Here’s a simple Kalman filter that could be used for exactly this situation. It came from some work I did on Android devices. General Kalman filter theory is all about estimates for vectors, with the accuracy of the estimates represented by covariance matrices. However, for estimating location on Android devices the general theory reduces to … Read more
RecyclerView is designed to be extensible, so there is no need to subclass the LayoutManager (as droidev suggested) just to perform the scrolling. Instead, just create a SmoothScroller with the preference SNAP_TO_START: RecyclerView.SmoothScroller smoothScroller = new LinearSmoothScroller(context) { @Override protected int getVerticalSnapPreference() { return LinearSmoothScroller.SNAP_TO_START; } }; Now you set the position where you want … Read more
You could use scipy.interpolate.spline to smooth out your data yourself: from scipy.interpolate import spline # 300 represents number of points to make between T.min and T.max xnew = np.linspace(T.min(), T.max(), 300) power_smooth = spline(T, power, xnew) plt.plot(xnew,power_smooth) plt.show() spline is deprecated in scipy 0.19.0, use BSpline class instead. Switching from spline to BSpline isn’t a … Read more
I prefer a Savitzky-Golay filter. It uses least squares to regress a small window of your data onto a polynomial, then uses the polynomial to estimate the point in the center of the window. Finally the window is shifted forward by one data point and the process repeats. This continues until every point has been … Read more