TBL data reduction#

[1]:

import plopp as pp
from ess.reduce import time_of_flight
from ess import tbl
import ess.tbl.data  # noqa: F401
from ess.tbl.types import *

Create and configure the workflow#

[2]:

wf = tbl.TblWorkflow()

wf[Filename[SampleRun]] = tbl.data.tutorial_sample_data()

Downloading file 'tbl_sample_data_2025-03.hdf' from 'https://public.esss.dk/groups/scipp/ess/tbl/1/tbl_sample_data_2025-03.hdf' to '/home/runner/.cache/ess/tbl/1'.

nGEM detector data#

[3]:

wf[NeXusDetectorName] = "ngem_detector"

wf.visualize(DetectorData[SampleRun], graph_attr={"rankdir": "LR"})

[3]:
../../_images/user-guide_tbl_tbl-data-reduction_5_0.svg 
[4]:

ngem = wf.compute(DetectorData[SampleRun])
ngem

[4]:
Show/Hide data repr Show/Hide attributes
scipp.DataArray (8.86 MB out of 8.86 MB)
    • dim_0: 2
    • dim_1: 128
    • dim_2: 128
    • detector_number
      (dim_0, dim_1, dim_2)
      int32
      1, 2, ..., 32767, 32768
      Values:
      array([[[    1,     2,     3, ...,   126,   127,   128],
        [  129,   130,   131, ...,   254,   255,   256],
        [  257,   258,   259, ...,   382,   383,   384],
        ...,
        [16001, 16002, 16003, ..., 16126, 16127, 16128],
        [16129, 16130, 16131, ..., 16254, 16255, 16256],
        [16257, 16258, 16259, ..., 16382, 16383, 16384]],

       [[16385, 16386, 16387, ..., 16510, 16511, 16512],
        [16513, 16514, 16515, ..., 16638, 16639, 16640],
        [16641, 16642, 16643, ..., 16766, 16767, 16768],
        ...,
        [32385, 32386, 32387, ..., 32510, 32511, 32512],
        [32513, 32514, 32515, ..., 32638, 32639, 32640],
        [32641, 32642, 32643, ..., 32766, 32767, 32768]]],
      shape=(2, 128, 128), dtype=int32)
    • gravity
      ()
      vector3
      m/s^2
      [ 0. -9.80665 0. ]
      Values:
      array([ 0.     , -9.80665,  0.     ])
    • position
      (dim_0, dim_1, dim_2)
      vector3
      m
      [-0.1488 0.1488 -0.995 ], [-0.1465 0.1488 -0.995 ], ..., [ 0.1465 -0.1488 -1.005 ], [ 0.1488 -0.1488 -1.005 ]
      Values:
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        [[-0.1488,  0.1465, -0.995 ],
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        ...,

        [[-0.1488, -0.1441, -0.995 ],
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        [[-0.1488, -0.1465, -0.995 ],
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        [[-0.1488, -0.1488, -0.995 ],
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       [[[-0.1488,  0.1488, -1.005 ],
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        [[-0.1488,  0.1465, -1.005 ],
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         ...,
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         [ 0.1465,  0.1465, -1.005 ],
         [ 0.1488,  0.1465, -1.005 ]],

        [[-0.1488,  0.1441, -1.005 ],
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         [ 0.1465,  0.1441, -1.005 ],
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        ...,

        [[-0.1488, -0.1441, -1.005 ],
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         [ 0.1465, -0.1441, -1.005 ],
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        [[-0.1488, -0.1465, -1.005 ],
         [-0.1465, -0.1465, -1.005 ],
         [-0.1441, -0.1465, -1.005 ],
         ...,
         [ 0.1441, -0.1465, -1.005 ],
         [ 0.1465, -0.1465, -1.005 ],
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        [[-0.1488, -0.1488, -1.005 ],
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         [ 0.1465, -0.1488, -1.005 ],
         [ 0.1488, -0.1488, -1.005 ]]]], shape=(2, 128, 128, 3))
    • sample_position
      ()
      vector3
      m
      [0. 0. 0.]
      Values:
      array([0., 0., 0.])
    • source_position
      ()
      vector3
      m
      [ 0. 0. 30.]
      Values:
      array([ 0.,  0., 30.])
    • x_pixel_offset
      (dim_0, dim_1, dim_2)
      float64
      m
      -0.149, -0.146, ..., 0.146, 0.149
      Values:
      array([[[-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488],
        [-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488],
        [-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488],
        ...,
        [-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488],
        [-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488],
        [-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488]],

       [[-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488],
        [-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488],
        [-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488],
        ...,
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        [-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488],
        [-0.1488, -0.1465, -0.1441, ...,  0.1441,  0.1465,  0.1488]]],
      shape=(2, 128, 128))
    • y_pixel_offset
      (dim_0, dim_1, dim_2)
      float64
      m
      0.149, 0.149, ..., -0.149, -0.149
      Values:
      array([[[ 0.1488,  0.1488,  0.1488, ...,  0.1488,  0.1488,  0.1488],
        [ 0.1465,  0.1465,  0.1465, ...,  0.1465,  0.1465,  0.1465],
        [ 0.1441,  0.1441,  0.1441, ...,  0.1441,  0.1441,  0.1441],
        ...,
        [-0.1441, -0.1441, -0.1441, ..., -0.1441, -0.1441, -0.1441],
        [-0.1465, -0.1465, -0.1465, ..., -0.1465, -0.1465, -0.1465],
        [-0.1488, -0.1488, -0.1488, ..., -0.1488, -0.1488, -0.1488]],

