major refactor after feedback and discussion offline

imap_processing/spice/geometry.py

@@ -10,15 +10,14 @@
 
 import typing
 from enum import IntEnum
-from typing import Optional, Union
+from pathlib import Path
+from typing import Union
 
-import cdflib
 import numpy as np
 import pandas as pd
 import spiceypy as spice
 
 from imap_processing.spice.kernels import ensure_spice
-from imap_processing.spice.time import met_to_j2000ns
 
 
 class SpiceBody(IntEnum):
@@ -92,89 +91,11 @@ def imap_state(
     return np.asarray(state)
 
 
-def generate_spin_data(
-    start_met: float, end_met: Optional[float] = None
-) -> pd.DataFrame:
+def get_spin_data(path_to_spin_file: Path) -> pd.DataFrame:
     """
-    Generate a spin table CSV covering one or more days.
+    Read spin file and return spin data.
 
-    Spin table contains the following fields:
-        (
-        spin_number,
-        spin_start_sec,
-        spin_start_subsec,
-        spin_period_sec,
-        spin_period_valid,
-        spin_phas_valid,
-        spin_period_source,
-        thruster_firing
-        )
-    This function creates spin data using start MET and end MET time.
-    Each spin start data uses the nominal 15 second spin period. The spins that
-    occur from 00:00(Mid-night) to 00:10 UTC are marked with flags for
-    thruster firing, invalid spin period, and invalid spin phase.
-
-    Parameters
-    ----------
-    start_met : float
-        Provides the start time in Mission Elapsed Time (MET).
-    end_met : float
-        Provides the end time in MET. If not provided, default to one day
-        from start time.
-
-    Returns
-    -------
-    spin_df : pandas.DataFrame
-        Spin data. May need to save data to CSV file.
-    """
-    if end_met is None:
-        # end_time is one day after start_time
-        end_met = start_met + 86400
-
-    # Create spin start second data of 15 seconds increment
-    spin_start_sec = np.arange(start_met, end_met, 15)
-
-    spin_dict = {
-        "spin_number": np.arange(spin_start_sec.size, dtype=np.uint32),
-        "spin_start_sec": spin_start_sec,
-        "spin_start_subsec": np.full(spin_start_sec.size, 0, dtype=np.uint32),
-        "spin_period_sec": np.full(spin_start_sec.size, 15.0, dtype=np.float32),
-        "spin_period_valid": np.ones(spin_start_sec.size, dtype=np.uint8),
-        "spin_phas_valid": np.ones(spin_start_sec.size, dtype=np.uint8),
-        "spin_period_source": np.zeros(spin_start_sec.size, dtype=np.uint8),
-        "thruster_firing": np.zeros(spin_start_sec.size, dtype=np.uint8),
-    }
-
-    # Convert spin_start_sec to datetime to set repointing times flags
-    spin_start_dates = met_to_j2000ns(spin_start_sec)
-    spin_start_dates = cdflib.cdfepoch.to_datetime(spin_start_dates)
-
-    # Convert DatetimeIndex to Series for using .dt accessor
-    spin_start_dates_series = pd.Series(spin_start_dates)
-
-    # Find index of all timestamps that fall within 10 minutes after midnight
-    repointing_times = spin_start_dates_series[
-        (spin_start_dates_series.dt.time >= pd.Timestamp("00:00:00").time())
-        & (spin_start_dates_series.dt.time < pd.Timestamp("00:10:00").time())
-    ]
-
-    repointing_times_index = repointing_times.index
-
-    # Use the repointing times to set thruster firing flag and spin period valid
-    spin_dict["thruster_firing"][repointing_times_index] = 1
-    spin_dict["spin_period_valid"][repointing_times_index] = 0
-    spin_dict["spin_phas_valid"][repointing_times_index] = 0
-
-    spin_df = pd.DataFrame.from_dict(spin_dict)
-    return spin_df
-
-
-def get_spin_data(start_met: float, end_met: Optional[float] = None) -> pd.DataFrame:
-    """
-    Get spin data for a given time range.
-
-    This function queries spin data for the input date range. Spin
-    table contains the following fields:
+    Spin data should contains the following fields:
         (
             spin_number,
             spin_start_sec,
@@ -188,27 +109,19 @@ def get_spin_data(start_met: float, end_met: Optional[float] = None) -> pd.DataF
 
     Parameters
     ----------
-    start_met : float
-        Provide the start time in Mission Elapsed Time (MET).
-    end_met : float
-        Provide the end time in MET. If not provided, default to one day
-        from start time.
+    path_to_spin_file : pathlib.Path
+        Input CSV file containing spin data.
 
