def _compare_two_replays(replay1, replay2):
"""
Compares two Replays and return their average distance
and standard deviation of distances.
"""
# get all coordinates in numpy arrays so that they're arranged like:
# [ x_1 x_2 ... x_n
# y_1 y_2 ... y_n ]
# indexed by columns first.
data1 = replay1.as_list_with_timestamps()
data2 = replay2.as_list_with_timestamps()
# interpolate
(data1, data2) = Replay.interpolate(data1, data2)
# remove time from each tuple
data1 = [d[1:] for d in data1]
data2 = [d[1:] for d in data2]
(mu, sigma) = Comparer._compute_data_similarity(data1, data2)
return (mu, sigma)
def draw_replays(user_replay, check_replay):
"""
Show an animation of both replays overlayed on top of eachother.
Args:
Replay user_replay: The first Replay to draw.
Replay check_replay: The second Replay to draw.
"""
data1 = user_replay.as_list_with_timestamps()
data2 = check_replay.as_list_with_timestamps()
# synchronize and interpolate
(data1, data2) = Replay.interpolate(data1, data2, unflip=True)
# skip breaks (risk pain if you don't sync first)
data1 = Replay.skip_breaks(data1)
data2 = Replay.skip_breaks(data2)
# implement naming data in interpolation
# if you want a guarantee about the order of the returned data
fps = 60
dt = 0
data1 = Replay.resample(data1, fps)
data2 = Replay.resample(data2, fps)
# replace with constants for screen sizes
data1 = [(512 - d[1], 384 - d[2]) for d in data1]
data2 = [(512 - d[1], 384 - d[2]) for d in data2]
data1 = np.transpose(data1)
data2 = np.transpose(data2)
# create plot for each replay and add legend with player names
fig, ax = plt.subplots()
plot1 = plt.plot('x',
'y',
"red",
animated=True,
label=user_replay.player_name)[0]
plot2 = plt.plot('',
'',
"blue",
animated=True,
label=check_replay.player_name)[0]
legend = ax.legend()
def init():
ax.set_xlim(0, 512)
ax.set_ylim(0, 384)
return plot1, plot2
def update(i):
plot1.set_data(data1[0][i - 100:i], data1[1][i - 100:i])
plot2.set_data(data2[0][i - 100:i], data2[1][i - 100:i])
return plot1, plot2
animation = FuncAnimation(fig,
update,
frames=itr.count(100),
init_func=init,
blit=True,
interval=dt)
plt.show(block=True)
# keep a reference to this otherwise it will get garbage collected instantly and not play.
return animation
