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Fix Hi L2 naming of bg variables #2677

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Merged
subagonsouth merged 1 commit into from
Feb 10, 2026
Merged

Fix Hi L2 naming of bg variables #2677

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4 changes: 2 additions & 2 deletions imap_processing/ena_maps/ena_maps.py
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Original file line number Diff line number Diff line change
Expand Up @@ -657,8 +657,8 @@ class HiPointingSet(LoHiBasePointingSet):
# renamed to match L2 variables
l1c_to_l2_var_mapping: ClassVar[dict[str, str]] = {
"exposure_times": "exposure_factor",
"background_rates": "bg_rates",
"background_rates_uncertainty": "bg_rates_unc",
"background_rates": "bg_rate",
"background_rates_uncertainty": "bg_rate_sys_err",
}

def __init__(self, dataset: xr.Dataset | str | Path):
Expand Down
18 changes: 9 additions & 9 deletions imap_processing/hi/hi_l2.py
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Expand Up @@ -28,13 +28,13 @@
SC_FRAME_VARS_TO_PROJECT = {
"counts",
"exposure_factor",
"bg_rates",
"bg_rates_unc",
"bg_rate",
"bg_rate_sys_err",
"obs_date",
}
HELIO_FRAME_VARS_TO_PROJECT = SC_FRAME_VARS_TO_PROJECT | {"energy_sc"}
# TODO: is an exposure time weighted average for obs_date appropriate?
FULL_EXPOSURE_TIME_AVERAGE_SET = {"bg_rates", "bg_rates_unc", "obs_date", "energy_sc"}
FULL_EXPOSURE_TIME_AVERAGE_SET = {"bg_rate", "bg_rate_sys_err", "obs_date", "energy_sc"}


# =============================================================================
Expand Down Expand Up @@ -297,7 +297,7 @@ def calculate_all_rates_and_intensities(
Parameters
----------
map_ds : xarray.Dataset
Map dataset with projected PSET data (counts, exposure_factor, bg_rates,
Map dataset with projected PSET data (counts, exposure_factor, bg_rate,
energy_delta_minus, energy_delta_plus, etc.) and an `energy` coordinate
containing the ESA nominal central energies in keV.
l2_ancillary_path_dict : dict[str, pathlib.Path]
Expand Down Expand Up @@ -362,7 +362,7 @@ def calculate_ena_signal_rates(map_ds: xr.Dataset) -> xr.Dataset:
Parameters
----------
map_ds : xarray.Dataset
Map dataset that has counts, exposure_factor, and bg_rates calculated.
Map dataset that has counts, exposure_factor, and bg_rate calculated.

Returns
-------
Expand All @@ -373,7 +373,7 @@ def calculate_ena_signal_rates(map_ds: xr.Dataset) -> xr.Dataset:
with np.errstate(divide="ignore"):
# Calculate the ENA Signal Rate
map_ds["ena_signal_rates"] = (
map_ds["counts"] / map_ds["exposure_factor"] - map_ds["bg_rates"]
map_ds["counts"] / map_ds["exposure_factor"] - map_ds["bg_rate"]
)
# Calculate the ENA Signal Rate Uncertainties
# The minimum count uncertainty is 1 for any pixel that has non-zero
Expand Down Expand Up @@ -440,7 +440,7 @@ def calculate_ena_intensity(
map_ds["ena_signal_rate_stat_unc"] / flux_conversion_divisor
)
map_ds["ena_intensity_sys_err"] = (
np.sqrt(map_ds["bg_rates"] * map_ds["exposure_factor"])
np.sqrt(map_ds["bg_rate"] * map_ds["exposure_factor"])
/ map_ds["exposure_factor"]
/ flux_conversion_divisor
)
Expand Down Expand Up @@ -562,7 +562,7 @@ def _calculate_improved_stat_variance(

logger.debug("Computing geometric factor normalized signal rates")

# signal_rates = counts / exposure_factor - bg_rates
# signal_rates = counts / exposure_factor - bg_rate
# signal_rates shape is: (n_epoch, n_energy, n_cal_prod, n_spatial_pixels)
signal_rates = map_ds["ena_signal_rates"]

Expand All @@ -581,7 +581,7 @@ def _calculate_improved_stat_variance(
logger.debug("Including background rates in uncertainty calculation")
# Convert averaged signal rates back to flux uncertainties
# Total count rates for Poisson uncertainty calculation
total_count_rates_for_uncertainty = map_ds["bg_rates"] + averaged_signal_rates
total_count_rates_for_uncertainty = map_ds["bg_rate"] + averaged_signal_rates

logger.debug("Computing improved flux uncertainties")
# Statistical variance:
Expand Down
2 changes: 1 addition & 1 deletion imap_processing/tests/ena_maps/test_ena_maps.py
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Original file line number Diff line number Diff line change
Expand Up @@ -154,7 +154,7 @@ def test_init(self, hi_pset_cdf_path):
assert hi_pset.num_points == 3600
np.testing.assert_array_equal(hi_pset.az_el_points.shape, (3600, 2))

for var_name in ["exposure_factor", "bg_rates", "bg_rates_unc"]:
for var_name in ["exposure_factor", "bg_rate", "bg_rate_sys_err"]:
assert var_name in hi_pset.data

