pyIntensityFeatures.utils.grids
===============================

.. py:module:: pyIntensityFeatures.utils.grids

.. autoapi-nested-parse::

   Functions to support, create, and process grids.

   ..
       !! processed by numpydoc !!


Functions
---------

.. autoapisummary::

   pyIntensityFeatures.utils.grids.unique
   pyIntensityFeatures.utils.grids.grid_intensity


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

.. py:function:: unique(vals, decimals=3, **kwargs)

   
   Identify the unique values to the desired significance.


   :Parameters:

       **vals** : array-like
           Input array that will be flattened unless `axis` is specified

       **decimals** : int
           Number of decimal places to round to. If the number is negative, it
           specifies the number of positions to the left of the decimal point.
           (default=3)

       **\*\*kwargs** : dict
           Keyword arguements supported by numpy's unique function.



   :Returns:

       **uvals** : array-like
           Sorted array of unique values.







   .. seealso::

       
       :obj:`np.unique`
           ..
       



   ..
       !! processed by numpydoc !!

.. py:function:: grid_intensity(intensity, mlat, mlt, eq_mlat=45.0, mlat_inc=1.0, mlt_inc=0.5)

   
   Create an intensity grid, using the mean and standard deviation.


   :Parameters:

       **intensity** : np.array
           Input intensity array with NaN fill values

       **mlat** : np.array
           Magnetic latitude at intensity locations

       **mlt** : np.array
           Magnetic local time at intensity locations

       **eq_mlat** : float
           Most equatorward magnetic latitude magnitude, do not account for the
           hemisphere (defaut=45.0)

       **mlat_inc** : float
           Magnetic latitude increment for output (default=1.0)

       **mlt_inc** : float
           Magnetic local time increment for output (default=0.5)



   :Returns:

       **mean_intensity** : np.array
           2D array of mean intensity values

       **std_intensity** : np.array
           2D array of intensity standard deviations

       **num_intensity** : np.array
           2D array of intensity counts per bin

       **mlat_bins** : np.array
           Magnetic latitude of output bin centres

       **mlt_bins** : np.array
           Magnetic local time of output bin centres








   .. rubric:: Notes

   The hemisphere is determined using the sign of the data in `mlat`



   ..
       !! processed by numpydoc !!