shboost-cmd-plot-and-animation

Cache selected columns from the ShBoost 2024 S3 dataset, create a hexbin CMD with log-scaled density, add optimized non‑overlapping stellar‑population annotations, and generate both a high‑resolution PNG and an MP4 animation.

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Repositório: arm2arm/AstroAgentAssistant
Última atividade na origem: 9 de julho de 2026 às 16:58
Idioma detectado do SKILL.md: inglês
Estrelas: 4
Forks: 1

Opções de instalação

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npx skills add https://github.com/arm2arm/AstroAgentAssistant --skill shboost-cmd-plot-and-animation

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SKILL.md

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name	shboost_cmd_plot_and_animation
title	ShBoost CMD Plot and Population Animation
description	Cache selected columns from the ShBoost 2024 S3 dataset, create a hexbin CMD with log-scaled density, add optimized non‑overlapping stellar‑population annotations, and generate both a high‑resolution PNG and an MP4 animation.
author	hermes

When to Use

Canonical Routing

This is a specialized or legacy example skill. For new work, start with astro-data-access-umbrella and route through:

s3-parquet-astro-access
astro-catalog-plotting-cache

Keep this skill for dataset-specific examples, but prefer the canonical skills for new implementations, live probes, REANA execution, and plotting/cache conventions.

Pitfalls

Do not hardcode credentials, tokens, or personal secrets.
Verify external service URLs, paths, and permissions before making changes.
Keep generated outputs reproducible and record input assumptions.

Verification

Confirm required inputs and credentials are available.
Run the smallest safe command or example before scaling up.
Check produced files, API responses, or plots before reporting success.

def plot_cmd(df: pd.DataFrame, png_path: str = "shboost_cmd.png"): sns.set_style("whitegrid") plt.rcParams.update({ "font.size": 12, "axes.titlesize": 14, "axes.labelsize": 13, "legend.fontsize": 11, "figure.figsize": (8, 6), "savefig.dpi": 300, "savefig.bbox": "tight", }) mesh = plt.hexbin(df["bprp0"], df["mg0"], gridsize=512, cmap="viridis", mincnt=1, linewidths=0.2, norm=LogNorm()) cb = plt.colorbar(mesh, label="Counts") cb.ax.set_ylabel("Counts", rotation=270, labelpad=15) cb.ax.set_yscale('log') # Colour map for population labels color_map = { "Main Sequence": "tab:blue", "Turn‑off / Subgiants": "tab:orange", "Red Giant Branch": "tab:red", "Red Clump": "tab:purple", "Horizontal Branch": "tab:brown", "AGB": "tab:pink", "White Dwarfs": "tab:gray", "Blue Stragglers": "tab:green", } def add_label(txt, xy, offset=(20,20)): plt.annotate(txt, xy=xy, xytext=offset, textcoords='offset points', fontsize=9, color=color_map.get(txt, 'white'), ha='center', va='center', bbox=dict(boxstyle='round,pad=0.2', fc='black', alpha=0.6), arrowprops=dict(arrowstyle='->', color='black', lw=0.8)) # Optimised placements (adjust if you change PLOT_ROWS) add_label('Main Sequence', xy=(1.5, 8), offset=(-60, -20)) add_label('Turn‑off / Subgiants', xy=(0.8, 4), offset=(-60, -20)) add_label('Red Giant Branch', xy=(1.9, 0), offset=(60, 40)) add_label('Red Clump', xy=(1.2, 0.8), offset=(60, -40)) add_label('Horizontal Branch', xy=(0.4, -1), offset=(-60, 30)) add_label('AGB', xy=(2.3, -0.5), offset=(60, 30)) add_label('White Dwarfs', xy=(-0.25, 13), offset=(-80, -30)) add_label('Blue Stragglers', xy=(-0.2, 7), offset=(-80, 30)) # Legend matching annotation colours from matplotlib.lines import Line2D pop_legend = [Line2D([0],[0],marker='o',color='w',label=name, markerfacecolor=color_map[name],markersize=8) for name in color_map] plt.legend(handles=pop_legend, loc='upper right', fontsize=8, framealpha=0.7, title='Populations') plt.title(f"ShBoost 2024 Colour‑Magnitude Diagram ({len(df):,} stars)") plt.xlabel("bprp0") plt.ylabel("mg0") plt.xlim(-4, 8) plt.gca().invert_yaxis() plt.tight_layout() plt.savefig(png_path, dpi=300) plt.close() print(f"✅ Saved PNG -> {png_path}")

