Lo L1B DE - Binning fixes (IMAP-Science-Operations-Center#2334)

* changed HAE to DPS binning

* fixed unit tests

* fixed energy edges bug that was reintroduced

* added comment for goodtimes bin condition

Author: sdhoyt

imap_processing/lo/l1b/lo_l1b.py

@@ -19,6 +19,7 @@
 from imap_processing.spice.geometry import (
     SpiceFrame,
     cartesian_to_latitudinal,
+    frame_transform,
     instrument_pointing,
 )
 from imap_processing.spice.repoint import get_pointing_times
@@ -760,8 +761,10 @@ def set_bad_or_goodtimes(
     # the bin_start and bin_end are 6 degree bins and need to be converted to
     # 0.1 degree bins to align with the spin_bins, so multiply by 60
     time_mask = (epochs[:, None] >= times_start) & (epochs[:, None] <= times_end)
+    # The ancillary file binning uses 0-59 for the 6 degree bins, so add 1 to bin_end
+    # so the upper bound is inclusive of the full bin range.
     bin_mask = (spin_bins[:, None] >= times_df["bin_start"].values * 60) & (
-        spin_bins[:, None] <= times_df["bin_end"].values * 60
+        spin_bins[:, None] < (times_df["bin_end"].values + 1) * 60
     )
 
     # Combined mask for epochs that fall within the time and bin ranges
@@ -853,8 +856,15 @@ def set_pointing_bin(l1b_de: xr.Dataset) -> xr.Dataset:
     x = l1b_de["hae_x"]
     y = l1b_de["hae_y"]
     z = l1b_de["hae_z"]
+    # Convert from HAE to DPS coordinates
+    dps_xyz = frame_transform(
+        ttj2000ns_to_et(l1b_de["epoch"]),
+        np.column_stack((x, y, z)),
+        SpiceFrame.IMAP_HAE,
+        SpiceFrame.IMAP_DPS,
+    )
     # convert the pointing direction to latitudinal coordinates
-    direction = cartesian_to_latitudinal(np.column_stack((x, y, z)))
+    direction = cartesian_to_latitudinal(dps_xyz)
     # first column: radius (Not needed)
     # second column: longitude
     lons = direction[:, 1]

imap_processing/lo/l1c/lo_l1c.py

@@ -295,8 +295,8 @@ def create_pset_counts(
     data = np.column_stack(
         (
             de_filtered["esa_step"],
-            de_filtered["pointing_bin_lon"],
-            de_filtered["pointing_bin_lat"],
+            de_filtered["spin_bin"],
+            de_filtered["off_angle_bin"],
         )
     )
     # Create the histogram with 3600 longitude bins, 40 latitude bins, and 7 energy bins
@@ -341,7 +341,7 @@ def calculate_exposure_times(counts: xr.DataArray, l1b_de: xr.Dataset) -> xr.Dat
         The exposure times for the L1B Direct Event dataset.
     """
     data = np.column_stack(
-        (l1b_de["esa_step"], l1b_de["pointing_bin_lon"], l1b_de["pointing_bin_lat"])
+        (l1b_de["esa_step"], l1b_de["spin_bin"], l1b_de["off_angle_bin"])
     )
 
     result = binned_statistic_dd(

imap_processing/tests/lo/test_lo_l1b.py

@@ -77,6 +77,10 @@ def attr_mgr_l1a():
     return attr_mgr
 
 
+@patch(
+    "imap_processing.lo.l1b.lo_l1b.frame_transform",
+    return_value=np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]),
+)
 @patch(
     "imap_processing.lo.l1b.lo_l1b.instrument_pointing",
     return_value=np.zeros((2000, 3)),
@@ -91,6 +95,7 @@ def attr_mgr_l1a():
     return_value=np.zeros((2000, 3)),
 )
 def test_lo_l1b(
+    mock_frame_transform,
     mock_instrument_pointing,
     mocked_get_pointing_times,
     mock_spin_number,
@@ -630,11 +635,15 @@ def test_set_direction(imap_ena_sim_metakernel):
     )
 
 
+@patch(
+    "imap_processing.lo.l1b.lo_l1b.frame_transform",
+    return_value=np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]),
+)
 @patch(
     "imap_processing.lo.l1b.lo_l1b.cartesian_to_latitudinal",
     return_value=np.array([[0, -180, -2], [0, 0, 0], [0, 90, 1], [0, 180, 2]]),
 )
-def test_pointing_bins(imap_ena_sim_metakernel):
+def test_pointing_bins(mock_cartesian_to_latitudinal, mock_frame_transform):
     # Arrange
     l1b_de = xr.Dataset(
         {

imap_processing/tests/lo/test_lo_l1c.py

@@ -23,8 +23,8 @@
 def l1b_de():
     l1b_de = xr.Dataset(
         {
-            "pointing_bin_lon": ("epoch", [20, 0, 20, 2000, 3500]),
-            "pointing_bin_lat": ("epoch", [20, 20, 20, 20, 20]),
+            "spin_bin": ("epoch", [20, 0, 20, 2000, 3500]),
+            "off_angle_bin": ("epoch", [20, 20, 20, 20, 20]),
             "esa_step": ("epoch", [1, 2, 1, 4, 5]),
             "coincidence_type": (
                 "epoch",
@@ -39,7 +39,6 @@ def l1b_de():
             "species": ("epoch", ["H", "O", "H", "H", "O"]),
             "spin_cycle": ("epoch", [1, 2, 3, 4, 5]),
             "avg_spin_durations": ("epoch", [15.2, 15.2, 14.9, 15, 14.9]),
-            "spin_bin": ("epoch", [1900, 2000, 3000, 3000, 3000]),
         },
         coords={
             "epoch": [
@@ -64,8 +63,8 @@ def repoint_met():
 def l1b_de_spin():
     l1b_de = xr.Dataset(
         {
-            "pointing_bin_lon": ("epoch", [20, 0, 20, 2000, 3500]),
-            "pointing_bin_lat": ("epoch", [20, 20, 20, 20, 20]),
+            "spin_bin": ("epoch", [20, 0, 20, 2000, 3500]),
+            "off_angle_bin": ("epoch", [20, 20, 20, 20, 20]),
             "esa_step": ("epoch", [1, 2, 1, 4, 5]),
             "coincidence_type": (
                 "epoch",
@@ -80,7 +79,6 @@ def l1b_de_spin():
             "species": ("epoch", ["H", "O", "H", "H", "O"]),
             "spin_cycle": ("epoch", [1, 2, 3, 4, 5]),
             "avg_spin_durations": ("epoch", [15.2, 15.2, 14.9, 15, 14.9]),
-            "spin_bin": ("epoch", [1900, 2000, 3000, 3000, 3000]),
         },
         coords={
             "epoch": met_to_ttj2000ns(np.arange(511000000, 511000000 + 200, 40) + 902),