update(arc-basic): letsplot — comprehensive quality review

plots/arc-basic/implementations/letsplot.py

@@ -1,7 +1,7 @@
 """ pyplots.ai
 arc-basic: Basic Arc Diagram
-Library: letsplot 4.8.2 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-23
+Library: letsplot 4.8.2 | Python 3.14.3
+Quality: 89/100 | Updated: 2026-02-23
 """
 
 import numpy as np
@@ -10,13 +10,18 @@
     LetsPlot,
     aes,
     element_blank,
+    element_rect,
     element_text,
     geom_path,
     geom_point,
+    geom_segment,
     geom_text,
     ggplot,
     ggsize,
     labs,
+    layer_tooltips,
+    scale_alpha_identity,
+    scale_color_identity,
     scale_size_identity,
     theme,
     xlim,
@@ -28,14 +33,12 @@
 LetsPlot.setup_html()
 
 # Data: Character interactions in a story chapter
-np.random.seed(42)
-
 nodes = ["Alice", "Bob", "Carol", "David", "Eve", "Frank", "Grace", "Henry", "Iris", "Jack"]
 n_nodes = len(nodes)
 
 # Edges: pairs of connected nodes with weights (source, target, weight)
 edges = [
-    (0, 1, 3),  # Alice-Bob (strong connection)
+    (0, 1, 3),  # Alice-Bob (strong)
     (0, 3, 2),  # Alice-David
     (1, 2, 2),  # Bob-Carol
     (2, 4, 1),  # Carol-Eve
@@ -52,9 +55,20 @@
     (8, 9, 2),  # Iris-Jack
 ]
 
-# Node positions along x-axis
-x_positions = np.linspace(0, 1, n_nodes)
-y_baseline = 0.1
+# Node positions along x-axis — wider spacing for label readability
+x_positions = np.linspace(0, 1.3, n_nodes)
+y_baseline = 0.06
+
+# Count connections per node for visual hierarchy
+connections = [0] * n_nodes
+for s, t, w in edges:
+    connections[s] += w
+    connections[t] += w
+
+# Arc color intensity by weight
+weight_colors = {1: "#6A9BB5", 2: "#306998", 3: "#1A3A5C"}
+weight_alphas = {1: 0.7, 2: 0.75, 3: 0.9}
+weight_labels = {1: "Weak", 2: "Moderate", 3: "Strong"}
 
 # Create arc data for geom_path
 arc_data = []
@@ -66,57 +80,138 @@
     distance = abs(end - start)
     height = 0.08 * distance
 
-    # Generate points along the arc (semi-circle)
+    # Generate points along the arc
     n_points = 50
     t = np.linspace(0, np.pi, n_points)
     arc_x = x_start + (x_end - x_start) * (1 - np.cos(t)) / 2
     arc_y = y_baseline + height * np.sin(t)
 
-    # Line width based on weight
-    line_size = 1.5 + weight * 1.0
+    line_size = 1.0 + weight * 1.2
+    color = weight_colors[weight]
+    alpha = weight_alphas[weight]
+    tooltip_text = f"{nodes[start]} \u2194 {nodes[end]}"
+    strength = weight_labels[weight]
 
     for i in range(n_points):
-        arc_data.append({"x": arc_x[i], "y": arc_y[i], "edge_id": edge_id, "weight": weight, "size": line_size})
+        arc_data.append(
+            {
+                "x": arc_x[i],
+                "y": arc_y[i],
+                "edge_id": edge_id,
+                "size": line_size,
+                "color": color,
+                "alpha": alpha,
+                "connection": tooltip_text,
+                "strength": strength,
+            }
+        )
 
 arc_df = pd.DataFrame(arc_data)
 
-# Node data
-node_df = pd.DataFrame({"x": x_positions, "y": [y_baseline] * n_nodes, "name": nodes})
+# Node data with size based on total connection weight (higher floor for peripheral nodes)
+max_conn = max(connections)
+node_sizes = [9 + 7 * (c / max_conn) for c in connections]
+node_df = pd.DataFrame(
+    {"x": x_positions, "y": [y_baseline] * n_nodes, "name": nodes, "node_size": node_sizes, "connections": connections}
+)
+
+# Baseline segment data
+baseline_df = pd.DataFrame({"x": [x_positions[0]], "xend": [x_positions[-1]], "y": [y_baseline], "yend": [y_baseline]})
 
