def solve_th(data): print("Solving %s" % data) model = "models/%s" % data["data"] pm = PEPAModel({"file": model, "solver": "sparse"}) pm.derive() pm.steady_state() th = pm.get_throughoutput() return "ok" if th else "error"
def solve_th(data): print("Solving %s" % data) model = "models/%s" % data["data"] pm = PEPAModel( { "file" : model, "solver" : "sparse"}) pm.derive() pm.steady_state() th = pm.get_throughoutput() return "ok" if th else "error"
def solve_ss(data): print("Solving %s" % data) model = "models/%s" % data["data"] pm = PEPAModel({"file": model, "solver": "sparse"}) pm.derive() pm.steady_state() ss = pm.get_steady_state_vector() return "ok" if ss else "error"
def solve_ss(data): print("Solving %s" % data) model = "models/%s" % data["data"] pm = PEPAModel({"file": model, "solver": "sparse"}) pm.derive() pm.steady_state() ss = pm.get_steady_state_vector() return "ok" if ss else "error"