def endScan(self):
session.experiment.data.finishScan()
try:
from nicos.core.data import ScanData
session.elogEvent('scanend', ScanData(self.dataset))
except Exception:
session.log.debug('could not add scan to electronic logbook',
exc=1)
session.breakpoint(1)
def getdataset(self, index):
"""Get one or more datasets.
:param index: (int) index of the dataset or '*' for all datasets
:returns: a list of datasets if index is '*', or a single dataset
otherwise; or None if the dataset does not exist
"""
if index == '*':
try:
self.send_ok_reply([ScanData(s) for s in
session.experiment.data.getLastScans()])
# session.experiment may be None or a stub
except (AttributeError, ConfigurationError):
self.send_ok_reply(None)
else:
index = int(index)
try:
dataset = ScanData(session.experiment.data.getLastScans()[index])
self.send_ok_reply(dataset)
except (IndexError, AttributeError, ConfigurationError):
self.send_ok_reply(None)
def test_scan_gen_elog(session):
m = session.getDevice('motor')
mm = session.getDevice('manual')
mm.move(0)
session.experiment.setDetectors([session.getDevice('det')])
try:
# plain scan, with some extras: infostring, firstmove
scan(m, 0, 1, 5, 0., 'test scan', manual=1)
dataset = ScanData(session.experiment.data.getLastScans()[-1])
genplot.plotDataset(dataset, path.join(runtime_root, 'testplt'), 'svg')
finally:
session.experiment.detlist = []
def _combine(self, op, sets):
if op == TOGETHER:
newset = ScanData()
newset.name = combineattr(sets, 'name', sep=', ')
newset.invisible = False
newset.curves = []
newset.scaninfo = 'combined set'
# combine xnameunits from those that are in all sets
all_xnu = set(sets[0].xnameunits)
for dset in sets[1:]:
all_xnu &= set(dset.xnameunits)
newset.xnameunits = ['Default'] + [xnu for xnu in sets[0].xnameunits
if xnu in all_xnu]
newset.default_xname = 'Default'
newset.normindices = sets[0].normindices
# for together only, the number of curves and their columns
# are irrelevant, just put all together
for dataset in sets:
for curve in dataset.curves:
newcurve = curve.copy()
if not newcurve.source:
newcurve.source = dataset.name
newset.curves.append(newcurve)
self.data.add_existing_dataset(newset, [dataset.uid for dataset in sets])
return newset.uid
# else, need same axes, and same number and types of curves
firstset = sets[0]
nameprops = [firstset.xnames, firstset.xunits]
curveprops = [(curve.description, curve.yindex)
for curve in firstset.curves]
for dataset in sets[1:]:
if [dataset.xnames, dataset.xunits] != nameprops:
self.showError('Sets have different axes.')
return
if [(curve.description, curve.yindex)
for curve in dataset.curves] != curveprops:
self.showError('Sets have different curves.')
return
if op == COMBINE:
newset = ScanData()
newset.name = combineattr(sets, 'name', sep=', ')
newset.invisible = False
newset.curves = []
newset.scaninfo = 'combined set'
newset.xnameunits = firstset.xnameunits
newset.default_xname = firstset.default_xname
newset.normindices = firstset.normindices
for curves in zip(*(dataset.curves for dataset in sets)):
newcurve = curves[0].copy()
newcurve.datay = DataProxy(c.datay for c in curves)
newcurve.datady = DataProxy(c.datady for c in curves)
newcurve.datax = {xnu: DataProxy(c.datax[xnu] for c in curves)
for xnu in newset.xnameunits}
newcurve.datanorm = {nn: DataProxy(c.datanorm[nn] for c in curves)
for i, nn in newset.normindices}
newset.curves.append(newcurve)
self.data.add_existing_dataset(newset,
[dataset.uid for dataset in sets])
return newset.uid
if op == ADD:
sep = ' + '
elif op == SUBTRACT:
sep = ' - '
elif op == DIVIDE:
sep = ' / '
newset = ScanData()
newset.name = combineattr(sets, 'name', sep=sep)
newset.invisible = False
newset.scaninfo = 'combined set'
newset.curves = []
newset.xnameunits = firstset.xnameunits
newset.default_xname = firstset.default_xname
if op in (SUBTRACT, DIVIDE):
# remove information about normalization -- doesn't make sense
newset.normindices = []
else:
newset.normindices = firstset.normindices
for curves in zip(*(dataset.curves for dataset in sets)):
newcurve = curves[0].deepcopy()
# CRUDE HACK: don't care about the x values, operate by index
removepoints = set()
for curve in curves[1:]:
for i in range(len(newcurve.datay)):
y1, y2 = float(newcurve.datay[i]), float(curve.datay[i])
if newcurve.dyindex != -1:
dy1 = newcurve.datady[i]
dy2 = curve.datady[i]
else:
dy1 = dy2 = 1.
if op == ADD:
newcurve.datay[i] = y1 + y2
newcurve.datady[i] = sqrt(dy1**2 + dy2**2)
for name in newcurve.datanorm:
newcurve.datanorm[name][i] += curve.datanorm[name][i]
elif op == SUBTRACT:
newcurve.datay[i] = y1 - y2
newcurve.datady[i] = sqrt(dy1**2 + dy2**2)
elif op == DIVIDE:
if y2 == 0:
y2 = 1. # generate a value for now
removepoints.add(i)
newcurve.datay[i] = y1 / y2
newcurve.datady[i] = sqrt((dy1/y2)**2 +
(dy2*y1 / y2**2)**2)
# remove points where we would have divided by zero
if removepoints:
newcurve.datay = [v for (i, v) in enumerate(newcurve.datay)
if i not in removepoints]
newcurve.datady = [v for (i, v) in enumerate(newcurve.datady)
if i not in removepoints]
for name in newcurve.datax:
newcurve.datax[name] = \
[v for (i, v) in enumerate(newcurve.datax[name])
if i not in removepoints]
for name in newcurve.datanorm:
newcurve.datanorm[name] = \
[v for (i, v) in enumerate(newcurve.datanorm[name])
if i not in removepoints]
newset.curves.append(newcurve)
self.data.add_existing_dataset(newset)
return newset.uid
def _emitDataset(self):
session.emitfunc('dataset', ScanData(self.dataset))