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 xt,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()