Correctly process ImageStack data for hover tooltips

[ianthomas23]

FIxes bug in ImageStack colormapping where we were modifying the user-supplied image data directly to deal with the color_baseline (user-specified or minimum of supplied data). The ImageStack rendered correctly but the hover tooltip was wrong. There was also a similar incorrect offset in color bar limits. This avoids changing the supplied image data and corrects the color bar limits. I have changed the existing tests which rather simplistically always had a minimum value of 0 so subtracting the minimum value had no effect.

• issues: fixes [BUG] ImageStack hover tooltip shows incorrect numbers #13452
• tests added / passed
• release document entry (if new feature or API change)

The image produced by the example listed in the issue is now:

A more complicated example directly comparing Bokeh and Datashader doing the colormapping:

from bokeh.models import EqHistColorMapper, WeightedStackColorMapper
from bokeh.palettes import varying_alpha_palette
from bokeh.plotting import figure, row, show
import datashader.transfer_functions as tf
import numpy as np
import xarray as xr

n = 20
min_alpha = 40
color_baseline = None
colors = ["red", "green", "blue"]

def categorical_data():
    samples = 1000
    rng = np.random.default_rng(92478)

    centers = [(0.3, 0.3), (0.7, 0.5), (0.3, 0.7)]
    radii = [0.2, 0.3, 0.15]
    ncats = len(radii)

    dx = 1.0/n
    data = np.zeros((n, n, ncats), dtype=np.uint32)

    for k in range(ncats):
        x = rng.normal(centers[k][0], radii[k], samples)
        y = rng.normal(centers[k][1], radii[k], samples)
        i = (x / dx).astype(int)
        j = (y / dx).astype(int)
        for ii, jj in zip(i, j):
            if 0 <= ii < n and 0 <= jj < n:
                if np.isnan(data[jj, ii, k]):
                    data[jj, ii, k] = 1
                else:
                    data[jj, ii, k] += 1
    return data

data = categorical_data()
data += 5

ps = []
for i in range(2):
    title = "Bokeh" if i == 0 else "Datashader"
    kwargs = dict(width=420, height=350, title=f"Colormapping in {title}")
    kwargs["tooltips"] = [("values", "@image")]
    if i > 0:
        kwargs["x_range"] = ps[0].x_range
        kwargs["y_range"] = ps[0].y_range
        kwargs["width"] = 350
    p = figure(**kwargs)
    ps.append(p)

    if i == 0:  # Bokeh colormapping
        alpha_mapper = EqHistColorMapper(palette=varying_alpha_palette(color="#000", n=10, start_alpha=min_alpha))
        color_mapper = WeightedStackColorMapper(
            palette=colors, nan_color=(0, 0, 0, 0),
            alpha_mapper=alpha_mapper, color_baseline=color_baseline,
        )
        im = p.image_stack(image=[data], x=0, y=0, dw=1, dh=1, color_mapper=color_mapper)

        color_bar = im.construct_color_bar()
        p.add_layout(color_bar, "right")
    else:  # Datashader colormapping
        coords = np.arange(n, dtype=np.float64)
        cat = ["A", "B", "C"]  # <U1 "F" "M"
        da = xr.DataArray(data=data, dims=["y", "x", "cat"],
            coords=dict(x=coords, y=coords, cat=["A", "B", "C"]))
        im = tf.shade(
            da, color_key=colors, min_alpha=min_alpha,
            color_baseline=color_baseline,
        ).to_numpy()
        p.image_rgba(image=[im], x=0, y=0, dw=1, dh=1)

show(row(ps))

[codecov]

Codecov Report

Merging #13454 (ce87d74) into branch-3.4 (6022971) will not change coverage.
The diff coverage is n/a.

@@             Coverage Diff             @@
##           branch-3.4   #13454   +/-   ##
===========================================
  Coverage       92.67%   92.67%           
===========================================
  Files             320      320           
  Lines           20361    20361           
===========================================
  Hits            18869    18869           
  Misses           1492     1492           

[github-actions]

This pull request has been automatically locked since there has not been any recent activity after it was closed. Please open a new issue for related bugs.