Bug in contour x/y values filtering in mpl_toolkits/basemap/__init__.py ?

Nadie ha tomado este issue todavía.

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.

```
[...]
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(xself.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_?

Comienza en mpl_toolkits/basemap/__init__.py, en la lógica de filtrado de contour(self, x, y, data, ...), y luego compara sus entradas con el matplotlib.tri triangulation traceback. Revisa el filtrado de límites de coordenadas propuesto y ejecuta las pruebas existentes de contour o contourf si están disponibles. Se considera terminado cuando contour maneja los datos no estructurados indicados sin pasar arrays de coordenadas vacíos a la triangulación.

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