Remove separate resampling step from TofWorkflow

Author: SimonHeybrock

src/ess/reduce/time_of_flight/__init__.py

@@ -6,12 +6,7 @@
 neutron time-of-arrival at the detectors.
 """
 
-from .eto_to_tof import (
-    default_parameters,
-    providers,
-    resample_detector_time_of_flight_data,
-    resample_monitor_time_of_flight_data,
-)
+from .eto_to_tof import default_parameters, providers
 from .simulation import simulate_beamline
 from .types import (
     DetectorLtotal,
@@ -24,8 +19,6 @@
     PulsePeriod,
     PulseStride,
     PulseStrideOffset,
-    ResampledDetectorTofData,
-    ResampledMonitorTofData,
     SimulationResults,
     TimeOfFlightLookupTable,
     TimeOfFlightLookupTableFilename,
@@ -36,25 +29,23 @@
 __all__ = [
     "DetectorLtotal",
     "DetectorTofData",
+    "DetectorTofData",
     "DistanceResolution",
     "GenericTofWorkflow",
     "LookupTableRelativeErrorThreshold",
     "LtotalRange",
     "MonitorLtotal",
     "MonitorTofData",
+    "MonitorTofData",
     "PulsePeriod",
     "PulseStride",
     "PulseStrideOffset",
-    "ResampledDetectorTofData",
-    "ResampledMonitorTofData",
     "SimulationResults",
     "TimeOfFlightLookupTable",
     "TimeOfFlightLookupTableFilename",
     "TimeResolution",
     "TofLutProvider",
     "default_parameters",
     "providers",
-    "resample_detector_time_of_flight_data",
-    "resample_monitor_time_of_flight_data",
     "simulate_beamline",
 ]

src/ess/reduce/time_of_flight/eto_to_tof.py

@@ -39,8 +39,6 @@
     PulsePeriod,
     PulseStride,
     PulseStrideOffset,
-    ResampledDetectorTofData,
-    ResampledMonitorTofData,
     SimulationResults,
     TimeOfFlightLookupTable,
     TimeResolution,
@@ -586,7 +584,8 @@ def _compute_tof_data(
     pulse_stride_offset: int,
 ) -> sc.DataArray:
     if da.bins is None:
-        return _time_of_flight_data_histogram(da=da, lookup=lookup, ltotal=ltotal)
+        data = _time_of_flight_data_histogram(da=da, lookup=lookup, ltotal=ltotal)
+        return rebin_strictly_increasing(data, dim='tof')
     else:
         return _time_of_flight_data_events(
             da=da,
@@ -664,26 +663,6 @@ def monitor_time_of_flight_data(
     )
 
 
-def resample_detector_time_of_flight_data(
-    da: DetectorTofData[RunType],
-) -> ResampledDetectorTofData[RunType]:
-    """
-    Resample the detector time-of-flight data to ensure that the bin edges are sorted.
-    """
-    return ResampledDetectorTofData[RunType](rebin_strictly_increasing(da, dim='tof'))
-
-
-def resample_monitor_time_of_flight_data(
-    da: MonitorTofData[RunType, MonitorType],
-) -> ResampledMonitorTofData[RunType, MonitorType]:
-    """
-    Resample the monitor time-of-flight data to ensure that the bin edges are sorted.
-    """
-    return ResampledMonitorTofData[RunType, MonitorType](
-        rebin_strictly_increasing(da, dim='tof')
-    )
-
-
 def default_parameters() -> dict:
     """
     Default parameters of the time-of-flight workflow.

src/ess/reduce/time_of_flight/types.py

@@ -130,43 +130,3 @@ class DetectorTofData(sl.Scope[RunType, sc.DataArray], sc.DataArray):
 
 class MonitorTofData(sl.Scope[RunType, MonitorType, sc.DataArray], sc.DataArray):
     """Monitor data with time-of-flight coordinate."""
-
-
-class ResampledDetectorTofData(sl.Scope[RunType, sc.DataArray], sc.DataArray):
-    """
-    Histogrammed detector data with time-of-flight coordinate, that has been resampled.
-
-    Histogrammed data that has been converted to `tof` will typically have
-    unsorted bin edges (due to either wrapping of `time_of_flight` or wavelength
-    overlap between subframes).
-    We thus resample the data to ensure that the bin edges are sorted.
-    It makes use of the ``to_events`` helper which generates a number of events in each
-    bin with a uniform distribution. The new events are then histogrammed using a set of
-    sorted bin edges to yield a new histogram with sorted bin edges.
-
-    WARNING:
-    This function is highly experimental, has limitations and should be used with
-    caution. It is a workaround to the issue that rebinning data with unsorted bin
-    edges is not supported in scipp.
-    """
-
-
-class ResampledMonitorTofData(
-    sl.Scope[RunType, MonitorType, sc.DataArray], sc.DataArray
-):
-    """
-    Histogrammed monitor data with time-of-flight coordinate, that has been resampled.
-
-    Histogrammed data that has been converted to `tof` will typically have
-    unsorted bin edges (due to either wrapping of `time_of_flight` or wavelength
-    overlap between subframes).
-    We thus resample the data to ensure that the bin edges are sorted.
-    It makes use of the ``to_events`` helper which generates a number of events in each
-    bin with a uniform distribution. The new events are then histogrammed using a set of
-    sorted bin edges to yield a new histogram with sorted bin edges.
-
-    WARNING:
-    This function is highly experimental, has limitations and should be used with
-    caution. It is a workaround to the issue that rebinning data with unsorted bin
-    edges is not supported in scipp.
-    """

tests/time_of_flight/unwrap_test.py

@@ -88,10 +88,7 @@ def _make_workflow_histogram_mode(
     ).rename(event_time_offset=dim)
 
     pl = sl.Pipeline(
-        (
-            *time_of_flight.providers(),
-            time_of_flight.resample_detector_time_of_flight_data,
-        ),
+        time_of_flight.providers(),
         params=time_of_flight.default_parameters(),
         constraints={RunType: [SampleRun], MonitorType: []},
     )
@@ -203,7 +200,7 @@ def test_standard_unwrap_histogram_mode(dist, dim, simulation_psc_choppers) -> N
         pulse_stride=1,
     )
 
-    tofs = pl.compute(time_of_flight.ResampledDetectorTofData[SampleRun])
+    tofs = pl.compute(time_of_flight.DetectorTofData[SampleRun])
 
     _validate_result_histogram_mode(
         tofs=tofs, ref=ref, percentile=96, diff_threshold=0.4, rtol=0.05
@@ -432,7 +429,7 @@ def test_pulse_skipping_unwrap_histogram_mode(simulation_pulse_skipping) -> None
         pulse_stride=2,
     )
 
-    tofs = pl.compute(time_of_flight.ResampledDetectorTofData[SampleRun])
+    tofs = pl.compute(time_of_flight.DetectorTofData[SampleRun])
 
     _validate_result_histogram_mode(
         tofs=tofs, ref=ref, percentile=96, diff_threshold=0.4, rtol=0.05