pyinterp.core.spline_float32

pyinterp.core.spline_float32(*args, **kwargs)

Overloaded function.

  1. spline_float32(grid: pyinterp.core.Grid2DFloat32, x: numpy.ndarray[numpy.float64], y: numpy.ndarray[numpy.float64], nx: int = 3, ny: int = 3, fitting_model: str = ‘c_spline’, boundary: str = ‘undef’, bounds_error: bool = False, num_threads: int = 0) -> numpy.ndarray[numpy.float64]

Spline gridded 2D interpolation.

Parameters:
  • grid – Grid containing the values to be interpolated.

  • x – X-values.

  • y – Y-values.

  • nx – The number of X coordinate values required to perform the interpolation. Defaults to 3.

  • ny – The number of Y coordinate values required to perform the interpolation. Defaults to 3.

  • fitting_model – Type of interpolation to be performed. Defaults to c_spline

  • boundary – Type of axis boundary management. Defaults to undef.

  • 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 value is set to NaN.

  • 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.

Returns:

Values interpolated

  1. spline_float32(grid: pyinterp.core.Grid3DFloat32, x: numpy.ndarray[numpy.float64], y: numpy.ndarray[numpy.float64], z: numpy.ndarray[numpy.float64], nx: int = 3, ny: int = 3, fitting_model: str = ‘c_spline’, boundary: str = ‘undef’, bounds_error: bool = False, num_threads: int = 0) -> numpy.ndarray[numpy.float64]

Spline gridded 3D interpolation.

A spline 2D interpolation is performed along the X and Y axes of the 3D grid, and linearly along the Z axis between the two values obtained by the spatial spline 2D interpolation.

Parameters:
  • grid – Grid containing the values to be interpolated.

  • x – X-values.

  • y – Y-values.

  • z – Z-values.

  • nx – The number of X coordinate values required to perform the interpolation. Defaults to 3.

  • ny – The number of Y coordinate values required to perform the interpolation. Defaults to 3.

  • fitting_model – Type of interpolation to be performed. Defaults to c_spline

  • boundary – Type of axis boundary management. Defaults to undef.

  • 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 value is set to NaN.

  • 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.

Returns:

Values interpolated.

  1. spline_float32(grid: pyinterp.core.TemporalGrid3DFloat32, x: numpy.ndarray[numpy.float64], y: numpy.ndarray[numpy.float64], z: numpy.ndarray[numpy.int64], nx: int = 3, ny: int = 3, fitting_model: str = ‘c_spline’, boundary: str = ‘undef’, bounds_error: bool = False, num_threads: int = 0) -> numpy.ndarray[numpy.float64]

Spline gridded 3D interpolation.

A spline 2D interpolation is performed along the X and Y axes of the 3D grid, and linearly along the Z axis between the two values obtained by the spatial spline 2D interpolation.

Parameters:
  • grid – Grid containing the values to be interpolated.

  • x – X-values.

  • y – Y-values.

  • z – Z-values.

  • nx – The number of X coordinate values required to perform the interpolation. Defaults to 3.

  • ny – The number of Y coordinate values required to perform the interpolation. Defaults to 3.

  • fitting_model – Type of interpolation to be performed. Defaults to c_spline

  • boundary – Type of axis boundary management. Defaults to undef.

  • 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 value is set to NaN.

  • 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.

Returns:

Values interpolated.

  1. spline_float32(grid: pyinterp.core.Grid4DFloat32, x: numpy.ndarray[numpy.float64], y: numpy.ndarray[numpy.float64], z: numpy.ndarray[numpy.float64], u: numpy.ndarray[numpy.float64], nx: int = 3, ny: int = 3, fitting_model: str = ‘c_spline’, boundary: str = ‘undef’, bounds_error: bool = False, num_threads: int = 0) -> numpy.ndarray[numpy.float64]

Spline gridded 4D interpolation

A spline 2D interpolation is performed along the X and Y axes of the 4D grid, and linearly along the Z and U axes between the four values obtained by the spatial spline 2D interpolation.

Parameters:
  • grid – Grid containing the values to be interpolated.

  • x – X-values.

  • y – Y-values.

  • z – Z-values.

  • u – U-values.

  • nx – The number of X coordinate values required to perform the interpolation. Defaults to 3.

  • ny – The number of Y coordinate values required to perform the interpolation. Defaults to 3.

  • fitting_model – Type of interpolation to be performed. Defaults to c_spline

  • boundary – Type of axis boundary management. Defaults to undef.

  • 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 value is set to NaN.

  • 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.

Returns:

Values interpolated.

  1. spline_float32(grid: pyinterp.core.TemporalGrid4DFloat32, x: numpy.ndarray[numpy.float64], y: numpy.ndarray[numpy.float64], z: numpy.ndarray[numpy.int64], u: numpy.ndarray[numpy.float64], nx: int = 3, ny: int = 3, fitting_model: str = ‘c_spline’, boundary: str = ‘undef’, bounds_error: bool = False, num_threads: int = 0) -> numpy.ndarray[numpy.float64]

Spline gridded 4D interpolation

A spline 2D interpolation is performed along the X and Y axes of the 4D grid, and linearly along the Z and U axes between the four values obtained by the spatial spline 2D interpolation.

Parameters:
  • grid – Grid containing the values to be interpolated.

  • x – X-values.

  • y – Y-values.

  • z – Z-values.

  • u – U-values.

  • nx – The number of X coordinate values required to perform the interpolation. Defaults to 3.

  • ny – The number of Y coordinate values required to perform the interpolation. Defaults to 3.

  • fitting_model – Type of interpolation to be performed. Defaults to c_spline

  • boundary – Type of axis boundary management. Defaults to undef.

  • 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 value is set to NaN.

  • 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.

Returns:

Values interpolated.