-
Notifications
You must be signed in to change notification settings - Fork 122
/
HB3AIntegratePeaks.py
201 lines (160 loc) · 9.56 KB
/
HB3AIntegratePeaks.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
# Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2020 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source,
# Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identifier: GPL - 3.0 +
from mantid.api import (AlgorithmFactory, FileAction, FileProperty,
PythonAlgorithm, PropertyMode, ADSValidator,
WorkspaceGroup, WorkspaceProperty, MultipleExperimentInfos,
IPeaksWorkspace)
from mantid.kernel import Direction, FloatBoundedValidator, StringListValidator, StringArrayProperty
from mantid.simpleapi import (DeleteWorkspace, IntegratePeaksMD,
SaveHKL, SaveReflections,
CreatePeaksWorkspace, CopySample,
AnalysisDataService, FilterPeaks,
CombinePeaksWorkspaces, mtd)
import numpy as np
class HB3AIntegratePeaks(PythonAlgorithm):
def category(self):
return "Crystal\\Integration"
def seeAlso(self):
return ["HB3AFindPeaks", "IntegratePeaksMD", "HB3AAdjustSampleNorm", "HB3APredictPeaks"]
def name(self):
return "HB3AIntegratePeaks"
def summary(self):
return 'Integrates peaks from the input MDEvent workspace and can optionally apply a Lorentz correction to ' \
'the output peaks workspace; output can be saved in different formats.'
def PyInit(self):
self.declareProperty(StringArrayProperty("InputWorkspace", direction=Direction.Input, validator=ADSValidator()),
doc="Input MDEvent workspace to use for integration")
self.declareProperty(StringArrayProperty("PeaksWorkspace", direction=Direction.Input, validator=ADSValidator()),
doc="Peaks workspace containing peaks to integrate")
positive_val = FloatBoundedValidator(lower=0.0)
self.declareProperty("PeakRadius", defaultValue=1.0, validator=positive_val,
doc="Fixed radius around each peak position in which to integrate"
" (same units as input workspace) ")
self.declareProperty("BackgroundInnerRadius", defaultValue=0.0, validator=positive_val,
doc="Inner radius used to evaluate the peak background")
self.declareProperty("BackgroundOuterRadius", defaultValue=0.0, validator=positive_val,
doc="Outer radius used to evaluate the peak background")
self.declareProperty("ApplyLorentz", defaultValue=True,
doc="Whether the Lorentz correction should be applied to the integrated peaks")
self.declareProperty("RemoveZeroIntensity", defaultValue=True,
doc="If to remove peaks with 0 or less intensity from the output")
formats = StringListValidator()
formats.addAllowedValue("SHELX")
formats.addAllowedValue("Fullprof")
self.declareProperty("OutputFormat", defaultValue="SHELX", validator=formats,
doc="Save direction cosines in HKL, or the fullprof format")
self.declareProperty(FileProperty(name="OutputFile", defaultValue="",
direction=Direction.Input,
action=FileAction.OptionalSave),
doc="Filepath to save the integrated peaks workspace in HKL format")
self.declareProperty(WorkspaceProperty("OutputWorkspace", defaultValue="", direction=Direction.Output,
optional=PropertyMode.Mandatory),
doc="Output peaks workspace (copy of input with updated peak intensities)")
def validateInputs(self):
issues = dict()
# Make sure outer radius > inner radius
inner_radius = self.getProperty("BackgroundInnerRadius").value
outer_radius = self.getProperty("BackgroundOuterRadius").value
if outer_radius < inner_radius:
issues['BackgroundOuterRadius'] = "Outer radius should be >= to inner radius"
input_workspaces, peak_workspaces = self._expand_groups()
if len(input_workspaces) != len(peak_workspaces):
issues["InputWorkspace"] = "The same number of PeaksWorkspace must be provided as InputWorkspace"
for input_ws in input_workspaces:
if not (isinstance(AnalysisDataService[input_ws], MultipleExperimentInfos)):
