feat(bokeh): implement scatter-pitch-events (#5094)

## Implementation: `scatter-pitch-events` - bokeh

Implements the **bokeh** version of `scatter-pitch-events`.

**File:** `plots/scatter-pitch-events/implementations/bokeh.py`

**Parent Issue:** #4417

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/23342848863)*

---------

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/scatter-pitch-events/implementations/bokeh.py

@@ -0,0 +1,248 @@
+""" pyplots.ai
+scatter-pitch-events: Soccer Pitch Event Map
+Library: bokeh 3.9.0 | Python 3.14.3
+Quality: 91/100 | Created: 2026-03-20
+"""
+
+import numpy as np
+import pandas as pd
+from bokeh.io import export_png, save
+from bokeh.models import Arrow, ColumnDataSource, Label, NormalHead, Range1d
+from bokeh.plotting import figure
+from bokeh.resources import CDN
+
+
+# Data
+np.random.seed(42)
+n_events = 120
+
+event_types = np.random.choice(["pass", "shot", "tackle", "interception"], size=n_events, p=[0.45, 0.15, 0.22, 0.18])
+
+x_start = np.zeros(n_events)
+y_start = np.zeros(n_events)
+x_end = np.zeros(n_events)
+y_end = np.zeros(n_events)
+outcomes = []
+
+for i, etype in enumerate(event_types):
+    if etype == "pass":
+        x_start[i] = np.random.uniform(10, 90)
+        y_start[i] = np.random.uniform(5, 63)
+        angle = np.random.uniform(-np.pi / 2, np.pi / 2)
+        dist = np.random.uniform(5, 40)
+        x_end[i] = np.clip(x_start[i] + dist * np.cos(angle), 0, 105)
+        y_end[i] = np.clip(y_start[i] + dist * np.sin(angle), 0, 68)
+        outcomes.append(np.random.choice(["successful", "unsuccessful"], p=[0.78, 0.22]))
+    elif etype == "shot":
+        x_start[i] = np.random.uniform(70, 100)
+        y_start[i] = np.random.uniform(15, 53)
+        x_end[i] = 105
+        y_end[i] = np.random.uniform(28, 40)
+        outcomes.append(np.random.choice(["successful", "unsuccessful"], p=[0.30, 0.70]))
+    elif etype == "tackle":
+        x_start[i] = np.random.uniform(15, 75)
+        y_start[i] = np.random.uniform(5, 63)
+        x_end[i] = x_start[i]
+        y_end[i] = y_start[i]
+        outcomes.append(np.random.choice(["successful", "unsuccessful"], p=[0.65, 0.35]))
+    else:
+        x_start[i] = np.random.uniform(20, 80)
+        y_start[i] = np.random.uniform(5, 63)
+        x_end[i] = x_start[i]
+        y_end[i] = y_start[i]
+        outcomes.append(np.random.choice(["successful", "unsuccessful"], p=[0.72, 0.28]))
+
+outcomes = np.array(outcomes)
+
+df = pd.DataFrame(
+    {"x": x_start, "y": y_start, "x_end": x_end, "y_end": y_end, "event_type": event_types, "outcome": outcomes}
+)
+
+# Colorblind-safe palette: blue, red, gold, purple (maximally distinct)
+event_colors = {"pass": "#306998", "shot": "#E63946", "tackle": "#E6A817", "interception": "#7B2D8E"}
+event_markers = {"pass": "circle", "shot": "star", "tackle": "triangle", "interception": "diamond"}
+
+# Visual hierarchy: shots are largest (focal point), others smaller
+event_sizes = {"pass": 18, "shot": 30, "tackle": 20, "interception": 22}
+
+# Plot
+p = figure(
+    width=4800,
+    height=2700,
+    title="scatter-pitch-events · bokeh · pyplots.ai",
+    x_range=Range1d(-6, 111),
+    y_range=Range1d(-16, 74),
