Develop and check research code in MATLAB/Octave or Python for signal processing, image analysis, statistics, and simulations. This skill supports reproducible workflows, checks units and assumptions, and prepares figures for papers and presentations.
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Research computing toolkit for optoelectronic information science and engineering, MATLAB/Octave, Python scientific analysis, signal processing, image processing, statistics, simulation, optimization, publication figures, sensor/time-series data, citation lookup, and common scientific libraries. Use when the user asks for MATLAB code, scientific Python, data analysis, plots, simulations, formulas, statistics, machine learning, optical/physical/materials computation, or reproducible research workflows.
安装前可以查看交给 AI 代理的指令内容。
Use this skill for科研计算 and software-assisted research:
Use research-writing-skill for manuscript prose. Use office-academic-skill for Word/PPT deliverables.
The user's field is光电信息科学与工程. Prefer examples and checks relevant to:
Do not fabricate physical parameters, material constants, software menu operations, experimental results, or paper conclusions. When uncertain, ask for the source file or mark the assumption.
rng for stochastic simulations when reproducibility matters..png and vector .svg when feasible.For MATLAB/Octave details, use references/scientific-skills/matlab/SKILL.md.
Load only the relevant bundled reference:
matplotlib, seaborn, scientific-visualization.statistical-analysis, statsmodels, timesfm-forecasting.scikit-learn.sympy.exploratory-data-analysis.pymoo.simpy.qutip.pymatgen.networkx.astropy.xlsx, pdf.paper-lookup, citation-management, literature-review.Some bundled references mention optional installs such as uv pip install ... or optional API keys for higher rate limits. Do not install packages, use cloud APIs, or send user data to external services unless the current task requires it and the user agrees.
For code:
For research analysis:
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Process astronomical data in Python with Astropy. This skill covers celestial coordinate, unit, and time conversions; reading and editing FITS astronomy files; matching object catalogs; and calculating cosmic distances using cosmological models.
中文简介正在准备中。当前显示英语简介。
Find academic papers through Google Scholar and PubMed, retrieve publication details from identifiers, and build BibTeX reference files. Check author and publication information, detect duplicates, and standardize formatting before using references in a manuscript.
中文简介正在准备中。当前显示英语简介。
Inspect scientific data files to understand their format, structure, and quality. Covering over 200 formats, this skill produces Markdown reports with statistical summaries, potential issues, and recommendations for preprocessing, visualization, and further analysis.
中文简介正在准备中。当前显示英语简介。
Search multiple academic databases, screen studies against documented criteria, and compare findings by theme. Produce literature reviews in Markdown and PDF with study quality assessments, verified citation details, and diagrams explaining the review process or findings.
中文简介正在准备中。当前显示英语简介。
Write MATLAB or GNU Octave scripts for matrix calculations, data analysis, signal processing, and scientific plots. The skill also helps explain syntax and functions, convert code between MATLAB and Python, and run scripts when an interpreter is installed.
中文简介正在准备中。当前显示英语简介。
Create charts in Python with detailed control over colors, axes, labels, legends, and layouts. Use it to build scientific figures, arrange multiple plots, and export results as PNG, PDF, or SVG files for papers and presentations.
中文简介正在准备中。当前显示英语简介。