Data preparation for NeurEco Parametric Frequency Sweep with the GUI#

The GUI expects the data for model construction or evaluation in form of paths to files containing the data.

  • The supported formats are:

    • CSV with “;” or “,” separator;

    • NumPy .npy

    • MATLAB MAT-files .mat (under development)

  • Files contain the numerical data, allowed types:

    • for input file: float, double

    • for output file:

      • NumPy: complex64, complex128

      • CSV: complex; each complex number with real part Re and imaginary part Im should be encoded with one of the following syntaxes:

        • Re+Imj, for example 0.1+0.1j

        • (Re+ Imj), for example (0.1+0.1j)

        • (Re, Im), for example (0.1,0.1)

  • Any input file should contain a table with:

    • Number of lines equal to a number of samples

    • Number of columns equal to a number of input features

    • The first column is dedicated to the frequency

    • CSV files could have one additional line for a header

  • Any output file should contain a table with:

    • Number of lines equal to a number of samples

    • Number of columns equal to a number of output features

    • CSV files could have one additional line for a header

  • input file and the corresponding output file should have the same number of samples

  • The data can be provided in chunks, in multiple input and output files. In this case pay attention to preserving the correspondence between input and output files

There is no need to normalize the data, as the normalization is handled by NeurEco, see Data normalization for Parametric Frequency Sweep.