+    toolbar_location=None,
+    match_aspect=True,
+)
+
+# Pitch background
+p.rect(x=52.5, y=34, width=105, height=68, fill_color="#4a9e50", fill_alpha=0.15, line_color=None)
+
+# Subtle pitch stripes for visual texture (alternating mow pattern)
+for stripe_x in range(0, 105, 10):
+    alpha = 0.04 if (stripe_x // 10) % 2 == 0 else 0.0
+    p.rect(x=stripe_x + 5, y=34, width=10, height=68, fill_color="#2E7D32", fill_alpha=alpha, line_color=None)
+
+# Danger zone gradient in attacking third — storytelling emphasis
+p.rect(x=96, y=34, width=18, height=68, fill_color="#E63946", fill_alpha=0.06, line_color=None)
+p.rect(x=100, y=34, width=10, height=68, fill_color="#E63946", fill_alpha=0.04, line_color=None)
+
+# Pitch outline
+p.line([0, 105, 105, 0, 0], [0, 0, 68, 68, 0], line_color="#2E7D32", line_width=4)
+
+# Halfway line
+p.line([52.5, 52.5], [0, 68], line_color="#2E7D32", line_width=3)
+
+# Center circle
+theta = np.linspace(0, 2 * np.pi, 100)
+p.line(52.5 + 9.15 * np.cos(theta), 34 + 9.15 * np.sin(theta), line_color="#2E7D32", line_width=3)
+p.scatter([52.5], [34], size=10, color="#2E7D32")
+
+# Left penalty area
+p.line([0, 16.5, 16.5, 0], [13.85, 13.85, 54.15, 54.15], line_color="#2E7D32", line_width=3)
+
+# Right penalty area
+p.line([105, 88.5, 88.5, 105], [13.85, 13.85, 54.15, 54.15], line_color="#2E7D32", line_width=3)
+
+# Left goal area
+p.line([0, 5.5, 5.5, 0], [24.85, 24.85, 43.15, 43.15], line_color="#2E7D32", line_width=3)
+
+# Right goal area
+p.line([105, 99.5, 99.5, 105], [24.85, 24.85, 43.15, 43.15], line_color="#2E7D32", line_width=3)
+
+# Penalty spots
+p.scatter([11, 94], [34, 34], size=8, color="#2E7D32")
+
+# Penalty arcs
+arc_theta = np.linspace(-0.93, 0.93, 50)
+p.line(11 + 9.15 * np.cos(arc_theta), 34 + 9.15 * np.sin(arc_theta), line_color="#2E7D32", line_width=3)
+p.line(94 - 9.15 * np.cos(arc_theta), 34 + 9.15 * np.sin(arc_theta), line_color="#2E7D32", line_width=3)
+
+# Corner arcs
+for cx, cy, a0, a1 in [
+    (0, 0, 0, np.pi / 2),
+    (105, 0, np.pi / 2, np.pi),
+    (105, 68, np.pi, 3 * np.pi / 2),
+    (0, 68, 3 * np.pi / 2, 2 * np.pi),
+]:
+    ca = np.linspace(a0, a1, 25)
+    p.line(cx + 1 * np.cos(ca), cy + 1 * np.sin(ca), line_color="#2E7D32", line_width=3)
+
+# Goal posts
+p.line([-1.5, 0], [30.34, 30.34], line_color="#555555", line_width=6)
+p.line([-1.5, 0], [37.66, 37.66], line_color="#555555", line_width=6)
+p.line([-1.5, -1.5], [30.34, 37.66], line_color="#555555", line_width=6)
+p.line([105, 106.5], [30.34, 30.34], line_color="#555555", line_width=6)
+p.line([105, 106.5], [37.66, 37.66], line_color="#555555", line_width=6)
+p.line([106.5, 106.5], [30.34, 37.66], line_color="#555555", line_width=6)
+
+# Directional arrows for passes and shots
+arrow_data = df[df["event_type"].isin(["pass", "shot"])]
+for _, row in arrow_data.iterrows():
+    color = event_colors[row["event_type"]]
+    alpha = 0.55 if row["outcome"] == "successful" else 0.25
+    lw = 2.5 if row["event_type"] == "shot" else 1.8
+    head_size = 14 if row["event_type"] == "shot" else 10
+    p.add_layout(
+        Arrow(
+            end=NormalHead(size=head_size, fill_color=color, fill_alpha=alpha, line_color=color, line_alpha=alpha),
