Code Documentation

IO module

delight.io.createGrids(params)

Create redshift grids from parameters in file.

delight.io.getDataFromFile(params, firstLine, lastLine, prefix='', ftype='catalog', getXY=True, CV=False)

Returns an iterator to parse an input catalog file. Returns the fluxes, redshifts, etc, and also GP inputs if getXY=True.

delight.io.parseParamFile(fileName, verbose=True, catFilesNeeded=True)

Parser for configuration inputtype parameter files, see examples for details. A bunch of them ar parsed.

delight.io.readBandCoefficients(params)

Read band/filter information, in particular the Gaussian Mixture coefs.

delight.io.readColumnPositions(params, prefix='training_', refFlux=True)

Read column/band information needed for parsing catalog file,

in particular the column positions.

delight.io.readSEDs(params)

Read SED parameters.

Photo-z GP module

Photo-z kernels module

Utils module

delight.utils.CIlevel(redshiftGrid, PDF, fraction, numlevels=200)

Computes confidence interval from PDF.

class delight.utils.approx_DL

Approximate luminosity_distance relation, agrees with astropy.FlatLambdaCDM(H0=70, Om0=0.3, Ob0=None) better than 1%

delight.utils.approx_flux_likelihood(f_obs, f_obs_var, f_mod, ell_hat=0, ell_var=0, f_mod_covar=None, marginalizeEll=True, normalized=False, renormalize=True, returnChi2=False, returnEllML=False)

Approximate flux likelihood, with scaling of both the mean and variance. This approximates the true likelihood with an iterative scheme.

delight.utils.computeMetrics(ztrue, redshiftGrid, PDF, confIntervals)

Compute various metrics on the PDF

delight.utils.dirichlet(alphas, rsize=1)

Draw samples from a Dirichlet distribution.

delight.utils.kldiv(p, q)

Kullback-Leibler divergence D(P || Q) for discrete distributions

delight.utils.random_X_bzl(size, numBands=5, redshiftMax=3.0)

Create random (but reasonable) input space for photo-z GP

delight.utils.random_filtercoefs(numBands, numCoefs)

Create random (but reasonable) coefficients describing numBands photometric filters as sum of gaussians

delight.utils.random_hyperparams()

Create random (but reasonable) hyperparameters for photo-z GP

delight.utils.random_linecoefs(numLines)

Create random (but reasonable) coefficients describing lines in SEDs

delight.utils.symmetrize(a)

Symmmetrize matrix