interpolate_cuts

lstchain.high_level.interpolate.interpolate_cuts(cuts, grid_points, target_point, method='linear')

Interpolates a grid of GH_CUTS or AL_CUTS tables to a target-point.

Wrapper around scipy.interpolate.griddata [1].

Parameters:

cuts: numpy.ndarray, shape=(N, M, …): Gammaness-cuts or Alpha-cuts for all combinations of grid-points, like energy. Shape (N:n_grid_points, M:n_energy_bins)
grid_points: numpy.ndarray, shape=(N, O): Array of the N O-dimensional morphing parameter values corresponding to the N input templates.
target_point: numpy.ndarray, shape=(O): Value for which the interpolation is performed (target point)
method: ‘linear’, ‘nearest’, ‘cubic’: Interpolation method for scipy.interpolate.griddata [1]. Defaults to ‘linear’.

Returns:

cuts_interp: numpy.ndarray, shape=(1, M, …): Gammaness-cuts or Alpha-cuts for the target grid-point, shape (1, M:n_energy_bins)

References

[1]