1 Commits
v3.2.5 ... main

Author SHA1 Message Date
5e96a20f23 Evaluating ToF to extract sub-frames and assign to correct neutron pulse not chopper pulse (#4)
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Interpolate neutorn times between chopper pulses and assign by ToF. If ToF too short (long wavelengths from previous pulse), assign them to the previous sub-pulse.

Reviewed with Jochen

Reviewed-on: #4
Co-authored-by: Artur Glavic <artur.glavic@psi.ch>
Co-committed-by: Artur Glavic <artur.glavic@psi.ch>
2026-03-10 15:00:10 +01:00
10 changed files with 95 additions and 12 deletions

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@@ -2,5 +2,5 @@
Package to handle data redction at AMOR instrument to be used by __main__.py script.
"""
__version__ = '3.2.5'
__version__ = '3.2.6'
__date__ = '2026-03-10'

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@@ -9,7 +9,7 @@ from typing import Tuple
from . import const
from .event_data_types import EventDataAction, EventDatasetProtocol, append_fields, EVENT_BITMASKS
from .helpers import filter_project_x, merge_frames, extract_walltime, add_log_to_pulses
from .helpers import filter_project_x, merge_frames, extract_walltime, add_log_to_pulses, merge_frames_w_index
from .instrument import Detector
from .options import IncidentAngle
from .header import Header
@@ -25,8 +25,9 @@ class ExtractWalltime(EventDataAction):
dataset.data.events = new_events
class MergeFrames(EventDataAction):
def __init__(self, lamdaCut=None):
def __init__(self, lamdaCut=None, extractNeutronPulses=False):
self.lamdaCut=lamdaCut
self.extractNeutronPulses=extractNeutronPulses
def perform_action(self, dataset: EventDatasetProtocol)->None:
if self.lamdaCut is None:
@@ -36,7 +37,34 @@ class MergeFrames(EventDataAction):
tofCut = lamdaCut*dataset.geometry.chopperDetectorDistance/const.hdm*1e-13
total_offset = (tofCut +
dataset.timing.tau * (dataset.timing.ch1TriggerPhase + dataset.timing.chopperPhase/2)/180)
dataset.data.events.tof = merge_frames(dataset.data.events.tof, tofCut, dataset.timing.tau, total_offset)
if self.extractNeutronPulses and 'wallTime' in dataset.data.events.dtype.names:
d = dataset.data
# put events into precise sub-frame
d.events.tof, subframes = merge_frames_w_index(d.events.tof, tofCut, dataset.timing.tau, total_offset)
subframes = subframes.astype(int)
# add a sub-pulse time 1-tau before and after each existing time
utimes, uidxs = np.unique(d.events.wallTime, return_inverse=True)
inter_times = np.empty(2*utimes.shape[0]+1, dtype=d.events.wallTime.dtype)
tauns = dataset.timing.tau*1e9
inter_times[0] = utimes[0]-tauns
inter_times[1::2] = utimes
inter_times[2::2] = utimes+tauns
# use subframe indices to sort existing events into new times
d.events.wallTime = inter_times[2*uidxs+subframes+1]
# expand pulses array with additional sub-frames
new_pulses = np.recarray(2*d.pulses.shape[0]+1, dtype=d.pulses.dtype)
new_pulses[0] = d.pulses[0]
new_pulses[1::2] = d.pulses
new_pulses[2::2] = d.pulses
new_pulses.time[0] = d.pulses.time[0]-tauns
new_pulses.time[2::2] = d.pulses.time+tauns
new_pulses.monitor /= 2.0 # ~preserve total monitor counts
d.pulses = new_pulses
else:
if self.extractNeutronPulses:
logging.error(" Trying to separate neutron pulses while wallTime is not extracted, yet!")
dataset.data.events.tof = merge_frames(dataset.data.events.tof, tofCut, dataset.timing.tau, total_offset)
class AnalyzePixelIDs(EventDataAction):

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@@ -46,6 +46,8 @@ EVENT_BITMASKS = {
}
def append_fields(input: np.recarray, new_fields: List[Tuple[str, np.dtype]]):
# TODO: This action is used often and time consuming as it runs len(flds) times over all indices.
# Could only be faster if array is allocated in the beginning with all fields, less flexible.
# add one ore more fields to a recarray, numpy functions seems to fail
flds = [(name, dtypei[0]) for name, dtypei in input.dtype.fields.items()]
flds += new_fields

