def plot_trajectory(dt, hardness, orig_maps, out_dir):
out_dir = os.path.join(out_dir, FLAGS.config_name+_get_suffix_str(),
FLAGS.imset)
fu.makedirs(out_dir)
out_file = os.path.join(out_dir, 'all_locs_at_t.pkl')
dt['hardness'] = hardness
utils.save_variables(out_file, dt.values(), dt.keys(), overwrite=True)
#Plot trajectories onto the maps
plt.set_cmap('gray')
for i in range(4000):
goal_loc = dt['all_goal_locs'][i, :, :]
locs = np.concatenate((dt['all_locs'][i,:,:],
dt['all_locs'][i,:,:]), axis=0)
xymin = np.minimum(np.min(goal_loc, axis=0), np.min(locs, axis=0))
xymax = np.maximum(np.max(goal_loc, axis=0), np.max(locs, axis=0))
xy1 = (xymax+xymin)/2. - 1.*np.maximum(np.max(xymax-xymin), 24)
xy2 = (xymax+xymin)/2. + 1.*np.maximum(np.max(xymax-xymin), 24)
fig, ax = utils.tight_imshow_figure(plt, figsize=(6,6))
ax.set_axis_on()
ax.patch.set_facecolor((0.333, 0.333, 0.333))
ax.set_xticks([])
ax.set_yticks([])
all_locs = dt['all_locs'][i,:,:]*1
uniq = np.where(np.any(all_locs[1:,:] != all_locs[:-1,:], axis=1))[0]+1
uniq = np.sort(uniq).tolist()
uniq.insert(0,0)
uniq = np.array(uniq)
all_locs = all_locs[uniq, :]
ax.plot(dt['all_locs'][i, 0, 0],
dt['all_locs'][i, 0, 1], 'b.', markersize=24)
ax.plot(dt['all_goal_locs'][i, 0, 0],
dt['all_goal_locs'][i, 0, 1], 'g*', markersize=19)
ax.plot(all_locs[:,0], all_locs[:,1], 'r', alpha=0.4, linewidth=2)
ax.scatter(all_locs[:,0], all_locs[:,1],
c=5+np.arange(all_locs.shape[0])*1./all_locs.shape[0],
cmap='Reds', s=30, linewidth=0)
ax.imshow(orig_maps, origin='lower', vmin=-1.0, vmax=2.0, aspect='equal')
ax.set_xlim([xy1[0], xy2[0]])
ax.set_ylim([xy1[1], xy2[1]])
file_name = os.path.join(out_dir, 'trajectory_{:04d}.png'.format(i))
print(file_name)
with fu.fopen(file_name, 'w') as f:
plt.savefig(f)
plt.close(fig)
def plot_trajectory(dt, hardness, orig_maps, out_dir):
out_dir = os.path.join(out_dir, FLAGS.config_name+_get_suffix_str(),
FLAGS.imset)
fu.makedirs(out_dir)
out_file = os.path.join(out_dir, 'all_locs_at_t.pkl')
dt['hardness'] = hardness
utils.save_variables(out_file, dt.values(), dt.keys(), overwrite=True)
#Plot trajectories onto the maps
plt.set_cmap('gray')
for i in range(4000):
goal_loc = dt['all_goal_locs'][i, :, :]
locs = np.concatenate((dt['all_locs'][i,:,:],
dt['all_locs'][i,:,:]), axis=0)
xymin = np.minimum(np.min(goal_loc, axis=0), np.min(locs, axis=0))
xymax = np.maximum(np.max(goal_loc, axis=0), np.max(locs, axis=0))
xy1 = (xymax+xymin)/2. - 1.*np.maximum(np.max(xymax-xymin), 24)
xy2 = (xymax+xymin)/2. + 1.*np.maximum(np.max(xymax-xymin), 24)
fig, ax = utils.tight_imshow_figure(plt, figsize=(6,6))
ax.set_axis_on()
ax.patch.set_facecolor((0.333, 0.333, 0.333))
ax.set_xticks([])
ax.set_yticks([])
all_locs = dt['all_locs'][i,:,:]*1
uniq = np.where(np.any(all_locs[1:,:] != all_locs[:-1,:], axis=1))[0]+1
uniq = np.sort(uniq).tolist()
uniq.insert(0,0)
uniq = np.array(uniq)
all_locs = all_locs[uniq, :]
ax.plot(dt['all_locs'][i, 0, 0],
dt['all_locs'][i, 0, 1], 'b.', markersize=24)
ax.plot(dt['all_goal_locs'][i, 0, 0],
dt['all_goal_locs'][i, 0, 1], 'g*', markersize=19)
ax.plot(all_locs[:,0], all_locs[:,1], 'r', alpha=0.4, linewidth=2)
ax.scatter(all_locs[:,0], all_locs[:,1],
c=5+np.arange(all_locs.shape[0])*1./all_locs.shape[0],
cmap='Reds', s=30, linewidth=0)
ax.imshow(orig_maps, origin='lower', vmin=-1.0, vmax=2.0, aspect='equal')
ax.set_xlim([xy1[0], xy2[0]])
ax.set_ylim([xy1[1], xy2[1]])
file_name = os.path.join(out_dir, 'trajectory_{:04d}.png'.format(i))
print(file_name)
with fu.fopen(file_name, 'w') as f:
plt.savefig(f)
plt.close(fig)