def test_example_1(self, dispatch):
import simulai
# Step 0 - Definition of model frame
frame = "Modelo"
# Step 1- Definition of input variables
espera = simulai.DiscreteVariable("Espera", 60, 300, 10,
"Models." + frame + ".espera")
stock = simulai.DiscreteVariable("Stock", 10, 50, 10,
"Models." + frame + ".stock")
numviajes = simulai.DiscreteVariable("Numero de viajes", 1, 5, 1,
"Models." + frame + ".numviajes")
var_input = [espera, stock, numviajes]
# Step 2- Definition of output variables
transportes = simulai.OutcomeVariable(
"Distancia Transportes", "Models." + frame + ".transportes", 2, 9)
buffers = simulai.OutcomeVariable("Llenado buffers",
"Models." + frame + ".buffers", 3,
20)
salidas = simulai.OutcomeVariable("Espera en las Salidas",
"Models." + frame + ".salidas", 2,
20)
var_output = [transportes, buffers, salidas]
# Step 3- Choice of method, plant and simulation file.
# Enter input variables and output variables.
my_method = simulai.Qlearning(v_i=var_input,
episodes_max=5,
steps_max=10)
my_plant = simulai.BasePlant(
method=my_method,
v_i=var_input,
v_o=var_output,
filename="MaterialHandling.spp",
modelname=frame,
)
# Step 4- Run the simulation
my_plant.process_simulation()
print(my_method.r_episode)
assert isinstance(my_method.r_episode, np.ndarray)
assert my_method.r_episode.all() == 0
def test_ini_saq1(self, dispatch, com, espera, stock, numviajes):
import simulai
basem = simulai.Qlearning(v_i=[espera], episodes_max=1, steps_max=10)
basem.ini_saq()
assert isinstance(basem.Q, np.ndarray)
assert isinstance(basem.S, np.ndarray)
assert isinstance(basem.actions, np.ndarray)
assert basem.Q.shape == (25, 3)
assert basem.S.shape == (25,)
assert basem.actions.shape == (3,)
assert (basem.Q == 0).all()
assert bool((basem.S == 0).all()) is False
assert bool((basem.actions == 0).all()) is False
with pytest.raises(Exception):
basen = simulai.Qlearning(
v_i=[espera, stock, numviajes, espera, stock],
episodes_max=1,
steps_max=10,
)
basen.ini_saq()
with pytest.raises(Exception):
basel = simulai.Qlearning(
v_i=[
simulai.DiscreteVariable(
"Espera", 10, 10000, 1, "Models.Modelo.espera"
)
],
episodes_max=1,
steps_max=10,
)
basel.ini_saq()
def test_process_sarsa(
self,
dispatch,
com,
espera,
stock,
numviajes,
transportes,
buffers,
salidas,
):
import simulai
pcss = simulai.Sarsa(
v_i=[
simulai.DiscreteVariable(
"Espera", 60, 300, 10, "Models.Modelo.espera"
),
simulai.DiscreteVariable(
"Stock", 10, 50, 10, "Models.Modelo.stock"
),
simulai.DiscreteVariable(
"Numero de viajes", 1, 5, 1, "Models.Modelo.numviajes"
),
],
episodes_max=1,
steps_max=10,
seed=24,
)
b = simulai.BasePlant(
method=pcss,
v_i=[espera, stock, numviajes],
v_o=[transportes, buffers, salidas],
filename="MaterialHandling.spp",
modelname="Model",
)
b.connection()
r_episodes, s0, a0 = pcss.process()
assert isinstance(r_episodes, np.ndarray), "Should be an array"
assert isinstance(s0, np.ndarray), "Should be an array"
assert a0 == 0
def test_discretevariable(self, dispatch, com, espera):
import simulai
parm = espera
assert isinstance(parm.name, str), "Should be a string"
assert isinstance(parm.lower_limit, int), "Should be an integer"
assert isinstance(parm.upper_limit, int), "Should be an integer"
assert isinstance(parm.step, int), "Should be an integer"
assert isinstance(parm.path, str), "Should be a string"
with pytest.raises(TypeError):
simulai.DiscreteVariable(
{"e": "Espera"}, 60, 300, 10, "Models.Modelo.espera"
)
with pytest.raises(TypeError):
simulai.DiscreteVariable(
"Espera", 60.0, 300, 10, "Models.Modelo.espera"
)
with pytest.raises(TypeError):
simulai.DiscreteVariable(
"Espera", 60, 300.0, 10, "Models.Modelo.espera"
)
with pytest.raises(TypeError):
simulai.DiscreteVariable(
"Espera", 60, 300, 10.0, "Models.Modelo.espera"
)
with pytest.raises(TypeError):
simulai.DiscreteVariable("Espera", 60, 300, 10, False)
with pytest.raises(ValueError):
simulai.DiscreteVariable(
"Espera", -60, 300, 10, "Models.Modelo.espera"
)
with pytest.raises(ValueError):
simulai.DiscreteVariable(
"Espera", 60, -300, 10, "Models.Modelo.espera"
)
with pytest.raises(ValueError):
simulai.DiscreteVariable(
"Espera", 60, 300, -10, "Models.Modelo.espera"
)
def numviajes(self):
import simulai
return simulai.DiscreteVariable(
"Numero de viajes", 1, 5, 1, "Models.Modelo.numviajes"
)
def stock(self):
import simulai
return simulai.DiscreteVariable(
"Stock", 10, 50, 10, "Models.Modelo.stock"
)
def espera_stp60(self):
import simulai
return simulai.DiscreteVariable(
"Espera", 60, 300, 60, "Models.Modelo.espera"
)
import simulai
# Step 0 - Definition of model frame
frame = "Modelo"
# Step 1- Definition of input variables
espera = simulai.DiscreteVariable("Espera", 60, 300, 10,
"Models." + frame + ".espera")
stock = simulai.DiscreteVariable("Stock", 10, 50, 10,
"Models." + frame + ".stock")
numviajes = simulai.DiscreteVariable("Numero de viajes", 1, 5, 1,
"Models." + frame + ".numviajes")
var_input = [espera, stock, numviajes]
# Step 2- Definition of output variables
transportes = simulai.OutcomeVariable("Distancia Transportes",
"Models." + frame + ".transportes", 2, 9)
buffers = simulai.OutcomeVariable("Llenado buffers",
"Models." + frame + ".buffers", 3, 20)
salidas = simulai.OutcomeVariable("Espera en las Salidas",
"Models." + frame + ".salidas", 2, 20)
var_output = [transportes, buffers, salidas]
# Step 3- Choice of method, plant and simulation file.
# Enter input variables and output variables.