# contour_plot behaves differently when I include the functional dependence

If I include the functional dependence of my function, the contour_plot routine behaves differently. MWE:

```
var('x y')
def check(x,y):
val=-1. # negative by default,
for j in range(1,10):
for i in range(1,10):
if ( ( (x>0.9*i) and (x<1.1*i) ) and ( (y>0.9*j) and (y<1.1*j) ) ):
val=1.
return val
```

So this is kind of a strange function, but basically if (x,y) are near any of the 2d grid points (1-10), the function is 1 instead of zero. If I call this function without specifying the functional dependence, it looks right:

```
contour_plot(check,(x,-1.,8.),(y,-1.,8.))
```

However, if I call them and specify them explicitly, I get the unexpected (to me):

```
contour_plot(check(x,y),(x,-1.,8.),(y,-1.,8.))
```

(I grabbed the depreciation warning too, although I don't see how it matters here).

This is not just academic, because what I really want to do is have a four-variable funcftion, a la

```
def h(x,y,z,w):
...
```

and do a contour plot on two variables, setting the other two constant, like

```
contour_plot(h(x,y,0,1),....)
```

I'm having trouble, and trying to debug. Any thoughts?