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HyPyP

imported

software/hypyp

The Hyperscanning Python Pipeline

Machine-generated from the listed sources and not yet reviewed by a human.

HyPyP project image
GitHub preview card for ppsp-team/HyPyP. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
BSD-3-Clause(osi)
Status
active
Maturity
deployed
Organization
ppsp-team
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
eeg · fnirs · hyperscanning · meg · neuroscience
Regulatory
unknown
built by · 6

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • processFNIRS2fnirs · hyperscanning · neuroscience

    Modular MATLAB toolbox for fNIRS analysis: import, preprocessing, hemoglobin conversion, QC, block/GLM modeling, group statistics (LME), connectivity & hyperscanning, and 3D visualization / diffuse…

  • analyse_OPMEGeeg · meg · neuroscience

    Nic & Rob's lair of scripts to analyse OPM data, using the Fieldtrip toolbox

  • AperiodicMethodseeg · meg · neuroscience

    Evaluating methods for estimating aperiodic activity in electrophysiological data.

  • electroCUDAeeg · meg · neuroscience

    Robust electrophysiology tools with GPU acceleration

  • fooofeeg · meg · neuroscience

    Parameterizing neural power spectra into periodic & aperiodic components.

  • hmpeeg · meg · neuroscience

    Repository for the hmp python package

sources
  1. api.github.com/repos/ppsp-team/HyPyP
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-07-28, 99 stars, license reported as BSD-3-Clause. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/31.json→ .entries["hypyp"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.