       [[ 0.1488,  0.1488,  0.1488, ...,  0.1488,  0.1488,  0.1488],
        [ 0.1465,  0.1465,  0.1465, ...,  0.1465,  0.1465,  0.1465],
        [ 0.1441,  0.1441,  0.1441, ...,  0.1441,  0.1441,  0.1441],
        ...,
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        [-0.1465, -0.1465, -0.1465, ..., -0.1465, -0.1465, -0.1465],
        [-0.1488, -0.1488, -0.1488, ..., -0.1488, -0.1488, -0.1488]]],
      shape=(2, 128, 128))
    • z_pixel_offset
      (dim_0, dim_1, dim_2)
      float64
      m
      0.005, 0.005, ..., -0.005, -0.005
      Values:
      array([[[ 0.005,  0.005,  0.005, ...,  0.005,  0.005,  0.005],
        [ 0.005,  0.005,  0.005, ...,  0.005,  0.005,  0.005],
        [ 0.005,  0.005,  0.005, ...,  0.005,  0.005,  0.005],
        ...,
        [ 0.005,  0.005,  0.005, ...,  0.005,  0.005,  0.005],
        [ 0.005,  0.005,  0.005, ...,  0.005,  0.005,  0.005],
        [ 0.005,  0.005,  0.005, ...,  0.005,  0.005,  0.005]],

       [[-0.005, -0.005, -0.005, ..., -0.005, -0.005, -0.005],
        [-0.005, -0.005, -0.005, ..., -0.005, -0.005, -0.005],
        [-0.005, -0.005, -0.005, ..., -0.005, -0.005, -0.005],
        ...,
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        [-0.005, -0.005, -0.005, ..., -0.005, -0.005, -0.005],
        [-0.005, -0.005, -0.005, ..., -0.005, -0.005, -0.005]]],
      shape=(2, 128, 128))
    • (dim_0, dim_1, dim_2)
      float32
      counts
      binned data [len=4, len=12, ..., len=18, len=13]
      dim='event',
content=DataArray(
          dims=(event: 352698),
          data=float32[counts],
          coords={'event_time_offset':int32[ns], 'event_time_zero':datetime64[ns]})
[5]:

ngem['dim_0', 0].hist().plot(aspect='equal') + ngem['dim_0', 1].hist().plot(aspect='equal')

[5]:
../../_images/user-guide_tbl_tbl-data-reduction_7_0.svg

Time-of-flight#

[6]:

wf.visualize(TofData[SampleRun], graph_attr={"rankdir": "LR"})

[6]:
../../_images/user-guide_tbl_tbl-data-reduction_9_0.svg

Cache the time-of-flight lookup table#

[7]:

table = wf.compute(time_of_flight.TimeOfFlightLookupTable)
table.squeeze().plot()

[7]:
../../_images/user-guide_tbl_tbl-data-reduction_11_0.svg 
[8]:

wf[TimeOfFlightLookupTable] = table

Results#

[9]:

ngem_tofs = wf.compute(TofData[SampleRun])
ngem_wavs = wf.compute(WavelengthData[SampleRun])

ngem_tofs.bins.concat().hist(tof=100).plot() + ngem_wavs.bins.concat().hist(wavelength=100).plot()

[9]:
../../_images/user-guide_tbl_tbl-data-reduction_14_0.svg

He3 detector data#

[10]:

he3_wf = wf.copy()

he3 = {}
for bank in ('he3_detector_bank0', 'he3_detector_bank1'):
    he3_wf[NeXusDetectorName] = bank
    he3[bank] = he3_wf.compute(DetectorData[SampleRun])

[11]:

lims = {'vmin': 0, 'vmax': 4500}

he3['he3_detector_bank0'].hist().plot(title='he3_bank0', **lims) + he3['he3_detector_bank1'].hist().plot(title='he3_bank1', **lims)

[11]:
../../_images/user-guide_tbl_tbl-data-reduction_17_0.svg

Time-of-flight#

[12]:

he3_tofs = {}
he3_wavs = {}

for bank in ('he3_detector_bank0', 'he3_detector_bank1'):
    he3_wf[NeXusDetectorName] = bank
    he3_tofs[bank] = he3_wf.compute(TofData[SampleRun]).bins.concat().hist(tof=100)
    he3_wavs[bank] = he3_wf.compute(WavelengthData[SampleRun]).bins.concat().hist(wavelength=100)

pp.plot(he3_tofs) + pp.plot(he3_wavs)

[12]:
../../_images/user-guide_tbl_tbl-data-reduction_19_0.svg