import logging from netCDF4 import Dataset from numpy import arange, dtype from physicalParameter import Roscop def writeNetCDF(fileName, fe): data = {} variables_1D = ['TIME', 'LATITUDE', 'LONGITUDE'] variables = variables_1D.copy() dims_2D = ['TIME', 'DEPTH'] # move to main after tests r = Roscop("code_roscop.csv") # create netcdf file nc = Dataset(fileName, "w", format="NETCDF3_CLASSIC") logging.debug(' ' + nc.data_model) # create dimensions # n is number of profiles, m the max size of profiles time = nc.createDimension("TIME", fe.n) lat = nc.createDimension("LATITUDE", fe.n) lon = nc.createDimension("LONGITUDE", fe.n) depth = nc.createDimension('DEPTH', fe.m) # debug logging.debug(" depth: {}, time: {}, lat: {}, lon: {}".format( len(depth), len(time), len(lat), len(lon))) # create variables # add dimensions before variables list for k in fe.keys: variables.append(k) # variables.extend(fe.keys()) for key in variables: # for each variables get the attributes list hash = r.returnCode(key) # _FillValue attribute must be set when variable is created # (using fill_value keyword to createVariable) if '_FillValue' in hash: fillvalue = hash['_FillValue'] # remove from the dictionary hash.pop('_FillValue') else: fillvalue = None # create the variable if any(key in item for item in variables_1D): data[key] = nc.createVariable( key, dtype(hash['types']).char, (key,), fill_value=fillvalue) else: data[key] = nc.createVariable( key, dtype(hash['types']).char, dims_2D, fill_value=fillvalue) # remove from the dictionary hash.pop('types') # create dynamically variable attributes for k in hash.keys(): setattr(data[key], k, hash[k]) nc._enddef() # debug for key in variables: logging.debug(" var: {}, dims: {}, shape: {}, dtype: {}, ndim: {}".format( key, data[key].dimensions, data[key].shape, data[key].dtype, data[key].ndim)) # write the data for key in variables: if any(key in item for item in variables_1D): data[key][:] = fe[key] else: data[key][:, :] = fe[key] # close the netcdf file nc.close()