def sample_plan(self, plan_id, plan_length, rho, views, view_values, view_costs, current_view_id):
remaining_views = dict()
for v in views:
remaining_views[v.ID] = v
# current_view_id = remaining_views.keys()[0] NOW FUNCTION ARGUMENT
plan = Plan(plan_id)
# pmf for values
value_pmf = self._generate_value_pmf(view_values)
# pmf for costs
cost_pmf = self._generate_cost_pmf(current_view_id, remaining_views.keys(), rho, view_costs)
# joint dist
joint = make_joint(value_pmf, cost_pmf)
joint.normalize()
for j in range(plan_length):
x = joint.random()
plan.append(remaining_views[x])
remaining_views.pop(x)
# sample without replacement
# adapt both pmfs: value and cost
value_pmf.unset(x)
value_pmf.normalize()
cost_pmf = self._generate_cost_pmf(x, remaining_views.keys(), rho, view_costs)
# re-generate joint dist
joint = make_joint(value_pmf, cost_pmf)
joint.normalize()
return plan
