rail.estimation.algos.random_gauss module

Example code that just spits out random numbers between 0 and 3 for z_mode, and Gaussian centered at z_mode with width random_width*(1+zmode).

class rail.estimation.algos.random_gauss.RandomGaussEstimator

Bases: CatEstimator

Random CatEstimator

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

  • hdf5_groupname ([str] default=photometry) – name of hdf5 group for data, if None, then set to ‘’

  • 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

  • nzbins ([int] default=301) – The number of gridpoints in the z grid

  • id_col ([str] default=object_id) – name of the object ID column

  • redshift_col ([str] default=redshift) – name of redshift column

  • calc_summary_stats ([bool] default=False) – Compute summary statistics

  • calculated_point_estimates ([list] default=[]) – List of strings defining which point estimates to automatically calculate using qp.Ensemble.Options include, ‘mean’, ‘mode’, ‘median’.

  • recompute_point_estimates ([bool] default=False) – Force recomputation of point estimates

  • rand_width ([float] default=0.025) – ad hock width of PDF

  • seed ([int] default=87) – random seed

  • column_name ([str] default=mag_i_lsst) – name of a column that has the correct number of galaxies to find length of

  • input (TableHandle (INPUT))

  • model (ModelHandle (INPUT))

  • output (QPHandle (OUTPUT))

__init__(args, **kwargs)

Constructor: Do CatEstimator specific initialization

Parameters:

  • args (Any)

  • kwargs (Any)

Return type:

None

entrypoint_function: str | None = 'estimate'
inputs = [('input', <class 'rail.core.data.TableHandle'>), ('model', <class 'rail.core.data.ModelHandle'>)]
interactive_function: str | None = 'random_gauss_estimator'
name = 'RandomGaussEstimator'
validate()

Validation which checks if the required column names by the stage exist in the data

Return type:

None

class rail.estimation.algos.random_gauss.RandomGaussInformer

Bases: CatInformer

Placeholder Informer

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.

  • hdf5_groupname ([str] default=photometry) – name of hdf5 group for data, if None, then set to ‘’

  • input (TableHandle (INPUT))

  • model (ModelHandle (OUTPUT))

entrypoint_function: str | None = 'inform'
interactive_function: str | None = 'random_gauss_informer'
name = 'RandomGaussInformer'
run()

Run the stage and return the execution status.

Subclasses must implemented this method.

Return type:

None