From 7a6f4559e5c42d4d7fd6e956bba3fdbaaffc20bb Mon Sep 17 00:00:00 2001
From: Ross Whitfield <whitfieldre@ornl.gov>
Date: Tue, 5 Nov 2019 13:36:14 -0500
Subject: [PATCH] Get ConvertWANDSCDtoQ working with HB3A data
---
.../plugins/algorithms/ConvertWANDSCDtoQ.py | 92 +++++++++++++++----
1 file changed, 73 insertions(+), 19 deletions(-)
diff --git a/Framework/PythonInterface/plugins/algorithms/ConvertWANDSCDtoQ.py b/Framework/PythonInterface/plugins/algorithms/ConvertWANDSCDtoQ.py
index c1c653d6ced..6aca2fe5031 100644
--- a/Framework/PythonInterface/plugins/algorithms/ConvertWANDSCDtoQ.py
+++ b/Framework/PythonInterface/plugins/algorithms/ConvertWANDSCDtoQ.py
@@ -75,6 +75,7 @@ class ConvertWANDSCDtoQ(PythonAlgorithm):
issues = dict()
inWS = self.getProperty("InputWorkspace").value
+ instrument = inWS.getExperimentInfo(0).getInstrument().getName()
if inWS.getNumDims() != 3:
issues["InputWorkspace"] = "InputWorkspace has wrong number of dimensions, need 3"
@@ -95,21 +96,29 @@ class ConvertWANDSCDtoQ(PythonAlgorithm):
# Check that all logs are there and are of correct length
run = inWS.getExperimentInfo(0).run()
- for prop in ['duration', 'monitor_count', 's1']:
- if run.hasProperty(prop):
- p = run.getProperty(prop).value
- if np.size(p) != number_of_runs:
- issues["InputWorkspace"] = "log {} is of incorrect length".format(prop)
- else:
- issues["InputWorkspace"] = "missing log {}".format(prop)
+
+ if instrument == "HB3A":
+ for prop in ['omega', 'chi', 'phi', 'monitor', 'time']:
+ if run.hasProperty(prop):
+ p = run.getProperty(prop).value
+ if np.size(p) != number_of_runs:
+ issues["InputWorkspace"] = "log {} is of incorrect length".format(prop)
+ else:
+ issues["InputWorkspace"] = "missing log {}".format(prop)
+ else:
+ for prop in ['duration', 'monitor_count', 's1']:
+ if run.hasProperty(prop):
+ p = run.getProperty(prop).value
+ if np.size(p) != number_of_runs:
+ issues["InputWorkspace"] = "log {} is of incorrect length".format(prop)
+ else:
+ issues["InputWorkspace"] = "missing log {}".format(prop)
for prop in ['azimuthal', 'twotheta']:
if run.hasProperty(prop):
p = run.getProperty(prop).value
if np.size(p) != d0.getNBins()*d1.getNBins():
issues["InputWorkspace"] = "log {} is of incorrect length".format(prop)
- else:
- issues["InputWorkspace"] = "missing log {}".format(prop)
normWS = self.getProperty("NormalisationWorkspace").value
@@ -143,6 +152,8 @@ class ConvertWANDSCDtoQ(PythonAlgorithm):
normWS = self.getProperty("NormalisationWorkspace").value
_norm = bool(normWS)
+ instrument = inWS.getExperimentInfo(0).getInstrument().getName()
+
dim0_min, dim0_max, dim0_bins = self.getProperty('BinningDim0').value
dim1_min, dim1_max, dim1_bins = self.getProperty('BinningDim1').value
dim2_min, dim2_max, dim2_bins = self.getProperty('BinningDim2').value
@@ -160,21 +171,38 @@ class ConvertWANDSCDtoQ(PythonAlgorithm):
progress = Progress(self, 0.0, 1.0, number_of_runs+4)
# Get rotation array
- s1 = np.deg2rad(inWS.getExperimentInfo(0).run().getProperty('s1').value) + np.deg2rad(self.getProperty("S1Offset").value)
+ if instrument == "HB3A":
+ omega = np.deg2rad(inWS.getExperimentInfo(0).run().getProperty('omega').value)
+ chi = np.deg2rad(inWS.getExperimentInfo(0).run().getProperty('chi').value)
+ phi = np.deg2rad(inWS.getExperimentInfo(0).run().getProperty('phi').value)
+ else:
+ s1 = np.deg2rad(inWS.getExperimentInfo(0).run().getProperty('s1').value) + np.deg2rad(self.getProperty("S1Offset").value)
normaliseBy = self.getProperty("NormaliseBy").value
if normaliseBy == "Monitor":
- scale = np.asarray(inWS.getExperimentInfo(0).run().getProperty('monitor_count').value)
+ if instrument == "HB3A":
+ scale = np.asarray(inWS.getExperimentInfo(0).run().getProperty('monitor').value)
+ else:
+ scale = np.asarray(inWS.getExperimentInfo(0).run().getProperty('monitor_count').value)
elif normaliseBy == "Time":
- scale = np.asarray(inWS.getExperimentInfo(0).run().getProperty('duration').value)
+ if instrument == "HB3A":
+ scale = np.asarray(inWS.getExperimentInfo(0).run().getProperty('time').value)
+ else:
+ scale = np.asarray(inWS.getExperimentInfo(0).run().getProperty('duration').value)
else:
scale = np.ones(number_of_runs)
if _norm:
if normaliseBy == "Monitor":
- norm_scale = np.sum(normWS.getExperimentInfo(0).run().getProperty('monitor_count').value)
+ if instrument == "HB3A":
+ norm_scale = np.sum(normWS.getExperimentInfo(0).run().getProperty('monitor').value)
+ else:
+ norm_scale = np.sum(normWS.getExperimentInfo(0).run().getProperty('monitor_count').value)
elif normaliseBy == "Time":
- norm_scale = np.sum(normWS.getExperimentInfo(0).run().getProperty('duration').value)
+ if instrument == "HB3A":
+ norm_scale = np.sum(normWS.getExperimentInfo(0).run().getProperty('time').value)
+ else:
+ norm_scale = np.sum(normWS.getExperimentInfo(0).run().getProperty('duration').value)
else:
norm_scale = 1.
