Why does my RocketPy Monte Carlo simulation trigger a 'Flight' object has no attribute 'apogee' error?

I'm modeling a rocket trajectory using RocketPy. The deterministic simulation runs fine, but when I try to run the Monte Carlo simulations, I encounter an error indicating that the Flight object is missing the apogee attribute:

AttributeError: 'Flight' object has no attribute 'apogee'

I have simplified my code as much as possible. Below is the rocket setup code:

PYTHONCopied
# Imports
from rocketpy import Environment, SolidMotor, Rocket, Flight, MonteCarlo
from rocketpy.stochastic import (
    StochasticEnvironment,
    StochasticSolidMotor,
    StochasticRocket,
    StochasticFlight,
)
import numpy as np

# Date:
import datetime

%matplotlib widget

# Environment
env = Environment(latitude=67.89325597913002,longitude=21.065756056273834, elevation=300) 
tomorrow = datetime.date.today() + datetime.timedelta(days=1)
env.set_date((tomorrow.year, tomorrow.month, tomorrow.day, 12))
env.set_atmospheric_model(type="Ensemble", file="GEFS")

# Motor

RedMotor = SolidMotor(
    thrust_source=r"...\Python Modelling\Thrust curves\RedMotor.eng",
    burn_time=13.1, # s
    dry_mass=1.815, # kg
    dry_inertia=(1.86, 1.86, 0.13),
    center_of_dry_mass_position=0,
    grains_center_of_mass_position=0,
    grain_number=1,
    grain_separation=0,
    grain_density=1750, # kg/m^3 
    grain_outer_radius=0.2612, # m
    grain_initial_inner_radius=0.0726, # m
    grain_initial_height=2.6072, # m
    nozzle_radius=0.235, # m
    throat_radius=0.0726, # m
    interpolation_method="linear",
    nozzle_position=2.1, # from CG of motor
    coordinate_system_orientation="combustion_chamber_to_nozzle",  # combustion_chamber_to_nozzle"
)

# Rocket

RedRocket = Rocket(
    radius=0.23,
    mass=184.77,
    inertia=(1315, 1315, 14.1155),
    power_off_drag=r"...\\Python Modelling\\Drag curves\\Cesaroni_6026M1670_PpowerOffDragCurve.eng",
    power_on_drag=r"...\\Python Modelling\\Drag curves\\Cesaroni_6026M1670_PpowerOnDragCurve.eng",
    center_of_mass_without_motor=4.45,
    coordinate_system_orientation="nose_to_tail",
)

rail_buttons = RedRocket.set_rail_buttons(
    upper_button_position=3.8,
    lower_button_position=1.5,
)

RedRocket.add_motor(RedMotor, position=6.6428125)

nose_cone = RedRocket.add_nose(length=0.9375, kind="ogive", position=0)

fin_set = RedRocket.add_trapezoidal_fins(
    n=4,
    root_chord=0.703125,
    tip_chord=0.703125,
    span=0.546875,
    position=8.01,
)

transition = RedRocket.add_tail(
    top_radius=0.23, bottom_radius=0.2795, length=0.705625, position=4.57,
)

Main = RedRocket.add_parachute(
    "Main",
    cd_s=2.2 * np.pi * (120 * 25.4 / 1000) * (120 * 25.4 / 1000) / 4,
    trigger=167.64,
    sampling_rate=105,
    lag=1,
    noise=(0, 8.3, 0.5),
)

Drogue = RedRocket.add_parachute(
    "Drogue",
    cd_s=1.5 * np.pi * (24 * 25.4 / 1000) * (24 * 25.4 / 1000) / 4,
    trigger="apogee",
    sampling_rate=105,
    lag=1,
    noise=(0, 8.3, 0.5),
)

# Flight
test_flight = Flight(
    rocket=RedRocket,
    environment=env,
    rail_length=5.2,
    inclination=60,
    heading=0,
)

test_flight.all_info()

For the stochastic setup, I use the following code:

PYTHONCopied
# Stochastic Environment

stochastic_env = StochasticEnvironment(
    environment=env,
    ensemble_member=list(range(env.num_ensemble_members)),
)

stochastic_env.visualize_attributes()

# Stochastic Motor

stochastic_motor = StochasticSolidMotor(
    solid_motor=RedMotor,
    burn_start_time=(0, 0.1, "binomial"),
    grains_center_of_mass_position=0.001,
    grain_density=50, 
    grain_separation=0.001,
    grain_initial_height=0.001,
    grain_initial_inner_radius= 0.00038, 
    grain_outer_radius= 0.00038, 
    total_impulse=(1.07*(RedMotor.total_impulse), (RedMotor.total_impulse/10)),
    throat_radius= 0.0005,
    nozzle_radius= 0.0005, 
    nozzle_position=0.001, 
)
stochastic_motor.visualize_attributes()

# Stochastic Rocket

stochastic_rocket = StochasticRocket(
    rocket=RedRocket,
    radius=0.23,
    mass= 184.77, 
    inertia_11= (1325.502, 0), 
    inertia_22= (1325.502,0.01000), 
    inertia_33= 0.01, 
    center_of_mass_without_motor=4.45, 
)
stochastic_rocket.visualize_attributes()

# Stochastic Flight

stochastic_flight = StochasticFlight(
    flight=test_flight,
    inclination=(60, 1),
    heading=(0, 2),
)
stochastic_flight.visualize_attributes()

Finally, this is how I run the Monte Carlo simulation:

PYTHONCopied
# Monte Carlo Simulations

test_dispersion = MonteCarlo(
    filename="monte_carlo_analysis_outputs/monte_carlo_class_example",
    environment=stochastic_env,
    rocket=stochastic_rocket,
    flight=stochastic_flight,
)

test_dispersion.simulate(
    number_of_simulations=1000, append=False)

The error occurs during this Monte Carlo simulation. What am I doing wrong, and how can I ensure that the apogee attribute is properly computed during each simulation?