def __init__(self, parent):
position = list(parent.position())
velocity = list(parent.velocity)
position[0] += sin(parent.direction) * parent.radius() * 3
position[1] += cos(parent.direction) * parent.radius() * 3
velocity[0] += sin(parent.direction) * parent.bullet_velocity
velocity[1] += cos(parent.direction) * parent.bullet_velocity
Mass.__init__(self, tuple(position), parent.bullet_mass, tuple(velocity), MAX_DENSITY, parent.arena)
Agent.__init__(self)
self.age = 0
def __init__(self, position, mass, steer_power, thrust_power, arena):
Mass.__init__(self, position, mass, [0, 0], 1, arena)
Agent.__init__(self)
self.direction = 0
self.omega = 0
self.decelerating, self.accelerating = False, False
self.steer_power = steer_power
self.thrust_power = thrust_power
self.bullet_velocity = 50
self.bullet_mass = 10
self.health = 1
def isotonic_experiment(muscle_stimulation, loads,
time_param=TimeParameters()):
# Muscle
muscle_parameters = MuscleParameters()
muscle = Muscle(muscle_parameters)
# Initial conditions
x0 = [0] * StatesIsotonic.NB_STATES.value
x0[StatesIsotonic.STIMULATION.value] = 0.
x0[StatesIsotonic.L_CE.value] = muscle.L_OPT
x0[StatesIsotonic.LOAD_POS.value] = muscle.L_OPT + muscle.L_SLACK
x0[StatesIsotonic.LOAD_SPEED.value] = 0.
# Containers
v_ce = []
tendon_force = []
# Integration
pylog.info("Running the experiments (this might take a while)...")
for load in loads:
# New load definition
mass_parameters = MassParameters()
mass_parameters.mass = load
mass = Mass(mass_parameters)
# System definition
sys = IsotonicMuscleSystem()
sys.add_muscle(muscle)
sys.add_mass(mass)
result = sys.integrate(x0=x0,
time=time_param.times,
time_step=time_param.t_step,
time_stabilize=time_param.t_stabilize,
stimulation=muscle_stimulation,
load=load)
# Result processing
if result.l_mtc[-1] > x0[StatesIsotonic.LOAD_POS.value]:
# Extension
index = result.v_ce.argmax()
v_ce.append(result.v_ce.max())
tendon_force.append(result.tendon_force[index])
else:
# Contraction
index = result.v_ce.argmin()
v_ce.append(result.v_ce.min())
tendon_force.append(result.tendon_force[index])
return v_ce, tendon_force
def initalizeBodies(self,config):
level=config.levels[0]
for i in range(1,len(config.colors)):
surfFeat=config.featureDict[config.featureTypes[i]]
self.inactiveMassList.append(
Mass(i,level["pos"][i],level["radii"][i],config.colors[i],config.secondColors[i],surfFeat,level["vels"][i])
)
plrSurfFeat=config.featureDict[config.featureTypes[0]]
plr=Player(config,0,level["pos"][0],level["radii"][0],config.colors[0],config.secondColors[0],plrSurfFeat,level["vels"][0])
self.inactiveMassList.append(plr)
self.totalMasses=len(self.inactiveMassList)
self.plr=plr
def handle_shoot(self):
# You can only shoot if you are a single cell
if len(self.cells) > 1:
return
if self.get_mass() < conf.MIN_MASS_TO_SHOOT:
return
# Must be moving in a direction in order to shoot
if self.angle is None:
return
cell = self.cells[0]
cell.mass = cell.mass - conf.MASS_MASS
(mass_x, mass_y) = cell.get_pos()
mass = Mass(mass_x, mass_y, self.color, self.angle, cell.radius)
self.game.add_mass(mass)
def exercise1d():
""" Exercise 1d
Under isotonic conditions external load is kept constant.
A constant stimulation is applied and then suddenly the muscle
is allowed contract. The instantaneous velocity at which the muscle
contracts is of our interest."""
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
pylog.warning("Isotonic muscle contraction to be implemented")
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# You can still access the muscle inside the system by doing
# >>> sys.muscle.L_OPT # To get the muscle optimal length
# Evaluate for a single muscle stimulation
muscle_stimulation = 1.
# Set the initial condition
x0 = [0.0, sys.muscle.L_OPT, sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0]
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 1.25
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
# Set max_vce
max_vce = []
# ---------------------------------------------
# Small load experiment
# ---------------------------------------------
load_table_small = [5, 10, 20, 50, 100]
# Begin plotting
plt.figure('Isotonic muscle experiment - load [10, 200] [N]')
max_vce_small = ex1d_for(sys, x0, time, time_step, time_stabilize,
muscle_stimulation, load_table_small, False)
plt.title('Isotonic muscle experiment - load [5, 140] [N]')
plt.xlabel('Time [s]')
plt.ylabel('Muscle contractile velocity [m/s]')
plt.legend(loc='upper right')
plt.grid()
# ---------------------------------------------
# Big load experiment
# ---------------------------------------------
load_table_big = [150, 200, 220, 250, 500, 1000, 1500]
# Begin plotting
plt.figure('Isotonic muscle experiment - load [150, 1500] [N]')
max_vce += ex1d_for(sys, x0, time, time_step, time_stabilize,
muscle_stimulation, load_table_big, True)
plt.title('Isotonic muscle experiment - load [150, 1500] [N]')
plt.xlabel('Time [s]')
plt.ylabel('Muscle contractile velocity [m/s]')
plt.legend(loc='upper right')
plt.grid()
# ---------------------------------------------
# Plot velocity - tension relation
# ---------------------------------------------
load = np.arange(5, 2500, 200)
(max_vce, active_force) = ex1d_for(sys, x0, time, time_step,
time_stabilize, muscle_stimulation,
load, False)
fig = plt.figure('Velocity - Tension')
ax = fig.add_subplot(111)
# Plot comments and line at 0 value
min_val = 0.0
if min(map(abs, max_vce)) not in max_vce:
min_val = -min(map(abs, max_vce))
else:
min_val = min(map(abs, max_vce))
xy = (load[max_vce.index(min_val)], min_val)
xytext = (load[max_vce.index(min_val)] + 50, min_val)
ax.annotate('load = {:0.1f}'.format(152.2), xy=xy, xytext=xytext)
plt.title('Velocity [m/s] - Tension [N]')
plt.xlabel('Tension [N]')
plt.ylabel('Velocity [m/s]')
plt.grid()
plt.plot(load, max_vce)
plt.plot(load[max_vce.index(min_val)], min_val, 'o')
def exercise1d():
""" Exercise 1d
Under isotonic conditions external load is kept constant.
A constant stimulation is applied and then suddenly the muscle
is allowed contract. The instantaneous velocity at which the muscle
contracts is of our interest."""
