scipy.interpolate.interpn¶

scipy.interpolate.interpn(points, values, xi, method='linear', bounds_error=True, fill_value=nan)[source]¶

Multidimensional interpolation on regular grids.

Parameters:

Parameters:	points : tuple of ndarray of float, with shapes (m1, ), …, (mn, ) The points defining the regular grid in n dimensions. values : array_like, shape (m1, …, mn, …) The data on the regular grid in n dimensions. xi : ndarray of shape (…, ndim) The coordinates to sample the gridded data at method : str, optional The method of interpolation to perform. Supported are “linear” and “nearest”, and “splinef2d”. “splinef2d” is only supported for 2-dimensional data. bounds_error : bool, optional If True, when interpolated values are requested outside of the domain of the input data, a ValueError is raised. If False, then fill_value is used. fill_value : number, optional If provided, the value to use for points outside of the interpolation domain. If None, values outside the domain are extrapolated. Extrapolation is not supported by method “splinef2d”.
Returns:	values_x : ndarray, shape xi.shape[:-1] + values.shape[ndim:] Interpolated values at input coordinates.

points : tuple of ndarray of float, with shapes (m1, ), …, (mn, ): The points defining the regular grid in n dimensions.
values : array_like, shape (m1, …, mn, …): The data on the regular grid in n dimensions.
xi : ndarray of shape (…, ndim): The coordinates to sample the gridded data at
method : str, optional: The method of interpolation to perform. Supported are “linear” and “nearest”, and “splinef2d”. “splinef2d” is only supported for 2-dimensional data.
bounds_error : bool, optional: If True, when interpolated values are requested outside of the domain of the input data, a ValueError is raised. If False, then fill_value is used.
fill_value : number, optional: If provided, the value to use for points outside of the interpolation domain. If None, values outside the domain are extrapolated. Extrapolation is not supported by method “splinef2d”.

Returns:

values_x : ndarray, shape xi.shape[:-1] + values.shape[ndim:]: Interpolated values at input coordinates.