pastas.stats.metrics.picp
=========================

.. py:function:: pastas.stats.metrics.picp(obs: pandas.Series, bounds: pandas.DataFrame)

   
   Compute the prediction interval coverage probability (PICP).

   :param obs: Pandas Series with the observed time series and a DateTimeIndex.
   :type obs: pandas.Series
   :param bounds: DataFrame with the lower (first column) and upper (second columns) bounds of the
                  prediction intervals.
   :type bounds: DataFrame

   .. rubric:: Notes

   The Prediction Interval Coverage Probability (PICP) is computed as follows:

   .. math:: PICP = \\frac{1}{N} \\sum_{i=1}^N a_i,
       a_i =
       \\begin{cases}
            1 & \\text{if} h_i \\text{in} [\\hat{h_i}^L, \\hat{h_i}^U], \\
            0 & \\text{otherwise}
       \\end{cases}

   .. rubric:: Examples

   >>> import pandas as pd
   >>> import numpy as np
   >>> from pastas.stats import picp
   >>> obs = pd.Series(np.random.rand(100),
   ...                     index=pd.date_range("2000-01-01", periods=100))
   >>> bounds = pd.DataFrame(np.random.rand(100, 2), index=obs.index)
   >>> picp(obs, bounds)















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