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
pylog.warning("Isotonic muscle contraction to be implemented")
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# You can still access the muscle inside the system by doing
# >>> sys.muscle.l_opt # To get the muscle optimal length
# Evalute for a single load
load = 250 / 9.81
# Evalute for a single muscle stimulation
muscle_stimulation = 1.0
# Set the initial condition
x0 = [0.0, sys.muscle.l_opt, sys.muscle.l_opt + sys.muscle.l_slack, 0.0]
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 0.4
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=muscle_stimulation,
load=load)
# Plotting
plt.figure('Isotonic muscle experiment')
plt.plot(result.time, result.v_ce)
plt.title('Isotonic muscle experiment')
plt.xlabel('Time [s]')
plt.ylabel('Muscle contracticle velocity [lopts/s]')
plt.grid()
######################################################################
######################################################################
######################################################################
######################################################################
######################################################################
######################################################################
### code for 1d
pylog.info(
"1d. relationship between muscle contractile velocity and external load"
)
load_start = 1
load_stop = 501
load_step = 10
load_range = np.arange(load_start, load_stop, load_step)
muscle_stimulation = 1.0
vels = []
tendon_forces = []
active_forces = []
passive_forces = []
total_forces = []
for temp_load in load_range:
temp_result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=muscle_stimulation,
load=temp_load)
temp_tendon_force = temp_result.tendon_force[-1]
temp_active_force = temp_result.active_force[-1]
temp_passive_force = temp_result.passive_force[-1]
temp_total_force = temp_active_force + temp_passive_force
tendon_forces = tendon_forces + [temp_tendon_force]
active_forces = active_forces + [temp_active_force]
passive_forces = passive_forces + [temp_passive_force]
total_forces = total_forces + [temp_total_force]
temp_l_mtu = temp_result.l_mtu[-1]
if temp_l_mtu < sys.muscle.l_opt + sys.muscle.l_slack:
vels = vels + [np.min(temp_result.v_ce)]
else:
vels = vels + [np.max(temp_result.v_ce)]
plt.figure(
'1d. Isotonic muscle experiment for tension and contractile velocities'
)
plt.plot(vels, tendon_forces)
plt.plot(vels, load_range)
plt.plot(vels, active_forces)
plt.plot(vels, passive_forces)
plt.plot(vels, total_forces)
plt.title(
'Isotonic muscle experiment for tension and contractile velocities')
plt.xlabel('Muscle contracticle velocity [lopts/s]')
plt.ylabel('Tension [N]')
plt.legend(("Tendon Force", "Load", "Active Force", "Passive Force",
"Total force"))
plt.grid()
plt.show()
######################################################################
######################################################################
######################################################################
######################################################################
######################################################################
######################################################################
### code for 1f
pylog.info(
"1f. relationship between muscle contractile velocity and external load with different stimulations"
)
muscle_stimulations = np.arange(0, muscle_stimulation + 0.1, 0.1)
load_start = 1
load_stop = 501
load_step = 10
load_range = np.arange(load_start, load_stop, load_step)
all_vels = []
all_tendon_forces = []
for temp_muscle_stimulation in muscle_stimulations:
temp_vels = []
temp_tendon_forces = []
for temp_load in load_range:
temp_result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=temp_muscle_stimulation,
load=temp_load)
temp_tendon_force = temp_result.tendon_force[-1]
temp_tendon_forces = temp_tendon_forces + [temp_tendon_force]
temp_l_mtu = temp_result.l_mtu[-1]
if temp_l_mtu < sys.muscle.l_opt + sys.muscle.l_slack:
temp_vels = temp_vels + [np.min(temp_result.v_ce)]
else:
temp_vels = temp_vels + [np.max(temp_result.v_ce)]
all_vels = all_vels + [temp_vels]
all_tendon_forces = all_tendon_forces + [temp_tendon_forces]
plt.figure(
'1f. Isotonic muscle experiment for loads and contractile velocities with different stimulations'
)
for i in range(len(muscle_stimulations)):
plt.plot(all_vels[i], load_range)
plt.title(
'Isotonic muscle experiment for loads and contractile velocities with different stimulations'
)
plt.xlabel('Muscle contracticle velocity [lopts/s]')
plt.ylabel('Tension [N]')
temp_legends = [
'stimulation = ' + format((temp_stimulation), '.1f')
for temp_stimulation in muscle_stimulations
]
plt.legend(temp_legends)
plt.grid()
plt.show()
plt.figure(
'1f. Isotonic muscle experiment for tendon forces and contractile velocities with different stimulations'
)
for i in range(len(muscle_stimulations)):
plt.plot(all_vels[i], all_tendon_forces[i])
plt.title(
'Isotonic muscle experiment for tendon forces and contractile velocities with different stimulations'
)
plt.xlabel('Muscle contracticle velocity [lopts/s]')
plt.ylabel('Tension [N]')
temp_legends = [
'stimulation = ' + format((temp_stimulation), '.1f')
for temp_stimulation in muscle_stimulations
]
plt.legend(temp_legends)
plt.grid()
plt.show()
def exercise1d():
""" Exercise 1d
Under isotonic conditions external load is kept constant.
A constant stimulation is applied and then suddenly the muscle
is allowed contract. The instantaneous velocity at which the muscle
contracts is of our interest."""
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
pylog.warning("Isotonic muscle contraction to be implemented")
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# You can still access the muscle inside the system by doing
# >>> sys.muscle.L_OPT # To get the muscle optimal length
# Evalute for a single load
load = 100.
# Evalute for a single muscle stimulation
muscle_stimulation = 1.
# Set the initial condition
x0 = [0.0, sys.muscle.L_OPT, sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0]
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 0.5
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
loads = np.arange(20, 351, 10)
velocities = []
for index, load in enumerate(loads):
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=muscle_stimulation,
load=load)
if (result.l_mtc[-1] < sys.muscle.L_OPT + sys.muscle.L_SLACK):
velocities.append(np.max(result.v_ce))
print('max')
else:
velocities.append(np.min(result.v_ce))
print('min')
#Muscle contracile Velocity - Tension (load) relationship
plt.figure('Isotonic muscle experiment')
plt.title('Isotonic muscle experiment')
plt.xlabel('Muscle Contractile Velocity [m/s]')
plt.ylabel('Tension (load) [N]')
plt.plot(velocities, loads)
plt.grid()
#For different stimulations 1.f
muscle_stimulation = np.arange(0, 1.1, 0.2)
plt.figure('Isotonic muscle exp with different stimulations')
plt.title('Isotonic muscle experiment with different stimulations')
for stim in muscle_stimulation:
velocities = []
for index, load in enumerate(loads):
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=stim,
load=load)
if (result.l_mtc[-1] < sys.muscle.L_OPT + sys.muscle.L_SLACK):
velocities.append(np.max(result.v_ce))
else:
velocities.append(np.min(result.v_ce))
plt.xlabel('Muscle Contractile Velocity [m/s]')
plt.ylabel('Tension (load) [N]')
plt.plot(velocities, loads)
plt.legend(('0', '0.2', '0.4', '0.6', '0.8', '1.0'))
plt.grid()
def mass_convert():
mass = Mass()
while True:
title()
option = str(input('''
[1] Kg a G
[2] G a Kg
[3] Kg a Lb
[4] Lb a Kg
[5] G a Onz
[6] Onz a G
[7] Kg a Tn
[s]alir
''')).lower()
if option == '1':
mass.kgAG()
elif option == '2':
mass.GaKg()
elif option == '3':
mass.KgaLb()
elif option == '4':
mass.LbaKg()
elif option == '5':
mass.GaOnz()
elif option == '6':
mass.OnaAG()
elif option == '7':
mass.kgATn()
elif option == 's':
break
else:
print('Ingreso un dato invalido')
from mass import Mass
def elastic_collision(A, B):
Vaf = A.velocity - 2 * B.mass / (A.mass + B.mass) * (A.velocity -
B.velocity)
Vbf = B.velocity - 2 * A.mass / (A.mass + B.mass) * (B.velocity -
A.velocity)
A.velocity = Vaf
B.velocity = Vbf
# Adjust masses here!
A = Mass(1, 5)
B = Mass(2, -3)
Pi = A.momentum() + B.momentum()
Ki = A.kinetic_energy() + B.kinetic_energy()
print "---[Before collision]---"
print "[Object A] %s" % A
print "[Object B] %s" % B
print "[Total] p=%f, K=%f" % (Pi, Ki)
elastic_collision(A, B)
Pf = A.momentum() + B.momentum()
Kf = A.kinetic_energy() + B.kinetic_energy()
print "---[After collision]---"
print "[Object A] %s" % A
print "[Object B] %s" % B
print "[Total] p=%f, K=%f" % (Pf, Kf)
def exercise1d():
""" Exercise 1d
Under isotonic conditions external load is kept constant.
A constant stimulation is applied and then suddenly the muscle
is allowed contract. The instantaneous velocity at which the muscle
contracts is of our interest."""
