Repository: bokeh/bokeh

Issue:
Allow to derive ColorBar's low/high from data
#### ALL software version info (bokeh, python, notebook, OS, browser, any other relevant packages)
bokeh: 1.10.0
python: 3.7.3
OS: Windows 10
browser: all

#### Description of expected behavior and the observed behavior
ColorBar tick labels do not show for geoplot patch plots. See the added image. Expectation: labels with the values for each color next to the legend.

Fails in both notebook version and standalone Bokeh server, on all browsers

The code in #8724 does show the colorbar labels, suggesting it could be related to using patches for filling the figure.

To run the code, you need the following geojson file:
[provinces.zip](https://github.com/bokeh/bokeh/files/3198886/provinces.zip)

#### Complete, minimal, self-contained example code that reproduces the issue

```
import geopandas as gpd 
from bokeh.palettes import Reds
from bokeh.models import GeoJSONDataSource, LinearColorMapper, ColorBar
from bokeh.plotting import figure, show

geodf = gpd.read_file("provinces.geojson")

color_mapper = LinearColorMapper(palette=Reds[9][::-1])
color_bar = ColorBar(color_mapper=color_mapper, 
                     location=(0,0),
                     label_standoff=8, )

p = figure()
geo_source = GeoJSONDataSource(geojson=geodf.to_json())
p.patches('xs', 'ys', fill_alpha=1, 
              fill_color={'field': 'index', 'transform': color_mapper}, 
              line_color='white', line_width=0.5, 
              source=geo_source)

p.add_layout(color_bar,'right')

show(p)
```

#### Screenshots or screencasts of the bug in action
![bokeh_plot](https://user-images.githubusercontent.com/7702207/58038041-2f5fd600-7b2f-11e9-8c65-0ff99a3d028e.png)



Discussion:
Closed as low and high are needed for labels, they are not derived from the data.
I will leave this open. We have ongoing work to allow derivation of low/high from data, among other things (PR #8922).

Resolving patch:
diff --git a/bokeh/models/mappers.py b/bokeh/models/mappers.py
--- a/bokeh/models/mappers.py
+++ b/bokeh/models/mappers.py
@@ -33,7 +33,9 @@
     Enum,
     Float,
     HatchPatternType,
+    Instance,
     Int,
+    List,
     MarkerType,
     Seq,
     String,
@@ -55,6 +57,7 @@
     'ContinuousColorMapper',
     'LinearColorMapper',
     'LogColorMapper',
+    'EqHistColorMapper'
 )
 
 #-----------------------------------------------------------------------------
@@ -192,14 +195,19 @@ class ContinuousColorMapper(ColorMapper):
 
     '''
 
-    low = Float(help="""
+    domain = List(Tuple(Instance("bokeh.models.renderers.GlyphRenderer"), Either(String, List(String))), default=[], help="""
+    A collection of glyph renderers to pool data from for establishing data metrics.
+    If empty, mapped data will be used instead.
+    """)
+
+    low = Float(default=None, help="""
     The minimum value of the range to map into the palette. Values below
-    this are clamped to ``low``.
+    this are clamped to ``low``. If ``None``, the value is inferred from data.
     """)
 
-    high = Float(help="""
+    high = Float(default=None, help="""
     The maximum value of the range to map into the palette. Values above
-    this are clamped to ``high``.
+    this are clamped to ``high``. If ``None``, the value is inferred from data.
     """)
 
     low_color = Color(default=None, help="""
@@ -246,6 +254,10 @@ class LogColorMapper(ContinuousColorMapper):
 
     '''
 
