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DNSMergeRuns.py
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DNSMergeRuns.py
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# Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 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 +
import mantid.simpleapi as api
from mantid.api import PythonAlgorithm, AlgorithmFactory, MatrixWorkspace, MatrixWorkspaceProperty, WorkspaceGroup
from mantid.kernel import Direction, StringArrayProperty, StringListValidator, V3D, StringArrayLengthValidator
import numpy as np
class DNSMergeRuns(PythonAlgorithm):
"""
Merges given runs into one matrix workspace.
This algorithm is written for the DNS @ MLZ,
but can be adjusted for other instruments if needed.
"""
properties_to_compare = [
"omega",
"slit_i_left_blade_position",
"slit_i_right_blade_position",
"slit_i_lower_blade_position",
"slit_i_upper_blade_position",
"polarisation",
"polarisation_comment",
"flipper",
]
def __init__(self):
"""
Init
"""
PythonAlgorithm.__init__(self)
self.workspace_names = []
self.xaxis = "2theta"
self.outws_name = None
def category(self):
"""
Returns category
"""
return "Workflow\\MLZ\\DNS"
def seeAlso(self):
return ["LoadDNSLegacy"]
def name(self):
"""
Returns name
"""
return "DNSMergeRuns"
def summary(self):
return "Merges runs performed at different detector bank positions into one matrix workspace."
def PyInit(self):
validator = StringArrayLengthValidator()
validator.setLengthMin(1) # group of workspaces may be given
self.declareProperty(
StringArrayProperty(name="WorkspaceNames", direction=Direction.Input, validator=validator),
doc="List of Workspace names to merge.",
)
self.declareProperty(
MatrixWorkspaceProperty("OutputWorkspace", "", direction=Direction.Output), doc="A workspace name to save the merged data."
)
H_AXIS = ["2theta", "|Q|", "d-Spacing"]
self.declareProperty("HorizontalAxis", "2theta", StringListValidator(H_AXIS), doc="X axis in the merged workspace")
return
def _expand_groups(self, input_list):
"""
returns names of the grouped workspaces
"""
workspaces = []
for wsname in input_list:
wks = api.AnalysisDataService.retrieve(wsname)
if isinstance(wks, WorkspaceGroup):
workspaces.extend(wks.getNames())
else:
workspaces.append(wsname)
self.log().notice("Workspaces: " + str(workspaces))
return workspaces
def validateInputs(self):
issues = dict()
input_list = self.getProperty("WorkspaceNames").value
for wsname in input_list:
if not api.AnalysisDataService.doesExist(wsname):
issues["WorkspaceNames"] = "Workspace " + wsname + " does not exist"
workspace_names = self._expand_groups(input_list)
if len(workspace_names) < 2:
issues["WorkspaceNames"] = "At least 2 workspaces required."
else:
# workspaces must have the same wavelength and normalization
result = api.CompareSampleLogs(workspace_names, "wavelength,normalized", 0.01)
if len(result) > 0:
issues["WorkspaceNames"] = "Cannot merge workspaces with different " + result
# All workspaces must have a MatrixWorkspace type
for wsname in workspace_names:
wks = api.AnalysisDataService.retrieve(wsname)
if not isinstance(wks, MatrixWorkspace):
issues["WorkspaceNames"] = "The Workspaces provided must all be of type 'MatrixWorkspace'"
return issues
ws0 = api.AnalysisDataService.retrieve(workspace_names[0])
ndims = ws0.getNumDims()
nhists = ws0.getNumberHistograms()
nblocks = ws0.blocksize()
# workspaces must exist and have the same dimensions
for wsname in workspace_names[1:]:
wks = api.AnalysisDataService.retrieve(wsname)
if wks.getNumDims() != ndims:
