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feat(seaborn): implement skewt-logp-atmospheric (#3927)
## Implementation: `skewt-logp-atmospheric` - seaborn Implements the **seaborn** version of `skewt-logp-atmospheric`. **File:** `plots/skewt-logp-atmospheric/implementations/seaborn.py` **Parent Issue:** #3802 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/21092078646)* --------- 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/skewt-logp-atmospheric/implementations/seaborn.py‎

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""" pyplots.ai
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skewt-logp-atmospheric: Skew-T Log-P Atmospheric Diagram
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Library: seaborn 0.13.2 | Python 3.13.11
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Quality: 90/100 | Created: 2026-01-17
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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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import pandas as pd
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import seaborn as sns
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from matplotlib.ticker import ScalarFormatter
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# Set seaborn style with whitegrid for subtle grid lines, using talk context for better scaling
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sns.set_theme(style="whitegrid", context="talk", font_scale=1.1)
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sns.set_palette("colorblind")
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# Synthetic atmospheric sounding data (typical mid-latitude summer profile)
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np.random.seed(42)
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pressure = np.array([1000, 925, 850, 700, 500, 400, 300, 250, 200, 150, 100])
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temperature = np.array([25, 18, 12, 2, -20, -35, -50, -55, -58, -60, -55])
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dewpoint = np.array([18, 14, 8, -5, -30, -45, -60, -65, -68, -70, -65])
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# Create figure with custom transform for skew-T
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fig, ax = plt.subplots(figsize=(16, 9))
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# Set up the axes with log scale for pressure (inverted)
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ax.set_yscale("log")
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ax.set_ylim(1050, 100) # Inverted: surface at bottom
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ax.set_xlim(-50, 50)
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# Custom skew transform (45 degrees)
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skew_angle = 45
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skew_slope = np.tan(np.radians(skew_angle))
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# Draw isotherms (temperature lines, skewed)
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isotherm_temps = np.arange(-80, 60, 10)
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p_range = np.logspace(np.log10(100), np.log10(1050), 100)
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for t in isotherm_temps:
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x_iso = t + skew_slope * (np.log(1000 / p_range))
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ax.plot(x_iso, p_range, color="#cccccc", linewidth=0.8, alpha=0.7, zorder=1)
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# Draw isobars (horizontal pressure lines)
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isobar_levels = [1000, 925, 850, 700, 500, 400, 300, 250, 200, 150, 100]
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for p in isobar_levels:
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ax.axhline(y=p, color="#dddddd", linewidth=0.8, alpha=0.7, zorder=1)
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# Draw dry adiabats (potential temperature lines)
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theta_values = np.arange(250, 450, 20) # Potential temperatures in K
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for theta in theta_values:
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p_adiabat = np.logspace(np.log10(100), np.log10(1050), 100)
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# T = theta * (p/1000)^(R/cp), where R/cp ≈ 0.286
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t_adiabat = theta * (p_adiabat / 1000) ** 0.286 - 273.15
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x_adiabat = t_adiabat + skew_slope * (np.log(1000 / p_adiabat))
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ax.plot(x_adiabat, p_adiabat, color="#8B4513", linewidth=0.6, alpha=0.5, zorder=1)
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# Draw moist adiabats (saturated adiabats - simplified)
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theta_e_values = np.arange(270, 370, 20) # Equivalent potential temperatures
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for theta_e in theta_e_values:
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p_moist = np.logspace(np.log10(100), np.log10(1050), 100)
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# Simplified moist adiabat approximation
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t_moist = (theta_e - 30) * (p_moist / 1000) ** 0.3 - 273.15
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x_moist = t_moist + skew_slope * (np.log(1000 / p_moist))
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ax.plot(x_moist, p_moist, color="#228B22", linewidth=0.6, alpha=0.4, linestyle="--", zorder=1)
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# Draw mixing ratio lines (constant water vapor mixing ratio)
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mixing_ratios = [1, 2, 4, 7, 10, 15, 20] # g/kg
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for w in mixing_ratios:
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p_mix = np.logspace(np.log10(400), np.log10(1050), 50)
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# Simplified mixing ratio to dewpoint: Td ≈ 35 * log10(w) - 15 + adjustment for pressure
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t_mix = 35 * np.log10(w) - 20 + 5 * np.log10(p_mix / 1000)
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x_mix = t_mix + skew_slope * (np.log(1000 / p_mix))
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ax.plot(x_mix, p_mix, color="#4169E1", linewidth=0.5, alpha=0.4, linestyle=":", zorder=1)
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# Apply skew transform to data for seaborn plotting
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x_temp = temperature + skew_slope * np.log(1000 / pressure)
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x_dew = dewpoint + skew_slope * np.log(1000 / pressure)
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# Create DataFrame for seaborn plotting
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df = pd.DataFrame(
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{
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"x": np.concatenate([x_temp, x_dew]),
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"pressure": np.concatenate([pressure, pressure]),
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"profile": ["Temperature"] * len(pressure) + ["Dewpoint"] * len(pressure),
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}
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)
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# Plot profiles using seaborn lineplot
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sns.lineplot(
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data=df,
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x="x",
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y="pressure",
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hue="profile",
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style="profile",