 # Label data (positioned below nodes)
-label_df = pd.DataFrame({"x": x_positions, "y": [y_baseline - 0.05] * n_nodes, "name": nodes})
+label_df = pd.DataFrame({"x": x_positions, "y": [y_baseline - 0.04] * n_nodes, "name": nodes})
+
+# Legend data: small line segments showing weight encoding
+legend_x = 1.1
+legend_y_start = 0.72
+legend_spacing = 0.06
+legend_line_len = 0.07
+legend_lines = pd.DataFrame(
+    {
+        "x": [legend_x] * 3,
+        "xend": [legend_x + legend_line_len] * 3,
+        "y": [legend_y_start - i * legend_spacing for i in range(3)],
+        "yend": [legend_y_start - i * legend_spacing for i in range(3)],
+        "color": [weight_colors[3], weight_colors[2], weight_colors[1]],
+        "size": [1.0 + 3 * 1.2, 1.0 + 2 * 1.2, 1.0 + 1 * 1.2],
+        "alpha": [weight_alphas[3], weight_alphas[2], weight_alphas[1]],
+    }
+)
+legend_text_df = pd.DataFrame(
+    {
+        "x": [legend_x + legend_line_len + 0.015] * 3,
+        "y": [legend_y_start - i * legend_spacing for i in range(3)],
+        "label": ["Strong (3)", "Moderate (2)", "Weak (1)"],
+    }
+)
+legend_title_df = pd.DataFrame({"x": [legend_x], "y": [legend_y_start + 0.05], "label": ["Connection Strength"]})
 
-# Create plot
+# Plot
 plot = (
     ggplot()
-    # Draw arcs with semi-transparency for overlapping connections
-    + geom_path(data=arc_df, mapping=aes(x="x", y="y", group="edge_id", size="size"), color="#306998", alpha=0.6)
+    # Subtle baseline
+    + geom_segment(data=baseline_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color="#D0D8E0", size=0.8)
+    # Arcs with weight-based color, transparency, and tooltips
+    + geom_path(
+        data=arc_df,
+        mapping=aes(x="x", y="y", group="edge_id", size="size", color="color", alpha="alpha"),
+        tooltips=layer_tooltips().title("@connection").line("Strength|@strength"),
+    )
     + scale_size_identity()
-    # Draw nodes
-    + geom_point(data=node_df, mapping=aes(x="x", y="y"), size=10, color="#FFD43B", fill="#FFD43B", stroke=2, shape=21)
-    # Add node labels
+    + scale_color_identity()
+    + scale_alpha_identity()
+    # Nodes sized by connection weight with tooltips
+    + geom_point(
+        data=node_df,
+        mapping=aes(x="x", y="y", size="node_size"),
+        color="#1A3A5C",
+        fill="#FFD43B",
+        stroke=1.5,
+        shape=21,
+        tooltips=layer_tooltips().title("@name").line("Total weight|@connections"),
+    )
+    + scale_size_identity()
+    # Node labels
     + geom_text(
-        data=label_df, mapping=aes(x="x", y="y", label="name"), size=14, color="#306998", fontface="bold", vjust=1
+        data=label_df, mapping=aes(x="x", y="y", label="name"), size=20, color="#1A3A5C", fontface="bold", vjust=1
+    )
+    # Weight legend
+    + geom_segment(
+        data=legend_lines,
+        mapping=aes(x="x", y="y", xend="xend", yend="yend", color="color", size="size", alpha="alpha"),
+        tooltips="none",
+    )
+    + geom_text(data=legend_text_df, mapping=aes(x="x", y="y", label="label"), size=16, color="#1A3A5C", hjust=0)
+    + geom_text(
+        data=legend_title_df,
+        mapping=aes(x="x", y="y", label="label"),
+        size=16,
+        color="#1A3A5C",
+        fontface="bold",
+        hjust=0,
     )
     # Styling
-    + xlim(-0.05, 1.05)
-    + ylim(-0.15, 0.85)
-    + labs(title="Character Interactions · arc-basic · letsplot · pyplots.ai")
+    + xlim(-0.05, 1.48)
+    + ylim(-0.01, 0.82)
+    + labs(
+        title="arc-basic \u00b7 letsplot \u00b7 pyplots.ai",
+        subtitle="Character interactions in a story chapter \u2014 node size reflects connection strength",
+    )
     + theme(
         axis_title=element_blank(),
         axis_text=element_blank(),
         axis_ticks=element_blank(),
         axis_line=element_blank(),
         panel_grid=element_blank(),
-        panel_background=element_blank(),
-        plot_title=element_text(size=24, face="bold"),
+        panel_background=element_rect(fill="white", color="white"),
+        plot_background=element_rect(fill="white", color="white"),
+        plot_title=element_text(size=24, face="bold", color="#1A3A5C"),
+        plot_subtitle=element_text(size=16, color="#4A6B82"),
         legend_position="none",
     )
     + ggsize(1600, 900)
 )
 
-# Save as PNG (scale 3x to get 4800 x 2700 px)
+# Save
 ggsave(plot, "plot.png", path=".", scale=3)
-
-# Save as HTML for interactive viewing
 ggsave(plot, "plot.html", path=".")