Add per-channel norm support for render_images

[timtreis]

Summary

• Closes Document how to perform on-the-fly normalization for channels. #460 — render_images now accepts a list of Normalize objects for per-channel normalization
• Essential for multi-channel protein/fluorescence data with vastly different intensity ranges per channel
• The rendering pipeline already read per-channel norms from CmapParams — this change only widens validation and routes per-channel norms into the existing CmapParams creation loop

Changes

• basic.py: Widen norm type to list[Normalize] | Normalize | None, update docstring, zip norm list with cmap list
• utils.py: Accept list[Normalize] in validation, reject empty lists and non-Normalize elements
• test_render_images.py: 5 new tests (per-channel norm, backward compat, length mismatch, empty list, invalid element)

Usage

from matplotlib.colors import Normalize

norms = [
    Normalize(vmin=0, vmax=0.05, clip=True),  # dim channel
    Normalize(vmin=0, vmax=1.0, clip=True),    # full range
    Normalize(vmin=0, vmax=0.5, clip=True),    # medium
]
sdata.pl.render_images(
    channel=[0, 1, 2],
    norm=norms,
    cmap=[plt.cm.gray] * 3,
).pl.show()

Test plan

• Per-channel norm list renders without error
• Single Normalize with multiple channels still works (backward compat)
• Norm list length mismatch → ValueError
• Empty norm list → ValueError
• Non-Normalize in list → TypeError
• Pre-commit (ruff, mypy) passes

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