Source code for mpas_tools.io

from __future__ import absolute_import, division, print_function, \
    unicode_literals

import numpy
import netCDF4
from datetime import datetime
import sys


[docs]def write_netcdf(ds, fileName, fillValues=netCDF4.default_fillvals, format='NETCDF3_64BIT', char_dim_name='StrLen'): """ Write an xarray.Dataset to a file with NetCDF4 fill values and the given name of the string dimension. Also adds the time and command-line to the history attribute. Parameters ---------- ds : xarray.Dataset The dataset to save fileName : str The path for the NetCDF file to write fillValues : dict, optional A dictionary of fill values for different NetCDF types format : {'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_64BIT', 'NETCDF3_CLASSIC'}, optional The NetCDF file format to use char_dim_name : str, optional The name of the dimension used for character strings, or None to let xarray figure this out. """ encodingDict = {} variableNames = list(ds.data_vars.keys()) + list(ds.coords.keys()) for variableName in variableNames: isNumeric = numpy.issubdtype(ds[variableName].dtype, numpy.number) if isNumeric and numpy.any(numpy.isnan(ds[variableName])): dtype = ds[variableName].dtype for fillType in fillValues: if dtype == numpy.dtype(fillType): encodingDict[variableName] = \ {'_FillValue': fillValues[fillType]} break else: encodingDict[variableName] = {'_FillValue': None} isString = numpy.issubdtype(ds[variableName].dtype, numpy.string_) if isString and char_dim_name is not None: encodingDict[variableName] = {'char_dim_name': char_dim_name} update_history(ds) ds.to_netcdf(fileName, encoding=encodingDict, format=format)
def update_history(ds): '''Add or append history to attributes of a data set''' thiscommand = datetime.now().strftime("%a %b %d %H:%M:%S %Y") + ": " + \ " ".join(sys.argv[:]) if 'history' in ds.attrs: newhist = '\n'.join([thiscommand, ds.attrs['history']]) else: newhist = thiscommand ds.attrs['history'] = newhist