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方向榜单 Legacy
| 图表与可视化 | 78 | Jaxon1216/MathModelHub · DRZ-hang/StatMate · yss-off/research-figure-kit |
01
Jaxon1216/MathModelHub
美赛/ICM综合准备资源库。包含可复用的数学建模Python代码、LaTeX/Word模板、数据分析笔记本和历年赛题组织。旨在优化竞赛流程,促进可复现研究。A comprehensive toolkit for MCM/ICM preparation. Features reusable Python code for mathematical modeling, LaTeX/Word templates, data analysis notebooks, and organized past problems. Aimed at streamlining the contest workflow and fostering reproducible research.
+4/周
19 ★
02
DRZ-hang/StatMate
以证据为先的 agent skill,基于真实研究数据生成可审计的统计分析、诊断、发表级图表、表格与教学报告。Evidence-first agent skill for auditable statistical analysis, diagnostics, publication figures, tables, and teaching reports from real research data.
4 ★
03
yss-off/research-figure-kit
可编辑、可验证、可复现的研究图表——面向 Draw.io 与科学可视化的 Codex 插件。Editable, verifiable, reproducible research figures — a Codex plugin for Draw.io and scientific visualization.
+4/周
1 ★
04
UCSB-Library-Research-Data-Services/SOAR2
夏季开放与可复现研究(SOAR²)训练营的项目官网。Program Website for the Summer Open And Reproducible Research (SOAR²) Camp
0 ★
05
outrotim/ideal-to-real-publication-figure
Codex skill:将已批准的科研图表蓝图转化为可溯源、使用真实数据的发表级图表。Codex skill for turning approved scientific figure blueprints into traceable real-data publication figures
0 ★
06
Mubashir-zz/glioma-nco-registry-study
289 项随机胶质母细胞瘤/HGG 临床试验中的客观神经认知终点。可复现的 R pipeline、Firth 惩罚回归、发表级图表与稿件。Objective neurocognitive endpoints in 289 randomized glioblastoma/HGG trials. Reproducible R pipeline, Firth penalized regression, publication figures and manuscript.
0 ★
07
Drz-debug/Drz-debug
统计学学生,专注于可复现研究与数据项目。Statistics student focused on reproducible research and data projects.
0 ★
08
docxology/DuckRabbit
Python 包,作为可复现的科学刺激生成视觉、听觉和视听错觉 —— 17 个已编目错觉导出为 PNG、WAV、GIF、MP4 和 NPZ,附带 SHA-256 清单与确定性随机种子,含 15 个附带源数据边车的发表级图表,测试覆盖率 90% 以上Python package that generates optical, auditory and audio-visual illusions as reproducible scientific stimuli — 17 catalogued illusions exported to PNG, WAV, GIF, MP4 and NPZ with SHA-256 manifests, deterministic seeds, 15 publication figures with source-data sidecars, and 90%+ test coverage.
0 ★
09
Abdulrahman-Albeladi/research-toolkit
可复用的 Python 与 notebook 工作流,用于多语言科研数据准备、统计分析及 AI 文本检测器评估。Reusable Python and notebook workflows for multilingual research-data preparation, statistical analysis, and AI-text detector evaluation.
0 ★