blueetl.extract.report

Generic Report extractor.

Classes

ReportExtractor(df, cached, filtered)

Report extractor class.

WindowSlice(t_start, t_stop, t_step, offset, ...)

Window slice attributes.
class blueetl.extract.report.ReportExtractor(df: DataFrame, cached: bool, filtered: bool)

Bases: BaseExtractor

Report extractor class.

Initialize the extractor.

Parameters:

  • df – Pandas DataFrame containing the extracted data.

  • cached – True if the data have been extracted from the cache, False otherwise.

  • filtered – True if the data have been filtered using a custom query, False otherwise.

static calculate_window_slice(rec) → WindowSlice

Calculate and return the window slice attributes.

classmethod from_simulations(simulations: Simulations, neurons: Neurons, windows: Windows, neuron_classes: NeuronClasses, name: str) → ReportExtractorT

Return a new instance from the given simulations, neurons, and windows.

Parameters:

  • simulations – Simulations extractor.

  • neurons – Neurons extractor.

  • windows – Windows extractor.

  • neuron_classes – NeuronClasses extractor.

  • name – name of the report in the simulation configuration.

Returns:

New instance.

class blueetl.extract.report.WindowSlice(t_start: float, t_stop: float, t_step: float | None, offset: float, name: str, trial: int)

Bases: object

Window slice attributes.