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markers={"Temperature": "o", "Dewpoint": "s"},
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dashes={"Temperature": "", "Dewpoint": (5, 2)},
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palette={"Temperature": "#E74C3C", "Dewpoint": "#306998"},
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linewidth=4,
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markersize=10,
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ax=ax,
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zorder=5,
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legend=True,
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)
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# Configure pressure axis - remove overlapping ticks (925 removed to avoid overlap with 1000)
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ax.yaxis.set_major_formatter(ScalarFormatter())
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display_ticks = [1000, 850, 700, 500, 400, 300, 250, 200, 150, 100]
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ax.set_yticks(display_ticks)
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ax.set_yticklabels([str(p) for p in display_ticks])
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# Labels and title with proper middle dot separator
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ax.set_xlabel("Temperature (°C)", fontsize=20)
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ax.set_ylabel("Pressure (hPa)", fontsize=20)
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ax.set_title("skewt-logp-atmospheric · seaborn · pyplots.ai", fontsize=24)
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ax.tick_params(axis="both", labelsize=16)
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# Use seaborn's despine to clean up the appearance (keep left and bottom spines only)
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sns.despine(ax=ax, top=True, right=True)
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# Configure legend from seaborn lineplot
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legend = ax.get_legend()
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legend.set_title("")
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for text in legend.get_texts():
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text.set_fontsize(16)
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legend.get_frame().set_alpha(0.9)
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# Add reference line labels with better positioning and improved visibility
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ax.text(45, 600, "Isotherms", fontsize=14, color="#555555", rotation=45, ha="center", fontweight="bold")
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ax.text(-25, 108, "Dry Adiabats", fontsize=13, color="#6B3510", ha="center", fontweight="bold")
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ax.text(0, 108, "Moist Adiabats", fontsize=13, color="#1A6B1A", ha="center", fontweight="bold")
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ax.text(22, 108, "Mixing Ratio", fontsize=13, color="#2E4A8B", ha="center", fontweight="bold")
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# Add subtle background and configure grid styling
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ax.set_facecolor("#fafafa")
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ax.grid(True, which="major", alpha=0.3, linestyle="-", linewidth=0.5, color="#888888")
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plt.tight_layout()
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plt.savefig("plot.png", dpi=300, bbox_inches="tight")

‎plots/skewt-logp-atmospheric/metadata/seaborn.yaml‎

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library: seaborn
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specification_id: skewt-logp-atmospheric
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created: '2026-01-17T09:26:00Z'
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updated: '2026-01-18T22:40:57Z'
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generated_by: claude-opus-4-5-20251101
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workflow_run: 21092078646
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issue: 3802
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python_version: 3.13.11
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library_version: 0.13.2
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preview_url: https://storage.googleapis.com/pyplots-images/plots/skewt-logp-atmospheric/seaborn/plot.png
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preview_thumb: https://storage.googleapis.com/pyplots-images/plots/skewt-logp-atmospheric/seaborn/plot_thumb.png
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preview_html: null
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quality_score: 90
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review:
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strengths:
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- Excellent implementation of the skew-T transform with proper 45-degree isotherms
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- Clean separation of temperature and dewpoint profiles with appropriate styling
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- Proper logarithmic/inverted pressure axis matching meteorological convention
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- Good use of seaborn theming (whitegrid, talk context) and despine function
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- All major reference lines present (isotherms, dry adiabats, moist adiabats, mixing
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ratio)
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- Professional label annotations for reference line types
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weaknesses:
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- Reference lines could have a dedicated legend entry for better interpretation
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- Minor reliance on matplotlib for the specialized atmospheric reference lines rather
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than seaborn-specific visualization methods
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image_description: The plot displays a Skew-T Log-P atmospheric diagram with a light
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gray (#fafafa) background. The pressure axis (y-axis) is logarithmic and inverted,
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ranging from 1000 hPa at the bottom to 100 hPa at the top, with labeled tick marks
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at 1000, 850, 700, 500, 400, 300, 250, 200, 150, and 100 hPa. The temperature
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axis (x-axis) spans from -50°C to 50°C. The temperature profile is shown as a
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solid red line with circular markers, while the dewpoint profile is displayed
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as a dashed blue line with square markers. Both lines decrease with altitude,
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with dewpoint consistently lower than temperature. Gray diagonal isotherms at
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45° skew angle cross the plot. Brown diagonal lines represent dry adiabats, green
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dashed lines show moist adiabats, and blue dotted lines indicate mixing ratio
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lines. Reference labels for "Dry Adiabats", "Moist Adiabats", and "Mixing Ratio"
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appear at the top, with "Isotherms" labeled on the right side. The title uses
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the correct format with middle dots. A legend in the upper right distinguishes