     Returns
     -------
     spin_data : pandas.DataFrame
-        Spin data. It's a dictionary with keys and values as numpy arrays.
+        Spin data.
     """
-    if end_met is None:
-        # end time is one day after start time
-        end_met = start_met + 86400
-
-    # TODO: write code to query spin database and return all spin data
-    # for the input date range once we have actual infrastructure in place.
-
-    # Call generate_spin_data function temporarily that generates sample spin data for
-    # the given date range.
-    return generate_spin_data(start_met, end_met)
+    # TODO: change this function if file type of spin data changes
+    # or if spin data is stored in a database
+    if path_to_spin_file.suffix != ".csv":
+        raise ValueError("Input file must be a CSV file.")
+    return pd.read_csv(path_to_spin_file)
 
 
 def get_spacecraft_spin_phase(

imap_processing/tests/conftest.py

@@ -2,13 +2,17 @@
 
 import os
 import re
+from typing import Optional
 
+import cdflib
 import imap_data_access
 import numpy as np
+import pandas as pd
 import pytest
 import spiceypy as spice
 
 from imap_processing import imap_module_directory
+from imap_processing.spice.time import met_to_j2000ns
 
 
 @pytest.fixture(autouse=True)
@@ -155,3 +159,79 @@ def _unset_metakernel_path(monkeypatch):
     """Temporarily unsets the SPICE_METAKERNEL environment variable"""
     if os.getenv("SPICE_METAKERNEL", None) is not None:
         monkeypatch.delenv("SPICE_METAKERNEL")
+
+
+@pytest.fixture()
+def generate_spin_data():
+    def make_data(start_met: int, end_met: Optional[int] = None) -> pd.DataFrame:
+        """
+        Generate a spin table CSV covering one or more days.
+        Spin table contains the following fields:
+            (
+            spin_number,
+            spin_start_sec,
+            spin_start_subsec,
+            spin_period_sec,
+            spin_period_valid,
+            spin_phas_valid,
+            spin_period_source,
+            thruster_firing
+            )
+        This function creates spin data using start MET and end MET time.
+        Each spin start data uses the nominal 15 second spin period. The spins that
+        occur from 00:00(Mid-night) to 00:10 UTC are marked with flags for
+        thruster firing, invalid spin period, and invalid spin phase.
+        Parameters
+        ----------
+        start_met : int
+            Provides the start time in Mission Elapsed Time (MET).
+        end_met : int
+            Provides the end time in MET. If not provided, default to one day
+            from start time.
+        Returns
+        -------
+        spin_df : pd.DataFrame
+            Spin data.
+        """
+        if end_met is None:
+            # end_time is one day after start_time
+            end_met = start_met + 86400
+
+        # Create spin start second data of 15 seconds increment
+        spin_start_sec = np.arange(start_met, end_met, 15)
+
+        spin_dict = {
+            "spin_number": np.arange(spin_start_sec.size, dtype=np.uint32),
+            "spin_start_sec": spin_start_sec,
+            "spin_start_subsec": np.full(spin_start_sec.size, 0, dtype=np.uint32),
+            "spin_period_sec": np.full(spin_start_sec.size, 15.0, dtype=np.float32),
+            "spin_period_valid": np.ones(spin_start_sec.size, dtype=np.uint8),
+            "spin_phas_valid": np.ones(spin_start_sec.size, dtype=np.uint8),
+            "spin_period_source": np.zeros(spin_start_sec.size, dtype=np.uint8),
+            "thruster_firing": np.zeros(spin_start_sec.size, dtype=np.uint8),
+        }
+
+        # Convert spin_start_sec to datetime to set repointing times flags
+        spin_start_dates = met_to_j2000ns(spin_start_sec)
+        spin_start_dates = cdflib.cdfepoch.to_datetime(spin_start_dates)
+
+        # Convert DatetimeIndex to Series for using .dt accessor
+        spin_start_dates_series = pd.Series(spin_start_dates)
+
+        # Find index of all timestamps that fall within 10 minutes after midnight
+        repointing_times = spin_start_dates_series[
+            (spin_start_dates_series.dt.time >= pd.Timestamp("00:00:00").time())
+            & (spin_start_dates_series.dt.time < pd.Timestamp("00:10:00").time())
+        ]
+
+        repointing_times_index = repointing_times.index
+
+        # Use the repointing times to set thruster firing flag and spin period valid
+        spin_dict["thruster_firing"][repointing_times_index] = 1
+        spin_dict["spin_period_valid"][repointing_times_index] = 0
+        spin_dict["spin_phas_valid"][repointing_times_index] = 0
+
+        spin_df = pd.DataFrame.from_dict(spin_dict)
+        return spin_df
+
+    return make_data

