问题描述
我有 1 个包含 12 个 netcdf 文件的文件夹。我如何使用 xarray 将所有 netcdf 文件合并为一个数据数组?
文件夹代表2015年,12个netcdf文件代表2015年每个月的数据。
我想也许我可以通过运行 for 循环并更改字符串中文件的每个编号来尝试操作字符串,因为我的文件(2015 年)是通过以下方式组织的:
EN.4.2.1.f.analysis.g10.201501.nc
EN.4.2.1.f.analysis.g10.201502.nc
EN.4.2.1.f.analysis.g10.201503.nc
....
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
import netCDF4 as s
import glob
import xarray as xr
from datetime import datetime
inpath='../../Data/EN.4.2.1_analyses/EN.4.2.1.analyses.g10.2015/'
# just loading in the first month (january) of 2015
en4_2015 = xr.open_dataset(inpath+'EN.4.2.1.f.analysis.g10.201501.nc')
如何将所有 netcdf 文件合并为一个数组而不是 12 个不同的 xarray?
我试过了:
import glob
import xarray as xr
from datetime import datetime
# List all matching files
files = glob.glob(inpath+'*.nc')
# Create list for
individual_files = []
# Loop through each file in the list
for i in files:
# Load a single dataset
timestep_ds = xr.open_dataset(i)
# Create a new variable called 'time' from the `time_coverage_start` field,and
# convert the string to a datetime object so xarray kNows it is time data
timestep_ds['time'] = datetime.strptime(timestep_ds.time_coverage_start,"%Y-%m-%dT%H:%M:%s.%fZ")
# Add the dataset to the list
individual_files.append(timestep_ds)
# Combine individual datasets into a single xarray along the 'time' dimension
modis_ds = xr.concat(individual_files,dim='time')
print(modis_ds)
AttributeError Traceback (most recent call last)
<ipython-input-36-34685efc1691> in <module>
10 # Create a new variable called 'time' from the `time_coverage_start` field,and
11 # convert the string to a datetime object so xarray kNows it is time data
---> 12 timestep_ds['time'] = datetime.strptime(timestep_ds.time_coverage_start,13 "%Y-%m-%dT%H:%M:%s.%fZ")
14
~/miniconda3/envs/py3_std_maps/lib/python3.8/site-packages/xarray/core/common.py in __getattr__(self,name)
226 with suppress(KeyError):
227 return source[name]
--> 228 raise AttributeError(
229 "{!r} object has no attribute {!r}".format(type(self).__name__,name)
230 )
AttributeError: 'Dataset' object has no attribute 'time_coverage_start'
解决方法
轻松修复!使用:
ds = xr.open_mfdataset(file_path_folder...time??/*nc')
时间不是说 2015 年,而是 20 年??获取21世纪的所有文件,19世纪一样??获取20世纪的所有文件等