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animate_knn.py
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animate_knn.py
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import sys
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import pickle
arch='vis_grnn'
v_max=3.0
scale=6.0
F=24
K=3
radius=1.5
n_agents = 50
seed=1
step=99
K_neighbor=25
trace_dir = '{}/vinit{}_scale{}_F{}_K{}_radius_{}_N{}_{}_neighbor{}_seed{}/timeSteps_{}.pkl'.format(arch, int(v_max), scale, F, K, radius, n_agents, 'knn', K_neighbor, seed, step)
trace = pickle.load(open(trace_dir, "rb" ))
fig, ax = plt.subplots()
fig.set_tight_layout(True)
# Query the figure's on-screen size and DPI. Note that when saving the figure to
# a file, we need to provide a DPI for that separately.
print('fig size: {0} DPI, size in inches {1}'.format(
fig.get_dpi(), fig.get_size_inches()))
# Plot a scatter that persists (isn't redrawn) and the initial line.
x = trace['init_state'][:,0]
y = trace['init_state'][:,1]
print(x.shape)
print(y.shape)
print('costs = ' + str(trace['costs'][0]))
print('final_cost = {}'.format(trace['costs'][0].sum()))
print('seperate mark')
#x = np.arange(0, 20, 0.1)
#ax.scatter(x, x + np.random.normal(0, 3.0, len(x)))
print(x)
print(y)
f = ax.scatter(x,y)
ax.set(xlim=(-10, 10), ylim=(-10, 10))
#line, = ax.plot(x, x - 5, 'r-', linewidth=2)
dec = 0
#for i in range(100):
# x = trace['states'][:, :, i]
#v = (x[:, 2] ** 2 + x[:, 3] ** 2) ** 0.5
# v = (np.mean(x[:, 2]) ** 2 + np.mean(x[:, 3]) ** 2 ) ** 0.5
# dec += v
final_cost = trace['costs'][0][30:].sum() / 10.0
print('final cost = {}'.format(final_cost))
def update(i):
#fig.clear()
label = 'timestep {0}'.format(i)
print(label)
# Update the line and the axes (with a new xlabel). Return a tuple of
# "artists" that have to be redrawn for this frame.
#print(trace['states'].shape)
x = trace['states'][:,0,i]
y = trace['states'][:,1,i]
cost = trace['costs'][:, i]
data = trace['states'][:,0:2,i]
#print(data.shape)
f.set_offsets(data)
#line.set_ydata(x - 5 + i)
#ax.set_xlabel(str(label) + ' cost ' + str(costs[:,i]))
ax.set_xlabel('label = {}, cost = {:.6f}'.format(label, cost[0]))
#print('record cost = {}'.format(cost))
#print('cal cost = {}'.format(np.sum(np.var(trace['states'][:, 2:4, i], axis=0))))
return ax
if __name__ == '__main__':
# FuncAnimation will call the 'update' function for each frame; here
# animating over 10 frames, with an interval of 200ms between frames.
anim = FuncAnimation(fig, update, frames=np.arange(0, step), interval=200)
if len(sys.argv) > 1 and sys.argv[1] == 'save':
save_path = '{}_vinit{}_scale{}_F{}_K{}_radius_{}_N{}_{}_neighbor{}_seed{}_t{}.gif'.format(arch, int(v_max), scale, F, K, radius, n_agents, 'knn', K_neighbor, seed, step)
anim.save(save_path, dpi=80, writer='imagemagick')
else:
# plt.show() will just loop the animation forever.
plt.show()
print('final_cost = {}'.format(trace['costs'][0].sum()))