piel.analysis.signals.time.integration.extract_pulse_metrics
============================================================

.. py:module:: piel.analysis.signals.time.integration.extract_pulse_metrics


Functions
---------

.. autoapisummary::

   piel.analysis.signals.time.integration.extract_pulse_metrics.extract_peak_to_peak_metrics_after_split_pulses


Module Contents
---------------

.. py:function:: extract_peak_to_peak_metrics_after_split_pulses(full_signal: piel.types.TimeSignalData, pre_pulse_time_s: float = 1e-09, post_pulse_time_s: float = 1e-09, noise_std_multiplier: float = 3.0, min_pulse_height: Optional[float] = None, min_pulse_distance_s: Optional[float] = None, data_time_signal_kwargs: Optional[dict] = None, metrics_kwargs: Optional[dict] = None) -> piel.types.ScalarMetricCollection

   Extracts pulses from the full signal and computes peak-to-peak metrics.

   Parameters:
   - full_signal (TimeSignalData): The complete time signal data to be analyzed.
   - pre_pulse_time_s (float): Time in seconds before the pulse to include.
   - post_pulse_time_s (float): Time in seconds after the pulse to include.
   - noise_std_multiplier (float): Multiplier for noise standard deviation to detect pulses.
   - min_pulse_height (Optional[float]): Minimum height of a pulse to be considered.
   - min_pulse_distance_s (Optional[float]): Minimum distance in seconds between pulses.
   - data_time_signal_kwargs (Optional[dict]): Additional keyword arguments for pulse extraction.
   - metrics_kwargs (Optional[dict]): Additional keyword arguments for metric extraction.

   Returns:
   - ScalarMetricCollection: Collection of extracted scalar metrics.