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HB3APredictPeaks.py
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HB3APredictPeaks.py
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# 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, IMDWorkspaceProperty, IPeaksWorkspaceProperty, PythonAlgorithm, PropertyMode
from mantid.kernel import Direction, FloatPropertyWithValue, StringListValidator, EnabledWhenProperty, PropertyCriterion
from mantid.simpleapi import (PredictPeaks, CloneMDWorkspace,
CopySample, DeleteWorkspace, PredictSatellitePeaks,
HFIRCalculateGoniometer, mtd)
import numpy as np
class HB3APredictPeaks(PythonAlgorithm):
def category(self):
return "Crystal\\Peaks;Crystal\\UBMatrix"
def seeAlso(self):
return ["PredictPeaks", "HB3AFindPeaks", "HB3AIntegratePeaks", "HB3AAdjustSampleNorm", "PredictSatellitePeaks"]
def name(self):
return "HB3APredictPeaks"
def summary(self):
return 'Given a MD workspace in Q-space, and an optional workspace for UB, predict the peaks covering for that data'
def PyInit(self):
self.declareProperty(IMDWorkspaceProperty("InputWorkspace", defaultValue="", optional=PropertyMode.Mandatory,
direction=Direction.Input),
doc="Input MD workspace (in Q-space) to use for peak prediction")
self.declareProperty(IPeaksWorkspaceProperty("UBWorkspace", defaultValue="", optional=PropertyMode.Optional,
direction=Direction.Input),
doc="PeaksWorkspace with UB matrix to use, if non is provided the UB from the InputWorkspace is used")
self.declareProperty(name="ReflectionCondition",
defaultValue="Primitive",
direction=Direction.Input,
validator=StringListValidator(
["Primitive",
"C-face centred",
"A-face centred",
"B-face centred",
"Body centred",
"All-face centred",
"Rhombohedrally centred, obverse",
"Rhombohedrally centred, reverse",
"Hexagonally centred, reverse"]),
doc="Reflection condition for Predicted Peaks.")
self.declareProperty("Wavelength", FloatPropertyWithValue.EMPTY_DBL,
doc="Wavelength value to use only if one was not found in the sample log")
self.declareProperty("SatellitePeaks", False, "If to Predict Satellite Peaks")
condition = EnabledWhenProperty("SatellitePeaks", PropertyCriterion.IsNotDefault)
self.declareProperty("ModVector1", "0.0,0.0,0.0", "Offsets for h, k, l directions")
self.declareProperty("ModVector2", "0.0,0.0,0.0", "Offsets for h, k, l directions")
self.declareProperty("ModVector3", "0.0,0.0,0.0", "Offsets for h, k, l directions")
self.declareProperty("MaxOrder", 0, "Maximum order to apply ModVectors. Default = 0")
self.declareProperty("GetModVectorsFromUB", False, "If false Modulation Vectors will be read from input")
self.declareProperty("CrossTerms", False, "Include cross terms (false)")
self.declareProperty("IncludeIntegerHKL", True, "If false order 0 peaks are not included in workspace (integer HKL)")
self.declareProperty("MinDSpacing", 1.0, "Minimum d-spacing of peaks to consider. Default = 1")
self.declareProperty("MaxDSpacing", 100.0, "Maximum d-spacing of peaks to consider. Default = 100")
self.setPropertySettings("ModVector1", condition)
self.setPropertySettings("ModVector2", condition)
self.setPropertySettings("ModVector3", condition)
self.setPropertySettings("MaxOrder", condition)
self.setPropertySettings("GetModVectorsFromUB", condition)
self.setPropertySettings("CrossTerms", condition)
self.setPropertySettings("IncludeIntegerHKL", condition)
self.declareProperty(IPeaksWorkspaceProperty("OutputWorkspace", defaultValue="", direction=Direction.Output,
optional=PropertyMode.Mandatory), doc="Output peaks workspace")
def validateInputs(self):
issues = dict()
input_ws = self.getProperty("InputWorkspace").value
if input_ws.getSpecialCoordinateSystem().name != "QSample":
issues["InputWorkspace"] = "Input workspace expected to be in QSample, " \
"workspace is in '{}'".format(input_ws.getSpecialCoordinateSystem().name)
elif input_ws.getNumDims() != 3:
issues["InputWorkspace"] = "Workspace has the wrong number of dimensions"
wavelength = self.getProperty("Wavelength")
if not wavelength.isDefault:
if wavelength.value <= 0.0:
