import logging from netCDF4 import Dataset from numpy import arange, dtype from physicalParameter import Roscop def writeNetCDF(fileName, fe): data = {} dims = ['TIME', 'LATITUDE', 'LONGITUDE'] variables = dims.copy() dims_4d = dims.copy() dims_4d = dims_4d.append('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) 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()) print(variables) 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 print(key) if any(key in item for item in dims): data[key] = nc.createVariable( key, dtype(hash['types']).char, (key,), fill_value=fillvalue) else: data[key] = nc.createVariable( key, dtype(hash['types']).char, dims_4d, 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]) # debug for key in variables: print(data[key])