def _create_indexed_workspace(self, fractional_peaks, ndim, hklm):
# Create table with the number of columns we need
indexed = CreateEmptyTableWorkspace()
names = fractional_peaks.getColumnNames()
types = fractional_peaks.columnTypes()
# Insert the extra columns for the addtional indicies
for i in range(ndim - 3):
names.insert(5 + i, 'm{}'.format(i + 1))
types.insert(5 + i, 'double')
names = np.array(names)
types = np.array(types)
# Create columns in the table workspace
for name, column_type in zip(names, types):
indexed.addColumn(column_type, name)
# Copy all columns from original workspace, ignoring HKLs
column_data = []
idx = np.arange(0, names.size)
hkl_mask = (idx < 5) | (idx > 4 + (ndim - 3))
for name in names[hkl_mask]:
column_data.append(fractional_peaks.column(name))
# Insert the addtional HKL columns into the data
for i, col in enumerate(hklm.T.tolist()):
column_data.insert(i + 2, col)
# Insert the columns into the table workspace
for i in range(fractional_peaks.rowCount()):
row = [column_data[j][i] for j in range(indexed.columnCount())]
indexed.addRow(row)
return indexed
def _create_indexed_workspace(self, fractional_peaks, ndim, hklm):
# Create table with the number of columns we need
types = ['int', 'long64', 'double', 'double', 'double', 'double', 'double', 'double',
'double', 'double', 'double', 'float', 'str', 'float', 'float', 'V3D', 'V3D']
indexed = CreateEmptyTableWorkspace()
names = fractional_peaks.getColumnNames()
# Insert the extra columns for the addtional indicies
for i in range(ndim - 3):
names.insert(5 + i, 'm{}'.format(i + 1))
types.insert(5 + i, 'double')
names = np.array(names)
types = np.array(types)
# Create columns in the table workspace
for name, column_type in zip(names, types):
indexed.addColumn(column_type, name)
# Copy all columns from original workspace, ignoring HKLs
column_data = []
idx = np.arange(0, names.size)
hkl_mask = (idx < 5) | (idx > 4 + (ndim - 3))
for name in names[hkl_mask]:
column_data.append(fractional_peaks.column(name))
# Insert the addtional HKL columns into the data
for i, col in enumerate(hklm.T.tolist()):
column_data.insert(i + 2, col)
# Insert the columns into the table workspace
for i in range(fractional_peaks.rowCount()):
row = [column_data[j][i] for j in range(indexed.columnCount())]
indexed.addRow(row)
return indexed
