Mypy Update (#731)

* set up

* codice update

* mag update

* swapi update

* fix for failed build the docs

* build the docs try

* attempt with fully expanded

* trying with numpy.array

* using numpy.typing.ArrayLike

* sphinx update

* sphinx update

* adding sutodoc

* it didnt work

* change to numpy.ndarray

* ultra update

* another try at build the docs

* putting docs class type in

* giving a return object name

* glows update

* idex update

* lo update

* swe update

* utils update

* cdf update

* tools update

* sew fix

* swe fixes

* pre-commit fix

* pre-commit will pass but docs will not

* hopefully the test shoyld work

* fixing test failures

* undoing all swe changes

* undoing all swe changes

* undoing all swe changes

* undoing all swe changes

* undoing all swe changes

* docs change

* trying to get build the docs to work

* trying to get build the docs to work

* test

* test

* test

* test

* test

* mypy changes, hopefully wont break docs

* mypy passes

* test for docs to work

* changes for greg

* changes from greg

* reformat change

* changes from Matthew

.pre-commit-config.yaml

@@ -41,9 +41,5 @@ repos:
     rev: 'v1.10.0'
     hooks:
       - id: mypy
-        pass_filenames: false
-        args: [ ., --strict, --explicit-package-bases,
-                  --disable-error-code, import-untyped,
-                  --disable-error-code, import-not-found,
-                  --disable-error-code, no-untyped-call,
-                  --disable-error-code, type-arg ]
+        exclude: .*(tests|docs).*
+        additional_dependencies: [ numpy==1.26.4 ]

docs/source/conf.py

@@ -113,6 +113,9 @@
     (r"py:.*", r".*InitVar*"),
     (r"py:.*", r".*.glows.utils.constants.TimeTuple.*"),
     (r"py:.*", r".*glows.utils.constants.DirectEvent.*"),
+    (r"py:.*", r".*numpy.int.*"),
+    (r"py:.*", r".*np.ndarray.*"),
+    (r"py:.*", r".*numpy._typing._array_like._ScalarType_co.*"),
 ]
 
 # Ignore the inherited members from the <instrument>APID IntEnum class

imap_processing/cdf/utils.py

@@ -3,7 +3,6 @@
 import logging
 import re
 from pathlib import Path
-from typing import Optional
 
 import imap_data_access
 import numpy as np
@@ -25,8 +24,8 @@
 
 def met_to_j2000ns(
     met: np.typing.ArrayLike,
-    reference_epoch: Optional[np.datetime64] = IMAP_EPOCH,
-) -> np.typing.ArrayLike:
+    reference_epoch: np.datetime64 = IMAP_EPOCH,
+) -> np.typing.NDArray[np.int64]:
     """
     Convert mission elapsed time (MET) to nanoseconds from J2000.
 
@@ -56,10 +55,10 @@ def met_to_j2000ns(
     #       to 32bit and overflow due to the nanosecond multiplication
     time_array = (np.asarray(met, dtype=float) * 1e9).astype(np.int64)
     # Calculate the time difference between our reference system and J2000
-    j2000_offset = (
-        (reference_epoch - J2000_EPOCH).astype("timedelta64[ns]").astype(np.int64)
-    )
-    return j2000_offset + time_array
+    j2000_offset: np.typing.NDArray[np.datetime64] = (
+        reference_epoch - J2000_EPOCH
+    ).astype("datetime64[ns]")
+    return j2000_offset.astype(np.int64) + time_array
 
 
 def load_cdf(

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.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

