pyglider.ncprocess#
Routines that are used for common processing of netcdf files after they have been converted to standard timeseries.
Functions#
extract_timeseries_profiles(): Extract and save each profile from a timeseries netCDF.make_gridfiles(): Turn a timeseries netCDF file into a vertically gridded netCDF.
- pyglider.ncprocess.extract_timeseries_profiles(inname, outdir, deploymentyaml, force=False)#
Extract and save each profile from a timeseries netCDF.
- Parameters:
- innamestr or Path
netcdf file to break into profiles
- outdirstr or Path
directory to place profiles
- deploymentyamlstr 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.
- forcebool, default False
Force an overwite even if profile netcdf already exists
- pyglider.ncprocess.make_gridfiles(inname, outdir, deploymentyaml, *, fnamesuffix='', depth_bins=None, dz=1, starttime='1970-01-01')#
Turn a timeseries netCDF file into a vertically gridded netCDF.
- Parameters:
- innamestr or Path
netcdf file to break into profiles
- outdirstr or Path
directory to place profiles
- deploymentyamlstr 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_binsarray, 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,dzis used to generate bins between 0 and 1100m- dzfloat, default = 1
Vertical grid spacing in meters. Ignored if
depth_binsis not None
- Returns:
- outnamestr
Name of gridded netCDF file. The gridded netCDF file has dimensions of ‘depth’ and ‘profile’, so each variable is gridded in depth bins and by profile number. Each profile has a time, latitude, and longitude. The depth values are the bin centers