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[ESSDIFFRACTION] Fix multiplication with mask #674

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[ESSDIFFRACTION] Fix multiplication with mask #674

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792c89f
Fix multiplication with mash
jl-wynen Jul 24, 2026
ad93645
Use where to apply masks
jl-wynen Jul 24, 2026
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9 changes: 6 additions & 3 deletions packages/essdiffraction/src/ess/dream/io/_common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,11 +13,14 @@ def prepare_reduced_data(da: sc.DataArray) -> sc.DataArray:
hist = da.hist() if da.is_binned else da.copy(deep=False)
hist.coords[hist.dim] = sc.midpoints(hist.coords[hist.dim])

if hist.masks:
if (mask := irreducible_mask(hist.masks, hist.dim)) is not None:
# No file format we use here supports masks, so the next
# best thing is to zero out masked data:
hist.data = hist.data.copy()
hist.values *= irreducible_mask(hist.masks, hist.dim).values
if hist.variances is not None:
replacement = sc.scalar(0.0, variance=0.0, unit=hist.unit, dtype=hist.dtype)

@nvaytet nvaytet Jul 24, 2026

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I guess this is the usual question: should the variance be 0, and thus being a very tight constraint on fits?

@nvaytet nvaytet Jul 24, 2026

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I think I would nan the masked values instead of 0. Makes them easier to distinguish from real zeros

@jl-wynen jl-wynen Jul 24, 2026

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Good point. I tried that and easydiffraction doesn't like it. It raises

TypeError: Value mismatch for <reduced_tof.data.1.intensity_meas>. Provided nan outside [0, inf]. Keeping current 0.0.

Judging by that error message, inf would be valid.

@AndrewSazonov How do we best encode masked data? In this case, it is masked because the vanadium measurement has a 0 in a bin.

@nvaytet nvaytet Jul 24, 2026

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Inf feels like it would just be a workaround/hack. Would make more sense if NaN was accepted downstream.

else:
replacement = sc.scalar(0.0, unit=hist.unit, dtype=hist.dtype)
hist.data = sc.where(mask, replacement, hist.data)
hist.masks.clear()

return hist
48 changes: 46 additions & 2 deletions packages/essdiffraction/tests/dream/io/cif_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,8 +4,10 @@
import io

import ess.dream.io.cif
import numpy as np
import pytest
import scipp as sc
import scipp.testing
from ess.powder.calibration import OutputCalibrationData
from ess.powder.types import (
Beamline,
Expand All @@ -23,8 +25,11 @@
def ioftof() -> IntensityTof:
return IntensityTof(
sc.DataArray(
sc.array(dims=['tof'], values=[2.1, 3.2], variances=[0.3, 0.4]),
coords={'tof': sc.linspace('tof', 0.1, 1.2, 3, unit='us')},
sc.array(dims=['tof'], values=[2.1, 3.2, 1.6], variances=[0.3, 0.4, 0.1]),
coords={
'tof': sc.array(dims=['tof'], values=[0.1, 0.3, 0.5, 0.7], unit='us')
},
masks={'bad': sc.array(dims=['tof'], values=[False, True, False])},
)
)

Expand Down Expand Up @@ -95,3 +100,42 @@ def test_save_reduced_tof(ioftof: IntensityTof, cal: OutputCalibrationData) -> N
_pd_proc.intensity_norm_su
"""
assert loop_header in result


def test_save_reduced_tof_writes_excpected_data(
ioftof: IntensityTof, cal: OutputCalibrationData
) -> None:
cif_ = ess.dream.io.cif.prepare_reduced_tof_cif(
ioftof,
authors=CIFAuthors([]),
beamline=Beamline(
name="DREAM",
),
source=ESS_SOURCE,
measurement=Measurement(
title="Test measurement",
),
reducers=ReducerSoftware([]),
calibration=cal,
)
result = save_reduced_tof_to_str(cif_)

loop_header = """loop_
_pd_data.point_id
_pd_meas.time_of_flight
_pd_proc.intensity_norm
_pd_proc.intensity_norm_su
"""
data_table = result[result.index(loop_header) + len(loop_header) :]
_, tof, val, std = np.loadtxt(io.StringIO(data_table), delimiter=' ').T
loaded = sc.DataArray(
sc.array(dims=['tof'], values=val, variances=std**2),
coords={'tof': sc.array(dims=['tof'], values=tof, unit='us')},
)

expected = sc.DataArray(
sc.array(dims=['tof'], values=[2.1, 0.0, 1.6], variances=[0.3, 0.0, 0.1]),
coords={'tof': sc.array(dims=['tof'], values=[0.2, 0.4, 0.6], unit='us')},
)
# Can't be identical because of conversion to standard deviations
sc.testing.assert_allclose(loaded, expected)
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