def __load_experiment_data__():
basename = sicsext.getBaseFilename()
fullname = str(System.getProperty('sics.data.path') + '/' + basename)
df.datasets.clear()
ds = df[fullname]
data = ds[str(data_name.value)]
axis = ds[str(axis_name.value)]
if data.size > axis.size:
data = data[:axis.size]
ds2 = Dataset(data, axes=[axis])
ds2.title = ds.id
ds2.location = fullname
Plot1.set_dataset(ds2)
Plot1.x_label = axis_name.value
Plot1.y_label = str(data_name.value)
Plot1.title = str(data_name.value) + ' vs ' + axis_name.value
Plot1.pv.getPlot().setMarkerEnabled(True)
def __load_experiment_data__():
basename = sicsext.getBaseFilename()
fullname = str(System.getProperty('sics.data.path') + '/' + basename)
df.datasets.clear()
ds = df[fullname]
data = ds[str(data_name.value)]
axis = ds[str(axis_name.value)]
if data.size > axis.size:
data = data[:axis.size]
ds2 = Dataset(data, axes=[axis])
ds2.title = ds.id
ds2.location = fullname
Plot1.set_dataset(ds2)
Plot1.x_label = axis_name.value
Plot1.y_label = str(data_name.value)
Plot1.title = str(data_name.value) + ' vs ' + axis_name.value
Plot1.pv.getPlot().setMarkerEnabled(True)
def load_experiment_data():
basename = sicsext.getBaseFilename()
fullname = str(System.getProperty('sics.data.path') + '/' + basename)
df.datasets.clear()
global __DATASOURCE__
try:
sysname = fullname.replace('/', '\\')
if __DATASOURCE__.getDataset(fullname) == None \
and __DATASOURCE__.getDataset(sysname) == None:
__DATASOURCE__.addDataset(fullname, False)
except:
log('error in adding dataset: ' + fullname)
ds = df[fullname]
dname = str(data_name.value)
data = SimpleData(ds[dname])
# data = ds[str(data_name.value)]
axis = SimpleData(ds[str(axis_name.value)])
if data.size > axis.size:
data = data[:axis.size]
if normalise.value:
if dname == 'bm1_counts':
tname = 'bm1_time'
elif dname == 'bm2_counts':
tname = 'bm2_time'
else:
tname = 'detector_time'
norm = ds[tname]
if norm != None and hasattr(norm, '__len__'):
avg = norm.sum() / len(norm)
niter = norm.item_iter()
if niter.next() <= 0:
niter.set_curr(1)
data = data / norm * avg
ds2 = Dataset(data, axes=[axis])
ds2.title = ds.id
ds2.location = fullname
fit_min.value = axis.min()
fit_max.value = axis.max()
Plot1.set_dataset(ds2)
Plot1.x_label = axis_name.value
Plot1.y_label = str(data_name.value)
Plot1.title = str(data_name.value) + ' vs ' + axis_name.value
Plot1.pv.getPlot().setMarkerEnabled(True)
def load_experiment_data():
basename = sicsext.getBaseFilename()
fullname = str(System.getProperty('sics.data.path') + '/' + basename)
df.datasets.clear()
global __DATASOURCE__
try:
sysname = fullname.replace('/', '\\')
if __DATASOURCE__.getDataset(fullname) == None \
and __DATASOURCE__.getDataset(sysname) == None:
__DATASOURCE__.addDataset(fullname, False)
except:
log('error in adding dataset: ' + fullname)
ds = df[fullname]
dname = str(data_name.value)
data = SimpleData(ds[dname])
# data = ds[str(data_name.value)]
axis = SimpleData(ds[str(axis_name.value)])
if data.size > axis.size:
data = data[:axis.size]
if normalise.value :
if dname == 'bm1_counts':