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@@ -165,7 +165,9 @@ class ApplyMask(EventDataAction):
self.bitmask_filter = bitmask_filter
def perform_action(self, dataset: EventDatasetProtocol) ->None:
# TODO: why is this action time consuming?
# TODO: Most time in test examples is spend here.
# While the actions here are very simple, they act on a large array,
# so even just comparison and indexing become time consuming.
d = dataset.data
pre_filter = d.events.shape[0]
if logging.getLogger().level <= logging.DEBUG:

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@@ -6,9 +6,13 @@ import numpy as np
from .event_data_types import EventDatasetProtocol, append_fields
try:
from .helpers_numba import merge_frames, extract_walltime, filter_project_x, calculate_derived_properties_focussing
from .helpers_numba import merge_frames, extract_walltime, filter_project_x, \
calculate_derived_properties_focussing, merge_frames_w_index
except ImportError:
from .helpers_fallback import merge_frames, extract_walltime, filter_project_x, calculate_derived_properties_focussing
import logging
logging.warning('Cannot import numba enhanced functions, is it installed?')
from .helpers_fallback import merge_frames, extract_walltime, filter_project_x, \
calculate_derived_properties_focussing, merge_frames_w_index
def add_log_to_pulses(key, dataset: EventDatasetProtocol):
"""

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@@ -8,6 +8,17 @@ def merge_frames(tof_e, tofCut, tau, total_offset):
# tof shifted to 1 frame
return np.remainder(tof_e-(tofCut-tau), tau)+total_offset
def merge_frames_w_index(tof_e, tofCut, tau, total_offset):
"""
Version of merge frames that also returns a frame index for each pulse:
0 - belongs to the frame it was measured in
-1 - arrived in this frame but belongs to the previous neutron pulse
1 - belongs to the second neutron pulse of the original frame
"""
new_tof = merge_frames(tof_e, tofCut, tau, total_offset)
frame_idx = np.floor_divide(tof_e-tofCut, tau)
return new_tof, frame_idx
def extract_walltime(tof_e, dataPacket_p, dataPacketTime_p):
output = np.empty(np.shape(tof_e)[0], dtype=np.int64)
for i in range(len(dataPacket_p)-1):

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@@ -11,6 +11,22 @@ def merge_frames(tof_e, tofCut, tau, total_offset):
tof_e_out[ti] = ((tof_e[ti]-dt)%tau)+total_offset # tof shifted to 1 frame
return tof_e_out
@nb.jit(nb.float64[:,:](nb.float64[:], nb.float64, nb.float64, nb.float64),
nopython=True, parallel=True, cache=True)
def merge_frames_w_index(tof_e, tofCut, tau, total_offset):
"""
Version of merge frames that also returns a frame index for each pulse:
0 - belongs to the frame it was measured in
-1 - arrived in this frame but belongs to the previous neutron pulse
1 - belongs to the second neutron pulse of the original frame
"""
tof_idx_out = np.empty((2, tof_e.shape[0]), dtype=np.float64)
dt = (tofCut-tau)
for ti in nb.prange(tof_e.shape[0]):
tof_idx_out[0, ti] = ((tof_e[ti]-dt)%tau)+total_offset # tof shifted to 1 frame
tof_idx_out[1, ti] = ((tof_e[ti]-tofCut) // tau) # tof shifted to 1 frame
return tof_idx_out
@nb.jit(nb.int64[:](nb.float64[:], nb.uint32[:], nb.int64[:]),
nopython=True, parallel=True, cache=True)
def extract_walltime(tof_e, dataPacket_p, dataPacketTime_p):

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@@ -480,6 +480,16 @@ class ReflectivityReductionConfig(ArgParsable):
},
)
extractNeutronPulses: bool = field(
default=False,
metadata={
'short': 'np',
'group': 'data manicure',
'help': 're-assign events to actual neutron pulses => '
'2xbetter filter resolution but extra computation (experimental)',
},
)
class OutputFomatOption(StrEnum):
Rqz_ort = "Rqz.ort"