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
pylog.warning("Isotonic muscle contraction to be implemented")
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# You can still access the muscle inside the system by doing
# >>> sys.muscle.L_OPT # To get the muscle optimal length
# Evalute for a single load
#load = 15.
# Evalute for a single muscle stimulation
muscle_stimulation = 1.
# Set the initial condition
x0 = [0.0, sys.muscle.L_OPT, sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0]
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 0.35
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
####custom code#####
load_range = np.arange(1, 361, 5)
my_velocity = []
plt.figure('Isotonic muscle experiment')
for load in load_range:
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=muscle_stimulation,
load=load)
my_velocity.append(max(abs(result.v_ce)))
i, = np.where(result.v_ce == my_velocity[-1])
if i.shape == (0, ): #checks for negative velocity
my_velocity[-1] *= -1
plt.plot(result.time, result.v_ce, label='Load: %s' % load)
# Plotting
#plt.plot(result.time, result.v_ce)
plt.title('Isotonic muscle experiment')
plt.xlabel('Time [s]')
plt.ylabel('Muscle contractilve velocity')
plt.grid()
plt.figure('Isotonic Experiment')
plt.plot(load_range, my_velocity)
plt.xlabel('Load[Kg]')
plt.ylabel('Maximal Muscle Contractile Velocity[m/s]')
plt.grid()
white = 255, 255, 255
screen = pygame.display.set_mode(size)
clock = pygame.time.Clock()
masses = []
preset = "lagrange"
if preset == "gas":
XPAD = 200
YPAD = 200
MINMAX = 200
for x in range(0, int(width / XPAD)):
for y in range(0, int(height / YPAD)):
masses.append(Mass(np.array([XPAD / 2 + x * XPAD, YPAD / 2 + y * YPAD]),\
np.array([r.uniform(-MINMAX, MINMAX), r.uniform(-MINMAX, MINMAX)]), 10))
elif preset == "three":
masses.append(Mass(np.array([500.0, 300.0]), np.array([0.0, 0.0]), 20))
masses.append(Mass(np.array([630.0, 300.0]), np.array([0.0, 0.0]), 20))
masses.append(Mass(np.array([600.0, 400.0]), np.array([0.0, 0.0]), 20))
elif preset == "lagrange":
masses.append(Mass(np.array([367.0, 456.0]), np.array([39.5, -148.3]), 1))
masses.append(Mass(np.array([500.0, 350.0]), np.array([150.0, 0.0]), 10))
masses.append(Mass(np.array([500.0, 500.0]), np.array([0.0, 0.0]), 50))
elif preset == "quad":
SPEED = 122
masses.append(Mass(np.array([500.0, 300.0]), np.array([-SPEED, 0.0]), 50))
masses.append(Mass(np.array([300.0, 500.0]), np.array([0.0, SPEED]), 50))
masses.append(Mass(np.array([500.0, 700.0]), np.array([SPEED, 0.0]), 50))
masses.append(Mass(np.array([700.0, 500.0]), np.array([0.0, -SPEED]), 50))
def exercise1d():
""" Exercise 1d
Under isotonic conditions external load is kept constant.
A constant stimulation is applied and then suddenly the muscle
is allowed contract. The instantaneous velocity at which the muscle
contracts is of our interest."""
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
pylog.warning("Isotonic muscle contraction to be implemented")
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# Evalute for a single muscle stimulation
muscle_stimulation = 1.
#sys.muscle.L_OPT=0.05
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 0.25
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
# You can still access the muscle inside the system by doing
# >>> sys.muscle.L_OPT # To get the muscle optimal
# Create a V_ce vector
V_ce_1d = np.zeros(100)
PF_ce_1d = np.zeros(100)
AF_ce_1d = np.zeros(100)
# Create load vector
Load = np.linspace(1, 600, num=100)
"""1.d) velocity-tension analysis """
for i in range(0, len(Load)):
# Set the initial condition
x0 = [
muscle_stimulation, sys.muscle.L_OPT,
sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0
]
# Evalute for a single load
load = Load[i]
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=muscle_stimulation,
load=load)
#print(sys.muscle.L_OPT+sys.muscle.L_SLACK)
#print(result.l_mtc[-1]-(sys.muscle.L_OPT+sys.muscle.L_SLACK))
if (result.l_mtc[-1] < sys.muscle.L_OPT + sys.muscle.L_SLACK):
V_ce_1d[i] = min(result.v_ce)
else:
V_ce_1d[i] = max(result.v_ce)
PF_ce_1d[i] = result.passive_force[-1]
AF_ce_1d[i] = result.active_force[-1]
# Plotting
plt.figure('Isotonic muscle experiment')
plt.plot(result.time, result.v_ce)
plt.title('Isotonic muscle experiment')
plt.xlabel('Time [s]')
plt.ylabel('Contractile element velocity')
plt.grid()
# Plot velocity versus tension
plt.figure()
plt.plot(V_ce_1d, Load)
plt.title('Isotonic muscle experiment')
plt.xlabel('Contractile element velocity')
plt.ylabel('Load')
plt.grid()
plt.axvline(0, color='r', linestyle='--')
# Plot velocity versus tension
plt.figure()
plt.plot(V_ce_1d, PF_ce_1d + AF_ce_1d)
#plt.plot(V_ce_1d, PF_ce_1d)
#plt.plot(V_ce_1d, AF_ce_1d, '--')
plt.title('Isotonic muscle experiment')
plt.xlabel('Contractile element velocity')
plt.ylabel('Total Force')
plt.grid()
#plt.legend(['total','passive', 'active'])
plt.axvline(0, color='r', linestyle='--')
""" 1.f) velocity-tension as a function of muscle activation """
# Create solution vector
#R_glob=np.zeros((5,50))
# Create muscle activation vector
dS = np.linspace(0.1, 1, num=5)
# Create a V_ce vector
V_ce = np.zeros((5, 100))
PF_ce = np.zeros((5, 100))
AF_ce = np.zeros((5, 100))
for i in range(0, len(Load)):
for j in range(0, len(dS)):
# Evalute for a single load
load = Load[i]
# Evalute for a single muscle stimulation
muscle_stimulation = dS[j]
# Set the initial condition
x0 = [
muscle_stimulation, sys.muscle.L_OPT,
sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0
]
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=muscle_stimulation,
load=load)
#R_glob[j,i]=result.tendon_force[len(result.tendon_force)-1]
#print(sys.muscle.L_OPT+sys.muscle.L_SLACK)
#print(result.l_mtc[-1]-(sys.muscle.L_OPT+sys.muscle.L_SLACK))
if (result.l_mtc[-1] < sys.muscle.L_OPT + sys.muscle.L_SLACK):
V_ce[j, i] = min(result.v_ce)
else:
V_ce[j, i] = max(result.v_ce)
PF_ce[j, i] = result.passive_force[-1]
AF_ce[j, i] = result.active_force[-1]
# # Plotting
# plt.figure('Isotonic muscle experiment')
# plt.plot(result.time, result.v_ce)
# plt.title('Isotonic muscle experiment')
# plt.xlabel('Time [s]')
# plt.ylabel('Contractile element velocity')
# plt.grid()
# Plot velocity versus tension
plt.figure()
for i in range(0, 5):
plt.plot(V_ce[i, :], PF_ce[i, :] + AF_ce[i, :])
plt.title('Isotonic muscle experiment')
plt.xlabel('Contractile element velocity')
plt.ylabel('Force')
plt.grid()
plt.legend([
'Stimulation = 0.1', 'Stimulation = 0.28', 'Stimulation = 0.46',
'Stimulation = 0.64', 'Stimulation = 0.82', 'Stimulation = 1'
])
class RocketSimulator(object):
def __init__(self):
self.T = 150
self.dt = 0.01
self.time = np.arange(0.0, self.T, self.dt)
self.N = len(self.time)
def initialize(self, design, launch_condition):
""" 初期化 """
self.name = design['name']
self.m_af = design['m_af']
self.I_af = design['I_af']
self.CP = design['CP']
self.CG_a = design['CG_a']
self.d = design['d']
self.area = np.pi * (self.d**2) / 4.0
self.len_a = design['len_a']
self.inertia_z0 = design['inertia_z0']
self.inertia_zT = design['inertia_zT']
self.engine = design['engine']
self.me_total = design['me_total']
self.me_prop = design['me_prop']
self.len_e = design['len_e']
self.d_e = design['d_e']
self.p0 = np.array([0., 0., 0.]) # position(x, y, z)
self.condition_name = launch_condition['name']
self.theta0 = launch_condition['AngleOfFire']
self.phi0 = launch_condition['azimuthal']
self.launch_rod = launch_condition['launch_rod']
self.v0 = np.array([0., 0., 0.]) # velocity(vx, vy, vz)
self.ome0 = np.array([0., 0., 0.])
