I am using numpy and matplotlib to do a statistical simulation. The simulation itself is pretty fast thanks to numPy vectorizatio, however the plotting is slow since I still use a for loop.
Here is the result:
Right now, I call matplotlib.pyplot.plt 10000 times - once for each tile in 100 × 100 square which can't possibly be optimal, but I can't think of how to do it better:
N = 100
for x in range(N):
for y in range(N):
plt.fill( myPath[x,y,0] ,myPath[x,y,1])
Let's say I stored all the varaibles in an numPy array myPath with shape (N,N,2,4) so that myPath[x,y,0] and myPath[x,y,1] give the x and y coordinates of the path.
How do I reduce the number of calls to plt in my visualization?
plt.fill(myPath[..., ..., 0], myPath[..., ..., 1])without a loop do the trick? – Morwenn Jun 3 '14 at 13:50