Web Reference: One-dimensional linear interpolation for monotonically increasing sample points. Returns the one-dimensional piecewise linear interpolant to a function with given discrete data points (xp, fp), evaluated at x. And to find a Y point given the X point: m = (ya - yb) / (xa - xb) return (xc - xb) * m + yb. This function will also extrapolate from the data points. There are several general facilities available in SciPy for interpolation and smoothing for data in 1, 2, and higher dimensions. The choice of a specific interpolation routine depends on the data: whether it is one-dimensional, is given on a structured grid, or is unstructured.
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