issues['Wavelength'] = "Wavelength should be greater than zero"
return issues
def PyExec(self):
input_ws = self.getProperty("InputWorkspace").value
ub_ws = self.getProperty("UBWorkspace").value
output_ws = self.getProperty("OutputWorkspace").valueAsStr
reflection_condition = self.getProperty("ReflectionCondition").value
# Whether to use the inner goniometer depending on omega and phi in sample logs
use_inner = False
min_angle = None
max_angle = None
wavelength = 0.0
if input_ws.getNumExperimentInfo() == 0:
# Warn if we could extract a wavelength from the workspace
raise RuntimeWarning("No experiment info was found in input '{}'".format(input_ws.getName()))
exp_info = input_ws.getExperimentInfo(0)
if exp_info.run().hasProperty("wavelength"):
wavelength = exp_info.run().getProperty("wavelength").value
if exp_info.run().hasProperty("omega") and exp_info.run().hasProperty("phi"):
gon = exp_info.run().getGoniometer().getEulerAngles('YZY')
if np.isclose(exp_info.run().getTimeAveragedStd("omega"), 0.0):
use_inner = True
min_angle = -exp_info.run().getLogData('phi').value.max()
max_angle = -exp_info.run().getLogData('phi').value.min()
# Sometimes you get the 180 degrees off what is expected from the log
phi_log = -exp_info.run().getLogData('phi').value[0]
if np.isclose(phi_log + 180, gon[2]):
min_angle += 180
max_angle += 180
elif np.isclose(phi_log - 180, gon[2]):
min_angle -= 180
max_angle -= 180
elif np.isclose(exp_info.run().getTimeAveragedStd("phi"), 0.0):
use_inner = False
min_angle = -exp_info.run().getLogData('omega').value.max()
max_angle = -exp_info.run().getLogData('omega').value.min()
# Sometimes you get the 180 degrees off what is expected from the log
omega_log = -exp_info.run().getLogData('omega').value[0]
if np.isclose(omega_log + 180, gon[0]):
min_angle += 180
max_angle += 180
elif np.isclose(omega_log - 180, gon[0]):
min_angle -= 180
max_angle -= 180
else:
self.log().warning("No appropriate goniometer rotation found, try anyway")
self.log().information("Using inner goniometer: {}".format(use_inner))
if not self.getProperty("Wavelength").isDefault:
wavelength = self.getProperty("Wavelength").value
elif wavelength == 0:
raise RuntimeWarning("No wavelength found, you need to provide one")
# temporary set UB on workspace if one is provided by UBWorkspace
tmp_ws_name = '__HB3APredictPeaks_UB_tmp'
if ub_ws is not None:
input_ws = CloneMDWorkspace(InputWorkspace=input_ws,
OutputWorkspace=tmp_ws_name)
CopySample(InputWorkspace=ub_ws,
OutputWorkspace=tmp_ws_name,
CopyName=False,
CopyMaterial=False,
CopyEnvironment=False,
CopyShape=False,
CopyLattice=True)
if self.getProperty("SatellitePeaks").value:
peaks = PredictPeaks(InputWorkspace=input_ws,
ReflectionCondition=reflection_condition,
MinDSpacing=self.getProperty("MinDSpacing").value,
MaxDSpacing=self.getProperty("MaxDSpacing").value,
OutputType='LeanElasticPeak',
CalculateWavelength=False,
OutputWorkspace=output_ws)
peaks = PredictSatellitePeaks(peaks,
ModVector1=self.getProperty("ModVector1").value,
ModVector2=self.getProperty("ModVector2").value,
ModVector3=self.getProperty("ModVector3").value,
MaxOrder=self.getProperty("MaxOrder").value,
GetModVectorsFromUB=self.getProperty("GetModVectorsFromUB").value,
CrossTerms=self.getProperty("CrossTerms").value,
IncludeIntegerHKL=self.getProperty("IncludeIntegerHKL").value,
MinDSpacing=self.getProperty("MinDSpacing").value,
MaxDSpacing=self.getProperty("MaxDSpacing").value,
SatellitePeaks=output_ws)
HFIRCalculateGoniometer(peaks, Wavelength=wavelength)
else:
peaks = PredictPeaks(InputWorkspace=input_ws,
ReflectionCondition=reflection_condition,
CalculateGoniometerForCW=True,
Wavelength=wavelength,
FlipX=True,
InnerGoniometer=use_inner,
MinAngle=min_angle,
MaxAngle=max_angle,
MinDSpacing=self.getProperty("MinDSpacing").value,
MaxDSpacing=self.getProperty("MaxDSpacing").value,
OutputWorkspace=output_ws)
# delete tmp workspace
if mtd.doesExist(tmp_ws_name):
DeleteWorkspace(tmp_ws_name)
self.setProperty("OutputWorkspace", peaks)
AlgorithmFactory.subscribe(HB3APredictPeaks)