> 2010/3/29 Alan G Isaac :
> > Can you explain this:
> > norm = colors.Normalize(vmin = -1, vmax = 1)
On 3/28/2010 10:05 PM, Friedrich Romstedt wrote:
> The normaliser takes some arbitrary value and returns a value in [0,
> 1]. Hence the name. The value \in [0, 1] is handed over to the
> cma
2010/3/29 Alan G Isaac :
> Can you explain this:
> norm = colors.Normalize(vmin = -1, vmax = 1)
The normaliser takes some arbitrary value and returns a value in [0,
1]. Hence the name. The value \in [0, 1] is handed over to the
cmap's __call__(), resulting in the color value. And yes, I guess y
On 3/28/2010 7:19 PM, Friedrich Romstedt wrote:
> I fixed your problem
Can you explain this:
norm = colors.Normalize(vmin = -1, vmax = 1)
I take it that this scales the range for the
color bar, which is what 'luminance' must
refer to in the docs? In which case, can
we just set vmin and vmax as i
2010/3/29 Alan G Isaac :
> OK, it's obvious one you point it out.
> Sorry for the typo in the example.
>
> Now suppose I want a colorbar labelled at -1, 0, 1
> but the highest value realized is <1. Can I somehow
> use ticks=(-1,0,1) anyway, or do I have to tick at
> the realized limits and then la
On 3/28/2010 3:04 PM, Ryan May wrote:
> it's just using indices, which run from 0 to 99. Since the limits
> are 0 to 100, bam...white space because, indeed, there is no data.
>
OK, it's obvious one you point it out.
Sorry for the typo in the example.
Now suppose I want a colorbar labelled at
On Sun, Mar 28, 2010 at 11:16 AM, Alan G Isaac wrote:
> Using contourf in version 0.99.1,
> I'm seeing an unwanted white strip to
> the top and right, adjacent to the axes.
> (In fact, the strip looks just wide
> enough to underlay the ticks.)
>
> Alan Isaac
>
> PS Simple example:
>
> x = np.linsp
Using contourf in version 0.99.1,
I'm seeing an unwanted white strip to
the top and right, adjacent to the axes.
(In fact, the strip looks just wide
enough to underlay the ticks.)
Alan Isaac
PS Simple example:
x = np.linspace(-5, 5, 100)
X, Y = np.meshgrid(x, x)
Z = np.sin(x*y[:,None])
fig = plt
