Implements switchable color vision deficiency simulation to the docs

docs/_gen_cmaps.py

@@ -9,7 +9,7 @@
 if TYPE_CHECKING:
     from cmap import _catalog
 from cmap import Colormap
-from cmap._util import report
+from cmap._util import report_cvds
 
 # TODO: convert to jinja
 TEMPLATE = """# {name}
@@ -32,6 +32,29 @@
 {{{{ cmap_gray: {name} 30 }}}}
 {{{{ cmap_sineramp: {name} }}}}
 
+<form id="cvd" class="radio-group">
+  <label class="radio-option" title="Full Vision">
+    <input type="radio" name="cvd_button" value="normal" checked>
+    <span class="material-icons">visibility</span>
+    <span class="radio-label"> Normal Vision</span>
+  </label>
+  <label class="radio-option" title="Protanopic">
+    <input type="radio" name="cvd_button" value="protan">
+    <span class="material-icons">filter_1</span>
+    <span class="radio-label"> Protanopic</span>
+  </label>
+  <label class="radio-option" title="Deuteranopic">
+    <input type="radio" name="cvd_button" value="deutan">
+    <span class="material-icons">filter_2</span>
+    <span class="radio-label"> Deuteranopic</span>
+  </label>
+  <label class="radio-option" title="Tritananopic">
+    <input type="radio" name="cvd_button" value="tritan">
+    <span class="material-icons">filter_3</span>
+    <span class="radio-label"> Tritanopic</span>
+  </label>
+</form>
+
 ## Perceptual Lightness
 
 <canvas class="linearity-chart cmap-chart" data-cmap-name="{name}" width="800" height="350"></canvas>
@@ -53,6 +76,19 @@
 
 <script>
 window.cmap_data = {data};
+
+cvd?.addEventListener("change", (e) => {{
+    const selected = cvd.querySelector('input[name="cvd_button"]:checked')?.value;
+    //window.cmap_data = {data}[selected];
+    console.log("CVD type selected:", selected);
+    // re-render the charts
+    initCharts();
+
+    console.log("Selected variant:", selected);
+}});
+
+
+
 <!-- Note: this is here because of `navigation.instant` in the mkdocs settings -->
 typeof(initCharts) !== 'undefined' && initCharts();
 </script>
@@ -111,11 +147,13 @@ def build_catalog(catalog: "_catalog.Catalog") -> None:
         # write data used for charts
         cm = Colormap(name)
         cmap_data = {
-            k: np.around(v, 4).tolist() if isinstance(v, np.ndarray) else v
-            for k, v in report(cm).items()
-            if k in INCLUDE_DATA
+            cvd_type: {
+                k: np.around(v, 4).tolist() if isinstance(v, np.ndarray) else v
+                for k, v in report.items()
+                if k in INCLUDE_DATA
+            }
+            for cvd_type, report in report_cvds(cm).items()
         }
-
         _aliases = [x for x in info.aliases if x != info.name]
         aliases = _make_aliases_md(_aliases) if _aliases else ""
 

docs/javascripts/cmap_charts.js

@@ -22,14 +22,20 @@ async function initCharts() {
       chartElems[cmap_name] = [charts[i]];
     }
   }
+  var cvd_type = document.getElementById("cvd").querySelector('input[name="cvd_button"]:checked')?.value;
   // Make all charts for each cmap name
   for (var cmap_name in chartElems) {
     // NOTE: we're using a global window variable here that will be
     // injected into the _gen_cmaps page... because it's much faster
     // on readthedocs than making an additional fetch request
-    var cmap_data = window.cmap_data[cmap_name];
+    var cmap_data = window.cmap_data[cmap_name][cvd_type] || window.cmap_data[cmap_name]["normal"];
     for (var i = 0; i < chartElems[cmap_name].length; i++) {
       var canv = chartElems[cmap_name][i];
+      const chart = Chart.getChart(canv);
+      if (chart) {
+        chart.destroy();
+      }
+
       if (canv.classList.contains("rgb-chart")) {
         makeRGBChart(canv, cmap_data);
       } else if (canv.classList.contains("hsl-chart")) {

