Filter

dabstract.abstract.abstract.Filter(data: Iterable, filter_fct: Callable, return_none: bool = True, lazy: bool = True, workers: int = 1, buffer_len: int = 3, *arg: List, **kwargs: Dict) → Union[dabstract.abstract.abstract.FilterAbstract, dabstract.abstract.abstract.DataAbstract, numpy.ndarray, List]

Factory function to allow for choice between lazy and direct example selection.

For both an instance of FilterAbstract is created. Different from lazy filtering, is that with direct filtering all examples are immediately evaluated.

For more information on the functionality of Filter please check the docstring of FilterAbstract().

Parameters

dataIterable

Iterable object to be filtered

filter_fctCallable

Callable function that needs to be applied.

return_nonebool

If True, return None if filter_fct is False If False, raises IndexError

lazybool

apply lazily or not (default = True)

workersint

amount of workers used for loading the data (default = 1)

buffer_lenint

buffer_len of the pool (default = 3)

argList

additional param to provide to the function if needed

kwargsDict

additional param to provide to the function if needed

Returns

FilterAbstract OR DataAbstract OR np.ndarray OR list

class dabstract.abstract.abstract.FilterAbstract(data: Iterable, filter_fct: Callable, return_none: bool = False, *args, **kwargs)

Bases: dabstract.abstract.abstract.Abstract

Filter on the fly. Interesting when the variable to filter on takes long to compute.

When the FilterAbstract wrapper is applied, the length of your data is undefined as filtering is based on a net yet excecuted function ‘filter_fct’.

The FilterAbstract class contain the following methods :: .get - return entry from FilterAbstract .keys - show the set of keys

The full explanation for each method is provided as a docstring at each method.

Parameters

dataIterable

Iterable object to be filtered

filter_fctCallable

Callable function that needs to be applied

return_nonebool

If True, return None if filter_fct is False If False, raises IndexError

kwargs:

additional param to provide to the function if needed

Returns

FilterAbstract class

get(index: int, return_info: bool = False, *arg: List, **kwargs: Dict) → Union[List, numpy.ndarray, Any]

Parameters

indexint

index to retrieve data from

return_infobool

return tuple (data, info) if True else data (default = False)

argList

additional param to provide to the function if needed

kwargsDict

additional param to provide to the function if needed

Returns

List OR np.ndarray OR Any

property len_defined