scipy.interpolate.SmoothBivariateSpline.__call__¶
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SmoothBivariateSpline.__call__(x, y, dx=0, dy=0, grid=True)[source]¶ Evaluate the spline or its derivatives at given positions.
Parameters: x, y : array_like
Input coordinates.
If grid is False, evaluate the spline at points
(x[i], y[i]), i=0, ..., len(x)-1. Standard Numpy broadcasting is obeyed.If grid is True: evaluate spline at the grid points defined by the coordinate arrays x, y. The arrays must be sorted to increasing order.
dx : int
Order of x-derivative
New in version 0.14.0.
dy : int
Order of y-derivative
New in version 0.14.0.
grid : bool
Whether to evaluate the results on a grid spanned by the input arrays, or at points specified by the input arrays.
New in version 0.14.0.