Refactor K-Means input handling to exclude cluster header lines and adjust heatmap margin settings for improved layout

main.js

@@ -25,7 +25,10 @@ document.getElementById("run").onclick = async () => {
 
     const groupEmbeddings = [];
     for (const g of groups) {
-        const lines = g.split(/\n/).filter(x => x.trim() != "");
+        // Remove lines starting with ##
+        const lines = g.split(/\n/)
+            .map(x => x.trim())
+            .filter(x => x && !x.startsWith('##'));
         const prompts = lines.map(s => `Instruct: ${task}\nQuery:${s}`);
         const out = await embed(prompts, { pooling: "mean", normalize: true });
         const embeddings = typeof out.tolist === 'function' ? out.tolist() : out.data;
@@ -52,13 +55,13 @@ document.getElementById("run").onclick = async () => {
     }
     // If clusterNames exist and match group count, use as axis labels
     let xLabels = clusterNames && clusterNames.length === n ? clusterNames : Array.from({length: n}, (_, i) => `Group ${i+1}`);
-    const data = [{ z: sim, type: "heatmap", colorscale: "Viridis", zmin: 0, zmax: 1, x: xLabels, y: xLabels }];
+    const data = [{ z: sim, type: "heatmap", colorscale: "Viridis", zmin: 0.7, zmax: 1, x: xLabels, y: xLabels }];
     Plotly.newPlot("plot-heatmap", data, {
         xaxis: { title: "Group", scaleanchor: "y", scaleratio: 1 },
         yaxis: { title: "Group", scaleanchor: "x", scaleratio: 1 },
         width: 500,
         height: 500,
-        margin: { t: 40, l: 40, r: 10, b: 40 },
+        margin: { t: 40, l: 200, r: 10, b: 200 },
         title: "Group Similarity Heatmap"
     });
 };