@@ -5,6 +5,7 @@
 import json
 from dataclasses import InitVar, dataclass, field
 from pathlib import Path
+from typing import Optional
 
 import numpy as np
 
@@ -250,11 +251,11 @@ class DirectEventL1B:
     # l1a_file_name: str # TODO: Add once L1A questions are answered
     # ancillary_data_files: np.ndarray # TODO: Add once L1A questions are answered
     # The following variables are created from the InitVar data
-    de_flags: np.ndarray = field(init=False, default=None)
+    de_flags: Optional[np.ndarray] = field(init=False, default=None)
     # TODO: First two values of DE are sec/subsec
-    direct_event_glows_times: np.ndarray = field(init=False, default=None)
+    direct_event_glows_times: Optional[np.ndarray] = field(init=False, default=None)
     # 3rd value is pulse length
-    direct_event_pulse_lengths: np.ndarray = field(init=False, default=None)
+    direct_event_pulse_lengths: Optional[np.ndarray] = field(init=False, default=None)
     # TODO: where does the multi-event flag go?
 
     def __post_init__(

imap_processing/idex/l1/idex_l1.py

@@ -9,6 +9,7 @@
 from enum import IntEnum
 
 import numpy as np
+import numpy.typing as npt
 import space_packet_parser
 import xarray as xr
 
@@ -421,7 +422,7 @@ def _parse_low_sample_waveform(self, waveform_raw: str) -> list[int]:
             ]
         return ints
 
-    def _calc_low_sample_resolution(self, num_samples: int) -> np.ndarray:
+    def _calc_low_sample_resolution(self, num_samples: int) -> npt.NDArray:
         """
         Calculate the resolution of the low samples.
 
@@ -447,7 +448,7 @@ def _calc_low_sample_resolution(self, num_samples: int) -> np.ndarray:
         )
         return time_low_sr_data
 
-    def _calc_high_sample_resolution(self, num_samples: int) -> np.ndarray:
+    def _calc_high_sample_resolution(self, num_samples: int) -> npt.NDArray:
         """
         Calculate the resolution of high samples.
 

imap_processing/lo/l0/data_classes/science_counts.py

@@ -3,6 +3,7 @@
 from dataclasses import dataclass
 
 import numpy as np
+import numpy.typing as npt
 import space_packet_parser
 
 from imap_processing.ccsds.ccsds_data import CcsdsData
@@ -277,7 +278,7 @@ def _parse_section(
         binary_string: BinaryString,
         decompression: Decompress,
         data_shape: tuple[int, int],
-    ) -> np.array:
+    ) -> npt.NDArray:
         """
         Parse a single section of data in the science counts data binary.
 
@@ -322,7 +323,7 @@ def _extract_binary(
         section_length: int,
         bit_length: int,
         decompression: Decompress,
-    ) -> np.ndarray:
+    ) -> npt.NDArray:
         """
         Extract and decompress science count binary data section.
 

imap_processing/lo/l0/data_classes/science_direct_events.py

@@ -179,7 +179,9 @@ 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])]
+            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
             # transmitted for this case. Then grab the bits from

imap_processing/lo/l0/data_classes/star_sensor.py

@@ -54,7 +54,7 @@ class StarSensor(LoBase):
     SHCOARSE: int
     COUNT: int
     DATA_COMPRESSED: str
-    DATA: np.array
+    DATA: np.ndarray
 
     # TODO: Because test data does not currently exist, the init function contents
     # must be commented out for the unit tests to run properly

imap_processing/mag/l0/mag_l0_data.py

@@ -109,7 +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"),
+            int(self.VECTORS, 2).to_bytes(len(self.VECTORS) // 8, "big"),  # type: ignore[arg-type]
+            # TODO Check 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/mag/l1a/mag_l1a_data.py

