Esempio n. 1
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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)
Esempio n. 2
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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)
Esempio n. 3
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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
Esempio n. 4
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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