linewidth=2.0)
image.patches.append(sphere1)
image.patches.append(sphere2)
image.patches.append(car)
image.patches.append(joint)
image.lines.append(rod1)
image.lines.append(rod2)
return image
if not 'no-pickle' in sys.argv:
# here we save the simulation results so we don't have to run
# the iteration again in case the following fails
S.save(fname='ex2_InvertedDualPendulumSwingUp.pcl')
if 'plot' in sys.argv or 'animate' in sys.argv:
A = Animation(drawfnc=draw,
simdata=S.sim_data,
plotsys=[(0, 'x'), (2, 'phi1'), (4, 'phi2')],
plotinputs=[(0, 'u')])
xmin = np.min(S.sim_data[1][:, 0])
xmax = np.max(S.sim_data[1][:, 0])
A.set_limits(xlim=(xmin - 1.0, xmax + 1.0), ylim=(-0.8, 0.8))
if 'plot' in sys.argv:
A.show(t=S.b)
if 'animate' in sys.argv:
color='black',
zorder=1,
linewidth=2.0)
image.patches.append(pendulum)
image.patches.append(car)
image.patches.append(joint)
image.lines.append(rod)
return image
if not 'no-pickle' in sys.argv:
# here we save the simulation results so we don't have to run
# the iteration again in case the following fails
S.save(fname='ex7_ConstrainedInvertedPendulum.pcl')
if 'plot' in sys.argv or 'animate' in sys.argv:
A = Animation(drawfnc=draw,
simdata=S.sim_data,
plotsys=[(0, 'x'), (1, 'dx')],
plotinputs=[(0, 'u1')])
xmin = np.min(S.sim_data[1][:, 0])
xmax = np.max(S.sim_data[1][:, 0])
A.set_limits(xlim=(xmin - 0.5, xmax + 0.5), ylim=(-0.6, 0.6))
if 'plot' in sys.argv:
A.show(t=S.b)
if 'animate' in sys.argv:
A.animate()
maxIt=3,
eps=1e-1,
sol_steps=100,
reltol=1e-3,
accIt=1,
show_ir=True)
# dt_sim=0.004
# time to run the iteration
x, u = S.solve()
if S.reached_accuracy:
print "successed!"
else:
print "Not successed!"
S.save(fname='pickles/model_trajectory' + str(Tb) + '.pcl')
import sys
import matplotlib as mpl
from pytrajectory.visualisation import Animation
from sympy import cos, sin
N = 3
# all rods have the same length
rod_lengths = [0.5] * N
# all pendulums have the same size
pendulum_sizes = [0.015] * N
car_width, car_height = [0.05, 0.02]
# joint
joint = mpl.patches.Circle((x_car, 0), 0.005, color='k')
image.lines.append(rod)
image.patches.append(sphere)
image.patches.append(cart)
image.patches.append(joint)
return image
if not 'no-pickle' in sys.argv:
# here we save the simulation results so we don't have to run
# the iteration again in case the following fails
S.save(fname='ex1_InvertedPendulumTranslation.pcl')
if 'plot' in sys.argv or 'animate' in sys.argv:
A = Animation(drawfnc=draw,
simdata=S.sim_data,
plotsys=[(0, 'x'), (2, 'phi')],
plotinputs=[(0, 'u')])
xmin = np.min(S.sim_data[1][:, 0])
xmax = np.max(S.sim_data[1][:, 0])
A.set_limits(xlim=(xmin - 0.5, xmax + 0.5), ylim=(-0.3, 0.8))
if 'plot' in sys.argv:
A.show(t=S.b)
if 'animate' in sys.argv:
print S.eqs.solver.res, "\n"
print S.eqs.solver.x0[:9]
sim_res.append(S.sim_data_xx[-1])
residum_res.append(S.eqs.solver.res)
if S.reached_accuracy:
print "success", i
userinput = raw_input("Press `q` to quit.\n")
if userinput == "q":
break
else:
print "fail"
reslist.append(S.eqs.solver.x0)
time.sleep(2)
S.save(fname='model_trajectory.pcl')
IPS()
import matplotlib as mpl
from pytrajectory.visualisation import Animation
from sympy import cos, sin
N = 3
# all rods have the same length
rod_lengths = [0.5] * N
# all pendulums have the same size
pendulum_sizes = [0.015] * N
car_width, car_height = [0.08, 0.04]
# pendulums
sphere1 = mpl.patches.Circle((x1, y1), 0.01, color='k')
sphere2 = mpl.patches.Circle((0, 0), 0.01, color='k')
image.lines.append(rod1)
image.lines.append(rod2)
image.patches.append(sphere1)
image.patches.append(sphere2)
return image
if not 'no-pickle' in sys.argv:
# here we save the simulation results so we don't have to run
# the iteration again in case the following fails
S.save(fname='ex5_Acrobot.pcl')
if 'plot' in sys.argv or 'animate' in sys.argv:
A = Animation(drawfnc=draw,
simdata=S.sim_data,
plotsys=[(0, 'phi1'), (2, 'phi2')],
plotinputs=[(0, 'u')])
A.set_limits(xlim=(-1.1, 1.1), ylim=(-1.1, 1.1))
if 'plot' in sys.argv:
A.show(t=S.b)
if 'animate' in sys.argv:
