def get_average_omega(exp_number, scan_number):
"""
Get average omega (omega-theta)
:param exp_number:
:param scan_number:
:return:
"""
# get table workspace
spice_table_name = util4.get_spice_table_name(exp_number, scan_number)
spice_table = AnalysisDataService.retrieve(spice_table_name)
# column index
col_omega_index = spice_table.getColumnNames().index('omega')
col_2theta_index = spice_table.getColumnNames().index('2theta')
# get the vectors
vec_size = spice_table.rowCount()
vec_omega = numpy.ndarray(shape=(vec_size, ), dtype='float')
vec_2theta = numpy.ndarray(shape=(vec_size, ), dtype='float')
for i_row in range(vec_size):
vec_omega[i_row] = spice_table.cell(i_row, col_omega_index)
vec_2theta[i_row] = spice_table.cell(i_row, col_2theta_index)
# END-FOR
vec_omega -= vec_2theta * 0.5
return numpy.sum(vec_omega)
def get_average_omega(exp_number, scan_number):
"""
Get average omega (omega-theta)
:param exp_number:
:param scan_number:
:return:
"""
# get table workspace
spice_table_name = util4.get_spice_table_name(exp_number, scan_number)
spice_table = AnalysisDataService.retrieve(spice_table_name)
# column index
col_omega_index = spice_table.getColumnNames().index('omega')
col_2theta_index = spice_table.getColumnNames().index('2theta')
# get the vectors
vec_size = spice_table.rowCount()
vec_omega = numpy.ndarray(shape=(vec_size, ), dtype='float')
vec_2theta = numpy.ndarray(shape=(vec_size, ), dtype='float')
for i_row in range(vec_size):
vec_omega[i_row] = spice_table.cell(i_row, col_omega_index)
vec_2theta[i_row] = spice_table.cell(i_row, col_2theta_index)
# END-FOR
vec_omega -= vec_2theta * 0.5
return numpy.sum(vec_omega)
def get_average_spice_table(exp_number, scan_number, col_name):
"""
"""
spice_table_name = util4.get_spice_table_name(exp_number, scan_number)
# spice_table_name = 'HB3A_Exp%d_%04d_SpiceTable' % (exp_number, scan_number)
# spice_table = mtd[spice_table_name]
spice_table = AnalysisDataService.retrieve(spice_table_name)
col_index = spice_table.getColumnNames().index(col_name)
row_number = spice_table.rowCount()
sum_item = 0.
for i_row in range(row_number):
sum_item += spice_table.cell(i_row, col_index)
avg_value = sum_item / float(row_number)
return avg_value
def get_average_spice_table(exp_number, scan_number, col_name):
"""
"""
spice_table_name = util4.get_spice_table_name(exp_number, scan_number)
# spice_table_name = 'HB3A_Exp%d_%04d_SpiceTable' % (exp_number, scan_number)
# spice_table = mtd[spice_table_name]
spice_table = AnalysisDataService.retrieve(spice_table_name)
col_index = spice_table.getColumnNames().index(col_name)
row_number = spice_table.rowCount()
sum_item = 0.
for i_row in range(row_number):
sum_item += spice_table.cell(i_row, col_index)
avg_value = sum_item / float(row_number)
return avg_value