def create_animation(df, png_path="shboost_cmd.png"): import matplotlib.animation as animation from matplotlib.colors import LogNorm fig, ax = plt.subplots() sns.set_style("whitegrid") plt.rcParams.update({"font.size": 12, "axes.titlesize": 14, "axes.labelsize": 13, "legend.fontsize": 11, "figure.figsize": (8, 6), "savefig.dpi": 300, "savefig.bbox": "tight"}) mesh = ax.hexbin(df["bprp0"], df["mg0"], gridsize=512, cmap="viridis", mincnt=1, linewidths=0.2, norm=LogNorm()) cb = fig.colorbar(mesh, label="Counts") cb.ax.set_ylabel("Counts", rotation=270, labelpad=15) cb.ax.set_yscale('log') ax.set_xlabel("bprp0") ax.set_ylabel("mg0") ax.set_xlim(-4, 8) ax.invert_yaxis() ax.set_title(f"ShBoost 2024 Colour‑Magnitude Diagram ({len(df):,} stars)") populations = [ ("Main Sequence", (1.5, 8)), ("Turn‑off / Subgiants", (0.8, 4)), ("Red Giant Branch", (1.9, 0)), ("Red Clump", (1.2, 0.8)), ("Horizontal Branch", (0.4, -1)), ("AGB", (2.3, -0.5)), ("White Dwarfs", (-0.25, 13)), ("Blue Stragglers", (-0.2, 7)), ] color_map = {name: col for name, col in zip([p[0] for p in populations], ["tab:blue","tab:orange","tab:red","tab:purple","tab:brown", "tab:pink","tab:gray","tab:green"])} from matplotlib.lines import Line2D pop_legend = [Line2D([0],[0],marker='o',color='w',label=name, markerfacecolor=color_map[name],markersize=8) for name in color_map] ax.legend(handles=pop_legend, loc='upper right', fontsize=8, framealpha=0.7, title='Populations') annotation = ax.annotate('', xy=(0,0), xytext=(0,0), textcoords='offset points', bbox=dict(boxstyle='round,pad=0.3', fc='black', alpha=0.6), arrowprops=dict(arrowstyle='->', color='red', lw=1)) def init(): annotation.set_visible(False) return (annotation,) def update(frame): name, xy = populations[frame] annotation.set_visible(True) annotation.set_text(name) annotation.xy = xy annotation.set_position((30, -30)) annotation.set_fontsize(12) annotation.set_color(color_map.get(name, 'white')) return (annotation,) anim = animation.FuncAnimation(fig, update, frames=len(populations), init_func=init, interval=2000, blit=False, repeat=True, save_count=len(populations)) out_path = os.path.join(os.path.dirname(png_path), 'shboost_population_animation.mp4') try: from matplotlib.animation import FFMpegWriter writer = FFMpegWriter(fps=0.5) anim.save(out_path, writer=writer) except Exception: out_path = os.path.join(os.path.dirname(png_path), 'shboost_population_animation.gif') from matplotlib.animation import PillowWriter anim.save(out_path, writer=PillowWriter(fps=0.5)) plt.close(fig) print(f"✅ Saved animation -> {out_path}")

shboost-cmd-plot-and-animation

Opções de instalação

Revise os arquivos de origem

When to Use

Canonical Routing

Pitfalls

Verification

When to Use

Canonical Routing

Pitfalls

Verification

Overview

Prerequisites

Constants (adjust as needed)

1. Load or Create Cache

2. Static CMD Plot (`plot_cmd`)

3. Animation (`create_animation`)

4. Execution

Tips & Gotchas

shboost-cmd-plot-and-animation

Informações da origem

Opções de instalação

Revise os arquivos de origem

Mais deste repositório

Mais deste repositório

When to Use

Canonical Routing

Pitfalls

Verification

When to Use

Canonical Routing

Pitfalls

Verification

Overview

Prerequisites

Constants (adjust as needed)

1. Load or Create Cache

2. Static CMD Plot (plot_cmd)

3. Animation (create_animation)

4. Execution

Tips & Gotchas

2. Static CMD Plot (`plot_cmd`)

3. Animation (`create_animation`)