wolfhece.assets.boxplot.distribution
====================================

.. py:module:: wolfhece.assets.boxplot.distribution

.. autoapi-nested-parse::

   Boxplot statistics distribution model.

   Computes quartiles, whiskers and outliers from one or more raw data series,
   following the standard Tukey fences convention (configurable whisker
   coefficient *whis*, default 1.5 × IQR).





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

.. py:class:: BoxplotStatistics

   Computed statistics for one data series.


   .. py:attribute:: label
      :type:  str


   .. py:attribute:: values
      :type:  numpy.ndarray


   .. py:attribute:: q1
      :type:  float


   .. py:attribute:: q2
      :type:  float


   .. py:attribute:: q3
      :type:  float


   .. py:attribute:: iqr
      :type:  float


   .. py:attribute:: whisker_low
      :type:  float


   .. py:attribute:: whisker_high
      :type:  float


   .. py:attribute:: outliers
      :type:  numpy.ndarray


   .. py:attribute:: mean
      :type:  float


.. py:class:: BoxplotDistributionModel(series: Sequence[Sequence[float]], labels: Sequence[str] | None = None, whis: float = 1.5)

   Compute and store boxplot statistics from raw series data.


   .. py:attribute:: _whis


   .. py:property:: n_series
      :type: int



   .. py:property:: labels
      :type: list[str]



   .. py:property:: whis
      :type: float



   .. py:method:: set_series(series: Sequence[Sequence[float]], labels: Sequence[str] | None = None, whis: float | None = None) -> None


   .. py:method:: statistics() -> list[BoxplotStatistics]

      Return computed statistics for every series.



   .. py:method:: global_y_bounds() -> tuple[float, float]

      Return (y_min, y_max) encompassing all values including outliers.



   .. py:method:: _set_series(series: Sequence[Sequence[float]], labels: Sequence[str] | None) -> None