Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.
API method:
GET /api/packages?search=hello&page=1&limit=20
where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned
in response headers.
If you'd like to join our channel webring send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.
TE-dependent analysis (tedana) is a Python library for denoising multi-echo functional MRI data.
This package provides Python tools for working with the BIDS schema.
The fsleyes-widgets package contains a collection of GUI widgets and utilities, based on wxPython, which are used by fsleyes-props and FSLeyes.
NiReports contains the two main components of the visual reporting system of NiPreps: 1) reportlets, visualizations for assessing the quality of a particular processing step within the neuroimaging pipeline, and 2) assemblers, end-user write out reportlets to a predetermined folder.
This package provides a Pydantic schema for BIDS Stats Models.
The nipype1-workflows repository contains legacy workflows from Nipype 1.x, showcasing nearly a decade of development in neuroimaging data processing and analysis.
FSL is a comprehensive library of analysis tools for FMRI, MRI and diffusion brain imaging data. FSLeyes is a GUI for visualizing and editing brain images, from different sources and platforms.
This package provides the version schemes used for packaging software from the NiPreps organization.
NiFreeze is a flexible framework for volume-to-volume motion estimation and correction in d/fMRI and PET, and eddy-current-derived distortion estimation in dMRI.
niworkflows is capable of converting between formats and resampling images to apply transforms generated by the most popular neuroimaging packages and libraries (AFNI, FSL, FreeSurfer, ITK, and SPM).
SDCFlows (Susceptibility Distortion Correction workFlows) is a Python library of NiPype-based workflows to preprocess B0 mapping data, estimate the corresponding fieldmap and finally correct for susceptibility distortions. Susceptibility-derived distortions are typically displayed by images acquired with EPI MR schemes.
This module can be used to extract or replace keywords in sentences, based on the FlashText algorithm.
Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the NLP and IR communities.
This package provides a fast implementation of the Levenshtein distance with C++ and Cython.
This package provides tools for unsupervised and semi-supervised morphological segmentation.
PyRuSH is the python implementation of RuSH, which is originally developed using Java. RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy.
WORLD Vocoder is a fast and high-quality vocoder which parameterizes speech into three components:
f0: Pitch contoursp: Harmonic spectral envelopeap: Aperiodic spectral envelope
It can also (re)synthesize speech using these features.
seqeval is a Python framework for sequence labeling evaluation. seqeval can evaluate the performance of chunking tasks such as named-entity recognition, part-of-speech tagging, semantic role labeling and so on.
This package provides a Python implementation of IAMsystem algorithm, a fast dictionary-based approach for semantic annotation, a.k.a entity linking.
Modular, fast NLP framework, compatible with Pytorch and spaCy, offering tailored support for French clinical notes.
This package provides Python bindings for the simstring text similarity matching library.
Extremely fast spelling checker and suggester in Python.
The following algorithms are supported currently:
Edit-distance
Editex
Soundex
Caverphone 1.0 and 2.0
Typox
All the above algorithms use an underlying Trie-based dictionary for efficient storage and fast computation.
PyFastNER is the Python implementation of FastNER. It uses hash function to process multiple rules at the same time. Similar to FastNER, PyFastNER supports token-based rules and character-based rules.
Quicksectx is a simple, fast and no-dependency Python implementation of interval search, adapted from the bx-python project.