SAGA.grid_spline.6: Cubic Spline Approximation

{"id": "SAGA.grid_spline.6", "title": "Cubic Spline Approximation", "description": "This tool approximates irregular scalar 2D data in specified points using C1-continuous bivariate cubic spline.<br/>Minimal Number of Points: minimal number of points locally involved in spline calculation (normally = 3)<br/><br/>Maximal Number of Points:npmax: maximal number of points locally involved in spline calculation (required > 10, recommended 20 < npmax < 60)<br/>Tolerance: relative tolerance multiple in fitting spline coefficients: the higher this value, the higher degree of the locally fitted spline (recommended 80 < k < 200)<br/><br/>Points per square: average number of points per square (increase if the point distribution is strongly non-uniform to get larger cells)<br/><br/>Author: Pavel Sakov, CSIRO Marine Research<br/><br/>Purpose: 2D data approximation with bivariate C1 cubic spline. 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