QualityQuery

class ctapipe.core.QualityQuery(**kwargs: Any)

Bases: Component

Manages a set of user-configurable (at runtime or in a config file) selection criteria that operate on the same type of input. Each time it is called, it returns a boolean array of whether or not each criterion passed. It also keeps track of the total number of times each criterium is passed, as well as a cumulative product of criterium (i.e. the criteria applied in-order)

Attributes Summary

quality_criteria

list of tuples of ('<description', 'expression string') to accept (select) a given data value.

Methods Summary

__call__(**kwargs)	Test that value passes all cuts
get_table_mask(table)	Get a boolean mask for the entries that pass the quality checks.
to_table([functions])	Return a tabular view of the latest quality summary

Attributes Documentation

quality_criteria

list of tuples of (‘<description’, ‘expression string’) to accept (select) a given data value. E.g. [('mycut', 'x > 3'),]. You may use numpy as np and astropy.units as u, but no other modules.

Methods Documentation

__call__(**kwargs) → ndarray

Test that value passes all cuts

Parameters:

**kwargs:

Are passed as locals to evaluate the given expression

Returns:

np.ndarray:

array of booleans with results of each selection criterion in order

get_table_mask(table)

Get a boolean mask for the entries that pass the quality checks.

Parameters:

tableTable

Table with columns matching the expressions used in the QualityQuery.quality_criteria.

Returns:

masknp.ndarray[bool]

Boolean mask of valid entries.

to_table(functions=False)

Return a tabular view of the latest quality summary

The columns are - criteria: name of each criterion - counts: counts of each criterion independently - cum_counts: counts of cumulative application of each criterion in order

Parameters:

functions: bool:

include the function string as a column

Returns:

astropy.table.Table