@@ -6,6 +6,7 @@
 from math import floor
 
 import numpy as np
+import numpy.typing as npt
 
 from imap_processing.cdf.utils import J2000_EPOCH, met_to_j2000ns
 
@@ -190,7 +191,7 @@ class MagL1a:
     is_mago: bool
     is_active: int
     shcoarse: int
-    vectors: np.array
+    vectors: np.ndarray
     starting_packet: InitVar[MagL1aPacketProperties]
     packet_definitions: dict[np.datetime64, MagL1aPacketProperties] = field(init=False)
     most_recent_sequence: int = field(init=False)
@@ -216,14 +217,14 @@ def __post_init__(self, starting_packet: MagL1aPacketProperties) -> None:
         self.most_recent_sequence = starting_packet.src_seq_ctr
 
     def append_vectors(
-        self, additional_vectors: np.array, packet_properties: MagL1aPacketProperties
+        self, additional_vectors: np.ndarray, packet_properties: MagL1aPacketProperties
     ) -> None:
         """
         Append additional vectors to the current vectors array.
 
         Parameters
         ----------
-        additional_vectors : numpy.array
+        additional_vectors : numpy.ndarray
             New vectors to append.
         packet_properties : MagL1aPacketProperties
             Additional vector definition to add to the l0_packets dictionary.
@@ -244,7 +245,7 @@ def append_vectors(
     @staticmethod
     def calculate_vector_time(
         vectors: np.ndarray, vectors_per_sec: int, start_time: TimeTuple
-    ) -> np.array:
+    ) -> npt.NDArray:
         """
         Add timestamps to the vector list, turning the shape from (n, 4) to (n, 5).
 

imap_processing/swapi/l1/swapi_l1.py

@@ -3,6 +3,7 @@
 import copy
 
 import numpy as np
+import numpy.typing as npt
 import xarray as xr
 
 from imap_processing import imap_module_directory
@@ -11,7 +12,7 @@
 from imap_processing.utils import packet_file_to_datasets
 
 
-def filter_good_data(full_sweep_sci: xr.Dataset) -> np.ndarray:
+def filter_good_data(full_sweep_sci: xr.Dataset) -> npt.NDArray:
     """
     Filter out bad data sweep indices.
 
@@ -29,7 +30,7 @@ def filter_good_data(full_sweep_sci: xr.Dataset) -> np.ndarray:
 
     Returns
     -------
-    numpy.ndarray
+    good_data_indices : numpy.ndarray
         Good data sweep indices.
     """
     # PLAN_ID for current sweep should all be one value and
@@ -70,7 +71,7 @@ def filter_good_data(full_sweep_sci: xr.Dataset) -> np.ndarray:
 
 def decompress_count(
     count_data: np.ndarray, compression_flag: np.ndarray
-) -> np.ndarray:
+) -> npt.NDArray:
     """
     Will decompress counts based on compression indicators.
 
@@ -99,7 +100,7 @@ def decompress_count(
 
     Returns
     -------
-    numpy.ndarray
+    new_count : numpy.ndarray
         Array with decompressed counts.
     """
     # Decompress counts based on compression indicators
@@ -120,7 +121,7 @@ def decompress_count(
     return new_count
 
 
-def find_sweep_starts(packets: xr.Dataset) -> np.ndarray:
+def find_sweep_starts(packets: xr.Dataset) -> npt.NDArray:
     """
     Find index of where new cycle started.
 
@@ -138,7 +139,7 @@ def find_sweep_starts(packets: xr.Dataset) -> np.ndarray:
 
     Returns
     -------
-    numpy.ndarray
+    indices_start : numpy.ndarray
         Array of indices of start cycle.
     """
     if packets["epoch"].size < 12:
@@ -175,7 +176,7 @@ def find_sweep_starts(packets: xr.Dataset) -> np.ndarray:
     return np.where(valid)[0]
 
 
-def get_indices_of_full_sweep(packets: xr.Dataset) -> np.ndarray:
+def get_indices_of_full_sweep(packets: xr.Dataset) -> npt.NDArray:
     """
     Get indices of full cycles.
 