issues["InputWorkspace"] = "Workspace need to be a MDEventWorkspace"
elif AnalysisDataService[input_ws].getSpecialCoordinateSystem().name != "QSample":
issues["InputWorkspace"] = "Input workspace expected to be in QSample, " \
"workspace is in '{}'".format(input_ws.getSpecialCoordinateSystem().name)
elif AnalysisDataService[input_ws].getNumDims() != 3:
issues["InputWorkspace"] = "Workspace has the wrong number of dimensions"
for peak_ws in peak_workspaces:
if not isinstance(AnalysisDataService[peak_ws], IPeaksWorkspace):
issues["PeaksWorkspace"] = "Workspace need to be a PeaksWorkspace or LeanElasticPeaksWorkspace"
return issues
def PyExec(self):
input_workspaces, peak_workspaces = self._expand_groups()
output_workspace_name = self.getPropertyValue("OutputWorkspace")
peak_radius = self.getProperty("PeakRadius").value
inner_radius = self.getProperty("BackgroundInnerRadius").value
outer_radius = self.getProperty("BackgroundOuterRadius").value
remove_0_intensity = self.getProperty("RemoveZeroIntensity").value
use_lorentz = self.getProperty("ApplyLorentz").value
multi_ws = len(input_workspaces) > 1
output_workspaces = []
for input_ws, peak_ws in zip(input_workspaces, peak_workspaces):
if multi_ws:
peaks_ws_name = input_ws + '_' + output_workspace_name
output_workspaces.append(peaks_ws_name)
else:
peaks_ws_name = output_workspace_name
IntegratePeaksMD(InputWorkspace=input_ws,
PeakRadius=peak_radius,
BackgroundInnerRadius=inner_radius,
BackgroundOuterRadius=outer_radius,
PeaksWorkspace=peak_ws,
OutputWorkspace=peaks_ws_name)
if multi_ws:
peaks_ws_name = output_workspace_name
CreatePeaksWorkspace(InstrumentWorkspace=input_workspaces[0],
NumberOfPeaks=0,
OutputWorkspace=peaks_ws_name,
OutputType=mtd[peak_workspaces[0]].id().replace('sWorkspace',''))
CopySample(InputWorkspace=output_workspaces[0],
OutputWorkspace=peaks_ws_name,
CopyName=False,
CopyMaterial=False,
CopyEnvironment=False,
CopyShape=False,
CopyLattice=True)
for peak_ws in output_workspaces:
CombinePeaksWorkspaces(peaks_ws_name, peak_ws, OutputWorkspace=peaks_ws_name)
DeleteWorkspace(peak_ws)
if use_lorentz:
# Apply Lorentz correction:
peaks = AnalysisDataService[peaks_ws_name]
for p in range(peaks.getNumberPeaks()):
peak = peaks.getPeak(p)
lorentz = abs(np.sin(peak.getScattering()) * np.cos(peak.getAzimuthal()))
peak.setIntensity(peak.getIntensity() * lorentz)
peak.setSigmaIntensity(peak.getSigmaIntensity() * lorentz)
if remove_0_intensity:
FilterPeaks(InputWorkspace=peaks_ws_name, OutputWorkspace=peaks_ws_name,
FilterVariable='Intensity', FilterValue=0, Operator='>')
# Write output only if a file path was provided
if not self.getProperty("OutputFile").isDefault:
out_format = self.getProperty("OutputFormat").value
filename = self.getProperty("OutputFile").value
if out_format == "SHELX":
SaveHKL(InputWorkspace=peaks_ws_name, Filename=filename, DirectionCosines=True, OutputWorkspace="__tmp")
DeleteWorkspace("__tmp")
elif out_format == "Fullprof":
SaveReflections(InputWorkspace=peaks_ws_name, Filename=filename, Format="Fullprof")
else:
# This shouldn't happen
RuntimeError("Invalid output format given")
self.setProperty("OutputWorkspace", AnalysisDataService[peaks_ws_name])
def _expand_groups(self):
"""expand workspace groups"""
workspaces = self.getProperty("InputWorkspace").value
input_workspaces = []
for wsname in workspaces:
wks = AnalysisDataService.retrieve(wsname)
if isinstance(wks, WorkspaceGroup):
input_workspaces.extend(wks.getNames())
else:
input_workspaces.append(wsname)
workspaces = self.getProperty("PeaksWorkspace").value
peaks_workspaces = []
for wsname in workspaces:
wks = AnalysisDataService.retrieve(wsname)
if isinstance(wks, WorkspaceGroup):
peaks_workspaces.extend(wks.getNames())
else:
peaks_workspaces.append(wsname)
return input_workspaces, peaks_workspaces
AlgorithmFactory.subscribe(HB3AIntegratePeaks)