matplotlib-users Mailing List for matplotlib

Hi,

I've noticed that the line density seems to vary if the x-values in a 
2D plot are not ordered and the x,y pairs fall on the same line.

For example, compare these 2 plots:
def f(x):
	return x+1
x1 = arange(5)
x2 = array([2,5,3,1,4])
plot(x1, f(x1))
show()
plot(x2, f(x2))
show()

For me, the plot generated by x2 (the second call of show) is dense in 
the middle and fades out at the edges.  I assume this is somehow due to 
the line redrawing over itself as it moves from point to point.

Is there a good way to clean it up, other than always sorting the x 
variable list?

Thanks,
Mark

>>>>> "Nils" == Nils Wagner <nw...@me...> writes:

    Nils> Dear experts, I am interested in a plot of equipotential
    Nils> curves.  If desired, the regions between contours should be
    Nils> shaded or colored to indicate their magnitude.

    Nils> Is this feature already available in matplotlib ?  A small
    Nils> example will be appreciated.

There is no contour per se, but you can use imshow or pcolor with a
custom colormap that has only few levels to emulate one, as shown in
this screenshot and example below

  http://nitace.bsd.uchicago.edu:8080/files/share/poormans_contour.png

We are interested in developing a real contour function however, which
also provides contour lines, etc, as mentioned on
http://matplotlib.sourceforge.net/goals.html.

Cheers,
John Hunter

#!/usr/bin/env python
from matplotlib.matlab import *


def bivariate_normal(X, Y, sigmax=1.0, sigmay=1.0,
                     mux=0.0, muy=0.0, sigmaxy=0.0):
    """
    Bivariate gaussan distribution for equal shape X, Y

    http://mathworld.wolfram.com/BivariateNormalDistribution.html
    """
    Xmu = X-mux
    Ymu = Y-muy

    rho = sigmaxy/(sigmax*sigmay)
    z = Xmu**2/sigmax**2 + Ymu**2/sigmay - 2*rho*Xmu*Ymu/(sigmax*sigmay)
    return 1.0/(2*pi*sigmax*sigmay*(1-rho**2)) * exp( -z/(2*(1-rho**2)))


delta = 0.01
x = arange(-3.0, 3.0, delta)
y = arange(-3.0, 3.0, delta)
X,Y = meshgrid(x, y)
Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1)

# difference of Gaussians
cmap = ColormapJet(10)  # only 10 levels for discrete color steps
im = imshow(Z2-Z1, cmap)

# set the interpolation method: 'nearest', 'bilinear', 'bicubic' and much more
im.set_interpolation('bilinear')

axis('off')
#savefig('test')
show()

Dear experts,

I am interested in a plot of equipotential curves.
If desired, the regions between contours should be shaded or colored to
indicate their magnitude.

Is this feature already available in matplotlib ?
A small example will be appreciated.

Thanks in advance.

Nils