pdf

BMCI.pdf(y_obs, x2_max=- 1, n_points=21)

A posteriori probability density function (PDF).

This function approximates the a posteriori PDF \(p(x | \mathbf{y})\). The PDF is just a weighted histogram of the retrieval values \(x\) in the databse that are below the \(X^2\) cutoff weighted by the corresponding weight \(w_i(\mathbf{y})\).

Parameters

• y_obs (numpy.array) – m-element array containing the observation for which to compute the posterior CDF.

• x2_max (float) – The \(\chi^2\) cutoff to apply to elements in the database. Ignored if less than zero.

• n_points (int) – The number of points at which to estimate the PDF.

Returns

A tuple (xs, ys) describing the estimated PSD.

Raises

ValueError – If the number of channels in the observations is different from the database.