QuantileInterpolator
- class pyirf.interpolation.QuantileInterpolator(grid_points, bin_edges, binned_pdf, quantile_resolution=0.001, normalization=PDFNormalization.AREA)[source]
Bases:
DiscretePDFInterpolator
Interpolator class providing quantile interpoalation.
Methods Summary
__call__
(target_point)Providing a common __call__ interface
interpolate
(target_point)Takes a grid of binned pdfs for a bunch of different parameters and interpolates it to given value of those parameters.
Methods Documentation
- __call__(target_point)
Providing a common __call__ interface
- Parameters:
- target_point: np.ndarray, shape=(1, n_dims)
Target for inter-/extrapolation When target_point is outside of the grids convex hull but extrapolator is None
- Returns:
- Interpolated result.
- interpolate(target_point)[source]
Takes a grid of binned pdfs for a bunch of different parameters and interpolates it to given value of those parameters. This function provides an adapted version of the quantile interpolation introduced in [1]. Instead of following this method closely, it implements different approaches to the steps shown in Fig. 5 of [1].
- Parameters:
- target_point: numpy.ndarray, shape=(1, n_dims)
Value for which the interpolation is performed (target point)
- Returns:
- f_new: numpy.ndarray, shape=(1, …, n_bins)
Interpolated and binned pdf
References
[1]B. E. Hollister and A. T. Pang (2013). Interpolation of Non-Gaussian Probability Distributions for Ensemble Visualization https://engineering.ucsc.edu/sites/default/files/technical-reports/UCSC-SOE-13-13.pdf