+class EqHistColorMapper(ContinuousColorMapper):
+    bins = Int(default=256*256, help="Number of histogram bins")
+
+
 #-----------------------------------------------------------------------------
 # Dev API
 #-----------------------------------------------------------------------------
diff --git a/examples/plotting/file/dynamic_color_mapping.py b/examples/plotting/file/dynamic_color_mapping.py
new file mode 100644
--- /dev/null
+++ b/examples/plotting/file/dynamic_color_mapping.py
@@ -0,0 +1,52 @@
+import numpy as np
+
+from bokeh.layouts import gridplot
+from bokeh.models import BasicTicker, BasicTickFormatter, ColorBar, LinearColorMapper
+from bokeh.palettes import Plasma256
+from bokeh.plotting import figure, show
+
+tooltips = [("x", "$x"), ("y", "$y"), ("r", "@radius")]
+tools = "pan,box_select,box_zoom,reset"
+
+def data_flat(c=1.0):
+    N = 500
+    x = np.random.random(size=N)
+    y = np.random.random(size=N)
+    r = c*np.linspace(0, 1, N)
+    return x*100, y*100, r
+
+def data_sloped():
+    N = 500
+    x = np.random.random(size=N)
+    y = np.random.random(size=N)
+    r = 2*(x + y)*np.linspace(0, 1, N)
+    return x*100, y*100, r
+
+mapper = LinearColorMapper(palette=Plasma256, low_color="white", high_color="black")
+
+p0 = figure(plot_width=500, plot_height=500, tooltips=tooltips, tools=tools)
+x0, y0, r0 = data_flat(0.8)
+g0 = p0.scatter(x0, y0, radius=r0, fill_color=dict(field="radius", transform=mapper), fill_alpha=0.6, line_color=None)
+mapper.domain.append((g0, "radius"))
+
+p1 = figure(plot_width=500, plot_height=500, tooltips=tooltips, tools=tools)
+x1, y1, r1 = data_flat(1.0)
+g1 = p1.scatter(x1, y1, radius=r1, fill_color=dict(field="radius", transform=mapper), fill_alpha=0.6, line_color=None)
+mapper.domain.append((g1, "radius"))
+
+p2 = figure(plot_width=500, plot_height=500, tooltips=tooltips, tools=tools)
+x2, y2, r2 = data_flat(1.2)
+g2 = p2.scatter(x2, y2, radius=r2, fill_color=dict(field="radius", transform=mapper), fill_alpha=0.6, line_color=None)
+mapper.domain.append((g2, "radius"))
+
+p3 = figure(plot_width=500, plot_height=500, tooltips=tooltips, tools=tools)
+x3, y3, r3 = data_sloped()
+g3 = p3.scatter(x3, y3, radius=r3, fill_color=dict(field="radius", transform=mapper), fill_alpha=0.6, line_color=None)
+mapper.domain.append((g3, "radius"))
+
+color_bar = ColorBar(color_mapper=mapper, location=(0, 0), orientation="horizontal",
+    padding=0, ticker=BasicTicker(), formatter=BasicTickFormatter())
+p3.add_layout(color_bar, "below")
+
+grid = gridplot([[p0, p1], [p2, p3]])
+show(grid)


