(Let's discuss the second point in the matplotlib list only.)

Can you try the following code :

import matplotlib.pyplot as plt

import numpy as np

x, y= np.arange(0,2*np.pi,.2), np.arange(0,2*np.pi,.2)

X,Y = np.meshgrid(x,y)

U,V = np.cos(X), np.sin(Y)

plt.pcolor(X,Y,U**2+V**2)

plt.quiver(X,Y,U,V)

plt.show()

If it is what you do want, then you then only need to import your own

data...

## ···

Le lundi 10 novembre 2008, wbrevis a écrit :

I'm trying to plot one of my experimental data using scipy. Until now,

all the work I did was using Matlab. For one of my normal data-

visualization, I read ASCII or Binary files containing 4 columns: The

first contains the x coordinate, the second the y one, and the third

and fourth columns the velocity in the x and y directions (u and v),

i.e. file= x y u v (ordered in columns). After reading the data in

Matlab, I normally do: pcolor(x,y,sqrt(u.^2+v.^2)), in order to

visualize in colors the velocity magnitude and then quiver(x,y,u,v) in

order to see the associated vectors. I was reading the manual of

scipy, including the plotting tools, but I am a bit lost (too much

information to start). Can somebody help me with suggestions on how to

read data using scipy and the best way to plot (pcolor+quiver)?. What

about the function quiver3d of mlab, can be used for 2d representation

of a flow field, together with surf (also mlab).Thank you in advance for your help and suggestions

--

Fabricio