self.density = launch_condition['density']
self.wind_R = launch_condition['StandardWind']
self.z_R = launch_condition['StandardHeight']
self.beta = launch_condition['WindDirection'] # wind direction
self.wind_direction = np.array(
[np.cos(self.beta), np.sin(self.beta), 0.0])
self.qua_theta0 = np.array(
[np.cos(0.5 * self.theta0),
np.sin(0.5 * self.theta0), 0., 0.]) # x軸theta[rad]回転, 射角
self.qua_phi0 = np.array(
[np.cos(0.5 * self.phi0), 0., 0.,
np.sin(0.5 * self.phi0)]) # z軸phi[rad]回転, 方位角
self.wind_direction = np.array(
[np.cos(self.beta), np.sin(self.beta), 0.0])
self.engine_data = np.loadtxt(self.engine)
self.force = Force(self.area, self.engine_data, self.T, self.density)
self.thrust = self.force.thrust()
self.mass = Mass(self.m_af, self.I_af, self.CG_a, self.len_a,
self.inertia_z0, self.inertia_zT, self.me_total,
self.me_prop, self.len_e, self.d_e,
self.force.burn_time, self.T)
self.M = self.mass.mass()
self.Me = self.mass.me_t()
self.Me_dot = self.mass.me_dot()
self.CG = self.mass.CG()
self.CG_dot = self.mass.CG_dot()
self.Ie = self.mass.iexg()
self.Inertia = self.mass.inertia()
self.Inertia_z = self.mass.inertia_z()
self.Inertia_dot = self.mass.inertia_dot()
self.Inertia_z_dot = self.mass.inertia_z_dot()
self.wind = Wind(self.z_R, self.wind_R)
def deriv_mc(self, pi, vi, quai, omei, t, nw, nb):
""" 運動方程式 """
qt = Quaternion()
# 機軸座標系の推力方向ベクトル
r_Ta = np.array([0., 0., 1.0])
# 慣性座標系重力加速度
gra = np.array([0., 0., -g])
# 機軸座標系の空力中心位置
r = np.array([0., 0., self.CG(t) - self.CP])
# 慣性座標系の推力方向ベクトル
r_T = qt.rotation(r_Ta, qt.coquat(quai))
r_T /= np.linalg.norm(r_T)
# 慣性テンソル
I = np.diag([self.Inertia(t), self.Inertia(t), self.Inertia_z(t)])
# 慣性テンソルの時間微分
I_dot = np.diag(
[self.Inertia_dot(t),
self.Inertia_dot(t),
self.Inertia_z_dot(t)])
# 慣性座標系対気速度
beta = self.beta + nb
v_air = (1 + nw) * self.wind.wind(pi[2]) * np.array(
[np.cos(beta), np.sin(beta), 0.0]) - vi
# 迎角
alpha = aoa.aoa(qt.rotation(v_air, quai))
# ランチロッド垂直抗力
N = 0
# ランチロッド進行中
if np.linalg.norm(pi) <= self.launch_rod and r_T[2] >= 0:
Mg_ = self.M(t) * gra - np.dot(self.M(t) * gra, r_T) * r_T
D_ = self.force.drag(alpha, v_air) - np.dot(
self.force.drag(alpha, v_air), r_T) * r_T
N = -Mg_ - D_
# 慣性座標系加速度
v_dot = gra + (self.thrust(t) * r_T + self.force.drag(alpha, v_air) +
N) / self.M(t)
# クォータニオンの導関数
qua_dot = qt.qua_dot(omei, quai)
# 機軸座標系角加速度
ome_dot = np.linalg.solve(
I, -np.cross(r, qt.rotation(self.force.drag(alpha, v_air), quai)) -
np.dot(I_dot, omei) - np.cross(omei, np.dot(I, omei)))
# ランチロッド進行中
if np.linalg.norm(pi) <= self.launch_rod:
# ランチロッド進行中は姿勢が一定なので角加速度0とする
ome_dot = np.array([0., 0., 0.])
return vi, v_dot, qua_dot, ome_dot
def simulate_mc(self, sd_w=0.1, sd_b=0.1):
noise_w = np.random.randn(self.N) * sd_w
noise_b = np.random.randn(self.N) * sd_b
""" 数値計算 """
qt = Quaternion()
p = np.empty((self.N + 1, 3))
v = np.empty((self.N + 1, 3))
qua = np.empty((self.N + 1, 4))
ome = np.empty((self.N + 1, 3))
p[0] = self.p0
v[0] = self.v0
qua[0] = qt.product(self.qua_phi0, self.qua_theta0)
ome[0] = self.ome0
count = 0
for (i, t) in enumerate(self.time):
# Euler method
p_dot, v_dot, qua_dot, ome_dot = self.deriv_mc(
p[i], v[i], qua[i], ome[i], t, noise_w[i], noise_b[i])
# if np.isnan(qua_dot).any() or np.isinf(qua_dot).any() or np.isnan(ome_dot).any() or np.isinf(ome_dot).any():
# count = i
# break
p[i + 1] = p[i] + p_dot * self.dt
v[i + 1] = v[i] + v_dot * self.dt
qua[i + 1] = qua[i] + qua_dot * self.dt
ome[i + 1] = ome[i] + ome_dot * self.dt
# vz<0かつz<0のとき計算を中断
if v[i + 1][2] < 0 and p[i + 1][2] < 0:
count = i + 1
break
qua[i + 1] /= np.linalg.norm(qua[i + 1])
if t <= self.force.burn_time:
p[i + 1][2] = max(0., p[i + 1][2])
# vz<0かつz<0のとき計算を中断
if v[i + 1][2] < 0 and p[i + 1][2] < 0:
count = i + 1
break
self.p = p[:count + 1]
self.v = v[:count + 1]
self.qua = qua[:count + 1]
self.ome = ome[:count + 1]
def falling_range(self, n=1000, sd_w=0.1, sd_b=0.1):
falling_area = []
max_alttitude = []
self.paths = []
for i in range(n):
self.simulate_mc(sd_w, sd_b)
falling_area.append(self.p[-1])
max_alttitude.append(self.p[:, 2].max())
self.paths.append(self.p)
if (i + 1) % 10 == 0:
print(str((i + 1) / n * 100) + '%')
self.paths = np.array(self.paths)
return np.array(falling_area), np.array(max_alttitude)
def output_kml(self, place):
# 原点からの距離
def dis2d(x, y):
return pow(pow(x, 2) + pow(y, 2), 0.5)
# y軸とベクトル(x, y)のなす角
def ang2d(x, y):
# y軸上
if x == 0:
if y >= 0:
return 0.0
else:
return 180.0
# x軸上
if y == 0:
if x >= 0:
return 90.0
else:
return 270.0
# 第1象限
if x > 0 and y > 0:
return np.arctan(x / y) * 180 / np.pi
# 第2象限
if x > 0 and y < 0:
return 180.0 + np.arctan(x / y) * 180 / np.pi
# 第3象限
if x < 0 and y < 0:
return 180.0 + np.arctan(x / y) * 180 / np.pi
# 第4象限
if x < 0 and y > 0:
return 360.0 + np.arctan(x / y) * 180 / np.pi
distance = [
dis2d(self.p[i, 0], self.p[i, 1]) for i in range(len(self.p))
]
angle = [ang2d(self.p[i, 0], self.p[i, 1]) for i in range(len(self.p))]
coordinate0 = place[1]
latitude = coordinate0[0]
longitude = coordinate0[1]
geod = pyproj.Geod(ellps='WGS84')
newLong = []
newLat = []
invAngle = []
for i in range(len(self.p)):
nlon, nlat, nang = geod.fwd(longitude, latitude, angle[i],
distance[i])
newLong.append(nlon)
newLat.append(nlat)
invAngle.append(nang)
kml = simplekml.Kml(open=1)
cood = []
for i in range(len(self.p)):
cood.append((newLong[i], newLat[i], self.p[i, 2]))
ls = kml.newlinestring(name=self.name + "'s Path")
ls.coords = cood
ls.style.linestyle.width = 3
ls.style.linestyle.color = simplekml.Color.blue
ls.altitudemode = simplekml.AltitudeMode.relativetoground
ls.extrude = 0
kml.save(self.name + "_" + place[0] + '_' + self.condition_name +
"_path.kml")
print("Kml file for Google Earth was created.")