docs/stylesheets/extra.css

@@ -176,3 +176,49 @@ body[data-md-color-scheme="slate"] .btn.active {
 #readthedocs-ea, .ethical-alabaster {
   display: none;
 }
+
+.radio-group {
+  display: flex;
+  gap: 1rem;
+  margin-bottom: 1rem;
+}
+
+.radio-option {
+  position: relative;
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  padding: 0.5em;
+  border-radius: 0.5em;
+  cursor: pointer;
+  transition: background-color 0.2s, box-shadow 0.2s;
+}
+
+.radio-option input[type="radio"] {
+  appearance: none;
+  position: absolute;
+  opacity: 0;
+  pointer-events: none;
+}
+
+.radio-option .material-icons {
+  font-size: 1rem;
+  color: var(--md-default-fg-color);
+  transition: color 0.2s;
+}
+
+.radio-option input[type="radio"]:checked ~ .material-icons,
+.radio-option input[type="radio"]:checked ~ .radio-label {
+  color: var(--md-accent-fg-color);
+}
+
+
+.radio-option:hover {
+  background-color: var(--md-default-bg-color--lighter);
+  box-shadow: 0 0 0 2px var(--md-accent-fg-color);
+}
+
+.radio-option .radio-label {
+  font-size: 0.65rem;
+  color: var(--md-default-fg-color);
+}

mkdocs.yml

@@ -117,6 +117,7 @@ plugins:
             summary: true
 
 extra_css:
+  - https://fonts.googleapis.com/icon?family=Material+Icons
   - stylesheets/extra.css
 
 extra_javascript:

src/cmap/_util.py

@@ -446,13 +446,27 @@
     lightness_derivs: np.ndarray
 
 
-def report(cm: Colormap, n: int = 256, uniform_space: str = "CAM02-UCS") -> ReportDict:
+class CVDReportDict(TypedDict):
+    normal: ReportDict
+    protan: ReportDict
+    deutan: ReportDict
+    tritan: ReportDict
+
+
+def report(
+    cm: Colormap,
+    n: int = 256,
+    uniform_space: str = "CAM02-UCS",
+    initial_space: dict | None = None,
+) -> ReportDict:
     """Generate a report of data describing a colormap.
 
     This is primarily used for generating charts in the documentation
     """
     from colorspacious import cspace_convert
 
+    if initial_space is None:
+        initial_space = {"name": "sRGB1"}
     if len(cm.color_stops) >= 100:
         RGBA = np.asarray(cm.color_stops.color_array)
         n = RGBA.shape[0]
@@ -462,6 +476,7 @@
         RGBA = cm(x)
     RGB = RGBA[:, :3]
 
+    RGB = np.clip(cast("np.ndarray", cspace_convert(RGB, initial_space, "sRGB1")), 0, 1)
     Jab = cast("np.ndarray", cspace_convert(RGB, "sRGB1", uniform_space))
 
     local_deltas = np.sqrt(np.sum((Jab[:-1, :] - Jab[1:, :]) ** 2, axis=-1))
@@ -504,6 +519,48 @@
     # H -> hue composition
 
 
+def report_cvds(
+    cm: Colormap, n: int = 256, uniform_space: str = "CAM02-UCS"
+) -> CVDReportDict:
+    """Generate a report of data describing a colormap for different CVD types.
+
+    This is primarily used for generating charts in the documentation
+    """
+    return {
+        "normal": report(cm, n=n, uniform_space=uniform_space),
+        "protan": report(
+            cm,
+            n=n,
+            uniform_space=uniform_space,
+            initial_space={
+                "name": "sRGB1+CVD",
+                "cvd_type": "protanomaly",
+                "severity": 100,
+            },
+        ),
+        "deutan": report(
+            cm,
+            n=n,
+            uniform_space=uniform_space,
+            initial_space={
+                "name": "sRGB1+CVD",
+                "cvd_type": "deuteranomaly",
+                "severity": 100,
+            },
+        ),
+        "tritan": report(
+            cm,
+            n=n,
+            uniform_space=uniform_space,
+            initial_space={
+                "name": "sRGB1+CVD",
+                "cvd_type": "tritanomaly",
+                "severity": 100,
+            },
+        ),
+    }
+
+
 def to_mpl(
     value: ColorStopsLike,
     /,