This is a first step towards #188 .
The idea is simply to make model.grid a cartesian product of two grids. A product grid could attach names to each factor as in grid = GridProduct( {'endo': endo_grid, 'exo': exo_grid} ), then one could be able to accessgrid.endoandgrid.exoinstead of the currentmodel.endo_gridandmodel.exo_grid. This would clarify that a decision rule is defined on one single grid. An unresolved issue is how to pass discretization information to solution routines. I have been thinking that a natural to do so would be to domodel.domain.discretize(n=[10,10])instead of the currentmodel.get_endo_grid(n=[10,10])`.
This is a first step towards #188 . The idea is simply to make
model.grid
a cartesian product of two grids. A product grid could attach names to each factor as ingrid = GridProduct( {'endo': endo_grid, 'exo': exo_grid} ), then one could be able to access
grid.endoand
grid.exoinstead of the current
model.endo_gridand
model.exo_grid. This would clarify that a decision rule is defined on one single grid. An unresolved issue is how to pass discretization information to solution routines. I have been thinking that a natural to do so would be to do
model.domain.discretize(n=[10,10])instead of the current
model.get_endo_grid(n=[10,10])`.