rail.estimation.algos.uniform_binning module

A classifier that uses pz point estimate to assign tomographic bins with uniform binning.

class rail.estimation.algos.uniform_binning.UniformBinningClassifier

Classifier that simply assigns tomographic bins based on a point estimate according to SRD.

Parameters:

output_mode ([str] default=default) – What to do with the outputs. The options are ‘default’, where outputs will be written to files and some returned, and ‘return’, where outputs will only be returned and not written.
chunk_size ([int] default=10000) – Number of objects per chunk for parallel processing or to evalute per loop in single node processing
object_id_col ([str] default=) – name of object id column
point_estimate_key ([str] default=zmode) – Which point estimate to use
zbin_edges ([list] default=[]) – The tomographic redshift bin edges.If this is given (contains two or more entries), all settings below will be ignored.
zmin ([float] default=0.0) – The minimum redshift of the z grid or sample
zmax ([float] default=3.0) – The maximum redshift of the z grid or sample
n_tom_bins ([int] default=5) – Number of tomographic bins
no_assign ([int] default=-99) – Value for no assignment flag
input (QPHandle (INPUT))
output (Hdf5Handle (OUTPUT))