feat(plotly): implement campbell-basic (#4244)

## Implementation: `campbell-basic` - plotly

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

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

**Parent Issue:** #4241

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/22043026911)*

---------

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/plotly.py

@@ -0,0 +1,284 @@
+""" pyplots.ai
+campbell-basic: Campbell Diagram
+Library: plotly 6.5.2 | Python 3.14.3
+Quality: 88/100 | Created: 2026-02-15
+"""
+
+import numpy as np
+import plotly.graph_objects as go
+
+
+# Data
+np.random.seed(42)
+speed_rpm = np.linspace(0, 6000, 80)
+speed_hz = speed_rpm / 60
+
+# Natural frequency modes (Hz) — enhanced gyroscopic effects for realistic variation
+mode_1_bending = 22 + 0.004 * speed_rpm + np.sin(speed_rpm / 1200) * 1.2  # forward whirl stiffening
+mode_2_bending = 48 - 0.003 * speed_rpm + np.cos(speed_rpm / 1800) * 1.4  # backward whirl softening
+mode_1_torsional = 55 + 0.0004 * speed_rpm  # torsional: nearly speed-independent
+mode_axial = 75 - 0.004 * speed_rpm + np.sin(speed_rpm / 1000) * 2.0  # axial with bearing coupling
+
+# Engine order lines: frequency = order * speed_rpm / 60
+orders = [1, 2, 3]
+order_freq = {order: order * speed_hz for order in orders}
+
+# Find critical speed intersections (engine order line crosses natural frequency curve)
+modes = {
+    "1st Bending": mode_1_bending,
+    "2nd Bending": mode_2_bending,
+    "1st Torsional": mode_1_torsional,
+    "Axial": mode_axial,
+}
+
+critical_speeds = []
+critical_freqs = []
+critical_labels = []
+for order in orders:
+    eo_freq = order_freq[order]
+    for mode_name, mode_freq in modes.items():
+        diff = mode_freq - eo_freq
+        sign_changes = np.where(np.diff(np.sign(diff)))[0]
+        for idx in sign_changes:
+            frac = abs(diff[idx]) / (abs(diff[idx]) + abs(diff[idx + 1]))
+            crit_rpm = speed_rpm[idx] + frac * (speed_rpm[idx + 1] - speed_rpm[idx])
+            crit_hz = crit_rpm / 60
+            crit_freq = order * crit_hz
+            critical_speeds.append(crit_rpm)
+            critical_freqs.append(crit_freq)
+            critical_labels.append(f"{mode_name} × {order}x")
+
+# Colorblind-safe palette (avoids red-green confusion)
+mode_colors = ["#306998", "#D4A017", "#9467BD", "#E07B39"]
+eo_color = "#7F7F7F"
+critical_color = "#C44E52"
+
+fig = go.Figure()
+
+# Track trace count for dynamic visibility toggling
+trace_count_before_modes = 0
+
+# Shaded bands at critical speed zones
+for cs_rpm in critical_speeds:
+    fig.add_vrect(x0=cs_rpm - 80, x1=cs_rpm + 80, fillcolor="rgba(196, 78, 82, 0.10)", line_width=0, layer="below")
+
+# Natural frequency curves with distinct dash patterns per mode type
+line_dashes = ["solid", "dash", "dot", "dashdot"]
+mode_trace_start = len(fig.data)
+for i, (mode_name, mode_freq) in enumerate(modes.items()):
+    fig.add_trace(
+        go.Scatter(
+            x=speed_rpm,
+            y=mode_freq,
+            mode="lines",
+            name=mode_name,
+            line={"color": mode_colors[i], "width": 3.5, "dash": line_dashes[i]},
+            hovertemplate=f"<b>{mode_name}</b><br>Speed: %{{x:.0f}} RPM<br>Freq: %{{y:.1f}} Hz<extra></extra>",
+        )
+    )
+n_mode_traces = len(fig.data) - mode_trace_start
+
+# Engine order lines (clipped to visible y-axis range)
+y_max = 110
+eo_trace_start = len(fig.data)
+for order in orders:
+    label = f"{order}x"
+    eo_y = order_freq[order]
+    mask = eo_y <= y_max
+    fig.add_trace(
+        go.Scatter(
+            x=speed_rpm[mask],
+            y=eo_y[mask],
+            mode="lines",
+            name=f"EO {label}",
+            line={"color": eo_color, "width": 2.4, "dash": "dash"},
+            hovertemplate=f"<b>EO {label}</b><br>Speed: %{{x:.0f}} RPM<br>Freq: %{{y:.1f}} Hz<extra></extra>",
+        )
+    )
+n_eo_traces = len(fig.data) - eo_trace_start
+
+# Engine order labels placed within the visible plot area
+for order in orders:
+    label = f"{order}x"
+    eo_y = order_freq[order]
+    visible_mask = eo_y <= y_max
+    visible_indices = np.where(visible_mask)[0]
+    label_idx = visible_indices[int(len(visible_indices) * 0.75)]
+    ann_x = speed_rpm[label_idx]
+    ann_y = eo_y[label_idx]
+    fig.add_annotation(
+        x=ann_x,
+        y=ann_y,
+        text=f"<b>{label}</b>",
+        showarrow=False,
+        xanchor="left",
+        yanchor="bottom",
+        xshift=8,
+        yshift=4,
+        font={"size": 16, "color": eo_color, "family": "Arial, sans-serif"},
+        bgcolor="rgba(255,255,255,0.85)",
+        borderpad=3,
+    )
+
+# Critical speed markers with descriptive hover
+crit_trace_start = len(fig.data)
+fig.add_trace(
+    go.Scatter(
+        x=critical_speeds,
+        y=critical_freqs,
+        mode="markers",
+        name="Critical Speed",
+        marker={"size": 14, "color": critical_color, "symbol": "diamond", "line": {"width": 2, "color": "white"}},
+        customdata=critical_labels,
+        hovertemplate="<b>Critical Speed</b><br>%{customdata}<br>Speed: %{x:.0f} RPM<br>Freq: %{y:.1f} Hz<extra></extra>",
+    )
+)
+n_crit_traces = len(fig.data) - crit_trace_start
+
+# Annotate the most critical intersection (highest frequency crossing = most dangerous)
+if critical_speeds:
+    max_idx = int(np.argmax(critical_freqs))
+    fig.add_annotation(
+        x=critical_speeds[max_idx],
+        y=critical_freqs[max_idx],
+        text=f"<b>⚠ {critical_freqs[max_idx]:.0f} Hz</b><br>{critical_labels[max_idx]}",
+        showarrow=True,
+        arrowhead=2,
+        arrowsize=1.2,
+        arrowcolor=critical_color,
+        arrowwidth=2,
+        ax=50,
+        ay=-45,
+        font={"size": 13, "color": critical_color, "family": "Arial, sans-serif"},
+        bgcolor="rgba(255,255,255,0.92)",
+        bordercolor=critical_color,
+        borderwidth=1.5,
+        borderpad=5,
+    )
+    # Annotate the lowest-RPM critical speed (first resonance encountered during run-up)
+    min_rpm_idx = int(np.argmin(critical_speeds))
+    if min_rpm_idx != max_idx:
+        fig.add_annotation(
+            x=critical_speeds[min_rpm_idx],
+            y=critical_freqs[min_rpm_idx],
+            text=f"<b>1st critical</b><br>{critical_speeds[min_rpm_idx]:.0f} RPM",
+            showarrow=True,
+            arrowhead=2,
+            arrowsize=1.2,
+            arrowcolor=critical_color,
+            arrowwidth=2,
+            ax=-55,
+            ay=40,
+            font={"size": 13, "color": critical_color, "family": "Arial, sans-serif"},
+            bgcolor="rgba(255,255,255,0.92)",
+            bordercolor=critical_color,
+            borderwidth=1.5,
+            borderpad=5,
+        )
+
+# Build dynamic visibility arrays for toggle buttons
+total_traces = len(fig.data)
+all_visible = [True] * total_traces
+modes_only = []
+for i in range(total_traces):
+    if eo_trace_start <= i < eo_trace_start + n_eo_traces:
+        modes_only.append(False)
+    else:
+        modes_only.append(True)
+
+# Layout — compact legend, tight margins
+fig.update_layout(
+    title={
+        "text": "campbell-basic · plotly · pyplots.ai",
+        "font": {"size": 28, "color": "#1A2A3A", "family": "Arial Black, Arial, sans-serif"},
+        "x": 0.5,
+        "xanchor": "center",
+        "y": 0.97,
+    },
+    xaxis={
+        "title": {
+            "text": "Rotational Speed (RPM)",
+            "font": {"size": 22, "color": "#333", "family": "Arial, sans-serif"},
+            "standoff": 10,
+        },
+        "tickfont": {"size": 18, "color": "#444"},
+        "showgrid": True,
+        "gridwidth": 1,
+        "gridcolor": "rgba(0,0,0,0.05)",
+        "zeroline": False,
+        "range": [0, 6100],
+        "dtick": 1000,
+        "showline": True,
+        "linewidth": 1,
+        "linecolor": "rgba(0,0,0,0.12)",
+        "mirror": False,
+        "spikemode": "across",
+        "spikethickness": 1,
+        "spikecolor": "rgba(0,0,0,0.3)",
+        "spikedash": "dot",
+    },
+    yaxis={
+        "title": {
+            "text": "Frequency (Hz)",
+            "font": {"size": 22, "color": "#333", "family": "Arial, sans-serif"},
+            "standoff": 10,
+        },
+        "tickfont": {"size": 18, "color": "#444"},
+        "showgrid": True,
+        "gridwidth": 1,
+        "gridcolor": "rgba(0,0,0,0.05)",
+        "zeroline": False,
+        "range": [0, y_max],
+        "dtick": 10,
+        "showline": True,
+        "linewidth": 1,
+        "linecolor": "rgba(0,0,0,0.12)",
+        "mirror": False,
+        "spikemode": "across",
+        "spikethickness": 1,
+        "spikecolor": "rgba(0,0,0,0.3)",
+        "spikedash": "dot",
+    },
+    legend={
+        "font": {"size": 14, "family": "Arial, sans-serif", "color": "#333"},
+        "bgcolor": "rgba(255,255,255,0.92)",
+        "bordercolor": "rgba(0,0,0,0.08)",
+        "borderwidth": 1,
+        "x": 0.01,
+        "y": 0.99,
+        "xanchor": "left",
+        "yanchor": "top",
+        "tracegroupgap": 1,
+        "itemsizing": "constant",
+        "itemwidth": 30,
+        "orientation": "h",
+    },
+    template="plotly_white",
+    margin={"l": 75, "r": 30, "t": 70, "b": 65},
+    plot_bgcolor="white",
+    paper_bgcolor="#F8F9FA",
+    hoverlabel={"bgcolor": "white", "font_size": 14, "bordercolor": "#DDD"},
+    hovermode="closest",
+    dragmode="zoom",
+    updatemenus=[
+        {
+            "type": "buttons",
+            "direction": "left",
+            "x": 1.0,
+            "y": 1.05,
+            "xanchor": "right",
+            "yanchor": "top",
+            "buttons": [
+                {"label": "All Modes", "method": "update", "args": [{"visible": all_visible}]},
+                {"label": "Modes Only", "method": "update", "args": [{"visible": modes_only}]},
+            ],
+            "font": {"size": 12},
+            "bgcolor": "rgba(255,255,255,0.9)",
+            "bordercolor": "rgba(0,0,0,0.1)",
+        }
+    ],
+)
+
+# Save
+fig.write_image("plot.png", width=1600, height=900, scale=3)
+fig.write_html("plot.html", include_plotlyjs="cdn")