def exercise1d():
""" Exercise 1d
Under isotonic conditions external load is kept constant.
A constant stimulation is applied and then suddenly the muscle
is allowed contract. The instantaneous velocity at which the muscle
contracts is of our interest."""
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
pylog.warning("Isotonic muscle contraction to be implemented")
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# You can still access the muscle inside the system by doing
# >>> sys.muscle.l_opt # To get the muscle optimal length
# Evalute for a single load
load = 250/9.81
# Evalute for a single muscle stimulation
muscle_stimulation = 1.0
# Set the initial condition
x0 = [0.0, sys.muscle.l_opt,
sys.muscle.l_opt + sys.muscle.l_slack, 0.0]
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 0.4
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
load = np.linspace(100/9.81,1700/9.81,50)
Stimu = np.linspace(0,1,6)
Vce = np.zeros((len(load),len(Stimu)))
plt.figure('Isotonix Globale')
for j in range(len(Stimu)):
# Vce = np.empty(len(load))
# Vcemax = np.empty(len(load))
# Vcemin = np.empty(len(load))
for i in range(len(load)):
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=Stimu[j],
load=load[i]
)
print(result.l_mtu[-1])
print(sys.muscle.l_opt + sys.muscle.l_slack)
if (result.l_mtu[-1] > sys.muscle.l_opt + sys.muscle.l_slack):
Vce[i,j]=(max(result.v_ce))
else: Vce[i,j] = min(result.v_ce)
Vce[:,j]
plt.plot(Vce[:,j],load, label ="MS %s" %round(Stimu[j],1))
plt.legend(loc = "upper left")
plt.xlabel('Vitesse max [m/s]')
plt.ylabel('Load [kg]')
# Plotting
plt.figure('Isotonic muscle experiment')
#plt.plot(result.time,
# result.v_ce)
plt.plot(Vce,load)
plt.title('Isotonic muscle experiment')
plt.xlabel('Vitesse max [m/s]')
plt.ylabel('Load [kg]')
#plt.xlabel('Time [s]')
#plt.ylabel('Muscle contracticle velocity [lopts/s]')
plt.grid()
#MUSCLE-Force Velocity relationship :
plt.figure('Muscle Force-Velocity')
plt.plot(result.v_ce,result.active_force, label ="Active Force")
plt.plot(result.v_ce,result.active_force+result.passive_force, label = "Passive + Active")
plt.plot(result.v_ce,result.passive_force, label = "Passive Force")
plt.legend(loc = "upper left")
plt.xlabel('Vitesse m')
plt.ylabel('Force')
def exercise1d():
""" Exercise 1d
Under isotonic conditions external load is kept constant.
A constant stimulation is applied and then suddenly the muscle
is allowed contract. The instantaneous velocity at which the muscle
contracts is of our interest."""
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
pylog.warning("Isotonic muscle contraction to be implemented")
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# You can still access the muscle inside the system by doing
# >>> sys.muscle.L_OPT # To get the muscle optimal length
# Evalute for a single load
load = 100.
# Evalute for a single muscle stimulation
muscle_stimulation = 1.
# Set the initial condition
x0 = [0.0, sys.muscle.L_OPT,
sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0]
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 0.3
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=muscle_stimulation,
load=load)
# Plotting
plt.figure('Isotonic muscle experiment')
plt.plot(result.time, result.v_ce)
plt.title('Isotonic muscle experiment')
plt.xlabel('Time [s]')
plt.ylabel('Muscle contractilve velocity')
plt.grid()
# Run 1.d
load = np.arange(0,1000,20)
plotVceLoad(load,[0.1,0.5,1])
def exercise1d():
""" Exercise 1d
Under isotonic conditions external load is kept constant.
A constant stimulation is applied and then suddenly the muscle
is allowed contract. The instantaneous velocity at which the muscle
contracts is of our interest."""
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# You can still access the muscle inside the system by doing
# >>> sys.muscle.L_OPT # To get the muscle optimal length
# Velocity-tension curve
# Evalute for various loads
load_min = 1
load_max = 301
N_load = 50
load_list = np.arange(load_min, load_max, (load_max - load_min) / N_load)
# Evalute for Stimulation = 1.0
stimulation = 1.0
# Set the initial condition
x0 = [0.0, sys.muscle.L_OPT, sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0]
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 0.3
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
max_velocity = np.zeros(N_load)
tendonF = np.zeros(N_load)
for ind_load, load in enumerate(load_list):
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=stimulation,
load=load)
if (result.l_mtc[-1] < (sys.muscle.L_OPT + sys.muscle.L_SLACK)):
max_velocity[ind_load] = np.max(-result.v_ce)
else:
max_velocity[ind_load] = np.min(-result.v_ce)
tendonF[ind_load] = result.tendon_force[-1]
# Plotting
plt.figure('Isotonic Muscle Experiment 1d')
v_min = np.amin(max_velocity)
v_max = np.amax(max_velocity)
plt.plot(max_velocity * 100 / -muscle.V_MAX, tendonF * 100 / muscle.F_MAX)
plt.axvline(linestyle='--', color='r', linewidth=2)
plt.text(v_min * 100 / -muscle.V_MAX, 20, r'lengthening', fontsize=14)
plt.text(v_max * 100 / -muscle.V_MAX * 1 / 3,
20,
r'shortening',
fontsize=14)
plt.xlabel('Maximal velocity [% of $V_{max}$]')
plt.ylabel('Tendon Force [% of $F_{max}$]')
plt.title(
'Velocity-tension curve for isotonic muscle experiment (Stimulation = 1.0)'
)
plt.grid()
def createMass(self, mass, charge, parent_mass, x, y, z):
"""
inserts new Masses into the masses list
"""
self.masses.insert(0, Mass(mass, charge, parent_mass, x, y, z))
def exercise1d():
""" Exercise 1d
Under isotonic conditions external load is kept constant.
A constant stimulation is applied and then suddenly the muscle
is allowed contract. The instantaneous velocity at which the muscle
contracts is of our interest."""
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# You can still access the muscle inside the system by doing
# >>> sys.muscle.L_OPT # To get the muscle optimal length
# Evalute for a single load
load = 100.
# Evalute for a single muscle stimulation
muscle_stimulation = 1.
