def save_video(interp, fname, last=None, interval=50):
"""
Saves a video with the sequence of interpretations as they were generated
by the interpretation process, beginning with *interp* and using *last* as
last frame. Video is stored in *fname* path. Duration of each frame is
controlled by *interval*, in milliseconds.
"""
interplist = []
queue = deque([interp])
while queue:
head = queue.popleft()
interplist.append(head)
queue.extend(head.child)
interplist.sort(key=lambda i:int(str(i)))
if last is not None:
interplist.append(last)
sig = sig_buf.get_signal(sig_buf.get_available_leads()[0])
fig = figure(figsize=(18, 3), dpi=100, tight_layout=True)
def update_figure(idx):
print(str(idx) + '/' + str(len(interplist)))
intplt = interplist[idx]
plot_observations(sig, intplt, fig, False)
fig.gca().set_xbound(lower=0, upper=len(sig))
return fig
ani = animation.FuncAnimation(fig, update_figure, len(interplist),
interval=interval, repeat=False)
ani.save(fname, bitrate=2048)
def __onclick(self, event):
"""Manager to the click event on the figure."""
#Left click
if event.button in (1, 2, 3) and event.inaxes:
trans = event.inaxes.transData
#Distance from nodes (in pixels)
for node in self.drnodes.copy():
posit = self.pos[node]
xn, yn = trans.transform(posit)
dx, dy = (event.x - xn, event.y - yn)
dist = sqrt(dx * dx + dy * dy)
#Nodes have a 10-pixel radius
if dist < 10:
#The clicked button will define the action
#Button 1: plot
#If the branch is already plot, we just show it
if event.button == 1:
if node in self._subfigs:
mgr = Gcf.get_fig_manager(
self._subfigs[node].fig.number)
mgr.window.activateWindow()
mgr.window.raise_()
else:
#Else plot the observations
signal = sig_buf.get_signal(
sig_buf.get_available_leads()[0])
#We have to keep a reference to the object to avoid
#garbage collection and loosing the event manager
#see http://matplotlib.org/users/event_handling.html
obsview = ObservationVisualizer(signal, node)
mgr = Gcf.get_fig_manager(obsview.fig.number)
mgr.window.move(0, 0)
obsview.fig.canvas.set_window_title(str(node))
self._subfigs[node] = obsview
obsview.draw()
#Button 2: Add child nodes of the selected one to the plot.
elif event.button == 2:
pyperclip.copy(str(node))
stack = [node]
while stack:
n = stack.pop()
self.drnodes.add(n)
if n is node or not n.is_firm:
stack.extend(self.graph[n].keys())
self.redraw()
#Button 3: Copy the branch name to the clipboard
elif event.button == 3:
pyperclip.copy(str(node))
print('Finished in {0:.3f} seconds'.format(time.time() - t0))
print('Created {0} interpretations ({1} kept alive)'.format(
interp.counter, interp.ndescendants))
#plotter.save_video(interp, '/tmp/vid.mp4', cntr.best.node)
#Best explanation
print(cntr.best)
be = cntr.best.node
be.recover_all()
#print('List of resulting observations:')
#pp(list(be.get_observations()))
#Drawing of the best explanation
brview = plotter.plot_observations(
sig_buf.get_signal(sig_buf.get_available_leads()[0]), be)
if args.o is not None:
if args.video:
plotter.save_video(interp, args.o, last=be)
else:
brview.fig.set_size_inches((12, 6))
brview.fig.gca().set_xbound(
lower=0,
upper=len(sig_buf.get_signal(sig_buf.get_available_leads()[0])))
brview.fig.savefig(args.o)
#Drawing of the search tree
#label_fncs = {}
##label_fncs['n'] = lambda br: str(br)
#label_fncs['e'] = lambda br: ''
#brview = plotter.plot_branch(interp, label_funcs=label_fncs, target=be,
# full_tree=True)
ltime = (pekbfs.last_time, t0)
while pekbfs.best is None:
IN.get_more_evidence()
acq_time = IN.get_acquisition_point()
#HINT debug code
fstr = 'Int: {0:05d} '
for i in range(int(sp2ms(acq_time - pekbfs.last_time) / 1000.0)):
fstr += '-'
fstr += ' Acq: {1}'
print(fstr.format(int(pekbfs.last_time), acq_time))
#End of debug code
pekbfs.step()
if pekbfs.last_time > ltime[0]:
ltime = (pekbfs.last_time, time.time())
if ms2sp((time.time() - ltime[1]) * 1000.0) > MAX_DELAY:
print('Pruning search')
if pekbfs.open:
prevopen = pekbfs.open
pekbfs.prune()
print('Finished in {0:.3f} seconds'.format(time.time() - t0))
print('Created {0} interpretations'.format(interp.counter))
be = pekbfs.best
brview = plotter.plot_observations(
sig_buf.get_signal(sig_buf.get_available_leads()[0]), pekbfs.best)
#Branches draw
label_fncs = {}
label_fncs['n'] = lambda br: str(br)
label_fncs['e'] = lambda br: ''
#brview = plotter.plot_branch(interp, label_funcs=label_fncs, target=pekbfs.best)
cntr.step(filt)
if cntr.last_time > ltime[0]:
ltime = (cntr.last_time, time.time())
#If the distance between acquisition time and interpretation time is
#excessive, the search tree is pruned.
if ms2sp((time.time() - ltime[1]) * 1000.0) * TFACTOR > MAX_DELAY:
print('Pruning search')
cntr.prune()
print('Finished in {0:.3f} seconds'.format(time.time() - t0))
print('Created {0} interpretations ({1} kept alive)'.format(
interp.counter, interp.ndescendants))
#plotter.save_video(interp, '/tmp/vid.mp4', cntr.best.node)
#Best explanation
print(cntr.best)
be = cntr.best.node
be.recover_all()
#print('List of resulting observations:')
#pp(list(be.get_observations()))
#Drawing of the best explanation
brview = plotter.plot_observations(
sig_buf.get_signal(sig_buf.get_available_leads()[0]), be)
#Drawing of the search tree
#label_fncs = {}
##label_fncs['n'] = lambda br: str(br)
#label_fncs['e'] = lambda br: ''
#brview = plotter.plot_branch(interp, label_funcs=label_fncs, target=be,
# full_tree=True)