I have been trying to plot unstructured data with contour and contourf, using the tri=True parameter. It works fine with contourf, but I get a huge traceback when using contour on the same data.
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File "/home/share/unix_files/cdat/versions/cdat_install_uv-2.1.0_x86_64_gcc4_13/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/tri/triangulation.py", line 55, in __init__
self.triangles, self._neighbors = _qhull.delaunay(x, y)
ValueError: x and y arrays must have a length of at least 3
After spending some time in the python debugger, I have found out that indeed the x and y coordinate arrays passed to the triangulation function had a zero size (and therefore less than 3 elements) because they were empty! More digging helped me find a very suspicious way of filtering the x and y values in the contour(self,x,y,data,args,*kwargs) function
# for unstructured grids, toss out points outside
# projection limb (don't use those points in triangulation).
[...]
mask = np.logical_or(x<self.xmin,y<self.xmin) +\
np.logical_or(x>self.xmax,y>self.xmax)
x = np.compress(mask,x)
y = np.compress(mask,y)
Why would y be compared to the values of xmin and xmax instead of ymin and ymax, and is the logical combination ok???
I think we want to keep the values where: xmin<=x<=xmax AND ymin<=y<=ymax. And the mask has to be True where we want to keep the value, in np.compress! This is a bit misleading because it works in the opposite way that masks work in np.ma ...
The contour function works fine if I replace the mask definition above with
mask = np.logical_and(np.logical_and(x>=self.xmin, x<=self.xmax),
np.logical_and(y>=self.ymin, y<=self.ymax))
Can somebody review this? And it may be wise to use a slightly less misleading name for the mask variable. Maybe replace mask with select_xy_ok?
I have been trying to plot unstructured data with contour and contourf, using the tri=True parameter. It works fine with contourf, but I get a huge traceback when using contour on the same data.
After spending some time in the python debugger, I have found out that indeed the x and y coordinate arrays passed to the triangulation function had a zero size (and therefore less than 3 elements) because they were empty! More digging helped me find a very suspicious way of filtering the x and y values in the contour(self,x,y,data,args,*kwargs) function
Why would y be compared to the values of xmin and xmax instead of ymin and ymax, and is the logical combination ok???
I think we want to keep the values where: xmin<=x<=xmax AND ymin<=y<=ymax. And the mask has to be True where we want to keep the value, in np.compress! This is a bit misleading because it works in the opposite way that masks work in np.ma ...
The contour function works fine if I replace the mask definition above with
Can somebody review this? And it may be wise to use a slightly less misleading name for the mask variable. Maybe replace mask with select_xy_ok?