pyinterp.quadrivariate#

pyinterp.quadrivariate(grid4d: Grid4D, x: ndarray, y: ndarray, z: ndarray, u: ndarray, interpolator: str = 'bilinear', z_method: str = 'linear', u_method: str = 'linear', bounds_error: bool = False, num_threads: int = 0, **kwargs) ndarray[source]#

Interpolate the values provided on the defined quadrivariate function.

Parameters:
  • grid4d – Function on a uniform 4-dimensional grid to be interpolated.

  • x – X-values.

  • y – Y-values.

  • z – Z-values.

  • u – U-values.

  • interpolator – The interpolation method to be performed on the surface defined by the Y and Y axes. Supported are bilinear and nearest, and inverse_distance_weighting. Default to bilinear.

  • z_method – The interpolation method to be performed on the Z axis. Supported are linear and nearest. Default to linear.

  • u_method – The interpolation method to be performed on the U axis. Supported are linear and nearest. Default to linear.

  • bounds_error – If True, when interpolated values are requested outside of the domain of the input axes (x,y), a ValueError is raised. If False, then the value is set to NaN. Default to False.

  • num_threads – The number of threads to use for the computation. If 0 all CPUs are used. If 1 is given, no parallel computing code is used at all, which is useful for debugging. Defaults to 0.

  • p – The power to be used by the interpolator inverse_distance_weighting. Default to 2.

Returns:

Values interpolated.