def test_qtohkl_corelli(self):
Load(Filename='CORELLI_29782.nxs', OutputWorkspace='data')
SetGoniometer(Workspace='data', Axis0='BL9:Mot:Sample:Axis1,0,1,0,1')
LoadIsawUB(InputWorkspace='data',
Filename='SingleCrystalDiffuseReduction_UB.mat')
ConvertToMD(InputWorkspace='data',
QDimensions='Q3D',
dEAnalysisMode='Elastic',
Q3DFrames='HKL',
QConversionScales='HKL',
OutputWorkspace='HKL',
Uproj='1,1,0',
Vproj='1,-1,0',
Wproj='0,0,1',
MinValues='-20,-20,-20',
MaxValues='20,20,20')
hkl_binned = BinMD('HKL',
AlignedDim0='[H,H,0],-10.05,10.05,201',
AlignedDim1='[H,-H,0],-10.05,10.05,201',
AlignedDim2='[0,0,L],-1.05,1.05,21')
ConvertToMD(InputWorkspace='data',
QDimensions='Q3D',
dEAnalysisMode='Elastic',
Q3DFrames='Q_sample',
OutputWorkspace='q_sample',
MinValues='-20,-20,-20',
MaxValues='20,20,20')
hkl = ConvertQtoHKLMDHisto(
InputWorkspace=mtd["q_sample"],
Uproj="1,1,0",
Vproj="1,-1,0",
Wproj="0,0,1",
Extents="-10.05,10.05,-10.05,10.05,-1.05,1.05",
Bins="201,201,21")
for i in range(hkl.getNumDims()):
self.assertEqual(
hkl_binned.getDimension(i).name,
hkl.getDimension(i).name)
orig_sig = hkl_binned.getSignalArray()
new_sig = hkl.getSignalArray()
np.testing.assert_allclose(np.asarray(new_sig),
np.asarray(orig_sig),
rtol=1.0e-5,
atol=3)
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
data, norm = MDNormSCD(InputWorkspace=mde,
FluxWorkspace=fl,
SolidAngleWorkspace=sa,
SkipSafetyCheck=True,
AlignedDim0=AlignedDim0,
AlignedDim1=AlignedDim1,
AlignedDim2=AlignedDim2)
mdh = data / norm
else:
mdh = BinMD(InputWorkspace=mde,
AlignedDim0=AlignedDim0,
AlignedDim1=AlignedDim1,
AlignedDim2=AlignedDim2,
AxisAligned=True)
intensity = mdh.getSignalArray()
vmin = 1
vmax = intensity.max()
if vmax > 1:
fig, ax = plt.subplots()
ax.set_title('{}=[{},{}]'.format(AxisNames[plot_param['axis3']],
plot_zmin, plot_zmax))
logNorm = colors.LogNorm(vmin=vmin, vmax=vmax)
cm = plt.cm.get_cmap('rainbow')
pcm = Plot2DMD(ax, mdh, NumEvNorm=False, norm=logNorm)
fig.colorbar(pcm, ax=ax)
#plotSlice(mdws, xydim=[plot_param['axis1'],plot_param['axis2']], slicepoint=[0,0,0.5*(plot_param['zmin']+plot_param['zmax'])], colorscalelog=True)
plt.show()
except Exception as e:
logger.error("Could not find UB: " + str(e))
SetGoniometer(ws2, Axis0="BL9:Mot:Sample:Axis2,0,1,0,1")
md1 = ConvertToMD(ws1,
QDimensions='Q3D',
dEAnalysisMode='Elastic',
Q3DFrames='Q_sample',
MinValues=[-10, -10, -10],
MaxValues=[10, 10, 10])
bin1 = BinMD(md1,
AlignedDim0='Q_sample_x,-10,10,1000',
AlignedDim1='Q_sample_z,-10,10,1000',
AlignedDim2='Q_sample_y,-10,10,1')
bin1 /= ws1.run().getProtonCharge()
s1 = bin1.getSignalArray().copy()
x = np.linspace(-1, 1, 1000)
X, Y = np.meshgrid(x, x)
mask = (X**2 + Y**2 > 1) + (X**2 + Y**2 < 0.25)
s1[mask] = 0
s1_mask = s1 < np.percentile(s1, 99.5)
mask[s1_mask[:, :, 0]] = True
s1[mask] = np.nan
start = ws2.getRun().getLogData('BL9:Mot:Sample:Axis2.RBV').value.mean()