def PyExec(self):
in_ws = mtd[self.getPropertyValue('InputWorkspace')]
out_ws_name = self.getPropertyValue('OutputWorkspace')
out_ws = ms.CreateEmptyTableWorkspace(OutputWorkspace=out_ws_name)
out_ws.addColumn('str', 'statistic')
stats = {
'standard_deviation': dict(),
'maximum': dict(),
'minimum': dict(),
'mean': dict(),
'median': dict(),
}
for name in in_ws.getColumnNames():
try:
col_stats = _stats_to_dict(Stats.getStatistics(np.array([float(v) for v in in_ws.column(name)])))
for statname in stats:
stats[statname][name] = col_stats[statname]
out_ws.addColumn('float', name)
except ValueError:
logger.notice('Column \'%s\' is not numerical, skipping' % name)
for name, stat in iteritems(stats):
stat1 = dict(stat)
stat1['statistic'] = name
out_ws.addRow(stat1)
self.setProperty('OutputWorkspace', out_ws)
def PyExec(self):
in_ws = mtd[self.getPropertyValue('InputWorkspace')]
out_ws_name = self.getPropertyValue('OutputWorkspace')
out_ws = ms.CreateEmptyTableWorkspace(OutputWOrkspace=out_ws_name)
out_ws.addColumn('str', 'statistic')
stats = {
'standard_deviation': dict(),
'maximum': dict(),
'minimum': dict(),
'mean': dict(),
'median': dict(),
}
for name in in_ws.getColumnNames():
try:
col_stats = _stats_to_dict(
Stats.getStatistics(
np.array([float(v) for v in in_ws.column(name)])))
for statname in stats.keys():
stats[statname][name] = col_stats[statname]
out_ws.addColumn('float', name)
except ValueError:
logger.notice('Column \'%s\' is not numerical, skipping' %
name)
for name, stat in stats.items():
stat1 = dict(stat)
stat1['statistic'] = name
out_ws.addRow(stat1)
self.setProperty('OutputWorkspace', out_ws_name)
def test_getStatistics_with_floats(self):
data = numpy.array([17.2,18.1,16.5,18.3,12.6])
stats = Stats.getStatistics(data)
self.assertAlmostEqual(16.54, stats.mean, places = 10)
self.assertAlmostEqual(2.0733, stats.standard_deviation, places = 4)
self.assertEquals(12.6, stats.minimum)
self.assertEquals(18.3, stats.maximum)
self.assertEquals(17.2, stats.median)
data = numpy.sort(data)
stats = Stats.getStatistics(data, sorted=True)
self.assertAlmostEqual(16.54, stats.mean, places = 10)
self.assertAlmostEqual(2.0733, stats.standard_deviation, places = 4)
self.assertEquals(12.6, stats.minimum)
self.assertEquals(18.3, stats.maximum)
self.assertEquals(17.2, stats.median)
def test_getStatistics_with_floats(self):
data = numpy.array([17.2, 18.1, 16.5, 18.3, 12.6])
stats = Stats.getStatistics(data)
self.assertAlmostEqual(16.54, stats.mean, places=10)
self.assertAlmostEqual(2.0733, stats.standard_deviation, places=4)
self.assertEquals(12.6, stats.minimum)
self.assertEquals(18.3, stats.maximum)
self.assertEquals(17.2, stats.median)
data = numpy.sort(data)
stats = Stats.getStatistics(data, sorted=True)
self.assertAlmostEqual(16.54, stats.mean, places=10)
self.assertAlmostEqual(2.0733, stats.standard_deviation, places=4)
self.assertEquals(12.6, stats.minimum)
self.assertEquals(18.3, stats.maximum)
self.assertEquals(17.2, stats.median)
def PyExec(self):
in_ws = mtd[self.getPropertyValue('InputWorkspace')]
indices_list = self.getPropertyValue('ColumnIndices')
out_ws_name = self.getPropertyValue('OutputWorkspace')
column_names = in_ws.getColumnNames()
# If column indices are not provided, then default to _ALL_ columns
if len(indices_list) > 0:
indices_list = [int(x) for x in indices_list.split(',')]
else:
indices_list = range(len(column_names))
out_ws = ms.CreateEmptyTableWorkspace(OutputWorkspace=out_ws_name)
out_ws.addColumn('str', 'Statistic')
stats = collections.OrderedDict([
('StandardDev', collections.OrderedDict()),
('Minimum', collections.OrderedDict()),
('Median', collections.OrderedDict()),
('Maximum', collections.OrderedDict()),
('Mean', collections.OrderedDict()),
])
for index in indices_list:
column_name = column_names[index]
try:
column_data = np.array([float(v) for v in in_ws.column(index)])
col_stats = _stats_to_dict(Stats.getStatistics(column_data))
for stat_name in stats:
stats[stat_name][column_name] = col_stats[stat_name]
out_ws.addColumn('float', column_name)
except RuntimeError:
logger.notice('Column \'%s\' is not numerical, skipping' %
column_name)
except:
logger.notice('Column \'%s\' is not numerical, skipping' %
column_name)
for index, stat_name in iteritems(stats):
stat = collections.OrderedDict(stat_name)
stat['Statistic'] = index
out_ws.addRow(stat)
self.setProperty('OutputWorkspace', out_ws)
def PyExec(self):
in_ws = mtd[self.getPropertyValue('InputWorkspace')]
indices_list = self.getPropertyValue('ColumnIndices')
out_ws_name = self.getPropertyValue('OutputWorkspace')
column_names = in_ws.getColumnNames()
# If column indices are not provided, then default to _ALL_ columns
if len(indices_list) > 0:
indices_list = [int(x) for x in indices_list.split(',')]
else:
indices_list = range(len(column_names))
out_ws = ms.CreateEmptyTableWorkspace(OutputWorkspace=out_ws_name)
out_ws.addColumn('str', 'Statistic')
stats = collections.OrderedDict([
('StandardDev', collections.OrderedDict()),
('Minimum', collections.OrderedDict()),
('Median', collections.OrderedDict()),
('Maximum', collections.OrderedDict()),
('Mean', collections.OrderedDict()),
])
for index in indices_list:
column_name = column_names[index]
try:
column_data = np.array([float(v) for v in in_ws.column(index)])
col_stats = _stats_to_dict(Stats.getStatistics(column_data))
for stat_name in stats:
stats[stat_name][column_name] = col_stats[stat_name]
out_ws.addColumn('float', column_name)
except RuntimeError:
logger.notice('Column \'%s\' is not numerical, skipping' % column_name)
except:
logger.notice('Column \'%s\' is not numerical, skipping' % column_name)
for index, stat_name in iteritems(stats):
stat = collections.OrderedDict(stat_name)
stat['Statistic'] = index
out_ws.addRow(stat)
self.setProperty('OutputWorkspace', out_ws)