# Set the initial condition
x0 = [0.0, sys.muscle.L_OPT,
sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0]
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 0.3
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
# Run the integration
load_array=np.arange(0.1,3000/sys.mass.parameters.g,5)
vel_ce=[]
act_force_int=[]
stimulation=[0.,0.2,0.4,0.6,0.8,1.]
colors=['r','g','b','c','m','y']
for loadx in load_array:
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=muscle_stimulation,
load=loadx)
if (loadx==150.1 or loadx==155.1):
plt.figure("Single Exp")
plt.title("Result for a single experiment")
plt.plot(result.time,result.v_ce*(-1))
plt.xlabel("Time [s]")
plt.ylabel("Velocity [m/s]")
plt.legend(('Shortening','Lengthening'))
pylog.info(result.l_mtc[-1])
plt.grid()
plt.show()
if result.l_mtc[-1] < ( muscle_parameters.l_opt + muscle_parameters.l_slack):
#pylog.info("min condition")
vel_ce.append(min(result.v_ce[:])*(-1))
act_force_int.append(max(result.active_force))
else:
vel_ce.append(max(result.v_ce[:])*(-1))
act_force_int.append(max(result.active_force))
# pylog.info("max condition")
plt.figure('Isotonic muscle experiment')
plt.plot(vel_ce,load_array*mass_parameters.g)
plt.plot(vel_ce,act_force_int)
plt.title('Isotonic Muscle Experiment')
plt.xlabel('Contractile Element Velocity [m/s]')
plt.ylabel('Force[N]')
plt.legend(("External Load","Internal Active Force"))
plt.grid()
plt.show()
plt.figure('Varying Stimulation')
leg=[]
for i,stim in enumerate(stimulation):
pylog.info("Stim is {}".format(stim))
vel_ce=[]
act_force_int=[]
for loadx in load_array:
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=stim,
load=loadx)
if result.l_mtc[-1] < ( muscle_parameters.l_opt + muscle_parameters.l_slack):
#pylog.info("min condition")
vel_ce.append(min(result.v_ce[:])*(-1))
act_force_int.append(max(result.active_force))
else:
vel_ce.append(max(result.v_ce[:])*(-1))
act_force_int.append(max(result.active_force))
plt.plot(vel_ce,load_array*mass_parameters.g,colors[i],label='Stimulation={}'.format(stim))
plt.plot(vel_ce,act_force_int,colors[i],linestyle=":",label='Stimulation={}'.format(stim))
leg.append(("Load-velocity plot with simulation={}".format(stim)))
leg.append(("Force-velocity with simulation={}".format(stim)))
plt.title('Varying Stimulation')
plt.legend(leg)
plt.xlabel('Contractile Element Velocity [m/s]')
plt.ylabel('Force[N]')
#("Stimulation = 0","Stimulation = 0.2","Stimulation = 0.4","Stimulation = 0.6","Stimulation = 0.8","Stimulation = 1")
plt.grid()
def exercise1f():
""" Exercise 1f
What happens to the force-velocity relationship when the stimulation is varied
between [0 - 1]?"""
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
# Instantiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# You can still access the muscle inside the system by doing
# >>> sys.muscle.L_OPT # To get the muscle optimal length
# Evaluate for a single load
load = 100.
# Set the initial condition
x0 = [0.0, sys.muscle.L_OPT, sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0]
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 1.25
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
# ---------------------------------------------
# maximum force over stimulation
# ---------------------------------------------
# Evaluate for different muscle stimulation
muscle_stimulation = np.arange(0, 1.1, 0.1)
max_active_force = []
max_passive_force = []
max_sum_force = []
# Begin plotting
for s in muscle_stimulation:
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=s,
load=load)
if abs(min(result.active_force)) > max(result.active_force):
max_active_force.append(min(result.active_force))
else:
max_active_force.append(max(result.active_force))
if abs(min(result.passive_force)) > max(result.passive_force):
max_passive_force.append(min(result.passive_force))
else:
max_passive_force.append(max(result.passive_force))
max_sum_force.append(max_active_force[-1] + max_passive_force[-1])
plt.figure('Isotonic muscle active force - stimulation [0, 1]')
plt.plot(muscle_stimulation,
max_active_force,
label='maximum active force')
plt.plot(muscle_stimulation,
max_passive_force,
label='maximum passive force')
plt.plot(muscle_stimulation, max_sum_force, label='maximum sum force')
plt.xlabel('Stimulation [-]')
plt.ylabel('Muscle sum forces [N]')
plt.legend(loc='upper right')
plt.grid()
# ---------------------------------------------
# force - velocity over stimulation
# ---------------------------------------------
muscle_stimulation = np.arange(0, 1.1, 0.1)
# Begin plotting
for s in muscle_stimulation:
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=s,
load=load)
plt.figure('Isotonic muscle active force - velocity')
plt.plot(result.v_ce[200:-1],
result.active_force[200:-1],
label='stimulation {:0.1f}'.format(s))
plt.figure('Isotonic muscle passive force - velocity')
plt.plot(result.v_ce[200:-1],
result.passive_force[200:-1],
label='stimulation {:0.1f}'.format(s))
plt.figure('Isotonic muscle sum forces - velocity')
plt.plot(result.v_ce[200:-1],
result.active_force[200:-1] + result.passive_force[200:-1],
label='stimulation {:0.1f}'.format(s))
plt.figure('Isotonic muscle active force - velocity')
plt.xlabel('Velocity contractile element [m/s]')
plt.ylabel('Active force [N]')
plt.legend(loc='upper right')
plt.grid()
plt.figure('Isotonic muscle passive force - velocity')
plt.xlabel('Velocity contractile element [m/s]')
plt.ylabel('Passive force [N]')
plt.legend(loc='upper right')
plt.grid()
plt.figure('Isotonic muscle sum forces - velocity')
plt.xlabel('Velocity contractile element [m/s]')
plt.ylabel('Sum forces [N]')
plt.legend(loc='upper right')
plt.grid()
# ---------------------------------------------
# Plot velocity - tension relation
# ---------------------------------------------
muscle_stimulation = np.arange(0, 1.1, 0.25)
load = np.arange(5, 1500, 20)
plt.figure('Velocity - Tension')
# Begin plotting
for s in muscle_stimulation:
(max_vce, active_force) = ex1d_for(sys, x0, time, time_step,
time_stabilize, s, load, False)
plt.plot(load, max_vce, label="stimulation {:0.1f}".format(s))
plt.title('Velocity [m/s] - Load [N]')
plt.xlabel('Load [N]')
plt.ylabel('Velocity [m/s]')
plt.legend(loc='lower right')
plt.grid()
def initialize(self, design, launch_condition):
""" 初期化 """
self.name = design['name']
self.m_af = design['m_af']
self.I_af = design['I_af']
self.CP = design['CP']
self.CG_a = design['CG_a']
self.d = design['d']
self.area = np.pi * (self.d**2) / 4.0
self.len_a = design['len_a']
self.inertia_z0 = design['inertia_z0']
self.inertia_zT = design['inertia_zT']
self.engine = design['engine']
self.me_total = design['me_total']
self.me_prop = design['me_prop']
self.len_e = design['len_e']
self.d_e = design['d_e']
self.p0 = np.array([0., 0., 0.]) # position(x, y, z)
self.condition_name = launch_condition['name']
self.theta0 = launch_condition['AngleOfFire']
self.phi0 = launch_condition['azimuthal']
self.launch_rod = launch_condition['launch_rod']
self.v0 = np.array([0., 0., 0.]) # velocity(vx, vy, vz)
self.ome0 = np.array([0., 0., 0.])
