Skip to main content

Algorithms for Single Particle Reconstruction

Project description

Logo

Azure Build Status Github Actions Status Coverage Status

ASPIRE - Algorithms for Single Particle Reconstruction - v0.6.3

This is the Python version to supersede the 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 see the docs.

Installation Instructions

For end-users

ASPIRE is a pip-installable package that works on Linux/Mac/Windows, and requires Python 3.6. The simplest option is to use Anaconda 64-bit for your platform with a minimum of Python 3.6 and pip, and then use pip to install aspire in that environment.

conda create -n aspire_env python=3.6 pip
conda activate aspire_env
pip install aspire

The final step above should install any dependent packages from pip automatically. To see what packages are required, browse setup.py.

Note that this step installs the base aspire package for you to work with, but not the unit tests/documentation. If you need to install ASPIRE for development purposes, read on.

For developers

After cloning this repo, the simplest option is to use Anaconda 64-bit for your platform, and use the provided environment.yml file to build a Conda environment to run ASPIRE. This is very similar to above except you will be based off of your local checkout, and you are free to rename aspire_dev used in the commands below. The pip line will install aspire in a locally editable mode, and is equivalent to python setup.py develop:

cd /path/to/git/clone/folder

# Create's the conda environment and installs base dependencies.
conda env create -f environment.yml --name aspire_dev

# Enable the environment
conda activate aspire_dev

# Install the aspire package in a locally editable way:
pip install -e .

If you prefer not to use Anaconda, or want to manage environments yourself, you should be able to use pip with Python >= 3.6. Please see the full documentation for details.

You may optionally install additional packages:

# Additional GPU packages (reqires CUDA)
pip install -e ".[gpu]"
# Additional developer tools
pip install -e ".[dev]"

Make sure everything works

Once ASPIRE is installed, make sure the unit tests run correctly on your platform by doing:

cd /path/to/git/clone/folder
pytest

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aspire-0.6.3.tar.gz (142.5 kB view details)

Uploaded Source

File details

Details for the file aspire-0.6.3.tar.gz.

File metadata

  • Download URL: aspire-0.6.3.tar.gz
  • Upload date:
  • Size: 142.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/52.0.0.post20210125 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.8.8

File hashes

Hashes for aspire-0.6.3.tar.gz
Algorithm Hash digest
SHA256 f0f12c5262133a6dce0f44f4d5d7c0b48f50f83f117c1af2f75b64224b544cb0
MD5 8d2f5c13a6517ca066179f5a2ad6c185
BLAKE2b-256 5e886c3747a60df2f7cc635a85047676d8516b36b721cecd4ac2af5e747d37a9

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page