[hugohadfield]

Thanks! So the example image is actually with both non-uniformly sampled measurements and noise :) works great for both/either

[hugohadfield]

Noise is added here: ``` # Generate noisy sinusoidal data with random time points np.random.seed(0) t = sorted(np.random.uniform(0.0, 10.0, 100)) noise_std = 0.01 y = np.sin(t) + noise_std * np.random.randn(len(t)) true_first_derivative = np.cos(t) true_second_derivative = -np.sin(t) ``` changing noise_std will change the magnitude of the noise added, hope that helps!

[youoy]

Ah true! Now I see it on the image too, I was looking at it on the phone and it did not look like it. I will definitely give it a try! Thank you very much