英文:
How do I create a Data Variable in an xarray.DataArray?
问题
如何将数据分配给或在保存DataArray时创建一个'数据变量'，最终存储在nc文件中？
在创建xarray.DataArray时，它只是将数据存储为一个数组，而不是像nc文件中一样存储为'数据变量'。
接下来，我想将DataArray保存为nc文件，其中数组存储为适当的'数据变量'并为其命名。
import numpy as np
import xarray as xr
T_data = np.random.random((100,10))
pressure = np.arange(0,100,1)
longitude = np.arange(350,360,1)
T_DataArray = xr.DataArray(data=T_data, coords={'p':pressure, 'lon':longitude}, dims=['p','lon'])
T_DataArray.to_netcdf(path='C:/my/path/file.nc')
（在这里，我特别想继续将此nc文件加载到MATLAB中，但无法访问存储的数据作为数据变量，ncread(file, ???)不起作用...）
如何在这里创建一个'正确'的nc文件，包括一个数据变量？
谢谢！
英文:
How do I assign data to or create a 'Data Variable' in a xarray.DataArray or finally in the nc-file when saving the DataArray?
When creating the xarray.DataArray, it simply stores the data as an array but not as a 'Data Variable' as one is used to from nc-files.
In the next step, I'd like to save the DataArray as an nc-file with the array stored as an appropriate 'Data Variable' and a name to it.
import numpy as np
import xarray as xr
T_data = np.random.random((100,10))
pressure = np.arange(0,100,1)
longitude = np.arange(350,360,1)
T_DataArray = xr.DataArray(data=T_data, coords={'p':pressure, 'lon':longitude}, dims=['p','lon'])
T_DataArray.to_netcdf(path='C:/my/path/file.nc')
(Here specifically, I'd like to continue loading this nc-file to MATLAB but can't access the stored data as a Data Variable, ncread(file, ???) doesn't work...)
How do I create a 'proper' nc-file including a Data Variable here?
Thank you!
答案1
得分: 0
NetCDF文件可以包括多个命名变量，因此您可能希望给您的变量一个有用的名称：
T_DataArray = xr.DataArray(
data=T_data,
coords={'p': pressure, 'lon': longitude},
dims=['p', 'lon'],
name='temperature'
)
T_DataArray.to_netcdf(path='./file.nc')
这将生成一个类似如下的NetCDF文件：
$ ncdump -h file.nc
netcdf file {
dimensions:
p = 100 ;
lon = 10 ;
variables:
int64 p(p) ;
int64 lon(lon) ;
double temperature(p, lon) ;
temperature:_FillValue = NaN ;
}
在MATLAB中，您需要引用文件（file.nc）和变量（"temperature"）。
英文:
NetCDF files can include multiple named variables so you probably want to give your variable a useful name:
T_DataArray = xr.DataArray(
data=T_data,
coords={'p':pressure, 'lon':longitude},
dims=['p','lon'],
name='temperature'
)
T_DataArray.to_netcdf(path='./file.nc')
This generates a netCDF file that looks like:
$ ncdump -h file.nc
netcdf file {
dimensions:
p = 100 ;
lon = 10 ;
variables:
int64 p(p) ;
int64 lon(lon) ;
double temperature(p, lon) ;
temperature:_FillValue = NaN ;
}
In matlab, you'll want to reference the file (file.nc) and the variable ("temperature").
答案2
得分: 0
以下是翻译好的部分：
我通常这样做：
```python
import numpy as np
import xarray as xr
T_data = np.random.random((100, 10))
pressure = np.arange(0, 100, 1)
longitude = np.arange(350, 360, 1)
T_DataArray = xr.DataArray(
data=T_data,
coords={
'p': pressure,
'lon': longitude
},
dims=['p', 'lon']
)
xr.Dataset({"temperature": T_DataArray}).to_netcdf(path='file.nc')
result:
ncdump -h file.nc
netcdf file {
dimensions:
p = 100 ;
lon = 10 ;
variables:
int64 p(p) ;
int64 lon(lon) ;
double temperature(p, lon) ;
temperature:_FillValue = NaN ;
}
英文:
I usually do this:
import numpy as np
import xarray as xr
T_data = np.random.random((100, 10))
pressure = np.arange(0, 100, 1)
longitude = np.arange(350, 360, 1)
T_DataArray = xr.DataArray(
data=T_data,
coords={
'p': pressure,
'lon': longitude
},
dims=['p', 'lon']
)
xr.Dataset({"temperature": T_DataArray}).to_netcdf(path='file.nc')
result:
ncdump -h file.nc
netcdf file {
dimensions:
p = 100 ;
lon = 10 ;
variables:
int64 p(p) ;
int64 lon(lon) ;
double temperature(p, lon) ;
temperature:_FillValue = NaN ;
}
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