New upstream version 0.8.4 (d00e2e62) · Commits · Debian Med / python-bx

.gitignore

+3 −0

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		@@ -22,3 +22,6 @@ nose*.egg

		# .eggs directory
		.eggs

		# Virtualenv
		.venv

.travis.yml

+55 −23

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		language: python
		sudo: false
		cache: pip
		os:
		- linux
		## - osx
		python:
		- 2.7
		- 3.3
		- '2.7'
		- '3.5'

		env:
		global:
		- PYTHON=python
		- TWINE_USERNAME=nsoranzo
		- secure: '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'

		_deploy_common: &deploy_common
		if: tag IS present
		install:
		- $PYTHON -m pip install cibuildwheel twine

		matrix:
		include:
		- stage: deploy
		python: '3.5'
		services:
		- docker
		env: CIBW_BEFORE_BUILD="yum install -y zlib-devel && pip install Cython numpy"
		<<: *deploy_common
		script:
		- cibuildwheel --output-dir dist
		- $PYTHON -m pip install Cython nose numpy python-lzo six
		- $PYTHON setup.py build_ext --inplace
		- $PYTHON setup.py sdist
		- twine check dist/*
		- twine upload --skip-existing dist/*
		- stage: deploy
		os: osx
		language: generic
		env:
		- PYTHON=python3
		- CIBW_BEFORE_BUILD="pip install Cython numpy"
		addons: {}
		<<: *deploy_common
		script:
		- cibuildwheel --output-dir dist
		- twine check dist/*
		- twine upload --skip-existing dist/*

		addons:
		apt:
		packages:
		- liblzo2-dev
		before_install:
		# Use miniconda for dependencies, pip is too slow -- https://gist.github.com/zonca/9958333
		- wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh
		- chmod +x miniconda.sh
		- ./miniconda.sh -b
		- export PATH=/home/travis/miniconda2/bin:$PATH
		- conda update --yes conda

		install:
		- conda create --yes -n testenv python=$TRAVIS_PYTHON_VERSION Cython numpy nose
		- source activate testenv
		- pip install python-lzo
		- python setup.py build_ext --inplace
		- python setup.py install
		- $PYTHON -m pip install Cython nose numpy python-lzo six
		- $PYTHON setup.py build_ext --inplace
		- $PYTHON setup.py install

		script:
		- nosetests

README.md

+1 −1

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		@@ -7,7 +7,7 @@
		The bx-python project is a python library and associated set of scripts to allow for rapid implementation of genome scale analyses. The library contains a variety of useful modules, but the particular strengths are:

		* Classes for reading and working with genome-scale multiple local alignments (in MAF, AXT, and LAV formats)
		* Generic data structure for indexing on disk files that contain blocks of data associated with intervals on various sequences (used, for example, to provide random access to individual alignments in huge files; optomized for use over network filesystems)
		* Generic data structure for indexing on disk files that contain blocks of data associated with intervals on various sequences (used, for example, to provide random access to individual alignments in huge files; optimized for use over network filesystems)
		* Data structures for working with intervals on sequences
		* "Binned bitsets" which act just like chromosome sized bit arrays, but lazily allocate regions and allow large blocks of all set or all unset bits to be stored compactly
		* "Intersecter" for performing fast intersection tests that preserve both query and target intervals and associated annotation

doc/source/index.rst

+1 −1

Original line number	Diff line number	Diff line
		@@ -4,7 +4,7 @@ About bx-python
		The bx-python project is a python library and associated set of scripts to allow for rapid implementation of genome scale analyses. The library contains a variety of useful modules, but the particular strengths are:

		* Classes for reading and working with genome-scale multiple local alignments (in MAF, AXT, and LAV formats)
		* Generic data structure for indexing on disk files that contain blocks of data associated with intervals on various sequences (used, for example, to provide random access to individual alignments in huge files; optomized for use over network filesystems)
		* Generic data structure for indexing on disk files that contain blocks of data associated with intervals on various sequences (used, for example, to provide random access to individual alignments in huge files; optimized for use over network filesystems)
		* Data structures for working with intervals on sequences
		* "Binned bitsets" which act just like chromosome sized bit arrays, but lazily allocate regions and allow large blocks of all set or all unset bits to be stored compactly
		* "Intersecter" for performing fast intersection tests that preserve both query and target intervals and associated annotation

lib/bx/align/score_tests.py

+42 −47

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		"""
		Tests for `bx.align.score`.
		"""
		import sys
		import unittest

		from numpy import array, cumsum, allclose
		@@ -24,8 +23,7 @@ aligns = [ ( "CCACTAGTTTTTAAATAATCTACTATCAAATAAAAGATTTGTTAATAATAAATTTTAAATCATTAA
		-299),
		("gggaattgaacaatgagaacacatggacacaggaaggggaacatcacacacc----------ggggcctgttgtggggtggggggaag",
		"ggaactagaacaagggagacacatacaaacaacaacaacaacaacacagcccttcccttcaaagagcttatagtctgatggaggagag",
		1690 )
		]
		1690)]

		mafs = """##maf
		a score=2883.0
		@@ -46,9 +44,7 @@ nonsymm_scheme = bx.align.score.build_scoring_scheme ( """ A C G T

		aligns_for_nonsymm_scheme = [("AAAACCCCGGGGTTTT",
		"ACGTACGTACGTACGT",
		-580 )
		]

		-580)]

		asymm_scheme = bx.align.score.build_scoring_scheme(""" 01 02 A C G T
		01 200 -200 -50 100 -50 100
		@@ -57,8 +53,7 @@ asymm_scheme = bx.align.score.build_scoring_scheme ( """ 01 02 A C

		aligns_for_asymm_scheme = [("\x01\x01\x01\x01\x01\x01",
		"ACGT\x01\x02",
		100 )
		]
		100)]


		class BasicTests(unittest.TestCase):
		@@ -66,12 +61,12 @@ class BasicTests( unittest.TestCase ):
		def test_scoring_text(self):
		ss = bx.align.score.hox70
		for t1, t2, score in aligns:
		self.assertEquals( bx.align.score.score_texts( ss, t1, t2 ), score )
		self.assertEqual(bx.align.score.score_texts(ss, t1, t2), score)

		def test_align(self):
		ss = bx.align.score.hox70
		for block in bx.align.maf.Reader(StringIO(mafs)):
		self.assertEquals( bx.align.score.score_alignment( ss, block ), float( block.score ) )
		self.assertEqual(bx.align.score.score_alignment(ss, block), float(block.score))

		def test_accumulate(self):
		ss = bx.align.score.hox70
		@@ -83,9 +78,9 @@ class BasicTests( unittest.TestCase ):
		def test_nonsymm_scoring(self):
		ss = nonsymm_scheme
		for t1, t2, score in aligns_for_nonsymm_scheme:
		self.assertEquals( bx.align.score.score_texts( ss, t1, t2 ), score )
		self.assertEqual(bx.align.score.score_texts(ss, t1, t2), score)

		def test_asymm_scoring(self):
		ss = asymm_scheme
		for t1, t2, score in aligns_for_asymm_scheme:
		self.assertEquals( bx.align.score.score_texts( ss, t1, t2 ), score )
		self.assertEqual(bx.align.score.score_texts(ss, t1, t2), score)