_l1.py

@@ -12,7 +12,7 @@
 from imap_processing.utils import packet_file_to_datasets
 
 
-def filter_good_data(full_sweep_sci: xr.Dataset) -> npt.NDArray:
+def filter_good_data(full_sweep_sci: xr.Dataset) -> np.ndarray:
     """
     Filter out bad data sweep indices.
 
@@ -30,7 +30,7 @@ def filter_good_data(full_sweep_sci: xr.Dataset) -> npt.NDArray:
 
     Returns
     -------
-    good_data_indices : np.ndarray
+    good_data_indices : numpy.ndarray
         Good data sweep indices.
     """
     # PLAN_ID for current sweep should all be one value and
@@ -71,7 +71,7 @@ def filter_good_data(full_sweep_sci: xr.Dataset) -> npt.NDArray:
 
 def decompress_count(
     count_data: np.ndarray, compression_flag: np.ndarray
-) -> npt.NDArray:
+) -> np.ndarray:
     """
     Will decompress counts based on compression indicators.
 
@@ -121,7 +121,7 @@ def decompress_count(
     return new_count
 
 
-def find_sweep_starts(packets: xr.Dataset) -> npt.NDArray:
+def find_sweep_starts(packets: xr.Dataset) -> np.ndarray:
     """
     Find index of where new cycle started.
 

imap_processing/swe/l1a/swe_science.py

@@ -112,7 +112,7 @@ def swe_science(decom_data: list, data_version: str) -> xr.Dataset:
     science_array = []
     raw_science_array = []
 
-    metadata_arrays: np.ndarray =np.array(collections.defaultdict(list))
+    metadata_arrays: np.ndarray = np.array(collections.defaultdict(list))
 
     # We know we can only have 8 bit numbers input, so iterate over all
     # possibilities once up front
@@ -142,7 +142,11 @@ def swe_science(decom_data: list, data_version: str) -> xr.Dataset:
         # Save data as np.int64 to be complaint with ISTP' FILLVAL
         science_array.append(uncompress_data.astype(np.int64))
         raw_science_array.append(raw_counts.astype(np.int64))
-        metadata_arrays = np.array(add_metadata_to_array(data_packet, dict(enumerate(metadata_arrays.flatten(), 1))))
+        metadata_arrays = np.array(
+            add_metadata_to_array(
+                data_packet, dict(enumerate(metadata_arrays.flatten(), 1))
+            )
+        )
 
     # Load CDF attrs
     cdf_attrs = ImapCdfAttributes()

imap_processing/swe/utils/swe_utils.py

@@ -1,7 +1,7 @@
 """Various utility classes and functions to support SWE processing."""
 
 from enum import IntEnum
-import numpy as np
+
 import space_packet_parser
 
 

tools/spice/spice_examples.py

@@ -8,7 +8,6 @@
 
 import logging
 
-import numpy as np
 import numpy.typing as npt
 import spiceypy as spice