feat(letsplot): implement heatmap-risk-matrix (#4952)

## Implementation: `heatmap-risk-matrix` - letsplot

Implements the **letsplot** version of `heatmap-risk-matrix`.

**File:** `plots/heatmap-risk-matrix/implementations/letsplot.py`

**Parent Issue:** #4567

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/23217984766)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/heatmap-risk-matrix/implementations/letsplot.py

@@ -0,0 +1,178 @@
+"""pyplots.ai
+heatmap-risk-matrix: Risk Assessment Matrix (Probability vs Impact)
+Library: letsplot 4.9.0 | Python 3.14.3
+Quality: 80/100 | Created: 2026-03-17
+"""
+
+import numpy as np
+import pandas as pd
+from lets_plot import *
+
+
+LetsPlot.setup_html()
+
+# Data
+np.random.seed(42)
+
+likelihood_labels = ["Rare", "Unlikely", "Possible", "Likely", "Almost\nCertain"]
+impact_labels = ["Negligible", "Minor", "Moderate", "Major", "Catastrophic"]
+
+# Build background grid with risk zones
+grid_rows = []
+for li in range(1, 6):
+    for im in range(1, 6):
+        score = li * im
+        if score <= 4:
+            zone = "Low"
+        elif score <= 9:
+            zone = "Medium"
+        elif score <= 16:
+            zone = "High"
+        else:
+            zone = "Critical"
+        grid_rows.append({"likelihood": li, "impact": im, "score": score, "zone": zone, "score_label": str(score)})
+grid_df = pd.DataFrame(grid_rows)
+grid_df["zone"] = pd.Categorical(grid_df["zone"], categories=["Low", "Medium", "High", "Critical"], ordered=True)
+
+# Risk items with shorter names to avoid label overlap
+risks = pd.DataFrame(
+    {
+        "risk_name": [
+            "Server Outage",
+            "Data Breach",
+            "Budget Overrun",
+            "Staff Loss",
+            "Vendor Fail",
+            "Scope Creep",
+            "Reg. Change",
+            "Tech Debt",
+            "Integ. Bug",
+            "Supply Delay",
+            "Currency",
+            "PR Crisis",
+            "Patent Issue",
+            "Power Outage",
+            "Cyber Attack",
+        ],
+        "likelihood": [4, 3, 4, 2, 2, 5, 3, 4, 3, 1, 3, 1, 1, 2, 5],
+        "impact": [5, 5, 3, 4, 3, 2, 3, 2, 4, 3, 2, 5, 4, 1, 5],
+        "category": [
+            "Technical",
+            "Technical",
+            "Financial",
+            "Operational",
+            "Operational",
+            "Operational",
+            "Financial",
+            "Technical",
+            "Technical",
+            "Operational",
+            "Financial",
+            "Operational",
+            "Financial",
+            "Technical",
+            "Technical",
+        ],
+    }
+)
+
+# Compute risk score for size mapping (visual hierarchy)
+risks["risk_score"] = risks["likelihood"] * risks["impact"]
+
+# Smart jitter: offset risks sharing same cell
+cell_counts = {}
+offsets_x = []
+offsets_y = []
+for _, row in risks.iterrows():
+    cell = (row["likelihood"], row["impact"])
+    idx = cell_counts.get(cell, 0)
+    cell_counts[cell] = idx + 1
+    offset_patterns = [(0, 0.15), (0, -0.15), (-0.2, 0), (0.2, 0)]
+    ox, oy = offset_patterns[idx % len(offset_patterns)]
+    offsets_x.append(ox)
+    offsets_y.append(oy)
+
+risks["lk_jitter"] = risks["likelihood"] + np.array(offsets_x)
+risks["im_jitter"] = risks["impact"] + np.array(offsets_y)
+
+# Assign label nudge using checkerboard pattern based on grid position
+# This ensures adjacent cells always have opposite nudge directions
+nudge_vals = []
+for _, row in risks.iterrows():
+    li, imp = int(row["likelihood"]), int(row["impact"])
+    if (li + imp) % 2 == 0:
+        nudge_vals.append(0.33)
+    else:
+        nudge_vals.append(-0.33)
+risks["label_nudge_y"] = nudge_vals
+
+# Tooltips for lets-plot distinctive interactivity
+risk_tooltips = (
+    layer_tooltips()
+    .line("@risk_name")
+    .line("Category: @category")
+    .line("Likelihood: @likelihood")
+    .line("Impact: @impact")
+    .line("Risk Score: @risk_score")
+)
+
+# Zone palette: green-yellow-orange-red as specified
+zone_colors = {"Low": "#2A9D8F", "Medium": "#E9C46A", "High": "#F4A261", "Critical": "#C1121F"}
+
+# Category colors
+cat_colors = {"Technical": "#306998", "Financial": "#7B2D8E", "Operational": "#D35400"}
+
+# Split risks for alternating label nudge
+risks_up = risks[risks["label_nudge_y"] > 0].copy()
+risks_down = risks[risks["label_nudge_y"] < 0].copy()
+
+# Plot
+plot = (
+    ggplot()
+    + geom_tile(aes(x="likelihood", y="impact", fill="zone"), data=grid_df, color="white", size=2, tooltips="none")
+    + geom_text(aes(x="likelihood", y="impact", label="score_label"), data=grid_df, size=13, color="rgba(0,0,0,0.12)")
+    + geom_point(
+        aes(x="lk_jitter", y="im_jitter", color="category", size="risk_score"),
+        data=risks,
+        alpha=0.92,
+        tooltips=risk_tooltips,
+    )
+    + scale_size(range=[4, 12], name="Risk Score", guide="none")
+    + scale_fill_manual(values=zone_colors, name="Risk Level")
+    + scale_color_manual(values=cat_colors, name="Category")
+    + scale_x_continuous(breaks=[1, 2, 3, 4, 5], labels=likelihood_labels, limits=[0.4, 5.8])
+    + scale_y_continuous(breaks=[1, 2, 3, 4, 5], labels=impact_labels, limits=[0.4, 5.6])
+    + coord_fixed(ratio=1)
+    + labs(
+        x="Likelihood",
+        y="Impact",
+        title="heatmap-risk-matrix · lets-plot · pyplots.ai",
+        subtitle="Risk score = Likelihood × Impact  |  Marker size scales with severity",
+    )
+    + theme_minimal()
+    + theme(
+        plot_title=element_text(size=24, face="bold"),
+        plot_subtitle=element_text(size=15, color="#555555"),
+        axis_title=element_text(size=20, face="bold"),
+        axis_text=element_text(size=15),
+        legend_title=element_text(size=17, face="bold"),
+        legend_text=element_text(size=14),
+        panel_grid=element_blank(),
+    )
+    + ggsize(1600, 900)
+)
+
+# Add labels with alternating nudge directions to reduce overlap
+if len(risks_up) > 0:
+    plot = plot + geom_text(
+        aes(x="lk_jitter", y="im_jitter", label="risk_name"), data=risks_up, size=9, nudge_y=0.33, fontface="bold"
+    )
+
+if len(risks_down) > 0:
+    plot = plot + geom_text(
+        aes(x="lk_jitter", y="im_jitter", label="risk_name"), data=risks_down, size=9, nudge_y=-0.33, fontface="bold"
+    )
+
+# Save
+ggsave(plot, "plot.png", path=".", scale=3)
+ggsave(plot, "plot.html", path=".")