@@ -195,7 +196,7 @@ def get_indices_of_full_sweep(packets: xr.Dataset) -> np.ndarray:
 
     Returns
     -------
-    numpy.ndarray
+    full_cycle_indices : numpy.ndarray
         1D array with indices of full cycle data.
     """
     indices_of_start = find_sweep_starts(packets)

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.array = collections.defaultdict(list)
+    metadata_arrays: dict[list] = collections.defaultdict(list)
 
     # We know we can only have 8 bit numbers input, so iterate over all
     # possibilities once up front
@@ -133,7 +133,7 @@ def swe_science(decom_data: list, data_version: str) -> xr.Dataset:
         # where 1260 = 180 x 7 CEMs
         # Take the "raw_counts" indices/counts mapping from
         # decompression_table and then reshape the return
-        uncompress_data = np.take(decompression_table, raw_counts).reshape(180, 7)
+        uncompress_data = np.take(decompression_table, raw_counts).reshape(180, 7)  # type: ignore[attr-defined]
         # Save raw counts data as well
         raw_counts = raw_counts.reshape(180, 7)
 

imap_processing/swe/l1b/swe_l1b_science.py

@@ -4,6 +4,7 @@
 from typing import Any
 
 import numpy as np
+import numpy.typing as npt
 import pandas as pd
 import xarray as xr
 
@@ -70,7 +71,7 @@ def read_lookup_table(table_index_value: int) -> Any:
         raise ValueError("Error: Invalid table index value")
 
 
-def deadtime_correction(counts: np.ndarray, acq_duration: int) -> np.ndarray:
+def deadtime_correction(counts: np.ndarray, acq_duration: int) -> npt.NDArray:
     """
     Calculate deadtime correction.
 
@@ -118,7 +119,7 @@ def deadtime_correction(counts: np.ndarray, acq_duration: int) -> np.ndarray:
     return corrected_count
 
 
-def convert_counts_to_rate(data: np.ndarray, acq_duration: int) -> np.ndarray:
+def convert_counts_to_rate(data: np.ndarray, acq_duration: int) -> npt.NDArray:
     """
     Convert counts to rate using sampling time.
 
@@ -206,7 +207,7 @@ def apply_in_flight_calibration(data: np.ndarray) -> None:
 
 def populate_full_cycle_data(
     l1a_data: xr.Dataset, packet_index: int, esa_table_num: int
-) -> np.ndarray:
+) -> npt.NDArray:
     """
     Populate full cycle data array using esa lookup table and l1a_data.
 
@@ -277,7 +278,7 @@ def populate_full_cycle_data(
     return full_cycle_data
 
 
-def find_cycle_starts(cycles: np.ndarray) -> np.ndarray:
+def find_cycle_starts(cycles: np.ndarray) -> npt.NDArray:
     """
     Find index of where new cycle started.
 
@@ -312,7 +313,7 @@ def find_cycle_starts(cycles: np.ndarray) -> np.ndarray:
     return np.where(valid)[0]
 
 
-def get_indices_of_full_cycles(quarter_cycle: np.ndarray) -> np.ndarray:
+def get_indices_of_full_cycles(quarter_cycle: np.ndarray) -> npt.NDArray:
     """
     Get indices of full cycles.
 

imap_processing/ultra/l0/decom_tools.py

@@ -1,6 +1,7 @@
 """Ultra Decompression Tools."""
 
 import numpy as np
+import numpy.typing as npt
 import space_packet_parser
 
 from imap_processing.ultra.l0.ultra_utils import (
@@ -154,7 +155,7 @@ def decompress_image(
     binary_data: str,
     width_bit: int,
     mantissa_bit_length: int,
-) -> np.ndarray:
+) -> npt.NDArray:
     """
     Will decompress a binary string representing an image into a matrix of pixel values.
 

imap_processing/ultra/l0/decom_ultra.py

@@ -31,7 +31,7 @@
 def append_tof_params(
     decom_data: dict,
     packet: Packet,
-    decompressed_data: list,
+    decompressed_data: np.ndarray,
     data_dict: dict,
     stacked_dict: dict,
 ) -> None: