pint.models.noise_model.make_interpolation_basis

pint.models.noise_model.make_interpolation_basis(toas: ndarray, nodes: ndarray | None = None, dt: float | None = None, kind: str = 'linear') → Tuple[ndarray, ndarray][source]

Construct an interpolation basis for the given TOAs and interpolation parameters using scipy.interpolate.interp1d.

Parameters:

  • toas – array-like Vector of time series (TOAs) in seconds.

  • nodes – array-like, optional Vector of interpolation nodes in MJD. If None, nodes are generated from dt.

  • dt – float, optional Time step in days for generating interpolation nodes if nodes is None.

  • kind – str, optional Interpolation kind passed to scipy.interpolate.interp1d. Default is “linear”. See scipy.interpolate.interp1d documentation for allowed values.

Returns:

M : the achromatic interpolation design matrix of shape (len(toas), n_nodes). nodes : the interpolation nodes in MJD corresponding to the columns of M.