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@@ -65,7 +65,7 @@ class ReflectivityReduction:
# the filtering only makes sense if using actual monitor data, not time
self.dataevent_actions |= eh.FilterMonitorThreshold(self.config.experiment.lowCurrentThreshold)
self.dataevent_actions |= eh.FilterStrangeTimes()
self.dataevent_actions |= ea.MergeFrames()
self.dataevent_actions |= ea.MergeFrames(extractNeutronPulses=self.config.reduction.extractNeutronPulses)
self.dataevent_actions |= ea.AnalyzePixelIDs(self.config.experiment.yRange)
self.dataevent_actions |= eh.TofTimeCorrection(self.config.experiment.incidentAngle==IncidentAngle.alphaF)
self.dataevent_actions |= ea.CalculateWavelength(self.config.experiment.lambdaRange)

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@@ -46,7 +46,7 @@ class MockEventData:
# list of data packates containing previous events
packets = np.recarray((1000,), dtype=PACKET_TYPE)
packets.start_index = np.linspace(0, events.shape[0]-1, packets.shape[0], dtype=np.uint32)
packets.time = np.linspace(1700000000000000000, 1700000000000000000+3_600_000_000,
packets.time = np.linspace(1700000000000000000, 1700000000000000000+3_600_000_000_000,
packets.shape[0], dtype=np.int64)
# chopper pulses within the measurement time
@@ -58,7 +58,7 @@ class MockEventData:
proton_current = np.recarray((50,), dtype=PC_TYPE)
proton_current.current = 1500.0
proton_current[np.random.randint(0, proton_current.shape[0]-1, 10)] = 0. # random time with no current
proton_current.time = np.linspace(1700000000000000300, 1700000000000000000+3_600_000_000,
proton_current.time = np.linspace(1700000000000000300, 1700000000000000000+3_600_000_000_000,
proton_current.shape[0], dtype=np.int64)
self.data = AmorEventStream(events, packets, pulses, proton_current)
@@ -420,20 +420,30 @@ class TestSimpleActions(TestCase):
dtype=np.int32))
def test_merge_frames(self):
action = MergeFrames(lamdaCut=0.0)
action = MergeFrames(lamdaCut=0.0, extractNeutronPulses=False)
action.perform_action(self.d)
self.assertEqual(self.d.data.events.tof.shape, self.d.orig_data.events.tof.shape)
np.testing.assert_array_compare(lambda x,y: x<=y, self.d.data.events.tof, self.d.orig_data.events.tof)
self.assertTrue((-self.d.timing.tau<=self.d.data.events.tof).all())
np.testing.assert_array_less(self.d.data.events.tof, self.d.timing.tau)
action = MergeFrames(lamdaCut=2.0)
action = MergeFrames(lamdaCut=2.0, extractNeutronPulses=False)
self.d.data.events.tof = self.d.orig_data.events.tof[:]
action.perform_action(self.d)
tofCut = 2.0*self.d.geometry.chopperDetectorDistance/const.hdm*1e-13
self.assertTrue((tofCut-self.d.timing.tau<=self.d.data.events.tof).all())
self.assertTrue((self.d.data.events.tof<=tofCut+self.d.timing.tau).all())
def test_merge_frames_splitting(self):
action = MergeFrames(lamdaCut=0.0, extractNeutronPulses=True)
self._extract_walltime()
action.perform_action(self.d)
self.assertEqual(self.d.data.events.tof.shape, self.d.orig_data.events.tof.shape)
np.testing.assert_array_compare(lambda x,y: x<=y, self.d.data.events.tof, self.d.orig_data.events.tof)
self.assertEqual(self.d.data.pulses.shape[0], self.d.orig_data.pulses.shape[0]*2+1)
np.testing.assert_array_less(self.d.orig_data.pulses.time[:-1], self.d.orig_data.pulses.time[1:])
np.testing.assert_array_less(self.d.data.pulses.time[:-1], self.d.data.pulses.time[1:])
def test_analyze_pixel_ids(self):
action = AnalyzePixelIDs((1000, 1001))
action.perform_action(self.d)