def test_from_cdf(self, hi_pset_cdf_path):
Expand Down
38 changes: 18 additions & 20 deletions imap_processing/tests/hi/test_hi_l2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -128,10 +128,10 @@ def sample_map_dataset():
"ena_intensity_sys_err": xr.DataArray(
np.random.rand(*shape) * 5 + 1, dims=list(coords.keys())
),
"bg_rates": xr.DataArray(
"bg_rate": xr.DataArray(
np.random.rand(*shape) * 20 + 5, dims=list(coords.keys())
),
"bg_rates_unc": xr.DataArray(
"bg_rate_sys_err": xr.DataArray(
np.random.rand(*shape) * 2 + 1, dims=list(coords.keys())
),
"exposure_factor": xr.DataArray(
Expand Down Expand Up @@ -301,10 +301,10 @@ def test_calculate_ena_signal_rates(empty_rectangular_map_dataset):
name="exposure_factor",
dims=list(exposure_sizes.keys()),
),
"bg_rates": xr.DataArray(
"bg_rate": xr.DataArray(
np.arange(np.prod(tuple(map_ds.sizes.values()))).reshape(counts_shape)
% 2,
name="bg_rates",
name="bg_rate",
dims=list(map_ds.sizes.keys()),
),
}
Expand All @@ -316,7 +316,7 @@ def test_calculate_ena_signal_rates(empty_rectangular_map_dataset):
assert var_name in result_ds
assert result_ds[var_name].shape == counts_shape
# Verify that there are no negative signal rates. The synthetic data combination
# where counts = 0, exposure_factor = 1, and bg_rates = 1 would result in
# where counts = 0, exposure_factor = 1, and bg_rate = 1 would result in
# an ena_signal_rate of (0 / 1) - 1 = -1
assert np.nanmin(result_ds["ena_signal_rates"].values) >= 0
# Verify that the minimum finite uncertainty is sqrt(1) / exposure_factor.
Expand Down Expand Up @@ -345,9 +345,9 @@ def ena_intensity_map_ds(empty_rectangular_map_dataset):
name="ena_signal_rate_stat_unc",
dims=list(map_ds.sizes.keys()),
),
"bg_rates_unc": xr.DataArray(
"bg_rate_sys_err": xr.DataArray(
np.arange(np.prod(tuple(map_ds.sizes.values()))).reshape(var_shape) % 3,
name="bg_rates_unc",
name="bg_rate_sys_err",
dims=list(map_ds.sizes.keys()),
),
}
Expand All @@ -359,7 +359,7 @@ def ena_intensity_map_ds(empty_rectangular_map_dataset):
)
map_ds.update(
{
"bg_rates": xr.DataArray(
"bg_rate": xr.DataArray(
np.ones(bg_shape) * 5.0,
dims=[d for d in map_ds.sizes.keys() if d != "calibration_prod"],
),
Expand Down Expand Up @@ -566,7 +566,7 @@ def test_weighted_average_mathematical_correctness():
np.array([100.0, 400.0]).reshape(1, 1, 2, 1, 1),
dims=list(coords.keys()),
),
"bg_rates": xr.DataArray(
"bg_rate": xr.DataArray(
np.array([5.0]).reshape(1, 1, 1, 1),
dims=[d for d in coords.keys() if d != "calibration_prod"],
),
Expand Down Expand Up @@ -624,7 +624,7 @@ def test_statistical_uncertainty_combination_correctness():
sys_err_values, dims=list(coords.keys())
),
"ena_signal_rates": xr.DataArray(flux_values, dims=list(coords.keys())),
"bg_rates": xr.DataArray(
"bg_rate": xr.DataArray(
np.array([1.0, 2.0]).reshape(1, 1, 2, 1, 1), dims=list(coords.keys())
),
"exposure_factor": xr.DataArray(
Expand Down Expand Up @@ -783,8 +783,8 @@ def test_process_single_pset_renames_variables(

# Check that variables were renamed
assert "exposure_factor" in result
assert "bg_rates" in result
assert "bg_rates_unc" in result
assert "bg_rate" in result
assert "bg_rate_sys_err" in result
# Original names should not exist
assert "exposure_times" not in result
assert "background_rates" not in result
Expand Down Expand Up @@ -834,16 +834,16 @@ def test_process_single_pset_exposure_time_weighting(
descriptor = MapDescriptor.from_string("h90-ena-h-sf-nsp-full-gcs-6deg-3mo")
energy_kev = xr.DataArray([0.5, 0.75, 1.1], dims=["esa_energy_step"])

# bg_rates should be multiplied by exposure_factor
# bg_rate should be multiplied by exposure_factor
result = process_single_pset(
mock_pset_dataset,
energy_kev,
descriptor,
vars_to_exposure_time_average={"bg_rates"},
vars_to_exposure_time_average={"bg_rate"},
)

# bg_rates was 5.0, exposure_factor is 100.0, so result should be 500.0
assert np.allclose(result["bg_rates"].values, 500.0)
# bg_rate was 5.0, exposure_factor is 100.0, so result should be 500.0
assert np.allclose(result["bg_rate"].values, 500.0)


@mock.patch("imap_processing.hi.hi_l2.calculate_ram_mask")
Expand Down Expand Up @@ -973,10 +973,8 @@ def mock_map_dataset_for_rates():
np.ones(exposure_shape) * 10.0,
dims=["epoch", "esa_energy_step", "longitude", "latitude"],
),
"bg_rates": xr.DataArray(
np.ones(shape) * 2.0, dims=list(coords.keys())[:5]
),
"bg_rates_unc": xr.DataArray(
"bg_rate": xr.DataArray(np.ones(shape) * 2.0, dims=list(coords.keys())[:5]),
"bg_rate_sys_err": xr.DataArray(
np.ones(shape) * 0.5, dims=list(coords.keys())[:5]
),
"obs_date": xr.DataArray(
Expand Down
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