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UFF (Universal File Format) read/write.

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pytest Documentation Status

pyuff

Universal File Format read and write

This module defines an UFF class to manipulate with the UFF (Universal File Format) files.

Read from and write of data-set types 15, 55, 58, 58b, 82, 151, 164, 2411, 2412, 2414, 2420, 2429, 2467 are supported.

Check out the documentation.

To install the package, run:

pip install pyuff

Showcase

To analyse UFF file we first load the uff module and example file:

import pyuff
uff_file = pyuff.UFF('data/beam.uff')

To check which datasets are written in the file use:

uff_file.get_set_types()

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)

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