算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
visualization-reporting【设计与创意】Guide MNE-Python plotting, visualization backends, topomaps, source visualization routing, and Report creation for Researcher.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this sub-skill when the task is to make, save, debug, or package MNE-Python visual outputs after the data object already exists: Raw/Epochs/Evoked browsers, static Matplotlib figures, topomaps, source-visualization routing, optional 3D backend decisions, and mne.Report HTML/HDF5 reports.
Raw.plot(...), mne.viz.plot_raw(...), event/annotation coloring, channel grouping, bad-channel inspection, and non-interactive exports. See workflows and backend choices.Epochs.plot(...), Epochs.plot_image(...), Epochs.plot_drop_log(...), Epochs.plot_topo_image(...), and PSD/topomap summaries. See workflows.mne.viz.plot_topomap(data, info_or_pos, show=False) with channel positions, masking, interpolation, vlim/cnorm, and axes/colorbar handling. See topomap workflow and troubleshooting.source-modeling-inverse; return here only for plotting and export choices. See backend compatibility.mne.Report, add Raw/Epochs/Evoked/custom figures/images/HTML, parse folders when appropriate, and save with open_browser=False for automation. See report workflow and API reference.mne CLI help to cli-datasets-config; this sub-skill only covers Python mne.Report and the plotting/report APIs.preprocessing-epochs-evoked; this sub-skill assumes the object to visualize is ready or gives only visualization-safe validation.show=False in scripts, notebooks that must run unattended, tests, and reports; explicitly save and close Matplotlib figures.matplotlib.pyplot in headless automation.open_browser=False, and pass overwrite=True only when replacing that exact output is desired.python sub-skills/visualization-reporting/scripts/plotting_backend_probe.py --format text
python sub-skills/visualization-reporting/scripts/plotting_backend_probe.py --output mne-topomap.png --report-output mne-report.html
Run the script from any project where MNE-Python is importable. It does not require original repository files or datasets.
This sub-skill distills public API stubs, source signatures, visualization/report API pages, visualization tutorials/examples, visualization/report tests, dependency metadata, and an installed signature report. Provenance paths include mne/viz, mne/report, mne/viz/__init__.pyi, mne/report/__init__.pyi, doc/api/visualization.rst, doc/api/report.rst, tutorials/visualization, examples/visualization, mne/viz/tests, mne/report/tests, and pyproject.toml.