Test patch:
diff --git a/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_gaussian_distributed_data b/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_gaussian_distributed_data
new file mode 100644
--- /dev/null
+++ b/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_gaussian_distributed_data
@@ -0,0 +1,3 @@
+Plot bbox=[0, 0, 300, 300]
+  LinearAxis bbox=[25, 275, 270, 25]
+  LinearAxis bbox=[0, 5, 25, 270]
diff --git a/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_pipeline_data b/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_pipeline_data
new file mode 100644
--- /dev/null
+++ b/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_pipeline_data
@@ -0,0 +1,3 @@
+Plot bbox=[0, 0, 300, 300]
+  LinearAxis bbox=[25, 275, 270, 25]
+  LinearAxis bbox=[0, 5, 25, 270]
diff --git a/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_sparse_cells_data b/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_sparse_cells_data
new file mode 100644
--- /dev/null
+++ b/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_sparse_cells_data
@@ -0,0 +1,3 @@
+Plot bbox=[0, 0, 300, 300]
+  LinearAxis bbox=[25, 275, 270, 25]
+  LinearAxis bbox=[0, 5, 25, 270]
diff --git a/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_sparse_squares_data b/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_sparse_squares_data
new file mode 100644
--- /dev/null
+++ b/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_sparse_squares_data
@@ -0,0 +1,3 @@
+Plot bbox=[0, 0, 300, 300]
+  LinearAxis bbox=[25, 275, 270, 25]
+  LinearAxis bbox=[0, 5, 25, 270]
diff --git a/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_uniformly_distributed_data b/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_uniformly_distributed_data
new file mode 100644
--- /dev/null
+++ b/bokehjs/test/baselines/Color_mapping__with_histogram_equalization__should_support_uniformly_distributed_data
@@ -0,0 +1,3 @@
+Plot bbox=[0, 0, 300, 300]
+  LinearAxis bbox=[25, 275, 270, 25]
+  LinearAxis bbox=[0, 5, 25, 270]
diff --git a/bokehjs/test/baselines/Color_mapping__with_multiple_domains__should_work b/bokehjs/test/baselines/Color_mapping__with_multiple_domains__should_work
new file mode 100644
--- /dev/null
+++ b/bokehjs/test/baselines/Color_mapping__with_multiple_domains__should_work
@@ -0,0 +1,13 @@
+GridBox bbox=[0, 0, 500, 500]
+  Plot bbox=[0, 0, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
+  Plot bbox=[250, 0, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
+  Plot bbox=[0, 250, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
+  Plot bbox=[250, 250, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
diff --git a/bokehjs/test/baselines/Color_mapping__with_multiple_domains__should_work_after_panning b/bokehjs/test/baselines/Color_mapping__with_multiple_domains__should_work_after_panning
new file mode 100644
--- /dev/null
+++ b/bokehjs/test/baselines/Color_mapping__with_multiple_domains__should_work_after_panning
@@ -0,0 +1,13 @@
+GridBox bbox=[0, 0, 500, 500]
+  Plot bbox=[0, 0, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
+  Plot bbox=[250, 0, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
+  Plot bbox=[0, 250, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
+  Plot bbox=[250, 250, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[3, 5, 28, 220]
diff --git a/bokehjs/test/baselines/Color_mapping__with_multiple_domains__should_work_after_selection b/bokehjs/test/baselines/Color_mapping__with_multiple_domains__should_work_after_selection
new file mode 100644
--- /dev/null
+++ b/bokehjs/test/baselines/Color_mapping__with_multiple_domains__should_work_after_selection
@@ -0,0 +1,13 @@
+GridBox bbox=[0, 0, 500, 500]
+  Plot bbox=[0, 0, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
+  Plot bbox=[250, 0, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
+  Plot bbox=[0, 250, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
+  Plot bbox=[250, 250, 250, 250]
+    LinearAxis bbox=[31, 225, 214, 25]
+    LinearAxis bbox=[0, 5, 31, 220]
diff --git a/bokehjs/test/baselines/linux/Color_mapping__with_histogram_equalization__should_support_gaussian_distributed_data.png b/bokehjs/test/baselines/linux/Color_mapping__with_histogram_equalization__should_support_gaussian_distributed_data.png
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diff --git a/bokehjs/test/baselines/windows/Color_mapping__with_multiple_domains__should_work_after_selection.png b/bokehjs/test/baselines/windows/Color_mapping__with_multiple_domains__should_work_after_selection.png
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diff --git a/bokehjs/test/codebase/size.ts b/bokehjs/test/codebase/size.ts
--- a/bokehjs/test/codebase/size.ts
+++ b/bokehjs/test/codebase/size.ts
@@ -8,7 +8,7 @@ const build_dir = path.normalize(`${__dirname}/../..`) // build/test/codebase ->
 
