Reading from the UFF file

To load all datasets from the UFF file to data object use:

data = uff_file.read_sets()

The first dataset 58 contains following keys:

data[4].keys()

Most important keys are x: x-axis and data: y-axis that define the stored response:

plt.semilogy(data[4]['x'], np.abs(data[4]['data']))
plt.xlabel('Frequency  [Hz]')
plt.ylabel('FRF Magnitude [dB m/N]')
plt.xlim([0,1000])
plt.show()

Writing measurement data to UFF file

Loading the accelerance data:

measurement_point_1 = np.genfromtxt('data/meas_point_1.txt', dtype=complex)
measurement_point_2 = np.genfromtxt('data/meas_point_2.txt', dtype=complex)
measurement_point_3 = np.genfromtxt('data/meas_point_3.txt', dtype=complex)

measurement_point_1[0] = np.nan*(1+1.j)

measurement = [measurement_point_1, measurement_point_2, measurement_point_3]

Creating the UFF file where we add dataset 58 for measurement consisting of the dictionary-like keys containing the measurement data and the information about the measurement:

for i in range(3):
    print('Adding point {:}'.format(i + 1))
    response_node = 1
    response_direction = 1
    reference_node = i + 1
    reference_direction = 1
    acceleration_complex = measurement[i]
    frequency = np.arange(0, 1001)
    name = 'TestCase'
    data = {'type':58,
            'func_type': 4,
            'rsp_node': response_node,
            'rsp_dir': response_direction,
            'ref_dir': reference_direction,
            'ref_node': reference_node,
            'data': acceleration_complex,
            'x': frequency,
            'id1': 'id1',
            'rsp_ent_name': name,
            'ref_ent_name': name,
            'abscissa_spacing':1,
            'abscissa_spec_data_type':18,
            'ordinate_spec_data_type':12,
            'orddenom_spec_data_type':13}
    uffwrite = pyuff.UFF('./data/measurement.uff')
    uffwrite.write_set(data,'add')

Or we can use support function prepare_58 to prepare the dictionary for creating the UFF file. Functions for other datasets can be found in supported datasets.

for i in range(3):
print('Adding point {:}'.format(i + 1))
response_node = 1
response_direction = 1
reference_node = i + 1
reference_direction = 1
acceleration_complex = measurement[i]
frequency = np.arange(0, 1001)
name = 'TestCase'
pyuff.prepare_58(func_type=4,
            rsp_node=response_node,
            rsp_dir=response_direction,
            ref_dir=reference_direction,
            ref_node=reference_node,
            data=acceleration_complex,
            x=frequency,
            id1='id1',
            rsp_ent_name=name,
            ref_ent_name=name,
            abscissa_spacing=1,
            abscissa_spec_data_type=18,
            ordinate_spec_data_type=12,
            orddenom_spec_data_type=13)