self.density = launch_condition['density']
self.wind_R = launch_condition['StandardWind']
self.z_R = launch_condition['StandardHeight']
self.beta = launch_condition['WindDirection'] # wind direction
self.wind_direction = np.array(
[np.cos(self.beta), np.sin(self.beta), 0.0])
self.qua_theta0 = np.array(
[np.cos(0.5 * self.theta0),
np.sin(0.5 * self.theta0), 0., 0.]) # x軸theta[rad]回転, 射角
self.qua_phi0 = np.array(
[np.cos(0.5 * self.phi0), 0., 0.,
np.sin(0.5 * self.phi0)]) # z軸phi[rad]回転, 方位角
self.wind_direction = np.array(
[np.cos(self.beta), np.sin(self.beta), 0.0])
self.engine_data = np.loadtxt(self.engine)
self.force = Force(self.area, self.engine_data, self.T, self.density)
self.thrust = self.force.thrust()
self.mass = Mass(self.m_af, self.I_af, self.CG_a, self.len_a,
self.inertia_z0, self.inertia_zT, self.me_total,
self.me_prop, self.len_e, self.d_e,
self.force.burn_time, self.T)
self.M = self.mass.mass()
self.Me = self.mass.me_t()
self.Me_dot = self.mass.me_dot()
self.CG = self.mass.CG()
self.CG_dot = self.mass.CG_dot()
self.Ie = self.mass.iexg()
self.Inertia = self.mass.inertia()
self.Inertia_z = self.mass.inertia_z()
self.Inertia_dot = self.mass.inertia_dot()
self.Inertia_z_dot = self.mass.inertia_z_dot()
self.wind = Wind(self.z_R, self.wind_R)
def __init__(self, position, mass, velocity, density, arena):
Mass.__init__(self, position, mass, velocity, density, arena)
Agent.__init__(self)
self.shape = [random() for i in xrange(24)]
self.direction = 0
self.omega = (random() - 0.5) * (pi/50)
def exercise1f():
""" Exercise 1f """
# Defination of muscles
muscle_parameters = MuscleParameters()
print(muscle_parameters.showParameters())
mass_parameters = MassParameters()
print(mass_parameters.showParameters())
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# Velocity-tension curve
# Evalute for various loads
load_min = 1
load_max = 501
N_load = 50
load_list = np.arange(load_min, load_max, (load_max - load_min) / N_load)
# Evalute for various muscle stimulation
N_stim = 4
muscle_stimulation = np.round(np.arange(N_stim) / (N_stim - 1), 2)
# Set the initial condition
x0 = [0.0, sys.muscle.L_OPT, sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0]
# Set the time for integration
t_start = 0.0
t_stop = 0.3
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
max_velocity = np.zeros((N_stim, N_load))
tendonF = np.zeros((N_stim, N_load))
for i, stim in enumerate(muscle_stimulation):
for ind_load, load in enumerate(load_list):
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=stim,
load=load)
if (result.l_mtc[-1] < (sys.muscle.L_OPT + sys.muscle.L_SLACK)):
max_velocity[i, ind_load] = np.max(-result.v_ce)
else:
max_velocity[i, ind_load] = np.min(-result.v_ce)
tendonF[i, ind_load] = result.tendon_force[-1]
# Plotting
plt.figure('Isotonic Muscle Experiment 1f')
v_min = np.amin(max_velocity)
v_max = np.amax(max_velocity)
for i, stim in enumerate(muscle_stimulation):
plt.plot(max_velocity[i, :] * 100 / -muscle.V_MAX,
tendonF[i, :] * 100 / muscle.F_MAX,
label='Tendon Force - Stimulation = {}'.format(stim))
plt.xlim(v_min * 100 / -muscle.V_MAX, v_max * 100 / -muscle.V_MAX)
plt.ylim(0, 200)
plt.axvline(linestyle='--', color='r', linewidth=2)
plt.text(v_min * 100 / -muscle.V_MAX * 2 / 3,
170,
r'lengthening',
fontsize=16)
plt.text(v_max * 100 / -muscle.V_MAX * 1 / 8,
170,
r'shortening',
fontsize=16)
plt.xlabel('Maximal velocity [% of $V_{max}$]')
plt.ylabel('Tendon Force [% of $F_{max}$]')
plt.title(
'Velocity-tension curves for isotonic muscle experiment with various muscle stimulations'
)
plt.legend()
plt.grid()
def plotVceLoad(load,ms=[1.]):
# Defination of muscles
muscle_parameters = MuscleParameters()
mass_parameters = MassParameters()
# Create muscle object
muscle = Muscle(muscle_parameters)
# Create mass object
mass = Mass(mass_parameters)
# Instatiate isotonic muscle system
sys = IsotonicMuscleSystem()
# Add the muscle to the system
sys.add_muscle(muscle)
# Add the mass to the system
sys.add_mass(mass)
# Evalute for a single load
#load = 100.
# Set the initial condition
x0 = [0.0, sys.muscle.L_OPT,
sys.muscle.L_OPT + sys.muscle.L_SLACK, 0.0]
# x0[0] - -> activation
# x0[1] - -> contractile length(l_ce)
# x0[2] - -> position of the mass/load
# x0[3] - -> velocity of the mass/load
# Set the time for integration
t_start = 0.0
t_stop = 0.3
time_step = 0.001
time_stabilize = 0.2
time = np.arange(t_start, t_stop, time_step)
plt.figure('Max Velocity-Tension curve')
for s in ms:
muscle_stimulation = s
v = []
for l in load:
# Run the integration
result = sys.integrate(x0=x0,
time=time,
time_step=time_step,
time_stabilize=time_stabilize,
stimulation=muscle_stimulation,
load=l)
# Find the max or min speed achieved
i = np.argmax(np.abs(result.v_ce))
v.append(-result.v_ce[i])
#if result[i].l_mtc < sys.muscle.L_OPT + sys.muscle.L_SLACK:
for i in range(len(v)):
if i >= 1 and v[i]*v[i-1] <=0:
plt.plot(load[i],v[i],color='green', marker='x', linestyle='dashed',
linewidth=2, markersize=12)
plt.plot(load, v,label='maximal speed\nMuscle stimulation: {}'.format(s))
plt.legend()
plt.title('Isotonic muscle experiment\nMax Velocity-Tension curve')
plt.xlabel('load [kg]')
plt.ylabel('CE speed [m/s]')
#axes = plt.gca()
#axes.set_xlim([0.05,0.2])
#axes.set_ylim([0,1700])
plt.grid()
class RocketSimulator(object):
def __init__(self):
self.T = 150
self.dt = 0.01
self.time = np.arange(0.0, self.T, self.dt)
self.N = len(self.time)
def initialize(self, design, launch_condition):
""" 初期化 """
self.name = design['name']
self.m_af = design['m_af']
self.I_af = design['I_af']
self.CP = design['CP']
self.CG_a = design['CG_a']
self.d = design['d']
self.area = np.pi * (self.d**2) / 4.0
self.len_a = design['len_a']
self.inertia_z0 = design['inertia_z0']
self.inertia_zT = design['inertia_zT']
self.engine = design['engine']
self.me_total = design['me_total']
self.me_prop = design['me_prop']
self.len_e = design['len_e']
self.d_e = design['d_e']
self.p0 = np.array([0., 0., 0.]) # position(x, y, z)
self.condition_name = launch_condition['name']
self.theta0 = launch_condition['AngleOfFire']
self.phi0 = launch_condition['azimuthal']
self.launch_rod = launch_condition['launch_rod']
self.v0 = np.array([0., 0., 0.]) # velocity(vx, vy, vz)
self.ome0 = np.array([0., 0., 0.])
