Phillip M. Feldman wrote:
> Hello Eric
>
> I've looked at the code in colors.py. I think that I'm starting to
> understand what's going on, but I'm unclear about a few things. In
> particular:
>
>  Why do we need to define both forward and reverse transformations?
> Shouldn't the forward transformation be sufficient?
The inverse is used by colorbar to autogenerate the boundaries and
values arrays when they are not specified. The norms that do not have
inverses have specialcase code in colorbar to handle this.
>
>  I don't follow what the snippet of code below is doing:
>
> if cbook.iterable(value):
> vtype = 'array'
> val = ma.asarray(value).astype(np.float)
> else:
> vtype = 'scalar'
> val = ma.array([value]).astype(np.float)
>
>  In some cases I'd like to map the data values to discrete output
> values, e.g., values below x_0 map to 0 (which the colormap in turn maps
> to red), values between x_0 and x_1 map to 0.5 (which maps to yellow),
> and values greater than x_1 map to 1 (which maps to green). Such a
> function does not have a mathematical inverse because it is a many to
> one mapping. How does one handle this situation?
BoundaryNorm does exactly thiswhen working with a suitable
colormapand its lack of an inverse is handled inside colorbar.
from matplotlib import colors
x_0 = 0
x_1 = 0.5
cmap = colors.ListedColormap(['y'])
cmap.set_under('r')
cmap.set_over('g')
norm = colors.BoundaryNorm([x_0, x_1], cmap.N)
z = (np.arange(100) / 50.0)  1.0
z.shape = (10,10)
imshow(z, cmap=cmap, norm=norm, interpolation='nearest')
>
> The ability to pass in an ordinary function (or a pair of functions if
> the inverse is really necessary) would be a great benefit.
I will try to get to this ASAP.
Eric
>
> Thanks!
>
> Phillip
>
> Eric Firing wrote:
>> Dr. Phillip M. Feldman wrote:
>>> I'd like to generate a scatter plot in which symbols are colored using a
>>> specified colormap, with a specified mapping from the range of the
>>> data to
>>> the [0,1] colormap interval. I thought at first that one could use
>>> the norm
>>> argument to specify a function that would perform this mapping, but from
>>> closer reading of the documentation (and experimentation) it seems as
>>> though
>>> one cannot do this. Is there another mechanism for doing this? (I could
>>> remap the data itself before plotting it, but this is unacceptable
>>> because
>>> the colorbar tic lables would then take values in [0,1] rather than
>>> values
>>> from the range of the data).
>>>
>>
>> I don't understandwhat you say you want to do is exactly what the
>> norm is designed for. Maybe the problem is that you can't pass in a
>> simple functionyou need to subclass colors.Normalize. An example is
>> colors.LogNorm.
>>
>> It looks like what we need is a FuncNorm, which would be initialized
>> with two functions, the forward and inverse transformation functions,
>> each taking vmin, vmax, and a val.
>>
>> Eric
>>
>
