issue_comments: 350666998

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https://github.com/pydata/xarray/issues/1773#issuecomment-350666998 https://api.github.com/repos/pydata/xarray/issues/1773 350666998 MDEyOklzc3VlQ29tbWVudDM1MDY2Njk5OA== 10050469 2017-12-11T09:23:00Z 2017-12-11T09:23:00Z MEMBER

Is this what you want?

```python import numpy as np import xarray as xr

DomainSpaceTimeSize = 5 # using cartesian 4D SpaceTimeDensity = [100, 5] # 100 divisions in space 5 in time

x_coord = np.linspace(-DomainSpaceTimeSize, +DomainSpaceTimeSize, SpaceTimeDensity[0]) y_coord = np.linspace(-DomainSpaceTimeSize, +DomainSpaceTimeSize, SpaceTimeDensity[0]) z_coord = np.linspace(-DomainSpaceTimeSize, +DomainSpaceTimeSize, SpaceTimeDensity[0]) t_coord = np.linspace(0, +DomainSpaceTimeSize, SpaceTimeDensity[1])

scale_func = lambda x, y, z, t: np.cos(1x+2y+3z-4t)

data = scale_func(*np.meshgrid(x_coord, y_coord, z_coord, t_coord))

da = xr.DataArray(data, dims=['x', 'y', 'z', 't'], coords={'x':x_coord, 'y':y_coord, 'z':z_coord, 't':t_coord})

da.sel(x=0.0, y=1.0, z=0.0, t=3.0, method='nearest') <xarray.DataArray ()> array(-0.8039436986070311) Coordinates: x float64 0.05051 z float64 0.05051 t float64 2.5 y float64 0.9596 ```

 
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