imap_processing/tests/spice/test_geometry.py

@@ -1,11 +1,13 @@
 """Tests coverage for imap_processing/spice/geometry.py"""
 
+from pathlib import Path
+
 import numpy as np
+import pandas as pd
 import pytest
 
 from imap_processing.spice.geometry import (
     SpiceBody,
-    generate_spin_data,
     get_spacecraft_spin_phase,
     get_spin_data,
     imap_state,
@@ -44,42 +46,27 @@ def test_get_spacecraft_spin_phase():
     assert len(spin_phases) == 1, "Spin phases length should match query times length."
 
 
-def test_get_spin_data():
+def test_get_spin_data(generate_spin_data, tmpdir):
     """Test get_spin_data() with generated spin data."""
+    # SWE test data time minus 56120 seconds to get mid-night time
+    start_time = 453051323.0 - 56120
+    spin_df = generate_spin_data(start_time)
+    spin_csv_file_path = Path(tmpdir) / "spin_data.spin.csv"
+    spin_df.to_csv(spin_csv_file_path, index=False)
 
-    start_time = 453051323.0
-
-    spin_data = get_spin_data(start_met=start_time)
-
-    assert len(spin_data.keys()) == 8, "Spin data must have 8 fields."
-
-
-def test_generate_spin_data():
-    """Test generate_spin_data() with generated spin data."""
-
-    start_time = 453051323.0
-    end_time = 453051323.0 + 86400
-
-    spin_data = generate_spin_data(start_time, end_time)
+    spin_data = get_spin_data(path_to_spin_file=spin_csv_file_path)
 
     assert len(spin_data.keys()) == 8, "Spin data must have 8 fields."
-    assert len(spin_data["spin_number"]) > 0, "Spin number must have some values."
-    assert len(spin_data["spin_start_sec"]) > 0, "Spin start sec must have some values."
-    assert (
-        len(spin_data["spin_start_subsec"]) > 0
-    ), "Spin start subsec must have some values."
-    assert (
-        len(spin_data["spin_period_sec"]) > 0
-    ), "Spin period sec must have some values."
-    assert (
-        len(spin_data["spin_period_valid"]) > 0
-    ), "Spin period valid must have some values."
-    assert (
-        len(spin_data["spin_phas_valid"]) > 0
-    ), "Spin phas valid must have some values."
-    assert (
-        len(spin_data["spin_period_source"]) > 0
-    ), "Spin period source must have some values."
-    assert (
-        len(spin_data["thruster_firing"]) > 0
-    ), "Thruster firing must have some values."
+    assert len(spin_data) == 5760, "One day should have 5,760 records of 15 seconds."
+    assert isinstance(spin_data, pd.DataFrame), "Return type must be pandas.DataFrame."
+
+    assert set(spin_data.columns) == {
+        "spin_number",
+        "spin_start_sec",
+        "spin_start_subsec",
+        "spin_period_sec",
+        "spin_period_valid",
+        "spin_phas_valid",
+        "spin_period_source",
+        "thruster_firing",
+    }, "Spin data must have the specified fields."