Merge pull request econ-ark#1389 from Mv77/plumbing/Parameters_solver

Use Parameters class in solver

HARK/core.py

@@ -1445,47 +1445,85 @@ def solve_one_cycle(agent, solution_last):
  A list of one period solutions for one "cycle" of the AgentType's
  microeconomic model.
  """
- # Calculate number of periods per cycle, defaults to 1 if all variables are time invariant
- if len(agent.time_vary) > 0:
- # name = agent.time_vary[0]
- # T = len(eval('agent.' + name))
- T = len(agent.__dict__[agent.time_vary[0]])
- else:
- T = 1
 
- solve_dict = {parameter: agent.__dict__[parameter] for parameter in agent.time_inv}
- solve_dict.update({parameter: None for parameter in agent.time_vary})
+ # Check if the agent has a 'Parameters' attribute of the 'Parameters' class
+ # if so, take advantage of it. Else, use the old method
+ if hasattr(agent, "params") and isinstance(agent.params, Parameters):
+ T = agent.params._length
 
- # Initialize the solution for this cycle, then iterate on periods
- solution_cycle = []
- solution_next = solution_last
+  # Initialize the solution for this cycle, then iterate on periods
+  solution_cycle = []
+  solution_next = solution_last
 
- cycles_range = [0] + list(range(T - 1, 0, -1))
- for k in range(T - 1, -1, -1) if agent.cycles == 1 else cycles_range:
- # Update which single period solver to use (if it depends on time)
- if hasattr(agent.solve_one_period, "__getitem__"):
- solve_one_period = agent.solve_one_period[k]
- else:
- solve_one_period = agent.solve_one_period
+ cycles_range = [0] + list(range(T - 1, 0, -1))
+ for k in range(T - 1, -1, -1) if agent.cycles == 1 else cycles_range:
+ # Update which single period solver to use (if it depends on time)
+ if hasattr(agent.solve_one_period, "__getitem__"):
+ solve_one_period = agent.solve_one_period[k]
+ else:
+ solve_one_period = agent.solve_one_period
+
+ if hasattr(solve_one_period, "solver_args"):
+ these_args = solve_one_period.solver_args
+ else:
+ these_args = get_arg_names(solve_one_period)
+
+ # Make a temporary dictionary for this period
+ temp_pars = agent.params[k]
+ temp_dict = {
+ name: solution_next if name == "solution_next" else temp_pars[name]
+ for name in these_args
+ }
+
+ # Solve one period, add it to the solution, and move to the next period
+ solution_t = solve_one_period(**temp_dict)
+ solution_cycle.insert(0, solution_t)
+ solution_next = solution_t
 
- if hasattr(solve_one_period, "solver_args"):
- these_args = solve_one_period.solver_args
+ else:
+ # Calculate number of periods per cycle, defaults to 1 if all variables are time invariant
+ if len(agent.time_vary) > 0:
+ # name = agent.time_vary[0]
+ # T = len(eval('agent.' + name))
+ T = len(agent.__dict__[agent.time_vary[0]])
  else:
- these_args = get_arg_names(solve_one_period)
+ T = 1
+
+ solve_dict = {
+ parameter: agent.__dict__[parameter] for parameter in agent.time_inv
+ }
+ solve_dict.update({parameter: None for parameter in agent.time_vary})
+
+ # Initialize the solution for this cycle, then iterate on periods
+ solution_cycle = []
+ solution_next = solution_last
+
+ cycles_range = [0] + list(range(T - 1, 0, -1))
+ for k in range(T - 1, -1, -1) if agent.cycles == 1 else cycles_range:
+ # Update which single period solver to use (if it depends on time)
+ if hasattr(agent.solve_one_period, "__getitem__"):
+ solve_one_period = agent.solve_one_period[k]
+ else:
+ solve_one_period = agent.solve_one_period
+
+ if hasattr(solve_one_period, "solver_args"):
+ these_args = solve_one_period.solver_args
+ else:
+ these_args = get_arg_names(solve_one_period)
 
- # Update time-varying single period inputs
- for name in agent.time_vary:
- if name in these_args:
- solve_dict[name] = agent.__dict__[name][k]
- solve_dict["solution_next"] = solution_next
+  # Update time-varying single period inputs
+  for name in agent.time_vary:
+  if name in these_args:
+  solve_dict[name] = agent.__dict__[name][k]
+  solve_dict["solution_next"] = solution_next
 
- # Make a temporary dictionary for this period
- temp_dict = {name: solve_dict[name] for name in these_args}
+  # Make a temporary dictionary for this period
+  temp_dict = {name: solve_dict[name] for name in these_args}
 
- # Solve one period, add it to the solution, and move to the next period
- solution_t = solve_one_period(**temp_dict)
- solution_cycle.insert(0, solution_t)
- solution_next = solution_t
+  # Solve one period, add it to the solution, and move to the next period
+  solution_t = solve_one_period(**temp_dict)
+  solution_cycle.insert(0, solution_t)
+  solution_next = solution_t
 
  # Return the list of per-period solutions
  return solution_cycle