feat(matplotlib): implement campbell-basic (#4246)

## Implementation: `campbell-basic` - matplotlib

Implements the **matplotlib** version of `campbell-basic`.

**File:** `plots/campbell-basic/implementations/matplotlib.py`

**Parent Issue:** #4241

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/22043026882)*

---------

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/campbell-basic/implementations/matplotlib.py

@@ -0,0 +1,210 @@
+""" pyplots.ai
+campbell-basic: Campbell Diagram
+Library: matplotlib 3.10.8 | Python 3.14.3
+Quality: 90/100 | Created: 2026-02-15
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+from matplotlib.lines import Line2D
+from matplotlib.patches import Patch
+from matplotlib.ticker import FuncFormatter
+
+
+# Data
+speed_rpm = np.linspace(0, 6000, 200)
+speed_hz = speed_rpm / 60
+
+# Natural frequency modes (Hz) - realistic gyroscopic effects
+mode_1_bending = 18 + 0.004 * speed_rpm - 1.5e-7 * speed_rpm**2
+mode_2_bending = 48 - 0.003 * speed_rpm + 2.0e-7 * speed_rpm**2
+mode_1_torsional = 58 + 0.0004 * speed_rpm
+mode_axial = 78 - 0.005 * speed_rpm + 4.0e-7 * speed_rpm**2
+mode_3_bending = 92 + 0.005 * speed_rpm - 3.5e-7 * speed_rpm**2
+
+modes = [mode_1_bending, mode_2_bending, mode_1_torsional, mode_axial, mode_3_bending]
+mode_labels = ["1st Bending", "2nd Bending", "1st Torsional", "Axial", "3rd Bending"]
+mode_colors = ["#306998", "#E8833A", "#2B9EB3", "#984EA3", "#A65628"]
+
+engine_orders = [1, 2, 3]
+eo_freq = {eo: eo * speed_hz for eo in engine_orders}
+
+# Find critical speed intersections via sign changes
+op_min, op_max = 2500, 4500
+critical_speeds, critical_freqs, critical_mlabels = [], [], []
+for mode, mlabel in zip(modes, mode_labels, strict=True):
+    for eo in engine_orders:
+        diff = mode - eo * speed_hz
+        for idx in np.where(np.diff(np.sign(diff)))[0]:
+            t = abs(diff[idx]) / (abs(diff[idx]) + abs(diff[idx + 1]))
+            rpm = speed_rpm[idx] + t * (speed_rpm[idx + 1] - speed_rpm[idx])
+            freq = mode[idx] + t * (mode[idx + 1] - mode[idx])
+            if 100 < rpm < 5900:
+                critical_speeds.append(rpm)
+                critical_freqs.append(freq)
+                critical_mlabels.append(mlabel)
+
+# Plot
+fig, ax = plt.subplots(figsize=(16, 9))
+y_max = 120
+
+# Operating range shading
+ax.axvspan(op_min, op_max, alpha=0.07, color="#306998", zorder=0)
+ax.axvline(op_min, color="#306998", linewidth=1.2, linestyle=":", alpha=0.5, zorder=1)
+ax.axvline(op_max, color="#306998", linewidth=1.2, linestyle=":", alpha=0.5, zorder=1)
+ax.text(
+    (op_min + op_max) / 2,
+    3,
+    "Operating Range",
+    fontsize=13,
+    color="#306998",
+    ha="center",
+    va="bottom",
+    fontstyle="italic",
+    alpha=0.6,
+)
+
+# Mode curves
+for mode, _label, color in zip(modes, mode_labels, mode_colors, strict=True):
+    ax.plot(speed_rpm, mode, linewidth=2.8, color=color, zorder=3, solid_capstyle="round")
+
+# End-of-line labels with vertical de-collision
+end_vals = [(mode[-1], label, color) for mode, label, color in zip(modes, mode_labels, mode_colors, strict=True)]
+end_vals.sort(key=lambda x: x[0])
+min_gap = 4.5  # minimum Hz gap between adjacent labels
+positions = [v[0] for v in end_vals]
+for i in range(1, len(positions)):
+    if positions[i] - positions[i - 1] < min_gap:
+        positions[i] = positions[i - 1] + min_gap
+for y_pos, (_, label, color) in zip(positions, end_vals, strict=True):
+    ax.annotate(
+        label,
+        xy=(speed_rpm[-1], y_pos),
+        xytext=(8, 0),
+        textcoords="offset points",
+        fontsize=10,
+        color=color,
+        fontweight="bold",
+        va="center",
+        zorder=4,
+    )
+
+# Engine order lines with rotated labels
+for eo in engine_orders:
+    eo_line = eo_freq[eo]
+    visible = eo_line <= y_max
+    ax.plot(
+        speed_rpm[visible], eo_line[visible], linewidth=1.8, color="#AAAAAA", linestyle=(0, (8, 4)), alpha=0.6, zorder=2
+    )
+    target_freq = y_max * 0.28
