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io-raw-data

io-raw-data

Read, create, inspect, annotate, concatenate, save, and export MNE-Python Raw/Info data containers.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: io-raw-data description: "Read, create, inspect, annotate, concatenate, save, and export MNE-Python Raw/Info data containers." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

IO and Raw Data

Use this sub-skill when the task starts from neurophysiology files or NumPy arrays and needs an MNE-Python Raw/BaseRaw object, Info metadata, channel picks/types, raw-level annotations, concatenation, preloading, FIF save, or external export.

Route by task

  • Read a file: choose mne.io.read_raw() for simple suffix-based dispatch, or a format-specific read_raw_* function when the format has sidecars, ambiguous suffixes, optional keyword choices, or better error messages. See file-formats and reader workflow.
  • Create synthetic data: use mne.create_info() plus mne.io.RawArray(data, info) with data shaped (n_channels, n_times) and MNE SI units. See RawArray workflow and the bundled helper create_synthetic_raw.py.
  • Inspect or subset a Raw object: use raw.info, raw.ch_names, raw.n_times, raw.times, raw.get_data(), raw.pick(), raw.drop_channels(), raw.reorder_channels(), raw.rename_channels(), and raw.set_channel_types(). See API reference.
  • Manage memory: default readers keep data on disk; use preload=True, preload="path.dat", or raw.load_data(memmap="path.dat") only when operations require writable in-memory data. Crop and pick before preloading when possible. See preload workflow.
  • Annotate raw spans: create mne.Annotations, call raw.set_annotations(), and remember that descriptions beginning with BAD are respected by many later processing functions. See annotations workflow.
  • Concatenate or save/export: use mne.io.concatenate_raws() or raw.append() only for compatible recordings; save MNE-native work with raw.save(...raw.fif), and use raw.export() for BrainVision, EDF, or EEGLAB only when optional exporters are installed. See save/export workflow.

Boundaries

Route these tasks elsewhere in the MNE-Python skill graph:

  • Events, Epochs, Evoked, filtering, artifact rejection, ICA/SSP, and cleaning decisions → preprocessing-epochs-evoked.
  • Raw plotting, browser backends, topomaps, figures, and reports → visualization-reporting.
  • Source estimates, BEM, forward/inverse, morphing, and labels → source-modeling-inverse.
  • CLI commands, dataset download/cache helpers, configuration, logging, and sys_info → cli-datasets-config.

Operating rules

  • Prefer verified public APIs in API reference; do not instantiate BaseRaw directly except for type checks.
  • Treat Raw methods as mostly in-place. Use raw.copy() before experimental channel picking, cropping, type changes, annotation replacement, concatenation, or filtering.
  • Do not make generated guidance depend on original repository files, examples, tests, or local environments. Source evidence was distilled into this subtree; use bundled references and scripts only at runtime.
  • For reader failures, first identify the file family, sidecars, optional dependencies, preload choice, units, channel names/types, and whether generic dispatch masked a more specific reader error. See troubleshooting.
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