def reduce(nxsfile,
qaxis,
outfile,
use_ei_guess=False,
ei_guess=None,
eaxis=None,
tof2E=True,
ibnorm='ByCurrent'):
"""reduce a NeXus file to a I(Q,E) histogram using Mantid
This is a wrapper of Mantid algorithms to reduce a NeXus file to IQE histogram.
Parameters
----------
nxsfile: str
path to nxs file
qaxis: 3-tuple of floats
Momentum transfer axis. (Qmin, dQ, Qmax). unit: inverse angstrom
outfile: str
path to save nxs data
use_ei_guess: boolean
Use incident energy guess
ei_guess: float
Initial guess of incident energy (meV)
eaxis: 3-tuple of floats
Energy transfer axis. (Emin, dE, Emax). unit: meV
tof2E: boolean
Conversion from time of flight axis to energy axis or not.
If the NeXus file is in time of flight, tof2E=True
If the NeXus file is processed and in energy transfer, tof2E=False
ibnorm: str
Incident beam normalization choice. Allowed values: None, ByCurrent, ToMonitor
For more details, see http://docs.mantidproject.org/nightly/algorithms/DgsReduction-v1.html
"""
from mantid.simpleapi import DgsReduction, SaveNexus, Load
from mantid import mtd
import mantid.simpleapi as msa
if tof2E == 'guess':
# XXX: this is a simple guess. all raw data files seem to have root "entry"
cmd = 'h5ls %s' % nxsfile
import subprocess as sp, shlex
o = sp.check_output(shlex.split(cmd)).strip().split()[0]
tof2E = o == 'entry'
if tof2E:
if use_ei_guess:
DgsReduction(
SampleInputFile=nxsfile,
IncidentEnergyGuess=ei_guess,
UseIncidentEnergyGuess=use_ei_guess,
OutputWorkspace='reduced',
EnergyTransferRange=eaxis,
IncidentBeamNormalisation=ibnorm,
)
else:
DgsReduction(
SampleInputFile=nxsfile,
OutputWorkspace='reduced',
EnergyTransferRange=eaxis,
IncidentBeamNormalisation=ibnorm,
)
reduced = mtd['reduced']
else:
reduced = Load(nxsfile)
# get eaxis info from mtd workspace, if necessary
if eaxis is None:
Edim = reduced.getXDimension()
emin = Edim.getMinimum()
emax = Edim.getMaximum()
de = Edim.getX(1) - Edim.getX(0)
eaxis = emin, de, emax
qmin, dq, qmax = qaxis
nq = int((qmax - qmin + dq / 2.) / dq)
emin, de, emax = eaxis
ne = int((emax - emin + de / 2.) / de)
#
md = msa.ConvertToMD(
InputWorkspace=reduced,
QDimensions='|Q|',
dEAnalysisMode='Direct',
MinValues="%s,%s" % (qmin, emin),
MaxValues="%s,%s" % (qmax, emax),
)
binned = msa.BinMD(
InputWorkspace=md,
AxisAligned=1,
AlignedDim0="|Q|,%s,%s,%s" % (qmin, qmax, nq),
AlignedDim1="DeltaE,%s,%s,%s" % (emin, emax, ne),
)
# create histogram
import histogram as H, histogram.hdf as hh
data = binned.getSignalArray().copy()
err2 = binned.getErrorSquaredArray().copy()
nev = binned.getNumEventsArray()
data /= nev
err2 /= (nev * nev)
import numpy as np
qaxis = H.axis('Q',
boundaries=np.arange(qmin, qmax + dq / 2., dq),
unit='1./angstrom')
eaxis = H.axis('E',
boundaries=np.arange(emin, emax + de / 2., de),
unit='meV')
hist = H.histogram('IQE', (qaxis, eaxis), data=data, errors=err2)
if outfile.endswith('.nxs'):
import warnings
warnings.warn(
"reduce function no longer writes iqe.nxs nexus file. it only writes iqe.h5 histogram file"
)
outfile = outfile[:-4] + '.h5'
hh.dump(hist, outfile)
return hist
def reduce(nxsfile,
qaxis,
outfile,
use_ei_guess=False,
ei_guess=None,
eaxis=None,
tof2E=True,
ibnorm='ByCurrent'):
from mantid.simpleapi import DgsReduction, SofQW3, SaveNexus, LoadInstrument, Load, MoveInstrumentComponent, \
MaskBTP, ConvertToMD, BinMD, ConvertMDHistoToMatrixWorkspace, GetEiT0atSNS, GetEi
from mantid import mtd
ws = Load(nxsfile)
if tof2E == 'guess':
axis = ws.getAxis(0).getUnit().caption().lower()
# axis name should be "Time-of-flight"
tof2E = "time" in axis and "flight" in axis
if tof2E:
# mask packs around beam
# MaskBTP(ws, Bank="98-102")
if not use_ei_guess:
run = ws.getRun()
Efixed = run.getLogData('mcvine-Ei').value
T0 = run.getLogData('mcvine-t0').value
else:
Efixed, T0 = ei_guess, 0
DgsReduction(
SampleInputWorkspace=ws,
IncidentEnergyGuess=Efixed,
UseIncidentEnergyGuess=True,
TimeZeroGuess=T0,
OutputWorkspace='reduced',
EnergyTransferRange=eaxis,
IncidentBeamNormalisation=ibnorm,
)
reduced = mtd['reduced']
else:
reduced = Load(nxsfile)
# if eaxis is not specified, use the data in reduced workspace
if eaxis is None:
Edim = reduced.getXDimension()
emin = Edim.getMinimum()
emax = Edim.getMaximum()
de = Edim.getX(1) - Edim.getX(0)
eaxis = emin, de, emax
qmin, dq, qmax = qaxis
nq = int(round((qmax - qmin) / dq))
emin, de, emax = eaxis
ne = int(round((emax - emin) / de))
md = ConvertToMD(
InputWorkspace='reduced',
QDimensions='|Q|',
dEAnalysisMode='Direct',
MinValues="%s,%s" % (qmin, emin),
MaxValues="%s,%s" % (qmax, emax),
SplitInto="%s,%s" % (nq, ne),
)
binned = BinMD(
InputWorkspace=md,
AxisAligned=1,
AlignedDim0="|Q|,%s,%s,%s" % (qmin, qmax, nq),
AlignedDim1="DeltaE,%s,%s,%s" % (emin, emax, ne),
)
# convert to histogram
import histogram as H, histogram.hdf as hh
data = binned.getSignalArray().copy()
err2 = binned.getErrorSquaredArray().copy()
nev = binned.getNumEventsArray()
data /= nev
err2 /= (nev * nev)
qaxis = H.axis('Q',
boundaries=np.arange(qmin, qmax + dq / 2., dq),
unit='1./angstrom')
eaxis = H.axis('E',
boundaries=np.arange(emin, emax + de / 2., de),
unit='meV')
hist = H.histogram('IQE', (qaxis, eaxis), data=data, errors=err2)
if outfile.endswith('.nxs'):
import warnings
warnings.warn(
"reduce function no longer writes iqe.nxs nexus file. it only writes iqe.h5 histogram file"
)
outfile = outfile[:-4] + '.h5'
hh.dump(hist, outfile)
return