norm_array = normWS.getSignalArray().sum(axis=2)
@@ -213,8 +241,22 @@ class ConvertWANDSCDtoQ(PythonAlgorithm):
k = 2*np.pi/self.getProperty("Wavelength").value
progress.report('Calculating Qlab for each pixel')
- polar = np.array(inWS.getExperimentInfo(0).run().getProperty('twotheta').value)
- azim = np.array(inWS.getExperimentInfo(0).run().getProperty('azimuthal').value)
+ if inWS.getExperimentInfo(0).run().hasProperty('twotheta'):
+ polar = np.array(inWS.getExperimentInfo(0).run().getProperty('twotheta').value)
+ else:
+ di = inWS.getExperimentInfo(0).detectorInfo()
+ polar = np.array([di.twoTheta(i) for i in range(di.size()) if not di.isMonitor(i)])
+ if inWS.getExperimentInfo(0).getInstrument().getName() == 'HB3A':
+ polar = polar.reshape(512*3, 512).T.flatten()
+
+ if inWS.getExperimentInfo(0).run().hasProperty('twotheta'):
+ azim = np.array(inWS.getExperimentInfo(0).run().getProperty('azimuthal').value)
+ else:
+ di = inWS.getExperimentInfo(0).detectorInfo()
+ azim = np.array([di.azimuthal(i) for i in range(di.size()) if not di.isMonitor(i)])
+ if inWS.getExperimentInfo(0).getInstrument().getName() == 'HB3A':
+ azim = azim.reshape(512*3, 512).T.flatten()
+
qlab = np.vstack((np.sin(polar)*np.cos(azim),
np.sin(polar)*np.sin(azim),
np.cos(polar) - 1)).T * -k # Kf - Ki(0,0,1)
@@ -246,9 +288,21 @@ class ConvertWANDSCDtoQ(PythonAlgorithm):
assert data_array[:,:,0].flags.fnc
for n in range(number_of_runs):
- R = np.array([[ np.cos(s1[n]), 0, np.sin(s1[n])],
- [ 0, 1, 0],
- [-np.sin(s1[n]), 0, np.cos(s1[n])]])
+ if instrument == "HB3A":
+ R1 = np.array([[np.cos(omega[n]), 0, -np.sin(omega[n])], # omega 0,1,0,-1
+ [ 0, 1, 0],
+ [np.sin(omega[n]), 0, np.cos(omega[n])]])
+ R2 = np.array([[ np.cos(chi[n]), np.sin(chi[n]), 0], # chi 0,0,1,-1
+ [-np.sin(chi[n]), np.cos(chi[n]), 0],
+ [ 0, 0, 1]])
+ R3 = np.array([[np.cos(phi[n]), 0, -np.sin(phi[n])], # phi 0,1,0,-1
+ [ 0, 1, 0],
+ [np.sin(phi[n]), 0, np.cos(phi[n])]])
+ R = np.dot(np.dot(R1, R2), R3)
+ else:
+ R = np.array([[ np.cos(s1[n]), 0, np.sin(s1[n])], # s1 0,1,0,1
+ [ 0, 1, 0],
+ [-np.sin(s1[n]), 0, np.cos(s1[n])]])
RUBW = np.dot(R,UBW)
q = np.round(np.dot(np.linalg.inv(RUBW),qlab.T)/bin_size-offset).astype(np.int)
q_index = np.ravel_multi_index(q, (dim0_bins+2, dim1_bins+2, dim2_bins+2), mode='clip')
--
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