rail.interactive.creation.degraders.spectroscopic_degraders module

rail.interactive.creation.degraders.spectroscopic_degraders.inv_redshift_incompleteness(**kwargs)

Degrader that simulates incompleteness with a selection function inversely proportional to redshift.

The survival probability of this selection function is p(z) = min(1, z_p/z), where z_p is the pivot redshift.

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The main interface method for Selector.

Adds noise to the input catalog

This will attach the input to this Selector

Then it will call the select() which add a flag column to the catalog. flag=1 means selected, 0 means dropped.

If dropRows = True, the dropped rows will not be presented in the output catalog, otherwise, all rows will be presented.

Finally, this will return a PqHandle providing access to that output data.

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This function was generated from the function rail.creation.degraders.spectroscopic_degraders.InvRedshiftIncompleteness.__call__

Parameters:

  • sample (TableLike, required) – The sample to be selected

  • pivot_redshift (float, required) – redshift at which the incompleteness begins

  • drop_rows (bool, optional) – Drop selected rows from output table Default: True

  • seed (unknown type, optional) – Set to an int to force reproducible results. Default: None

Returns:

A handle giving access to a table with selected sample

Return type:

pandas.core.frame.DataFrame

rail.interactive.creation.degraders.spectroscopic_degraders.line_confusion(**kwargs)

Degrader that simulates emission line confusion.

degrader = LineConfusion(true_wavelen=3727,
                         wrong_wavelen=5007,
                         frac_wrong=0.05)

is a degrader that misidentifies 5% of OII lines (at 3727 angstroms) as OIII lines (at 5007 angstroms), which results in a larger spectroscopic redshift.

Note that when selecting the galaxies for which the lines are confused, the degrader ignores galaxies for which this line confusion would result in a negative redshift, which can occur for low redshift galaxies when wrong_wavelen < true_wavelen.

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The main interface method for Noisifier.

Adds noise to the input catalog

This will attach the input to this Noisifier

Then it will call the _initNoiseModel() and _addNoise(), which need to be implemented by the sub-classes.

The _initNoiseModel() method will initialize the noise model of the sub-classes, and store the noise model as self.noiseModel

The _addNoise() method will add noise to the flux and magnitude of the column of the catalog.

The finalize() method will check the end results (like preserving number of rows)

Finally, this will return a PqHandle providing access to that output data.

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This function was generated from the function rail.creation.degraders.spectroscopic_degraders.LineConfusion.__call__

Parameters:

  • sample (TableLike, required) – The sample to be degraded.

  • true_wavelen (float, required) – wavelength of the true emission line

  • wrong_wavelen (float, required) – wavelength of the wrong emission line

  • frac_wrong (float, required) – fraction of galaxies with confused emission lines

  • seed (int, optional) – Set to an int to force reproducible results. Default: None An integer to set the numpy random seed, by default None.

Returns:

A handle giving access to a table with degraded sample.

Return type:

pandas.core.frame.DataFrame