README.rst
keras_biological_gaps_sequencess
=========================================================================================
|travis| |sonar_quality| |sonar_maintainability| |codacy|
|code_climate_maintainability| |pip| |downloads|
Python package to generate on-hot encoded biological gaps to use for training and prediction.
How do I install this package?
----------------------------------------------
As usual, just download it using pip:
.. code:: shell
pip install keras_biological_gaps_sequencess
Tests Coverage
----------------------------------------------
Since some software handling coverages sometimes
get slightly different results, here's three of them:
|coveralls| |sonar_coverage| |code_climate_coverage|
Available datasets
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Currently, there is only a dataset of gaps available
within the package: the mapping of known gaps from hg19
to hg38. In the future, we will be adding more mapping.
Usage example
-----------------------------------------------
To use the sequence you can do as follows:
.. code:: Python
biological_gap_sequence = BiologicalGapsSequence(
source="hg19",
target="hg38",
source_window_size=1000,
target_window_size=1000,
batch_size=32
)
model = build_my_denoiser()
model.fit_generator(
biological_gap_sequence,
steps_per_epoch=biological_gap_sequence.steps_per_epoch,
epochs=2,
shuffle=True
)
.. |travis| image:: https://travis-ci.org/LucaCappelletti94/keras_biological_gaps_sequencess.png
:target: https://travis-ci.org/LucaCappelletti94/keras_biological_gaps_sequencess
:alt: Travis CI build
.. |sonar_quality| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_keras_biological_gaps_sequencess&metric=alert_status
:target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_keras_biological_gaps_sequencess
:alt: SonarCloud Quality
.. |sonar_maintainability| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_keras_biological_gaps_sequencess&metric=sqale_rating
:target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_keras_biological_gaps_sequencess
:alt: SonarCloud Maintainability
.. |sonar_coverage| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_keras_biological_gaps_sequencess&metric=coverage
:target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_keras_biological_gaps_sequencess
:alt: SonarCloud Coverage
.. |coveralls| image:: https://coveralls.io/repos/github/LucaCappelletti94/keras_biological_gaps_sequencess/badge.svg?branch=master
:target: https://coveralls.io/github/LucaCappelletti94/keras_biological_gaps_sequencess?branch=master
:alt: Coveralls Coverage
.. |pip| image:: https://badge.fury.io/py/keras-biological-gaps-sequence.svg
:target: https://badge.fury.io/py/keras-biological-gaps-sequence
:alt: Pypi project
.. |downloads| image:: https://pepy.tech/badge/keras-biological-gaps-sequence
:target: https://pepy.tech/badge/keras-biological-gaps-sequence
:alt: Pypi total project downloads
.. |codacy| image:: https://api.codacy.com/project/badge/Grade/90f25e6d3ab3448d9da0401f441dff79
:target: https://www.codacy.com/manual/LucaCappelletti94/keras_biological_gaps_sequencess?utm_source=github.com&utm_medium=referral&utm_content=LucaCappelletti94/keras_biological_gaps_sequencess&utm_campaign=Badge_Grade
:alt: Codacy Maintainability
.. |code_climate_maintainability| image:: https://api.codeclimate.com/v1/badges/0bc73c94073503d4d54a/maintainability
:target: https://codeclimate.com/github/LucaCappelletti94/keras_biological_gaps_sequencess/maintainability
:alt: Maintainability
.. |code_climate_coverage| image:: https://api.codeclimate.com/v1/badges/0bc73c94073503d4d54a/test_coverage
:target: https://codeclimate.com/github/LucaCappelletti94/keras_biological_gaps_sequencess/test_coverage
:alt: Code Climate Coverate