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aspire

Algorithms for Single Particle Reconstruction

https://github.com/computationalcryoem/aspire-python

Science Score: 59.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 5 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ✓
    Committers with academic emails
    9 of 25 committers (36.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (18.9%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Algorithms for Single Particle Reconstruction

Basic Info
  • Host: GitHub
  • Owner: ComputationalCryoEM
  • License: gpl-3.0
  • Language: Python
  • Default Branch: main
  • Homepage: http://spr.math.princeton.edu
  • Size: 245 MB
Statistics
  • Stars: 56
  • Watchers: 6
  • Forks: 25
  • Open Issues: 114
  • Releases: 22
Created almost 7 years ago · Last pushed 6 months ago
Metadata Files
Readme Contributing License Code of conduct Codeowners Zenodo

README.md

Logo

Github Actions Status codecov DOI Downloads

ASPIRE - Algorithms for Single Particle Reconstruction - v0.14.0

The ASPIRE-Python project supersedes Matlab ASPIRE.

ASPIRE is an open-source software package for processing single-particle cryo-EM data to determine three-dimensional structures of biological macromolecules. The package includes advanced algorithms based on rigorous mathematics and recent developments in statistics and machine learning. It provides unique and improved solutions to important computational challenges of the cryo-EM processing pipeline, including 3-D ab-initio modeling, 2-D class averaging, automatic particle picking, and 3-D heterogeneity analysis.

For more information about the project, algorithms, and related publications please refer to the ASPIRE Project website.

For full documentation and tutorials see the docs.

Please cite using the following DOI. This DOI represents all versions, and will always resolve to the latest one.

``` ComputationalCryoEM/ASPIRE-Python: v0.14.0 https://doi.org/10.5281/zenodo.5657281

```

Installation Instructions

Getting Started - Installation

ASPIRE is a pip-installable package for Linux/Mac/Windows, and requires Python 3.9-3.12. The recommended method of installation for getting started is to use Anaconda (64-bit) for your platform to install Python. Python's package manager pip can then be used to install aspire safely in that environment.

If you are unfamiliar with conda, the Miniconda distribution for x86_64 is recommended.

Assuming you have conda and a compatible system, the following steps will checkout current code release, create an environment, and install ASPIRE.

```

Clone the code

git clone https://github.com/ComputationalCryoEM/ASPIRE-Python.git cd ASPIRE-Python

Create a fresh environment

conda create --name aspire python=3.9 pip

Enable the environment

conda activate aspire

Install the aspire package from the checked out code

with the additional dev extension.

pip install -e ".[dev]" ```

If you prefer not to use Anaconda, or have other preferences for managing environments, you should be able to directly use pip with Python >= 3.9 from the local checkout or via PyPI. Please see the full documentation for details and advanced instructions.

Installation Testing

To check the installation, a unit test suite is provided, taking approximate 15 minutes on an average machine.

pytest

Owner

  • Name: ComputationalCryoEM
  • Login: ComputationalCryoEM
  • Kind: organization

Computational CryoEM projects related to ASPIRE

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 2,498
  • Total Committers: 25
  • Avg Commits per committer: 99.92
  • Development Distribution Score (DDS): 0.613
Top Committers
Name Email Commits
Garrett Wright g****g@g****m 967
Josh Carmichael c****l@p****u 460
Junchao Xia j****a@h****m 435
rbrook c****k@g****m 158
Chris Langfield c****d@g****m 114
Vineet Bansal v****l@g****m 80
Garrett Wright g****t@p****u 49
Joakim Andén j****n@k****e 48
Gabi g****r@g****m 44
Chris Langfield 3****d@u****m 39
ayeltg a****g@u****m 17
Joakim Andén j****n@f****g 12
itaysason i****n@m****m 12
Christopher Langfield c****2@t****u 11
Vineet Bansal v****l@p****m 10
itaysason i****n@m****l 8
Amit Moscovich m****h@g****m 6
Junchao Xia j****a@p****u 6
Amit Singer a****r@u****m 6
Yoel y****h@p****l 6
Garrett Wright 4****g@u****m 4
Josh Carmichael 6****c@u****m 3
rbrook r****k@u****m 1
Yoel Shkolnisky y****u@e****m 1
Yunpeng Shi y****s@p****u 1
Committer Domains (Top 20 + Academic)
princeton.edu: 4 post.tau.ac.il: 1 mail.tau.ac.il: 1 tigercpu.princeton.edu: 1 mail.com: 1 flatironinstitute.org: 1 kth.se: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 192
  • Total pull requests: 238
  • Average time to close issues: 7 months
  • Average time to close pull requests: 16 days
  • Total issue authors: 16
  • Total pull request authors: 9
  • Average comments per issue: 2.5
  • Average comments per pull request: 2.41
  • Merged pull requests: 201
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 34
  • Pull requests: 47
  • Average time to close issues: 14 days
  • Average time to close pull requests: 11 days
  • Issue authors: 4
  • Pull request authors: 4
  • Average comments per issue: 0.91
  • Average comments per pull request: 1.91
  • Merged pull requests: 28
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • garrettwrong (110)
  • j-c-c (43)
  • janden (10)
  • junchaoxia (6)
  • krissowat (5)
  • chris-langfield (5)
  • mosco (2)
  • zxt-triumph (2)
  • ThinkJanice (2)
  • Grigori200 (1)
  • remy-aber (1)
  • 09pouchol (1)
  • remy-abergel (1)
  • helenahu39 (1)
  • ghost (1)
Pull Request Authors
  • garrettwrong (202)
  • j-c-c (99)
  • certifiedp (8)
  • vineetbansal (5)
  • krissowat (3)
  • chris-langfield (2)
  • janden (2)
  • mosco (2)
  • itamero (1)
Top Labels
Issue Labels
cleanup (83) enhancement (68) bug (49) CI (36) good first issue (22) support (21) extern (18) documentation (17) Optimization (13) dependencies (10) GPU (4) wontfix (4) theory (3) question (3) help wanted (2) duplicate (1) invalid (1)
Pull Request Labels
cleanup (148) bug (102) enhancement (83) CI (79) extern (49) documentation (45) dependencies (37) good first issue (18) GPU (18) Optimization (17) support (6) invalid (2) help wanted (2) Python 3.11 (1) theory (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 249 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 24
  • Total maintainers: 3
pypi.org: aspire

Algorithms for Single Particle Reconstruction

  • Versions: 24
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 249 Last month
Rankings
Dependent packages count: 7.4%
Forks count: 8.6%
Stargazers count: 10.4%
Average: 12.8%
Downloads: 15.3%
Dependent repos count: 22.2%
Maintainers (3)
garrettwrong janden jcarmichael
Last synced: 7 months ago

Dependencies

.github/workflows/long_workflow.yml actions
  • actions/checkout v3 composite
.github/workflows/workflow.yml actions
  • actions/cache v3 composite
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • actions/upload-artifact v3 composite
  • codecov/codecov-action v3 composite
  • conda-incubator/setup-miniconda v2 composite
pyproject.toml pypi
  • PyWavelets *
  • click *
  • confuse >= 2.0.0
  • finufft *
  • gemmi >= 0.4.8
  • grpcio >= 1.54.2
  • joblib *
  • matplotlib >= 3.2.0
  • mrcfile *
  • numpy >=1.21.5
  • packaging *
  • pillow *
  • pooch >=1.7.0
  • psutil *
  • pyfftw *
  • pymanopt *
  • ray *
  • scikit-image *
  • scikit-learn *
  • scipy >= 1.10.0
  • setuptools >= 0.41
  • tqdm *