In [1]:

    

# import everything
# note: we assume that we are running in "pylab" mode (e.g.: "from pylab import *")
import models.VPP_anyleg as vpp
reload(vpp)
import models.VppAnalyze as vpa


    

In [3]:

    

# define initial conditions
IC0 = [0, 1.085, 0, 1.15, 0, -.05]
P0 = vpp.P0(13000, 69. * pi / 180.)

# define a struct-like object
class mystruct(object):
    pass

steps = []
IC = IC0[:]
t0 = 0
for n in range(6):
# compute kinematic results
    s = mystruct()
    s.t, s.y, (s.x_foot1, s.x_foot2, s.t_td, s.t_to), s.Forces = vpp.VPP_step(IC, P0, with_forces=True)
    s.x_foot2 = P0['x_foot1'] # store "old" foot position
    s.t += t0
    s.t_td += t0
    s.t_to += t0
    t0 = s.t[-1]
    s.P = P0
    steps.append(s)
    IC = s.y[-1, :]
    P0['x_foot1'] = s.x_foot1


    

In [4]:

    

#quick sanity check of simulation results
figure()
plot(hstack([s.y[:,0] for s in steps]), hstack([s.y[:,1] for s in steps]))


    

    
Out[4]:





[<matplotlib.lines.Line2D at 0x41fd610>]






    

In [5]:

    

# store data in workspace
import mutils.io as mio
mio.msave("../data/vpp_sim.dat", steps)


    

In [7]:

    

# sample visualization
#initialize the plotting frame
import mutils.plotting as mplt
reload(mplt)
fig2 = mplt.mfig('a5', 'my figure')

# TODO: continue here. Edit mutils/plotting.py -> plain entry
fig2.set_layout(mplt.layouts['plain']) # plain format: suitable for videos
# erase ticks
ax = fig2.axes[0]
ax.set_frame_on(False)
ax.set_xticks([])
ax.set_yticks([])
#plot simulation result (1 step)
s = steps[0]
ax.plot(s.t, s.Forces[:, 1], 'r')
ax.plot(s.t, s.Forces[:, 3], 'b')
draw()


    

In [ ]: