Matplotlib animate space vs time plot - animation

Question

I'm currently working on traffic jams analysis and was wondering if there's a way to animate the generation of a plot of such jams.
A plot of this things grow from up to the lower end of the figure, each 'row' is a time instance. The horizontal axis is just the road indicating at each point the position of each vehicle and, with a certain numeric value, the velocity of it. So applying different colors to different velocities, you get a plot that shows how a jam evolves through time in a given road.
My question is, how can I use matplotlib to generate an animation of each instance of the road in time to get such a plot?
The plot is something like this:
I'm simulating a road with vehicles with certain velocities through time, so I wish to animate a plot showing how the traffic jams evolve...
EDIT:
I add some code to make clear what I'm already doing
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation, rc
plt.rcParams['animation.ffmpeg_path'] = u'/usr/bin/ffmpeg'
# model params
vmax = 5
lenroad = 50
prob = 0.4
# sim params
numiters = 10
# traffic model
def nasch():
gaps = np.full(road.shape, -1)
road_r4 = np.full(road.shape, -1)
for n,x in enumerate(road):
if x > -1:
d = 1
while road[(n+d) % len(road)] < 0:
d += 1
d -= 1
gaps[n] = d
road_r1 = np.where(road!=-1, np.minimum(road+1, vmax), -1)
road_r2 = np.where(road_r1!=-1, np.minimum(road_r1, gaps), -1)
road_r3 = np.where(road_r2!=-1, np.where(np.random.rand() < prob, np.maximum(road-1, 0), road), -1)
for n,x in enumerate(road_r3):
if x > -1:
road_r4[(n+x) % len(road_r3)] = x
return road_r4
def plot_nasch(*args):
road = nasch()
plot.set_array([road])
return plot,
# init road
road = np.random.randint(-10, vmax+1, [lenroad])
road = np.where(road>-1, road, -1)
# simulate
fig = plt.figure()
plot = plt.imshow([road], cmap='Pastel2', interpolation='nearest')
for i in range(numiters):
ani = animation.FuncAnimation(fig, plot_nasch, frames=100, interval=500, blit=True)
plt.show()
And I get the following figure, just one road instead of each road painted at the bottom of the previous one:

Answer 1

This is possibly what you want, although I'm not sure why you want to animate the time, since time is already one of the axes in the plot.
The idea here is to store the simulation results of a time-step row by row in an array and replot this array. Thereby previous simulation results are not lost.
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation, rc
# model params
vmax = 5
lenroad = 50
prob = 0.4
# sim params
numiters = 25
# traffic model
def nasch():
global road
gaps = np.full(road.shape, -1)
road_r4 = np.full(road.shape, -1)
for n,x in enumerate(road):
if x > -1:
d = 1
while road[(n+d) % len(road)] < 0:
d += 1
d -= 1
gaps[n] = d
road_r1 = np.where(road!=-1, np.minimum(road+1, vmax), -1)
road_r2 = np.where(road_r1!=-1, np.minimum(road_r1, gaps), -1)
road_r3 = np.where(road_r2!=-1, np.where(np.random.rand() < prob, np.maximum(road-1, 0), road), -1)
for n,x in enumerate(road_r3):
if x > -1:
road_r4[(n+x) % len(road_r3)] = x
return road_r4
def plot_nasch(i):
print i
global road
road = nasch()
#store result in array
road_over_time[i+1,:] = road
# plot complete array
plot.set_array(road_over_time)
# init road
road = np.random.randint(-10, vmax+1, [lenroad])
road = np.where(road>-1, road, -1)
# initiate array
road_over_time = np.zeros((numiters+1, lenroad))*np.nan
road_over_time[0,:] = road
fig = plt.figure()
plot = plt.imshow(road_over_time, cmap='Pastel2', interpolation='nearest', vmin=-1.5, vmax=6.5)
plt.colorbar()
ani = animation.FuncAnimation(fig, plot_nasch, frames=numiters, init_func=lambda : 1, interval=400, blit=False, repeat=False)
plt.show()