+            x_start=row["x"],
+            y_start=row["y"],
+            x_end=row["x_end"],
+            y_end=row["y_end"],
+            line_color=color,
+            line_alpha=alpha,
+            line_width=lw,
+        )
+    )
+
+# Event markers — shots emphasized as focal point
+for etype in ["pass", "tackle", "interception", "shot"]:
+    for outcome in ["successful", "unsuccessful"]:
+        mask = (df["event_type"] == etype) & (df["outcome"] == outcome)
+        subset = df[mask]
+        if len(subset) == 0:
+            continue
+        alpha = 0.9 if outcome == "successful" else 0.45
+        fill = event_colors[etype] if outcome == "successful" else "white"
+        line_w = 4 if etype == "shot" else 2.5
+        source = ColumnDataSource(data={"x": subset["x"].values, "y": subset["y"].values})
+        p.scatter(
+            x="x",
+            y="y",
+            source=source,
+            marker=event_markers[etype],
+            size=event_sizes[etype],
+            fill_color=fill,
+            fill_alpha=alpha,
+            line_color=event_colors[etype],
+            line_width=line_w,
+            line_alpha=0.95,
+            legend_label=f"{etype.capitalize()} ({outcome})",
+        )
+
+# Storytelling annotation — highlight the danger zone
+shot_data = df[df["event_type"] == "shot"]
+n_shots = len(shot_data)
+n_on_target = len(shot_data[shot_data["outcome"] == "successful"])
+p.add_layout(
+    Label(
+        x=96,
+        y=66,
+        text=f"{n_shots} shots · {n_on_target} on target",
+        text_font_size="22pt",
+        text_color="#B71C1C",
+        text_font_style="bold",
+        text_alpha=0.8,
+    )
+)
+
+# Legend — positioned below pitch
+p.legend.location = "bottom_center"
+p.legend.orientation = "horizontal"
+p.legend.label_text_font_size = "22pt"
+p.legend.label_text_color = "#333333"
+p.legend.glyph_width = 32
+p.legend.glyph_height = 32
+p.legend.spacing = 30
+p.legend.padding = 15
+p.legend.background_fill_alpha = 0.92
+p.legend.background_fill_color = "white"
+p.legend.border_line_color = "#CCCCCC"
+p.legend.border_line_width = 2
+p.legend.ncols = 4
+p.legend.click_policy = "hide"
+
+# Style
+p.title.text_font_size = "52pt"
+p.title.text_color = "#222222"
+p.title.text_font_style = "bold"
+
+p.xaxis.axis_label = "Pitch Length (m)"
+p.yaxis.axis_label = "Pitch Width (m)"
+p.xaxis.axis_label_text_font_size = "36pt"
+p.yaxis.axis_label_text_font_size = "36pt"
+p.xaxis.major_label_text_font_size = "26pt"
+p.yaxis.major_label_text_font_size = "26pt"
+p.xaxis.axis_label_text_color = "#444444"
+p.yaxis.axis_label_text_color = "#444444"
+p.xaxis.major_label_text_color = "#555555"
+p.yaxis.major_label_text_color = "#555555"
+
+p.xaxis.axis_line_color = None
+p.yaxis.axis_line_color = None
+p.xaxis.major_tick_line_color = None
+p.yaxis.major_tick_line_color = None
+p.xaxis.minor_tick_line_color = None
+p.yaxis.minor_tick_line_color = None
+
+p.grid.grid_line_color = None
+
+p.background_fill_color = "#FAFAFA"
+p.border_fill_color = "#FAFAFA"
+p.outline_line_color = None
+
+# Save
+export_png(p, filename="plot.png")
+save(p, filename="plot.html", resources=CDN, title="scatter-pitch-events · bokeh · pyplots.ai")