 const LIMITS = new Map([
   // es2017
-  ["js/bokeh.min.js",                750],
+  ["js/bokeh.min.js",                800],
   ["js/bokeh-widgets.min.js",        300],
   ["js/bokeh-tables.min.js",         350],
   ["js/bokeh-api.min.js",             90],
diff --git a/bokehjs/test/integration/color_mapping.ts b/bokehjs/test/integration/color_mapping.ts
new file mode 100644
--- /dev/null
+++ b/bokehjs/test/integration/color_mapping.ts
@@ -0,0 +1,236 @@
+import {display, fig, grid} from "./utils"
+
+import pipeline from "./data"
+
+import {Plot, Range1d, GlyphRenderer, LinearColorMapper, EqHistColorMapper} from "@bokehjs/models"
+import {Plasma256} from "@bokehjs/api/palettes"
+import {Float64NDArray} from "@bokehjs/core/util/ndarray"
+import {linspace} from "@bokehjs/core/util/array"
+import {Random} from "@bokehjs/core/util/random"
+
+describe("Color mapping", () => {
+
+  describe("with histogram equalization", () => {
+    function sparse_squares(): Float64NDArray {
+      const N = 100
+
+      const buffer = new ArrayBuffer(8*N*N)
+      const array = new Float64NDArray(buffer, [N, N])
+      array.fill(0)
+
+      function assign([xm, xn]: [number, number], [ym, yn]: [number, number], v: number): void {
+        for (let i = xm; i < xn; i++) {
+          for (let j = ym; j < yn; j++) {
+            array[i*N + j] = v
+          }
+        }
+      }
+
+      assign([ 5, 10], [ 5, 10], 10)
+      assign([50, 60], [50, 60], 100)
+      assign([70, 80], [70, 80], 1000)
+
+      return array
+    }
+
+    function simple_noise(): Float64NDArray {
+      const random = new Random(1)
+      const N = 10
+
+      const buffer = new ArrayBuffer(8*N*N)
+      const array = new Float64NDArray(buffer, [N, N])
+
+      for (let i = 0; i < N; i++) {
+        for (let j = 0; j < N; j++) {
+          array[i*N + j] = random.float()**10
+        }
+      }
+
+      return array
+    }
+
+    function simple_gaussian(): Float64NDArray {
+      const {exp, PI} = Math
+
+      const N = 100
+      const x = linspace(-5, 5, N)
+      const y = linspace(-5, 5, N)
+
+      const buffer = new ArrayBuffer(8*N*N)
+      const array = new Float64NDArray(buffer, [N, N])
+
+      let k = 0
+      for (const xi of x) {
+        for (const yi of y) {
+          array[k++] = 1/(2*PI) * exp(-(xi**2)/2 - yi**2/2)
+        }
+      }
+
+      return array
+    }
+
+    function sparse_cells(): Float64NDArray {
+      const {sin, cos} = Math
+
+      const N = 100
+      const x = linspace(0, 10, N)
+      const y = linspace(0, 10, N)
+
+      const buffer = new ArrayBuffer(8*N*N)
+      const array = new Float64NDArray(buffer, [N, N])
+
+      let k = 0
+      for (const xi of x) {
+        for (const yi of y) {
+          array[k++] = sin(xi)*cos(yi)
+        }
+      }
+
+      array[5*N + 5] = 10
+
+      return array
+    }
+
+    function eqhist_mapped_plot(data: Float64NDArray) {
+      const color_mapper = new EqHistColorMapper({palette: Plasma256})
+      const p = fig([300, 300], {x_range: [0, 10], y_range: [0, 10]})
+      p.image({image: [data as any], x: 0, y: 0, dw: 10, dh: 10, color_mapper})
+      return p
+    }
+
+    it("should support pipeline data", async () =>{
+      const p = eqhist_mapped_plot(pipeline)
+      await display(p, [350, 350])
+    })
+
+    it("should support sparse squares data", async () =>{
+      const squares = sparse_squares()
+      const p = eqhist_mapped_plot(squares)
+      await display(p, [350, 350])
+    })
+
+    it("should support uniformly distributed data", async () =>{
+      const noise = simple_noise()
+      const p = eqhist_mapped_plot(noise)
+      await display(p, [350, 350])
+    })
+
+    it("should support gaussian distributed data", async () =>{
+      const gaussian = simple_gaussian()
+      const p = eqhist_mapped_plot(gaussian)
+      await display(p, [350, 350])
+    })
+
+    it("should support sparse cells data", async () =>{
+      const cells = sparse_cells()
+      const p = eqhist_mapped_plot(cells)
+      await display(p, [350, 350])
+    })
+  })
+
+  describe("with multiple domains", () => {
+    function make_grid() {
+      const random = new Random(1)
+
+      function data_flat(c: number) {
+        const N = 500
+        const x = random.floats(N)
+        const y = random.floats(N)
+        const r = linspace(0, 1, N)
+        return [
+          x.map((xi) => 100*xi),
+          y.map((yi) => 100*yi),
+          r.map((ri) => c*ri),
+        ]
+      }
+
+      function data_sloped(c: number) {
+        const N = 500
+        const x = random.floats(N)
+        const y = random.floats(N)
