matplotlib-devel Mailing List for matplotlib

On 2012/08/29 10:07 AM, David Raymond wrote:
>
> I think that I have found a serious bug in vector plotting (quiver)
> when the "angle=xy" option is used on a plot with a large aspect
> ratio.  It is my understanding that with this option, the vector with
> tail at (x,y) would have its head at (x + vx,y + vy); at least this is
> what it says in the documentation.

Not a bug.
Note this in the documentation:

   *scale_units*: *None*, or any of the *units* options.
     For example, if *scale_units* is 'inches', *scale* is 2.0, and
     ``(u,v) = (1,0)``, then the vector will be 0.5 inches long.
     If *scale_units* is 'width', then the vector will be half the width
     of the axes.

     If *scale_units* is 'x' then the vector will be 0.5 x-axis
     units.  To plot vectors in the x-y plane, with u and v having
     the same units as x and y, use
     "angles='xy', scale_units='xy', scale=1".

Try this modified call to quiver:

q = plt.quiver(X, Y, vx, vy, angles='xy', scale_units='xy')

Eric

On 2012/08/29 10:07 AM, David Raymond wrote:
>
> I think that I have found a serious bug in vector plotting (quiver)

I think you are correct, but a quick look at the code has not yet 
revealed what is going wrong.  I will look into it.

Eric

> when the "angle=xy" option is used on a plot with a large aspect
> ratio.  It is my understanding that with this option, the vector with
> tail at (x,y) would have its head at (x + vx,y + vy); at least this is
> what it says in the documentation.
>
> The problem is best illustrated by the following example:
>
> ------------
>
> #!/usr/bin/python
> #
> from numpy import *
> import matplotlib.pyplot as plt
>
> lx = 100.
> ly = 10.
> pi = 3.14159
> kx = pi/lx
> ky = pi/ly
> nx = 21
> ny = 21
> x = linspace(0,lx,nx)
> y = linspace(0,ly,ny)
> (X,Y) = meshgrid(x,y)
>
> # this is a streamfunction
> psi = sin(kx*X)*sin(ky*Y)
>
> # these are the velocity components derived from the streamfunction
> vx = ky*sin(kx*X)*cos(ky*Y)
> vy = -kx*cos(kx*X)*sin(ky*Y)
>
> # plot the x velocity
> cx = plt.contourf(x,y,vx)
> b = plt.colorbar(cx, orientation='vertical')
> tl = plt.title("vx")
> xlab = plt.xlabel("x")
> ylab = plt.ylabel("y")
> plt.show()
>
> # plot the y velocity
> cy = plt.contourf(x,y,vy)
> b = plt.colorbar(cy, orientation='vertical')
> tl = plt.title("vy")
> xlab = plt.xlabel("x")
> ylab = plt.ylabel("y")
> plt.show()
>
> # plot the streamfunction and the velocity vectors using the angles=xy option
> cp = plt.contour(x,y,psi)
> q = plt.quiver(X,Y,vx,vy,angles='xy')
> tl = plt.title("psi contours, (vx,vy) vectors")
> xlab = plt.xlabel("x")
> ylab = plt.ylabel("y")
> plt.show()
>
> ------------------------------------
>
> The contour plot of vy, the y component of the vector, clearly shows
> that vy is non-zero at y = 5.  However, the vector plot has it zero
> along this line.  Interestingly, vx appears to be represented correctly
> on the x = 50 line.  The magnitude of vectors should be inversely
> proportional to the spacing of streamfunction contours, and this is
> manifestly untrue in the vector plot.
>
> Please tell me if I am doing something stupid.
>
> Dave
>
> PS: I am using matplotlib 1.1.1 and numpy 1.6.2 on Arch linux.  (Yes,
> I have to set the #!/bin/python line in the example to #!/bin/python2
> on Arch, since Arch has python3 as default!)
>

I think that I have found a serious bug in vector plotting (quiver)
when the "angle=xy" option is used on a plot with a large aspect
ratio.  It is my understanding that with this option, the vector with
tail at (x,y) would have its head at (x + vx,y + vy); at least this is
what it says in the documentation.

The problem is best illustrated by the following example:

------------

#!/usr/bin/python
#
from numpy import *
import matplotlib.pyplot as plt

lx = 100.
ly = 10.
pi = 3.14159
kx = pi/lx
ky = pi/ly
nx = 21
ny = 21
x = linspace(0,lx,nx)
y = linspace(0,ly,ny)
(X,Y) = meshgrid(x,y)

# this is a streamfunction
psi = sin(kx*X)*sin(ky*Y)

# these are the velocity components derived from the streamfunction
vx = ky*sin(kx*X)*cos(ky*Y)
vy = -kx*cos(kx*X)*sin(ky*Y)

# plot the x velocity
cx = plt.contourf(x,y,vx)
b = plt.colorbar(cx, orientation='vertical')
tl = plt.title("vx")
xlab = plt.xlabel("x")
ylab = plt.ylabel("y")
plt.show()

# plot the y velocity
cy = plt.contourf(x,y,vy)
b = plt.colorbar(cy, orientation='vertical')
tl = plt.title("vy")
xlab = plt.xlabel("x")
ylab = plt.ylabel("y")
plt.show()

# plot the streamfunction and the velocity vectors using the angles=xy option
cp = plt.contour(x,y,psi)
q = plt.quiver(X,Y,vx,vy,angles='xy')
tl = plt.title("psi contours, (vx,vy) vectors")
xlab = plt.xlabel("x")
ylab = plt.ylabel("y")
plt.show()

------------------------------------

The contour plot of vy, the y component of the vector, clearly shows
that vy is non-zero at y = 5.  However, the vector plot has it zero
along this line.  Interestingly, vx appears to be represented correctly
on the x = 50 line.  The magnitude of vectors should be inversely
proportional to the spacing of streamfunction contours, and this is
manifestly untrue in the vector plot.

Please tell me if I am doing something stupid.

Dave

PS: I am using matplotlib 1.1.1 and numpy 1.6.2 on Arch linux.  (Yes,
I have to set the #!/bin/python line in the example to #!/bin/python2
on Arch, since Arch has python3 as default!)

-- 
David J. Raymond
Prof. of Physics
New Mexico Tech
http://www.physics.nmt.edu/~raymond/index.html

thanks, Keith, looks like Michael fixed the apostrophe. But not the
misspelling of Eliot's last name. I've update it now.

On Tue, Aug 28, 2012 at 8:50 AM,  <kei...@bt...> wrote:
> “TS Elliots’ maxim” should be “T. S. Eliot’s maxim” J
>
>
>
> Keith
>
>
>
>
>
>
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-- 
Paul Ivanov
314 address only used for lists,  off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

On Wed, Aug 22, 2012 at 6:40 AM, Eric Firing <ef...@ha...> wrote:
> Correction: now I can't reproduce what I thought I was seeing; plt.gca()
> is returning an AxesSubplot as it should.  Maybe the problem is in the
> axes_grid1 toolkit.  It is appearing in the last figure of the
> tight_layout tutorial in the docs.

For axes which uses axes_locator, tight_layout works if the
axes_locator have associated subplotspec.
And, only allowing instance of SubplotBase is too strict.

The PR below addresses this issue.

https://github.com/matplotlib/matplotlib/pull/1170

And it will work again for the axes_grid1 cases.

Regards,

-JJ