+    target_rpm = target_freq * 60 / eo
+    if target_rpm < 5800:
+        slope_display = (eo / 60) * (9 / y_max) / (16 / 6000)
+        angle_deg = np.degrees(np.arctan(slope_display))
+        ax.annotate(
+            f"{eo}×",
+            xy=(target_rpm, target_freq),
+            fontsize=14,
+            color="#777777",
+            fontweight="bold",
+            ha="center",
+            va="bottom",
+            rotation=angle_deg,
+            rotation_mode="anchor",
+            zorder=4,
+            bbox={"boxstyle": "round,pad=0.15", "facecolor": "white", "edgecolor": "none", "alpha": 0.8},
+        )
+
+# Critical speed markers
+cs_arr, cf_arr = np.array(critical_speeds), np.array(critical_freqs)
+in_op = (cs_arr >= op_min) & (cs_arr <= op_max)
+
+if np.any(~in_op):
+    ax.scatter(
+        cs_arr[~in_op], cf_arr[~in_op], s=200, color="#D62728", edgecolors="white", linewidth=1.5, zorder=5, alpha=0.45
+    )
+
+if np.any(in_op):
+    ax.scatter(
+        cs_arr[in_op], cf_arr[in_op], s=350, color="#D62728", edgecolors="white", linewidth=2, zorder=6, marker="D"
+    )
+    # Annotate critical intersections inside operating range with well-separated offsets
+    op_s, op_f, op_m = cs_arr[in_op], cf_arr[in_op], np.array(critical_mlabels)[in_op]
+    order = np.argsort(op_f)
+    n = len(order)
+    for rank, si in enumerate(order):
+        # Alternate left/right with increasing vertical spread to avoid overlap
+        sign = 1 if rank % 2 == 0 else -1
+        dx = sign * 35
+        dy = -30 + rank * (60 / max(n - 1, 1))
+        ax.annotate(
+            op_m[si],
+            xy=(op_s[si], op_f[si]),
+            xytext=(dx, dy),
+            textcoords="offset points",
+            fontsize=11,
+            color="#B71C1C",
+            fontweight="bold",
+            arrowprops={"arrowstyle": "-|>", "color": "#B71C1C", "lw": 1.0, "shrinkB": 4},
+            zorder=7,
+            bbox={
+                "boxstyle": "round,pad=0.25",
+                "facecolor": "#FFF3F3",
+                "edgecolor": "#B71C1C",
+                "alpha": 0.9,
+                "linewidth": 0.7,
+            },
+        )
+
+# Style
+ax.set_xlabel("Rotational Speed (RPM)", fontsize=20)
+ax.set_ylabel("Frequency (Hz)", fontsize=20)
+ax.set_title("campbell-basic · matplotlib · pyplots.ai", fontsize=24, fontweight="medium", pad=16)
+ax.tick_params(axis="both", labelsize=16)
+for spine in ("top", "right"):
+    ax.spines[spine].set_visible(False)
+for spine in ("left", "bottom"):
+    ax.spines[spine].set_linewidth(0.6)
+    ax.spines[spine].set_color("#555555")
+ax.set_xlim(0, 6000)
+ax.set_ylim(0, y_max)
+ax.yaxis.grid(True, alpha=0.15, linewidth=0.6, color="#CCCCCC")
+ax.xaxis.grid(True, alpha=0.08, linewidth=0.4, color="#CCCCCC")
+
+# Format x-axis with thousand separator for readability
+ax.xaxis.set_major_formatter(FuncFormatter(lambda x, _: f"{x:,.0f}"))
+
+# Compact two-column legend positioned in upper-left to avoid covering data
+eo_handle = Line2D([0], [0], color="#AAAAAA", linewidth=1.8, linestyle=(0, (8, 4)), alpha=0.6)
+crit_outside = Line2D(
+    [0], [0], marker="o", color="none", markerfacecolor="#D62728", markeredgecolor="white", markersize=10, alpha=0.5
+)
+crit_inside = Line2D(
+    [0], [0], marker="D", color="none", markerfacecolor="#D62728", markeredgecolor="white", markersize=10
+)
+op_handle = Patch(facecolor="#306998", alpha=0.12, edgecolor="none")
+
+handles = [Line2D([0], [0], color=c, linewidth=2.8) for c in mode_colors] + [
+    eo_handle,
+    crit_outside,
+    crit_inside,
+    op_handle,
+]
+labels = mode_labels + ["Engine Order (1×–3×)", "Critical Speed", "Critical (op. range)", "Operating Range"]
+
+ax.legend(
+    handles,
+    labels,
+    fontsize=11,
+    loc="upper left",
+    ncol=2,
+    framealpha=0.92,
+    edgecolor="#DDDDDD",
+    borderpad=0.5,
+    labelspacing=0.4,
+    handlelength=1.4,
+    columnspacing=1.0,
+)
+
+plt.tight_layout()
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")