+        const r = linspace(0, 1, N)
+        return [
+          x.map((xi) => 100*xi),
+          y.map((yi) => 100*yi),
+          r.map((ri, i) => c*(x[i] + y[i])*ri),
+        ]
+      }
+
+      const mapper = new LinearColorMapper({palette: Plasma256, low_color: "white", high_color: "black"})
+
+      const range = () => new Range1d({start: 0, end: 100})
+
+      const p0 = fig([250, 250], {x_range: range(), y_range: range()})
+      const [x0, y0, r0] = data_flat(0.8)
+      const g0 = p0.circle({
+        x: x0, y: y0, radius: r0,
+        fill_color: {field: "radius", transform: mapper} as any, // XXX: bad types in VectorSpec, ColorMapper and Transform
+        fill_alpha: 0.6, line_color: null,
+      })
+      mapper.domain.push([g0, "radius"])
+
+      const p1 = fig([250, 250], {x_range: range(), y_range: range()})
+      const [x1, y1, r1] = data_flat(1.0)
+      const g1 = p1.circle({
+        x: x1, y: y1, radius: r1,
+        fill_color: {field: "radius", transform: mapper} as any,
+        fill_alpha: 0.6, line_color: null,
+      })
+      mapper.domain.push([g1, "radius"])
+
+      const p2 = fig([250, 250], {x_range: range(), y_range: range()})
+      const [x2, y2, r2] = data_flat(1.2)
+      const g2 = p2.circle({
+        x: x2, y: y2, radius: r2,
+        fill_color: {field: "radius", transform: mapper} as any,
+        fill_alpha: 0.6, line_color: null,
+      })
+      mapper.domain.push([g2, "radius"])
+
+      const p3 = fig([250, 250], {x_range: range(), y_range: range()})
+      const [x3, y3, r3] = data_sloped(2.0)
+      const g3 = p3.circle({
+        x: x3, y: y3, radius: r3,
+        fill_color: {field: "radius", transform: mapper} as any,
+        fill_alpha: 0.6, line_color: null,
+      })
+      mapper.domain.push([g3, "radius"])
+
+      // XXX: force change due to using Array.push()
+      mapper.properties.domain.change.emit()
+
+      return grid([[p0, p1], [p2, p3]])
+    }
+
+    it("should work", async () => {
+      const grid = make_grid()
+      await display(grid, [550, 550])
+    })
+
+    it("should work after panning", async () => {
+      const grid = make_grid()
+      const {view} = await display(grid, [550, 550])
+      const pv3 = view.child_views[3] as Plot["__view_type__"]
+      const p3 = pv3.model
+      // TODO: synchronized
+      p3.x_range.start = -60
+      p3.x_range.end = 40
+      p3.y_range.start = -60
+      p3.y_range.end = 40
+      await pv3.ready
+    })
+
+    it("should work after selection", async () => {
+      const grid = make_grid()
+      const {view} = await display(grid, [550, 550])
+      const pv3 = view.child_views[3] as Plot["__view_type__"]
+      const g3 = pv3.model.renderers[0] as GlyphRenderer
+      const gv3 = pv3.renderer_views.get(g3) as GlyphRenderer["__view_type__"]
+      const sel = gv3.model.get_selection_manager()
+      const [sx0, sx1] = pv3.frame.x_scale.r_compute(20, 40)
+      const [sy0, sy1] = pv3.frame.y_scale.r_compute(20, 40)
+      sel.select([gv3], {type: "rect", sx0, sy0, sx1, sy1}, true, "append")
+      await pv3.ready
+    })
+  })
+})
diff --git a/bokehjs/test/integration/data.ts b/bokehjs/test/integration/data.ts
new file mode 100644
--- /dev/null
+++ b/bokehjs/test/integration/data.ts
@@ -0,0 +1,251 @@
+import {Float64NDArray} from "@bokehjs/core/util/ndarray"
+
+const data = new Float64NDArray([
+  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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+  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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+], [245, 221])
+
+export default data
diff --git a/bokehjs/test/integration/index.ts b/bokehjs/test/integration/index.ts
--- a/bokehjs/test/integration/index.ts
+++ b/bokehjs/test/integration/index.ts
@@ -6,3 +6,4 @@ import "./glyphs"
 import "./tiles"
 import "./regressions"
 import "./widgets"
+import "./color_mapping"
diff --git a/tests/unit/bokeh/models/test_mappers.py b/tests/unit/bokeh/models/test_mappers.py
--- a/tests/unit/bokeh/models/test_mappers.py
+++ b/tests/unit/bokeh/models/test_mappers.py
@@ -94,6 +94,7 @@ def test_basic(self) -> None:
         mapper = bmm.LinearColorMapper()
         check_properties_existence(mapper, [
             "palette",
+            "domain",
             "low",
             "high",
             "low_color",
@@ -107,6 +108,7 @@ def test_basic(self) -> None:
         mapper = bmm.LogColorMapper()
         check_properties_existence(mapper, [
             "palette",
+            "domain",
             "low",
             "high",
             "low_color",