pyglider.ncprocess
==================

.. py:module:: pyglider.ncprocess

.. autoapi-nested-parse::

   Routines that are used for common processing of netcdf files after they have
   been converted to standard timeseries.

   ..
       !! processed by numpydoc !!


Functions
---------

.. autoapisummary::

   pyglider.ncprocess.extract_timeseries_profiles
   pyglider.ncprocess.make_gridfiles


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

.. py:function:: extract_timeseries_profiles(inname, outdir, deploymentyaml, force=False)

   
   Extract and save each profile from a timeseries netCDF.


   :Parameters:

       **inname** : str or Path
           netcdf file to break into profiles

       **outdir** : str or Path
           directory to place profiles

       **deploymentyaml** : str or Path
           location of deployment yaml file for the netCDF file.  This should
           be the same yaml file that was used to make the timeseries file.

       **force** : bool, default False
           Force an overwite even if profile netcdf already exists














   ..
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.. py:function:: make_gridfiles(inname, outdir, deploymentyaml, *, fnamesuffix='', depth_bins=None, dz=1, starttime='1970-01-01', maskfunction=None, max_gap=100)

   
   Turn a timeseries netCDF file into a vertically gridded netCDF.


   :Parameters:

       **inname** : str or Path
           netcdf file to break into profiles

       **outdir** : str or Path
           directory to place profiles

       **deploymentyaml** : str or Path
           location of deployment yaml file for the netCDF file.  This should
           be the same yaml file that was used to make the timeseries file.

       **depth_bins** : array, default = None
           User-defined depth bins, for instance ``np.arange(0, 1000.1, 1)``.
           If not None, these are the depth bins into which the data will be
           gridded.  If None, ``dz`` is used to generate bins between 0 and 1100m

       **dz** : float, default = 1
           Vertical grid spacing in meters.

       **maskfunction** : callable or None, optional
           Function applied to the dataset before gridding,
           usually to choose what data will be set to NaN based on quality flags.

       **max_gap** : int, default = 100
           Maximum number of consecutive NaN values to fill when interpolating.  This is used to
           prevent interpolation across large gaps in the data.

       **-------**
           ..

       **outname** : str
           Name of gridded netCDF file. The gridded netCDF file has coordinates of
           'depth' and 'profile', so each variable is gridded in depth bins and by
           profile number.  Each profile has a time, latitude, and longitude.
           If deploymentyaml is a list, data is parsed for deployment information,
           with subsequent files overwriting previous files.

       **Note:**
           ..

       **By default, the arithmetic mean is used to bin all variables, except for those with**
           ..

       **an average_method attribute inherited from the timeseries. This attribute is specified**
           ..

       **in the YAML configuration file when the timeseries is created. For example, if a variable**
           ..

       **has average_method: geometric mean, the geometric mean is used when gridding that variable.**
           ..

       **Variables with average_method: QC_protocol are treated as discrete quality flags rather than**
           ..

       **continuous data, and the maximum flag within each bin is used for gridding (e.g., if any**
           ..

       **value in a bin is QC3, the gridded bin is assigned QC3).**
           ..














   ..
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