Last active
August 8, 2022 15:47
-
-
Save aidanheerdegen/4b40b0ab94d0059f3ca636eea801d69b to your computer and use it in GitHub Desktop.
Using xarray to calculate daily averages over multiple years
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import numpy as np | |
from netCDF4 import Dataset | |
import sys | |
import xarray | |
from xarray.ufuncs import * | |
from glob import glob | |
import os | |
import string | |
# Path to the files directories | |
directory = '/g/data1/v45/mom01_comparison/KDS75/' | |
start_index = 150 | |
end_index = 158 | |
file_paths=[] | |
for index in range(start_index, end_index+1): | |
file_paths.extend(glob(os.path.join(directory,'output{:03d}'.format(index),'rregionoceankerg__*.nc'))) | |
print 'Found ',len(file_paths),' files' | |
# Open the list of files as a single dataset | |
ds = xarray.open_mfdataset(file_paths, engine='netcdf4', chunks={'time':1,'st_ocean':11,'yu_ocean_sub01':133,'xu_ocean_sub01':515},decode_times=False,mask_and_scale=True) | |
ds["time"].attrs["units"] = 'days since 1900-01-01' | |
ds["time"].attrs["calendar_type"] = string.lower(ds["time"].attrs["calendar_type"]) | |
ds["time"].attrs["calendar"] = string.lower(ds["time"].attrs["calendar"]) | |
ds = xarray.decode_cf(ds,decode_times=True) | |
print ds["time"] | |
# attrs = {'units': 'days since 1700-01-01'} | |
mld = ds["mld"] | |
mldave = mld.groupby("time.month").mean(dim='time') | |
print mldave.shape | |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment