isofit.utils.reducers
=====================

.. py:module:: isofit.utils.reducers


Functions
---------

.. autoapisummary::

   isofit.utils.reducers.band_mean
   isofit.utils.reducers.class_priority


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

.. py:function:: band_mean(vals)

   Wrapper for the np.mean reducer. A wrapper is necessary
   because you need to pass it a row-axis call.
   :param vals: (N-locs x bands) array of pixel values

   :returns: (b x 1) array of band-means


.. py:function:: class_priority(vals, thresh=0.25)

   Wrapper for the priority reducer. This might not be the correct
   place for this reducer. The rules are as follows:
   If pct(n) > thresh: -> class = n
   elif pct(n-1) > thresh: -> class = n-1
   else pct(0) > thresh -> class = 0
   This will mean that the largest int class will take precedence.
   The threshold controls how many pixels in the SUB have to be a class
   for it to be important.
   :param vals: (N-locs) array of pixel classes

   :returns: (int) Super pixel class