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Show HN: Automated smooth Nth order derivatives of noisy data
Automated, smooth, N'th order derivatives of non-uniformly sampled time series data - hugohadfield/kalmangrad
kalmangrad is a python package that calculates automated smooth N'th order derivatives of non-uniformly sampled time series data. The approach leverages Bayesian filtering techniques to compute derivatives up to any specified order, offering a robust alternative to traditional numerical differentiation methods that are sensitive to noise. The main function provided is grad, which estimates the derivatives of the input data y sampled at times t.
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