[KateEisenhower]

Hello all,

currently I am trying to plot streamlines with python. It is working so far and following is a kind of minimal example:

import numpy as np
import matplotlib.pyplot as plt

Y, X = np.mgrid[-2:2:4j, -2:2:4j]

U = np.array([[-77., -3.4, -3.4, -14.],
[-5.6, -2.1,-2.1,-5.6],
[-4.3,-0.7,-0.7,-4.3],
[-3.,0.5,0.5,13.]])

V = np.array([[-500., 5, -5., 5.],
[-1.4, 500,1.2,2.5],
[-1.4,-0.1,1.2,2.5],
[-5.,-3.6,-2.3,-1.]])

speed = np.sqrt(U*U +V*V)

fig0, ax0 = plt.subplots()
strm  = ax0.streamplot(X, Y, U, V, density = 3, color = speed, arrowsize = 1, arrowstyle = '->', minlength = 0.2, linewidth = 1, transform = None, cmap=plt.cm.autumn)
fig0.colorbar(strm.lines)

plt.show()

As you can see, the velocity-component V on the upper left hand corner (-500) is way higher than the rest. However pyplot shows me this velocity component on the lower left hand corner in the plot.

I would really appreciate if someone could point me in the right direction.

Best regards,

Kate

[Phicau]

Hi Kate,

I guess that is the standard, the first row starting from the bottom. What you are looking for is this:

U = np.flipud(U)
V = np.flipud(V)

Best,

Pablo

[KateEisenhower]

Hello Pablo,

thank you! This flipud utility is exactly what I need then.
But can you explain what the thinking is behind plotting the data upside down in standard mode?

All the best,

Kate