issues["WorkspaceNames"] = "Number of dimensions for workspace " + wks.name() + " does not match to one for " + ws0.name()
if wks.getNumberHistograms() != nhists:
issues["WorkspaceNames"] = "Number of histohrams for workspace " + wks.name() + " does not match to one for " + ws0.name()
if wks.blocksize() != nblocks:
issues["WorkspaceNames"] = "Number of blocks for workspace " + wks.name() + " does not match to one for " + ws0.name()
return issues
def _merge_workspaces(self):
"""
merges given workspaces into one
@param norm If True, normalization workspaces will be merged
"""
arr = []
beamDirection = V3D(0, 0, 1)
# merge workspaces, existance has been checked by _can_merge function
for ws_name in self.workspace_names:
wks = api.AnalysisDataService.retrieve(ws_name)
samplePos = wks.getInstrument().getSample().getPos()
n_hists = wks.getNumberHistograms()
two_theta = np.array([wks.getDetector(i).getTwoTheta(samplePos, beamDirection) for i in range(0, n_hists)])
# round to approximate hardware accuracy 0.05 degree ~ 1 mrad
two_theta = np.round(two_theta, 4)
dataY = np.rot90(wks.extractY())[0]
dataE = np.rot90(wks.extractE())[0]
for i in range(n_hists):
arr.append([two_theta[i], dataY[i], dataE[i]])
data = np.array(arr)
# sum up intensities for dublicated angles
data_sorted = data[np.argsort(data[:, 0])]
# unique values
unX = np.unique(data_sorted[:, 0])
if len(data_sorted[:, 0]) - len(unX) > 0:
arr = []
self.log().information("There are dublicated 2Theta angles in the dataset. Sum up the intensities.")
# we must sum up the values
for i in range(len(unX)):
idx = np.where(np.fabs(data_sorted[:, 0] - unX[i]) < 1e-4)
new_y = sum(data_sorted[idx][:, 1])
err = data_sorted[idx][:, 2]
new_e = np.sqrt(np.dot(err, err))
arr.append([unX[i], new_y, new_e])
data = np.array(arr)
# define x axis
wks = api.AnalysisDataService.retrieve(self.workspace_names[0])
wavelength = wks.getRun().getProperty("wavelength").value
if self.xaxis == "2theta":
data[:, 0] = np.round(np.degrees(data[:, 0]), 2)
unitx = "Degrees"
elif self.xaxis == "|Q|":
data[:, 0] = np.fabs(4.0 * np.pi * np.sin(0.5 * data[:, 0]) / wavelength)
unitx = "MomentumTransfer"
elif self.xaxis == "d-Spacing":
data[:, 0] = np.fabs(0.5 * wavelength / np.sin(0.5 * data[:, 0]))
unitx = "dSpacing"
else:
message = "The value for X axis " + self.xaxis + " is invalid! Cannot merge."
self.log().error(message)
raise RuntimeError(message)
data_sorted = data[np.argsort(data[:, 0])]
api.CreateWorkspace(
dataX=data_sorted[:, 0], dataY=data_sorted[:, 1], dataE=data_sorted[:, 2], UnitX=unitx, OutputWorkspace=self.outws_name
)
outws = api.AnalysisDataService.retrieve(self.outws_name)
# assume that all input workspaces have the same YUnits and YUnitLabel
wks = api.AnalysisDataService.retrieve(self.workspace_names[0])
outws.setYUnit(wks.YUnit())
outws.setYUnitLabel(wks.YUnitLabel())
return
def PyExec(self):
# Input
input_list = self.getProperty("WorkspaceNames").value
self.outws_name = self.getProperty("OutputWorkspace").valueAsStr
self.xaxis = self.getProperty("HorizontalAxis").value
self.workspace_names = self._expand_groups(input_list)
self.log().information("Workspaces to merge: %i" % (len(self.workspace_names)))
# produce warnings is some optional sample logs do not match
result = api.CompareSampleLogs(self.workspace_names, self.properties_to_compare, 1e-2)
self._merge_workspaces()
outws = api.AnalysisDataService.retrieve(self.outws_name)
api.CopyLogs(self.workspace_names[0], outws)
# remove logs which do not match
if result:
api.RemoveLogs(outws, result)
self.setProperty("OutputWorkspace", outws)
return
# Register algorithm with Mantid
AlgorithmFactory.subscribe(DNSMergeRuns)