self.density = launch_condition['density']
self.wind_R = launch_condition['StandardWind']
self.z_R = launch_condition['StandardHeight']
self.beta = launch_condition['WindDirection'] # wind direction
self.wind_direction = np.array(
[np.cos(self.beta), np.sin(self.beta), 0.0])
self.qua_theta0 = np.array(
[np.cos(0.5 * self.theta0),
np.sin(0.5 * self.theta0), 0., 0.]) # x軸theta[rad]回転, 射角
self.qua_phi0 = np.array(
[np.cos(0.5 * self.phi0), 0., 0.,
np.sin(0.5 * self.phi0)]) # z軸phi[rad]回転, 方位角
self.wind_direction = np.array(
[np.cos(self.beta), np.sin(self.beta), 0.0])
self.engine_data = np.loadtxt(self.engine)
self.force = Force(self.area, self.engine_data, self.T, self.density)
self.thrust = self.force.thrust()
self.mass = Mass(self.m_af, self.I_af, self.CG_a, self.len_a,
self.inertia_z0, self.inertia_zT, self.me_total,
self.me_prop, self.len_e, self.d_e,
self.force.burn_time, self.T)
self.M = self.mass.mass()
self.Me = self.mass.me_t()
self.Me_dot = self.mass.me_dot()
self.CG = self.mass.CG()
self.CG_dot = self.mass.CG_dot()
self.Ie = self.mass.iexg()
self.Inertia = self.mass.inertia()
self.Inertia_z = self.mass.inertia_z()
self.Inertia_dot = self.mass.inertia_dot()
self.Inertia_z_dot = self.mass.inertia_z_dot()
self.wind = Wind(self.z_R, self.wind_R)
def deriv(self, pi, vi, quai, omei, t):
""" 運動方程式 """
qt = Quaternion()
# 機軸座標系の推力方向ベクトル
r_Ta = np.array([0., 0., 1.0])
# 慣性座標系重力加速度
gra = np.array([0., 0., -g])
# 機軸座標系の空力中心位置
r = np.array([0., 0., self.CG(t) - self.CP])
# 慣性座標系の推力方向ベクトル
r_T = qt.rotation(r_Ta, qt.coquat(quai))
r_T /= np.linalg.norm(r_T)
# 慣性テンソル
I = np.diag([self.Inertia(t), self.Inertia(t), self.Inertia_z(t)])
# 慣性テンソルの時間微分
I_dot = np.diag(
[self.Inertia_dot(t),
self.Inertia_dot(t),
self.Inertia_z_dot(t)])
# 慣性座標系対気速度
v_air = self.wind.wind(pi[2]) * self.wind_direction - vi
# 迎角
alpha = aoa.aoa(qt.rotation(v_air, quai))
# ランチロッド垂直抗力
N = 0
# ランチロッド進行中
if np.linalg.norm(pi) <= self.launch_rod and r_T[2] >= 0:
Mg_ = self.M(t) * gra - np.dot(self.M(t) * gra, r_T) * r_T
D_ = self.force.drag(alpha, v_air) - np.dot(
self.force.drag(alpha, v_air), r_T) * r_T
N = -Mg_ - D_
# 慣性座標系加速度
v_dot = gra + (self.thrust(t) * r_T + self.force.drag(alpha, v_air) +
N) / self.M(t)
# クォータニオンの導関数
qua_dot = qt.qua_dot(omei, quai)
# 機軸座標系角加速度
ome_dot = np.linalg.solve(
I, -np.cross(r, qt.rotation(self.force.drag(alpha, v_air), quai)) -
np.dot(I_dot, omei) - np.cross(omei, np.dot(I, omei)))
# ランチロッド進行中
if np.linalg.norm(pi) <= self.launch_rod:
# ランチロッド進行中は姿勢が一定なので角加速度0とする
ome_dot = np.array([0., 0., 0.])
return vi, v_dot, qua_dot, ome_dot
def simulate(self, method='RungeKutta', log=False):
""" 数値計算 """
qt = Quaternion()
p = np.empty((self.N + 1, 3))
v = np.empty((self.N + 1, 3))
qua = np.empty((self.N + 1, 4))
ome = np.empty((self.N + 1, 3))
p[0] = self.p0
v[0] = self.v0
qua[0] = qt.product(self.qua_phi0, self.qua_theta0)
ome[0] = self.ome0
count = 0
for (i, t) in enumerate(self.time):
if method == 'RungeKutta':
# Runge-Kutta method
pk1, vk1, quak1, omek1 = self.deriv(p[i], v[i], qua[i], ome[i],
t)
pk2, vk2, quak2, omek2 = self.deriv(
p[i] + pk1 * self.dt * 0.5, v[i] + vk1 * self.dt * 0.5,
qua[i] + quak1 * self.dt * 0.5,
ome[i] + omek1 * self.dt * 0.5, t + self.dt * 0.5)
pk3, vk3, quak3, omek3 = self.deriv(
p[i] + pk2 * self.dt * 0.5, v[i] + vk2 * self.dt * 0.5,
qua[i] + quak2 * self.dt * 0.5,
ome[i] + omek2 * self.dt * 0.5, t + self.dt * 0.5)
pk4, vk4, quak4, omek4 = self.deriv(p[i] + pk3 * self.dt,
v[i] + vk3 * self.dt,
qua[i] + quak3 * self.dt,
ome[i] + omek3 * self.dt,
t + self.dt)
p[i + 1] = p[i] + (pk1 + 2 * pk2 + 2 * pk3 + pk4) * self.dt / 6
v[i + 1] = v[i] + (vk1 + 2 * vk2 + 2 * vk3 + vk4) * self.dt / 6
qua[i + 1] = qua[i] + (quak1 + 2 * quak2 + 2 * quak3 +
quak4) * self.dt / 6
ome[i + 1] = ome[i] + (omek1 + 2 * omek2 + 2 * omek3 +
omek4) * self.dt / 6
elif method == 'Euler':
# Euler method
p_dot, v_dot, qua_dot, ome_dot = self.deriv(
p[i], v[i], qua[i], ome[i], t)
p[i + 1] = p[i] + p_dot * self.dt
v[i + 1] = v[i] + v_dot * self.dt
qua[i + 1] = qua[i] + qua_dot * self.dt
ome[i + 1] = ome[i] + ome_dot * self.dt
if t <= self.force.burn_time:
p[i + 1][2] = max(0., p[i + 1][2])
# vz<0かつz<0のとき計算を中断
if v[i + 1][2] < 0 and p[i + 1][2] < 0:
count = i + 1
print("Calculation was successfully completed.")
break
self.p = p[:count + 1]
self.v = v[:count + 1]
self.qua = qua[:count + 1]
self.ome = ome[:count + 1]
if log:
np.savetxt(self.name + "_" + self.condition_name + "_position.csv",
p,
delimiter=",")
print("Position file was created.")
print("Altitude is " + str(max(p[:, 2])) + "[m].")
def output_kml(self, place):
# 原点からの距離
def dis2d(x, y):
return pow(pow(x, 2) + pow(y, 2), 0.5)
# y軸とベクトル(x, y)のなす角
def ang2d(x, y):
# y軸上
if x == 0:
if y >= 0:
return 0.0
else:
return 180.0
# x軸上
if y == 0:
if x >= 0:
return 90.0
else:
return 270.0
# 第1象限
if x > 0 and y > 0:
return np.arctan(x / y) * 180 / np.pi
# 第2象限
if x > 0 and y < 0:
return 180.0 + np.arctan(x / y) * 180 / np.pi
# 第3象限
if x < 0 and y < 0:
return 180.0 + np.arctan(x / y) * 180 / np.pi
# 第4象限
if x < 0 and y > 0:
return 360.0 + np.arctan(x / y) * 180 / np.pi
distance = [
dis2d(self.p[i, 0], self.p[i, 1]) for i in range(len(self.p))
]
angle = [ang2d(self.p[i, 0], self.p[i, 1]) for i in range(len(self.p))]
coordinate0 = place[1]
latitude = coordinate0[0]
longitude = coordinate0[1]
geod = pyproj.Geod(ellps='WGS84')
newLong = []
newLat = []
invAngle = []
for i in range(len(self.p)):
nlon, nlat, nang = geod.fwd(longitude, latitude, angle[i],
distance[i])
newLong.append(nlon)
newLat.append(nlat)
invAngle.append(nang)
kml = simplekml.Kml(open=1)
cood = []
for i in range(len(self.p)):
cood.append((newLong[i], newLat[i], self.p[i, 2]))
ls = kml.newlinestring(name=self.name + "'s Path")
ls.coords = cood
ls.style.linestyle.width = 3
ls.style.linestyle.color = simplekml.Color.blue
ls.altitudemode = simplekml.AltitudeMode.relativetoground
ls.extrude = 0
kml.save(self.name + "_" + place[0] + '_' + self.condition_name +
"_path.kml")
print("Kml file for Google Earth was created.")