Skip to main content

Package to analyze biological data.

Project description

Installation

  1. Install Anaconda

    Our recommended approach is to use Anaconda, which is a distribution of Python containing most of the numeric and scientific software needed to get started. If you are a Mac or Linux user, have used Python before and are comfortable using pip to install software, you may want to skip this step and use your existing Python installation.

    Anaconda has a simple graphical installer which can be downloaded from https://www.anaconda.com/distribution/#download-section - select your operating system and download the Python 3.7 version. The default installer options are usually appropriate.

  2. Open a terminal

    We will install most packages with conda:

    $ conda create -n magine_env python=3.7
    $ conda activate magine_env
    $ conda config --add channels conda-forge
    $ conda install jinja2 statsmodels networkx graphviz
    $ conda install -c marufr python-igraph

    Windows users: Please download and install igraph and pycairo using the wheel files provided by Christoph Gohlke, found at https://www.lfd.uci.edu/~gohlke/ . Download and install via pip.

  3. Install MAGINE

    The installation is very straightforward with pip - type the following in a terminal:

    $ pip install magine
  4. Start Python and MAGINE

    From the terminal or command prompt type

    $ jupyter notebook

    You will then be at the Python prompt. Type import magine to try loading magine. If no error messages appear and the next Python prompt appears, you have succeeded in installing magine!

Documentation

The manual is available online at http://magine.readthedocs.io.

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

MAGINE-0.0.5.tar.gz (2.7 MB view details)

Uploaded Source

Built Distribution

MAGINE-0.0.5-py3-none-any.whl (2.7 MB view details)

Uploaded Python 3

File details

Details for the file MAGINE-0.0.5.tar.gz.

File metadata

  • Download URL: MAGINE-0.0.5.tar.gz
  • Upload date:
  • Size: 2.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.20.1 setuptools/40.6.2 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.1

File hashes

Hashes for MAGINE-0.0.5.tar.gz
Algorithm Hash digest
SHA256 dd9476eaf0895e5ac93e5f8fe4cffa08c60de2a8c5d5efc1a4d7ff396a5d9ab9
MD5 99f2a03c1a12e44a39348aa60ea16884
BLAKE2b-256 18d938b701e6f59358cf5d443b2f2af8091741b02345dd6c98e64e586449e082

See more details on using hashes here.

File details

Details for the file MAGINE-0.0.5-py3-none-any.whl.

File metadata

  • Download URL: MAGINE-0.0.5-py3-none-any.whl
  • Upload date:
  • Size: 2.7 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.20.1 setuptools/40.6.2 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.1

File hashes

Hashes for MAGINE-0.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 1a1797113f967026a11c1c8b4354d0ff3265444b21020e24888f913effcebbf3
MD5 4488090750b372152b91e307d16e40c4
BLAKE2b-256 f4199c245a9ebd2125f485f0d9af3285a6a5dd241f126f770c7aa0f1e4b2e9b0

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