A.animate()
A.save('ex5_Acrobot.gif')
xx = S[:, 0].copy()
yy = S[:, 1].copy()
S[:, 0] = xx * cos(theta) - yy * sin(theta) + x
S[:, 1] = yy * cos(theta) + xx * sin(theta) + y
aircraft = mpl.patches.Polygon(S, closed=True, facecolor='0.75')
image.patches.append(aircraft)
return image
if not 'no-pickle' in sys.argv:
# here we save the simulation results so we don't have to run
# the iteration again in case the following fails
S.save(fname='ex3_Aircraft.pcl')
if 'plot' in sys.argv or 'animate' in sys.argv:
A = Animation(drawfnc=draw,
simdata=S.sim_data,
plotsys=[(4, 'theta')],
plotinputs=[(0, 'F1'), (1, 'F2')])
A.set_limits(xlim=(-1, 11), ylim=(-1, 7))
if 'plot' in sys.argv:
A.show(t=S.b)
if 'animate' in sys.argv:
A.animate()
A.save('ex3_Aircraft.gif')
rod1 = mpl.lines.Line2D([0,x1],[0,y1],color='k',zorder=0,linewidth=2.0)
rod2 = mpl.lines.Line2D([x1,x2],[y1,y2],color='k',zorder=0,linewidth=2.0)
# pendulums
sphere1 = mpl.patches.Circle((x1,y1),0.01,color='k')
sphere2 = mpl.patches.Circle((0,0),0.01,color='k')
image.lines.append(rod1)
image.lines.append(rod2)
image.patches.append(sphere1)
image.patches.append(sphere2)
return image
if not 'no-pickle' in sys.argv:
# here we save the simulation results so we don't have to run
# the iteration again in case the following fails
S.save(fname='ex4_UnderactuatedManipulator.pcl')
if 'plot' in sys.argv or 'animate' in sys.argv:
A = Animation(drawfnc=draw, simdata=S.sim_data,
plotsys=[(0,'phi1'), (2,'phi2')], plotinputs=[(0,'u')])
A.set_limits(xlim= (-0.1,0.6), ylim=(-0.4,0.65))
if 'plot' in sys.argv:
A.show(t=S.b)
if 'animate' in sys.argv:
A.animate()
A.save('ex4_UnderactuatedManipulator.gif')
linewidth=2.0)
# finally we add the patches and line to the image
image.patches.append(pendulum)
image.patches.append(car)
image.patches.append(joint)
image.lines.append(rod)
# and return the image
return image
if not 'no-pickle' in sys.argv:
# here we save the simulation results so we don't have to run
# the iteration again in case the following fails
S.save(fname='ex0_InvertedPendulumSwingUp.pcl')
# now we can create an instance of the `Animation` class
# with our draw function and the simulation results
#
# this was aked for by one user:
# save the simulation data (solution of IVP) to csv
tt, xx, uu = S.sim_data
export_array = np.hstack((tt.reshape(-1, 1), xx, uu))
# to actually save the array uncomment the following:
# np.savetxt("ex0_result.csv", export_array, delimiter=",")
# first column: time
car = mpl.patches.Rectangle((x_car - 0.5 * car_width, y_car - car_heigth),
car_width,
car_heigth,
fill=True,
facecolor='grey',
linewidth=2.0)
image.patches.append(car)
return image
if not 'no-pickle' in sys.argv:
# here we save the simulation results so we don't have to run
# the iteration again in case the following fails
S.save(fname='ex6_ConstrainedDoubleIntegrator.pcl')
if 'plot' in sys.argv or 'animate' in sys.argv:
A = Animation(drawfnc=draw,
simdata=S.sim_data,
plotsys=[(0, 'x'), (1, 'dx')],
plotinputs=[(0, 'u')])
xmin = np.min(S.sim_data[1][:, 0])
xmax = np.max(S.sim_data[1][:, 0])
A.set_limits(xlim=(xmin - 0.1, xmax + 0.1), ylim=(-0.1, 0.1))
if 'plot' in sys.argv:
A.show(t=S.b)
if 'animate' in sys.argv:
A.animate()
# add the patches and lines to the image
image.patches.append(pendulum1)
image.patches.append(pendulum2)
image.patches.append(car)
image.patches.append(joint)
image.lines.append(rod1)
image.lines.append(rod2)
# and return the image
return image
if not 'no-pickle' in sys.argv:
# here we save the simulation results so we don't have to run
# the iteration again in case the following fails
S.save(fname='ex8_ConstrainedDoublePendulum.pcl')
if 'plot' in sys.argv or 'animate' in sys.argv:
# create Animation object
A = Animation(drawfnc=draw,
simdata=S.sim_data,
plotsys=[(0, '$x$'), (1, '$\\dot{x}$')],
plotinputs=[(0, '$u$')])
xmin = np.min(S.sim_data[1][:, 0])
xmax = np.max(S.sim_data[1][:, 0])
A.set_limits(xlim=(xmin - 1.0, xmax + 1.0), ylim=(-1.2, 1.2))
if 'plot' in sys.argv:
A.show(t=S.b)
if 'animate' in sys.argv: