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feat(matplotlib): implement smith-chart-basic (#3868)
## Implementation: `smith-chart-basic` - matplotlib Implements the **matplotlib** version of `smith-chart-basic`. **File:** `plots/smith-chart-basic/implementations/matplotlib.py` **Parent Issue:** #3792 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/21047488873)* --------- 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>
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‎plots/smith-chart-basic/implementations/matplotlib.py‎

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""" pyplots.ai
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smith-chart-basic: Smith Chart for RF/Impedance
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Library: matplotlib 3.10.8 | Python 3.13.11
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Quality: 91/100 | Created: 2026-01-15
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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# Reference impedance
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Z0 = 50 # ohms
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# Generate example data: antenna impedance sweep from 1 GHz to 6 GHz
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np.random.seed(42)
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frequency = np.linspace(1e9, 6e9, 50) # 50 frequency points
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# Simulate realistic antenna impedance variation with frequency
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# This creates a spiral-like pattern typical of antenna impedance measurements
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z_real = 50 + 30 * np.sin(2 * np.pi * (frequency - 1e9) / 2e9) + 10 * np.cos(4 * np.pi * (frequency - 1e9) / 5e9)
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z_imag = 20 * np.cos(2 * np.pi * (frequency - 1e9) / 1.5e9) + 15 * np.sin(3 * np.pi * (frequency - 1e9) / 5e9)
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# Normalize impedance
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z_norm = (z_real + 1j * z_imag) / Z0
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# Convert to reflection coefficient (gamma)
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gamma = (z_norm - 1) / (z_norm + 1)
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# Create square figure for Smith chart
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fig, ax = plt.subplots(figsize=(12, 12))
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ax.set_aspect("equal")
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# Colors
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grid_color = "#888888"
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circle_color = "#306998"
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data_color = "#FFD43B"
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# Draw constant resistance circles
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r_values = [0, 0.2, 0.5, 1, 2, 5]
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theta = np.linspace(0, 2 * np.pi, 500)
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for r in r_values:
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# Center and radius of constant resistance circle
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center = r / (r + 1)
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radius = 1 / (r + 1)
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x_circle = center + radius * np.cos(theta)
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y_circle = radius * np.sin(theta)
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# Clip to unit circle
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mask = x_circle**2 + y_circle**2 <= 1.001
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x_clipped = np.where(mask, x_circle, np.nan)
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y_clipped = np.where(mask, y_circle, np.nan)
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ax.plot(x_clipped, y_clipped, color=grid_color, linewidth=1, alpha=0.6)
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# Label resistance circles
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if r > 0:
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label_x = center + radius
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if label_x <= 1:
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ax.text(label_x + 0.02, 0.02, f"{r}", fontsize=12, color=grid_color, ha="left", va="bottom")
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# Draw constant reactance arcs
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x_values = [0.2, 0.5, 1, 2, 5]
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for x in x_values:
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# Positive reactance (inductive - upper half)
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center_y = 1 / x
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radius = 1 / x
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arc_theta = np.linspace(0, np.pi, 500)
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x_arc = 1 + radius * np.cos(arc_theta + np.pi)
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y_arc = center_y + radius * np.sin(arc_theta + np.pi)
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# Clip to unit circle
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mask = x_arc**2 + y_arc**2 <= 1.001
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x_clipped = np.where(mask, x_arc, np.nan)
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y_clipped = np.where(mask, y_arc, np.nan)
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ax.plot(x_clipped, y_clipped, color=grid_color, linewidth=1, alpha=0.6)
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# Negative reactance (capacitive - lower half)
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y_arc_neg = -center_y + radius * np.sin(arc_theta)
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mask = x_arc**2 + y_arc_neg**2 <= 1.001
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x_clipped = np.where(mask, x_arc, np.nan)
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y_clipped = np.where(mask, y_arc_neg, np.nan)
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ax.plot(x_clipped, y_clipped, color=grid_color, linewidth=1, alpha=0.6)
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# Label reactance arcs
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# Find intersection with unit circle
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if x <= 1:
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angle = 2 * np.arctan(1 / x)
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label_x = np.cos(angle)
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label_y = np.sin(angle)
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ax.text(label_x, label_y + 0.05, f"+j{x}", fontsize=11, color=grid_color, ha="center", va="bottom")
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ax.text(label_x, -label_y - 0.05, f"-j{x}", fontsize=11, color=grid_color, ha="center", va="top")
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# Draw horizontal axis (real axis, x=0)
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ax.axhline(y=0, color=grid_color, linewidth=1, alpha=0.6)
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# Draw unit circle (boundary)
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unit_theta = np.linspace(0, 2 * np.pi, 500)
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ax.plot(np.cos(unit_theta), np.sin(unit_theta), color=circle_color, linewidth=2.5)
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# Draw center point (matched condition)
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ax.plot(0, 0, "o", color=circle_color, markersize=10, label="Matched (Z=Z₀)")
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# Plot impedance locus
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ax.plot(gamma.real, gamma.imag, color=data_color, linewidth=3, label="Impedance Locus", zorder=5)
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ax.scatter(gamma.real, gamma.imag, c=data_color, s=60, edgecolors="black", linewidths=0.5, zorder=6)
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# Add frequency labels at key points
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freq_label_indices = [0, 12, 24, 36, 49] # Start, middle points, end
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for idx in freq_label_indices:
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freq_ghz = frequency[idx] / 1e9
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x_pos = gamma.real[idx]
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y_pos = gamma.imag[idx]
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# Offset labels to avoid overlap with data points
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offset_x = 0.08 if x_pos < 0.5 else -0.08
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offset_y = 0.08 if y_pos >= 0 else -0.08
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ax.annotate(
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f"{freq_ghz:.1f} GHz",
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(x_pos, y_pos),
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xytext=(x_pos + offset_x, y_pos + offset_y),
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fontsize=14,
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fontweight="bold",
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color="black",
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arrowprops={"arrowstyle": "->", "color": "black", "lw": 1.5},
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zorder=10,
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)
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# Draw VSWR circles (optional - constant reflection coefficient magnitude)
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vswr_values = [1.5, 2, 3]
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vswr_angles = [np.pi / 4, np.pi / 3, 5 * np.pi / 12] # Different angles for each label
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for vswr, label_angle in zip(vswr_values, vswr_angles, strict=True):
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gamma_mag = (vswr - 1) / (vswr + 1)
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vswr_theta = np.linspace(0, 2 * np.pi, 200)
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ax.plot(
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gamma_mag * np.cos(vswr_theta),
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gamma_mag * np.sin(vswr_theta),
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"--",
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color="#CC4444",
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linewidth=1.5,
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alpha=0.7,
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label=f"VSWR={vswr}" if vswr == 1.5 else "",
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)
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# Label VSWR circles at different angles to avoid overlap
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label_x = gamma_mag * np.cos(label_angle)
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label_y = gamma_mag * np.sin(label_angle)
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ax.text(label_x, label_y + 0.06, f"VSWR={vswr}", fontsize=11, color="#CC4444", alpha=0.9, ha="center")
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# Styling
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ax.set_xlim(-1.25, 1.25)
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ax.set_ylim(-1.25, 1.25)
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ax.set_xlabel("Real(Γ)", fontsize=20)
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ax.set_ylabel("Imag(Γ)", fontsize=20)
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ax.set_title("smith-chart-basic · matplotlib · pyplots.ai", fontsize=24)
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ax.tick_params(axis="both", labelsize=16)
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ax.legend(fontsize=14, loc="upper left")
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# Remove axis ticks for cleaner Smith chart appearance
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ax.set_xticks([])
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ax.set_yticks([])
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# Add axis labels on chart edge
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ax.text(1.15, 0, "Open\n(Γ=1)", fontsize=12, ha="center", va="center", color=circle_color)
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ax.text(-1.15, 0, "Short\n(Γ=-1)", fontsize=12, ha="center", va="center", color=circle_color)
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ax.text(0, 1.15, "+jX\n(Inductive)", fontsize=12, ha="center", va="center", color=grid_color)
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ax.text(0, -1.15, "-jX\n(Capacitive)", fontsize=12, ha="center", va="center", color=grid_color)
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plt.tight_layout()
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plt.savefig("plot.png", dpi=300, bbox_inches="tight")

‎plots/smith-chart-basic/metadata/matplotlib.yaml‎

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library: matplotlib
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specification_id: smith-chart-basic
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created: '2026-01-15T21:52:42Z'
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updated: '2026-01-15T21:55:17Z'
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generated_by: claude-opus-4-5-20251101
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workflow_run: 21047488873
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issue: 3792
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python_version: 3.13.11
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library_version: 3.10.8
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preview_url: https://storage.googleapis.com/pyplots-images/plots/smith-chart-basic/matplotlib/plot.png
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preview_thumb: https://storage.googleapis.com/pyplots-images/plots/smith-chart-basic/matplotlib/plot_thumb.png
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preview_html: null
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quality_score: 91
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review:
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strengths:
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- Excellent implementation of a complex specialized chart type from scratch
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- All Smith chart grid elements (resistance circles, reactance arcs) are mathematically
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correct with proper clipping to unit circle
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- Comprehensive labeling including Open/Short/Inductive/Capacitive annotations at
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chart boundaries
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- Optional VSWR circles add engineering value beyond the basic spec requirements
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- Clean, well-organized code with clear comments explaining each section
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- Realistic antenna impedance data that creates a visually interesting spiral pattern
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weaknesses:
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- Grid alpha at 0.6 is slightly too prominent; 0.3-0.4 would provide subtler background
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- Does not leverage distinctive matplotlib features (uses only basic plot, scatter,
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text, annotate)
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image_description: The plot displays a Smith chart for RF/impedance visualization.
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The outer boundary is a solid blue circle representing |Γ|=1 (total reflection).
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Inside, gray constant resistance circles (labeled 0.2, 0.5, 1, 2, 5) are drawn
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centered along the horizontal axis, and constant reactance arcs curve from the
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right edge. The chart shows inductive (+jX) on the upper half and capacitive (-jX)
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on the lower half, with labels at the cardinal positions. A yellow impedance locus
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curve traces the antenna impedance sweep from 1.0 GHz to 6.0 GHz with circular
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markers at each frequency point. Key frequencies (1.0, 2.2, 3.4, 4.7, 6.0 GHz)
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are labeled with black arrows. Three red dashed VSWR circles (1.5, 2, 3) are drawn
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concentrically from the center. The matched condition (Z=Z₀) is marked at the
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center with a blue dot. Corner labels indicate "Open (Γ=1)", "Short (Γ=-1)", "+jX
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(Inductive)", and "-jX (Capacitive)". The legend in the upper left shows "Matched
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(Z=Z₀)", "Impedance Locus", and "VSWR=1.5".
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criteria_checklist:
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visual_quality:
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score: 37
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max: 40
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items:
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- id: VQ-01
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name: Text Legibility
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score: 10
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max: 10
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passed: true
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comment: Title at 24pt, axis labels at 20pt, frequency labels at 14pt bold,
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all perfectly readable at full size
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- id: VQ-02
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name: No Overlap
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score: 7
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max: 8
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passed: true
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comment: Minor overlap of some reactance arc labels with other elements, but
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main content readable
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- id: VQ-03
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name: Element Visibility
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score: 8
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max: 8
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passed: true
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comment: Yellow locus with s=60 markers and linewidth=3 is clearly visible
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against gray grid
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- id: VQ-04
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name: Color Accessibility
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score: 5
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max: 5
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passed: true
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comment: Blue/yellow/red/gray palette is colorblind-safe with good contrast
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- id: VQ-05
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name: Layout Balance
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score: 5
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max: 5
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passed: true
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comment: Square 12x12 figure fills canvas well with balanced margins
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- id: VQ-06
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name: Axis Labels
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score: 1
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max: 2
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passed: true
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comment: Real(Γ) and Imag(Γ) are descriptive but dimensionless quantities
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- id: VQ-07
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name: Grid & Legend
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score: 1
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max: 2
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passed: true
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comment: Grid at alpha=0.6 is slightly prominent; legend is well-placed
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spec_compliance:
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score: 25
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max: 25
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items:
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- id: SC-01
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name: Plot Type
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score: 8
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max: 8
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passed: true
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comment: Correct Smith chart with constant resistance circles and constant
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reactance arcs
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- id: SC-02
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name: Data Mapping
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score: 5
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max: 5
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passed: true
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comment: Complex impedance correctly converted to reflection coefficient Γ
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and plotted
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- id: SC-03
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name: Required Features
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score: 5
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max: 5
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passed: true
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comment: 'All spec features present: resistance circles, reactance arcs, impedance
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locus, frequency labels, VSWR circles'
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- id: SC-04
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name: Data Range
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score: 3
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max: 3
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passed: true
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comment: All data points visible within the unit circle boundary
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- id: SC-05
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name: Legend Accuracy
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score: 2
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max: 2
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passed: true
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comment: Legend correctly identifies matched condition, impedance locus, and
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VSWR reference
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- id: SC-06
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name: Title Format
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score: 2
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max: 2
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passed: true
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comment: 'Uses correct format: smith-chart-basic · matplotlib · pyplots.ai'
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data_quality:
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score: 19
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max: 20
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items:
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- id: DQ-01
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name: Feature Coverage
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score: 8
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max: 8
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passed: true
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comment: Shows spiral impedance locus typical of antenna measurements, both
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inductive and capacitive regions traversed
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- id: DQ-02
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name: Realistic Context
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score: 6
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max: 7
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passed: true
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comment: Antenna impedance sweep from 1-6 GHz is a plausible RF engineering
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scenario
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- id: DQ-03
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name: Appropriate Scale
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score: 5
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max: 5
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passed: true
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comment: Impedance values around 50Ω with ±30Ω variation is realistic for
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antenna measurements
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code_quality:
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score: 10
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max: 10
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items:
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- id: CQ-01
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name: KISS Structure
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score: 3
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max: 3
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passed: true
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comment: Follows imports → data → plot → save structure without functions/classes
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- id: CQ-02
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name: Reproducibility
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score: 3
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max: 3
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passed: true
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comment: Uses np.random.seed(42) for reproducible results
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- id: CQ-03
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name: Clean Imports
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score: 2
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max: 2
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passed: true
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comment: Only matplotlib.pyplot and numpy are imported, both are used
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- id: CQ-04
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name: No Deprecated API
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score: 1
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max: 1
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passed: true
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comment: No deprecated matplotlib API used
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- id: CQ-05
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name: Output Correct
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score: 1
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max: 1
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passed: true
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comment: Saves as plot.png with dpi=300 and bbox_inches=tight
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library_features:
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score: 0
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max: 5
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items:
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- id: LF-01
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name: Distinctive Features
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score: 0
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max: 5
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passed: false
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comment: Manually draws all Smith chart elements; does not showcase distinctive
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matplotlib features beyond basic plotting
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verdict: APPROVED
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impl_tags:
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dependencies: []
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techniques:
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- annotations
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- patches
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- manual-ticks
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patterns:
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- data-generation
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- iteration-over-groups
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dataprep: []
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styling:
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- alpha-blending
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- edge-highlighting

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