I am working with a directed acyclic graph that models the `nx`

random variables over `nt`

time steps. I built a mesh grid representing positional coordinates in this graph to retrieve the value of the variable x_{t,i} where *t* is the time coordinate and *i* is one of the `nx`

random variables.

How can I obtain a list of key-value pair coordinates where the key is a pair of time (`t_idx`

) and positional (`x_idx`

) coordinate and the value is the next **imediate** coordinate where the variable is **observed**? It is possible to compute a boolean mask to know where the data is observed.

```
# time and positional coordinate
t_idx , x_idx = torch.meshgrid(torch.arange(arg.nt, out=torch.LongTensor()),
torch.arange(arg.nx, out=torch.LongTensor())
)
# time and positional coordinate with observed data
mask_data = (~torch.isnan(train_data)).squeeze(-1).nonzero()
```