# -*- coding: utf-8 -*-

# Define self package variable
__version__ = '2.0a5'
__all__ = ["pycoQC", "common"]
__description__="""
PycoQC-2 is a Pure Python 3 package for Jupyter Notebook, computing metrics and
generating simple QC plots from the sequencing summary report generated by
Oxford Nanopore technologies Albacore basecaller
"""
__long_description__="""
As opposed to more exhaustive QC programs for nanopore data, pycoQC is very fast as it relies entirely on the sequencing_summary.txt file generated by ONT Albacore basecaller.
Consequently, pycoQC will only provide metrics at read level metrics (and not at base level).
The package supports 1D and 1D2 runs analysed with Albacore.

PycoQC requires the following fields in the sequencing.summary.txt file:

1D run => read_id, run_id, channel, start_time, sequence_length_template, mean_qscore_template

1D2 run => read_id, run_id, channel, start_time, sequence_length_2d, mean_qscore_2d

In addition it will try to get the following optional fields if they are available:

calibration_strand_genome_template, barcode_arrangement"""

# Collect info in a dictionnary for setup.py
setup_dict = {
    "name": __name__,
    "version": __version__,
    "description": __description__,
    "long_description": __long_description__,
    "url": "https://github.com/a-slide/pycoQC",
    "author": 'Adrien Leger',
    "author_email": 'aleg@ebi.ac.uk',
    "license": 'GPLv3',
    "python_requires":'>=3.3',
    "classifiers": [
        'Development Status :: 3 - Alpha',
        'Intended Audience :: Science/Research',
        'Topic :: Scientific/Engineering :: Bio-Informatics',
        'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
        'Programming Language :: Python :: 3'],
    "install_requires": [
        'numpy>=1.13',
        'scipy>=1.1',
        'plotly>=3.3',
        'pandas>=0.23'],
    "packages": [__name__],
    "package_dir": {__name__: __name__},
    }
