fix: mark glasbey as qualitative

[matthiasschabel]

glasbey is recorded as a continuous miscellaneous colormap, but it is a categorical palette: 256 maximally distinct colors for labelling categories, ordered so that any prefix stays distinguishable (Glasbey et al., doi:10.1002/col.20327 — "Colour displays for categorical images").

Two consequences today:

>>> from cmap import Colormap
>>> cm = Colormap("glasbey")
>>> cm.category, cm.interpolation
('miscellaneous', 'linear')      # blends between unrelated categories
>>> len(cm.lut(1000))
1000                             # from a palette that defines 256

Evidence, using only colormaps this catalog labels — median distance between adjacent entries:

import numpy as np
from cmap import Colormap

def step(name):
    cm = Colormap(name)
    lut = np.asarray(cm.lut(cm.num_colors), float)[:, :3]
    return float(np.median(np.linalg.norm(np.diff(lut, axis=0), axis=1)))

	median adjacent step
glasbey	0.698
catalog's qualitative colormaps	0.524 (range 0.163–1.077)
matplotlib:viridis	0.006
cmocean:thermal	0.007

Change

src/cmap/data/glasbey/record.json: category → qualitative, interpolation → false, matching how tol's discrete palettes are recorded.

After: category == "qualitative", interpolation == "nearest", and num_colors == 256 is respected.

One test added in tests/test_glasbey.py.