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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
# SPDX - License - Identifier: GPL - 3.0 +
#pylint: disable=no-init
from __future__ import (absolute_import, division, print_function)
from mantid.api import PythonAlgorithm, AlgorithmFactory, ITableWorkspaceProperty, WorkspaceFactory
from mantid.kernel import Direction
from mantid.simpleapi import *
from mantid import mtd
# Create an empty table workspace to be populated by a python script.
class OptimizeCrystalPlacementByRun(PythonAlgorithm):
def summary(self):
return "Optimizes the sample position for each run in a peaks workspace."
def category(self):
return 'Crystal\\Corrections'
def seeAlso(self):
return [ "OptimizeCrystalPlacement" ]
def PyInit(self):
# Declare properties
self.declareProperty(ITableWorkspaceProperty("InputWorkspace", "", Direction.Input),
"The name of the peaks workspace that will be optimized.")
self.declareProperty("Tolerance", 0.15, "Tolerance of indexing of peaks.")
self.declareProperty(ITableWorkspaceProperty("OutputWorkspace", "", Direction.Output),
"The name of the peaks workspace that will be created.")
def PyExec(self):
ws = self.getProperty("InputWorkspace").value
ws_append = self.getProperty("OutputWorkspace").value
ws_group = 'ws_group'
tolerance = self.getProperty("Tolerance").value
if not ws.sample().hasOrientedLattice():
FindUBUsingIndexedPeaks(PeaksWorkspace=ws,Tolerance=tolerance)
num,err=IndexPeaks(PeaksWorkspace=ws,Tolerance=tolerance)
print('Initial Number indexed: %s error: %s\n'%(num, err))
stats = StatisticsOfTableWorkspace(InputWorkspace=ws)
stat_col = stats.column('Statistic')
minR = int(stats.column('RunNumber')[stat_col.index('Minimum')])
maxR = int(stats.column('RunNumber')[stat_col.index('Maximum')]) + 1
group = []
for run in range(minR, maxR):
FilterPeaks(InputWorkspace=ws, OutputWorkspace=str(run), FilterVariable='RunNumber', FilterValue=run, Operator='=')
run = mtd[str(run)]
peaks = run.getNumberPeaks()
if peaks == 0:
AnalysisDataService.remove( str(run))
else:
group.append(str(run))
GroupWorkspaces(InputWorkspaces=group, OutputWorkspace=ws_group)
OptimizeCrystalPlacement(PeaksWorkspace=ws_group, ModifiedPeaksWorkspace=ws_group, AdjustSampleOffsets=True, MaxSamplePositionChangeMeters=0.005,MaxIndexingError=tolerance)
CloneWorkspace(InputWorkspace=str(minR),OutputWorkspace=ws_append)
for run in range(minR+1, maxR):
if AnalysisDataService.doesExist( str(run)):
CombinePeaksWorkspaces(LHSWorkspace=ws_append, RHSWorkspace=str(run),OutputWorkspace=ws_append)
print('Optimized %s sample position: %s\n'%(str(run),mtd[str(run)].getPeak(0).getSamplePos()))
AnalysisDataService.remove( str(run))
num,err=IndexPeaks(PeaksWorkspace=ws_append,Tolerance=tolerance)
print('After Optimization Number indexed: %s error: %s\n'%(num, err))
AnalysisDataService.remove(ws_group)
self.setProperty("OutputWorkspace", ws_append)
# Register algorithm with Mantid
AlgorithmFactory.subscribe(OptimizeCrystalPlacementByRun)