The project has produced a software package, implemented in the programming language Python, and named “PyDynamic”, which demonstrates the application of the methods developed in JRP IND09 to end user data. The PyDynamic software offers propagation of uncertainties for: Application of the discrete Fourier transform and its inverse; Filtering with an FIR or IIR filter with uncertain coefficients; Design of a FIR filter as the inverse of a frequency response with uncertain coefficients; Design of an IIR filter as the inverse of a frequency response with uncertain coefficients; Deconvolution in the frequency domain by division; Multiplication in the frequency domain; Transformation from amplitude and phase to a representation by real and imaginary parts. For the validation of the propagation of uncertainties, the Monte-Carlo method can be applied using a memory-efficient implementation of Monte-Carlo for digital filtering. The PyDynamic software can be accessed via the PyDynamic GitHub Website GitHub or the PyDynamic PyPi Website.