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Temperature and Dewpoint profiles.
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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, ticks at 16pt, all clearly readable
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- id: VQ-02
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name: No Overlap
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score: 8
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max: 8
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passed: true
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comment: No overlapping text elements; tick label at 925 hPa removed to prevent
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overlap
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- id: VQ-03
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name: Element Visibility
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score: 7
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max: 8
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passed: true
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comment: Markers and lines are visible with good sizing; reference lines slightly
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subtle
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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: Red/blue colorblind-safe palette, good contrast between profiles
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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: Plot fills canvas well, balanced margins, legend well-positioned
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- id: VQ-06
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name: Axis Labels
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score: 2
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max: 2
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passed: true
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comment: 'Descriptive with units: Temperature (°C) and Pressure (hPa)'
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- id: VQ-07
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name: Grid & Legend
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score: 0
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max: 2
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passed: false
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comment: Grid is subtle but legend frame slightly obscures corner of plot
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area
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spec_compliance:
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score: 23
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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 Skew-T Log-P diagram type
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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: Pressure on y-axis (log/inverted), temperature with skew transform
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on x-axis
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- id: SC-03
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name: Required Features
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score: 4
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max: 5
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passed: true
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comment: Has isotherms, dry adiabats, moist adiabats, mixing ratio lines;
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wind barbs optional and not included
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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: Full range from surface to upper atmosphere displayed
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- id: SC-05
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name: Legend Accuracy
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score: 1
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max: 2
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passed: false
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comment: Legend shows profiles but reference line types not in legend
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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: 'Correct format: skewt-logp-atmospheric · seaborn · pyplots.ai'
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data_quality:
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score: 18
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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: 7
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max: 8
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passed: true
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comment: Shows typical mid-latitude summer sounding with decreasing temperature
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and dewpoint; temperature inversion near tropopause visible
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- id: DQ-02
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name: Realistic Context
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score: 7
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max: 7
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passed: true
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comment: Realistic atmospheric profile with sensible meteorological data
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- id: DQ-03
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name: Appropriate Scale
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score: 4
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max: 5
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passed: true
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comment: Realistic values; surface temp 25°C and dewpoint 18°C appropriate;
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upper atmosphere temps realistic
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code_quality:
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score: 9
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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: 'Simple linear structure: imports → data → plot → save'
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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 reproducibility
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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: All imports 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: Uses current seaborn and matplotlib APIs
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- id: CQ-05
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name: Output Correct
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score: 0
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max: 1
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passed: false
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comment: Saves as plot.png but header says 0.13.2 while current seaborn may
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differ
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library_features:
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score: 3
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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: 3
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max: 5
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passed: true
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comment: Uses sns.lineplot, sns.set_theme, sns.despine, and colorblind palette,
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but heavy reliance on matplotlib for the specialized thermodynamic lines
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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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- 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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- grid-styling

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