tname = 'bm1_time'
elif dname == 'bm2_counts':
tname = 'bm2_time'
else:
tname = 'detector_time'
norm = ds[tname]
if norm != None and hasattr(norm, '__len__'):
avg = norm.sum() / len(norm)
niter = norm.item_iter()
if niter.next() <= 0:
niter.set_curr(1)
data = data / norm * avg
ds2 = Dataset(data, axes=[axis])
ds2.title = ds.id
ds2.location = fullname
fit_min.value = axis.min()
fit_max.value = axis.max()
Plot1.set_dataset(ds2)
Plot1.x_label = axis_name.value
Plot1.y_label = str(data_name.value)
Plot1.title = str(data_name.value) + ' vs ' + axis_name.value
Plot1.pv.getPlot().setMarkerEnabled(True)
def load_experiment_data(fullname = None):
if fullname == None:
basename = sicsext.getBaseFilename()
fullname = str(System.getProperty('sics.data.path') + '/' + basename)
df.datasets.clear()
ds = df[fullname]
dname = str(data_name.value)
if dname == 'first_5_tubes':
if ds.ndim == 4:
data = ds[:,:,:,0:5].sum(0)
elif ds.ndim == 3:
data = ds[:,:,0:5].sum(0)
elif ds.ndim == 2:
data = ds[:,0:5].sum(0)
else:
raise Exception('invalid data dimension: {}'.format(ds.ndim))
elif dname == 'tube_9':
if ds.ndim == 4:
data = ds[:,:,:,9].sum(0)
elif ds.ndim == 3:
data = ds[:,:,9].sum(0)
elif ds.ndim == 2:
data = ds[:,9].sum(0)
else:
raise Exception('invalid data dimension: {}'.format(ds.ndim))
elif dname == 'tube_10':
if ds.ndim == 4:
data = ds[:,:,:,10].sum(0)
elif ds.ndim == 3:
data = ds[:,:,10].sum(0)
elif ds.ndim == 2:
data = ds[:,10].sum(0)
else:
raise Exception('invalid data dimension: {}'.format(ds.ndim))
else:
data = SimpleData(ds[dname])
# data = ds[str(data_name.value)]
if axis_name.value.strip() == '':
axis = ds.axes[0]
axis_name.value = axis.name
# axis = ds.get_metadata(str(axis_name.value))
else:
if fix_axis.value:
axis = SimpleData(ds[str(axis_name.value)])
else:
axis = ds.axes[0]
axis_name.value = axis.name
if not hasattr(axis, '__len__'):
axis = SimpleData([axis], title = (axis_name.value))
if data.size > axis.size:
data = data[:axis.size]
if normalise.value :
if dname == 'bm1_counts':
tname = 'bm1_time'
elif dname == 'bm2_counts':
tname = 'bm2_time'
else:
tname = 'detector_time'
norm = ds[tname]
if norm != None and hasattr(norm, '__len__'):
avg = norm.sum() / len(norm)
niter = norm.item_iter()
if niter.next() <= 0:
niter.set_curr(1)
data = data / norm * avg
ds2 = Dataset(data, axes=[axis])
ds2.title = ds.id
ds2.location = fullname
fit_min.value = axis.min()
fit_max.value = axis.max()
Plot1.set_dataset(ds2)
if dname == 'first_5_tubes' and show_individuals.value:
for i in xrange(5):
if ds.ndim == 4:
di = ds[:,:,:,i].sum(0)
if normalise.value :
tname = 'detector_time'
norm = ds[tname]
if norm != None and hasattr(norm, '__len__'):
avg = norm.sum() / len(norm)
niter = norm.item_iter()
if niter.next() <= 0:
niter.set_curr(1)
di = di / norm * avg
di2 = Dataset(di, axes=[axis])
di2.title = 'tube {}'.format(i)
Plot1.add_dataset(di2)
Plot1.x_label = axis_name.value
Plot1.y_label = str(data_name.value)
Plot1.title = str(data_name.value) + ' vs ' + axis_name.value
Plot1.pv.getPlot().setMarkerEnabled(True)
