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Metadata-Version: 1.1
Name: intervaltree
Version: 2.1.0
Summary: Editable interval tree data structure for Python 2 and 3
Home-page: https://github.com/chaimleib/intervaltree
Author: Chaim-Leib Halbert, Konstantin Tretyakov
Author-email: chaim.leib.halbert@gmail.com
License: Apache License, Version 2.0
Download-URL: https://github.com/chaimleib/intervaltree/tarball/2.1.0
Description: .. This file is automatically generated by setup.py from README.md and CHANGELOG.md.
        
        intervaltree
        ============
        
        A mutable, self-balancing interval tree for Python 2 and 3. Queries may
        be by point, by range overlap, or by range envelopment.
        
        This library was designed to allow tagging text and time intervals,
        where the intervals include the lower bound but not the upper bound.
        
        Installing
        ----------
        
        .. code:: sh
        
            pip install intervaltree
        
        Features
        --------
        
        -  Supports Python 2.6+ and Python 3.2+
        -  Initializing
        
           -  blank ``tree = IntervalTree()``
           -  from an iterable of ``Interval`` objects
              (``tree = IntervalTree(intervals)``)
           -  from an iterable of tuples
              (``tree = IntervalTree.from_tuples(interval_tuples)``)
        
        -  Insertions
        
           -  ``tree[begin:end] = data``
           -  ``tree.add(interval)``
           -  ``tree.addi(begin, end, data)``
        
        -  Deletions
        
           -  ``tree.remove(interval)`` (raises ``ValueError`` if not present)
           -  ``tree.discard(interval)`` (quiet if not present)
           -  ``tree.removei(begin, end, data)`` (short for
              ``tree.remove(Interval(begin, end, data))``)
           -  ``tree.discardi(begin, end, data)`` (short for
              ``tree.discard(Interval(begin, end, data))``)
           -  ``tree.remove_overlap(point)``
           -  ``tree.remove_overlap(begin, end)`` (removes all overlapping the
              range)
           -  ``tree.remove_envelop(begin, end)`` (removes all enveloped in the
              range)
        
        -  Overlap queries
        
           -  ``tree[point]``
           -  ``tree[begin:end]``
           -  ``tree.search(point)``
           -  ``tree.search(begin, end)``
        
        -  Envelop queries
        
           -  ``tree.search(begin, end, strict=True)``
        
        -  Membership queries
        
           -  ``interval_obj in tree`` (this is fastest, O(1))
           -  ``tree.containsi(begin, end, data)``
           -  ``tree.overlaps(point)``
           -  ``tree.overlaps(begin, end)``
        
        -  Iterable
        
           -  ``for interval_obj in tree:``
           -  ``tree.items()``
        
        -  Sizing
        
           -  ``len(tree)``
           -  ``tree.is_empty()``
           -  ``not tree``
           -  ``tree.begin()`` (the ``begin`` coordinate of the leftmost
              interval)
           -  ``tree.end()`` (the ``end`` coordinate of the rightmost interval)
        
        -  Set-like operations
        
           -  union
        
              -  ``result_tree = tree.union(iterable)``
              -  ``result_tree = tree1 | tree2``
              -  ``tree.update(iterable)``
              -  ``tree |= other_tree``
        
           -  difference
        
              -  ``result_tree = tree.difference(iterable)``
              -  ``result_tree = tree1 - tree2``
              -  ``tree.difference_update(iterable)``
              -  ``tree -= other_tree``
        
           -  intersection
        
              -  ``result_tree = tree.intersection(iterable)``
              -  ``result_tree = tree1 & tree2``
              -  ``tree.intersection_update(iterable)``
              -  ``tree &= other_tree``
        
           -  symmetric difference
        
              -  ``result_tree = tree.symmetric_difference(iterable)``
              -  ``result_tree = tree1 ^ tree2``
              -  ``tree.symmetric_difference_update(iterable)``
              -  ``tree ^= other_tree``
        
           -  comparison
        
              -  ``tree1.issubset(tree2)`` or ``tree1 <= tree2``
              -  ``tree1 <= tree2``
              -  ``tree1.issuperset(tree2)`` or ``tree1 > tree2``
              -  ``tree1 >= tree2``
              -  ``tree1 == tree2``
        
        -  Restructuring
        
           -  ``chop(begin, end)`` (slice intervals and remove everything
              between ``begin`` and ``end``)
           -  ``slice(point)`` (slice intervals at ``point``)
           -  ``split_overlaps()`` (slice at all interval boundaries)
        
        -  Copying and typecasting
        
           -  ``IntervalTree(tree)`` (``Interval`` objects are same as those in
              tree)
           -  ``tree.copy()`` (``Interval`` objects are shallow copies of those
              in tree)
           -  ``set(tree)`` (can later be fed into ``IntervalTree()``)
           -  ``list(tree)`` (ditto)
        
        -  Pickle-friendly
        -  Automatic AVL balancing
        
        Examples
        --------
        
        -  Getting started
        
           .. code:: python
        
               >>> from intervaltree import Interval, IntervalTree
               >>> t = IntervalTree()
               >>> t
               IntervalTree()
        
        -  Adding intervals - any object works!
        
           .. code:: python
        
               >>> t[1:2] = "1-2"
               >>> t[4:7] = (4, 7)
               >>> t[5:9] = {5: 9}
        
        -  Query by point
        
           | The result of a query is a ``set`` object, so if ordering is
             important,
           | you must sort it first.
        
           .. code:: python
        
               >>> sorted(t[6])
               [Interval(4, 7, (4, 7)), Interval(5, 9, {5: 9})]
               >>> sorted(t[6])[0]
               Interval(4, 7, (4, 7))
        
        -  Query by range
        
           Note that ranges are inclusive of the lower limit, but non-inclusive
           of the upper limit. So:
        
           .. code:: python
        
               >>> sorted(t[2:4])
               []
        
           But:
        
           .. code:: python
        
               >>> sorted(t[1:5])
               [Interval(1, 2, '1-2'), Interval(4, 7, (4, 7))]
        
        -  Accessing an ``Interval`` object
        
           .. code:: python
        
               >>> iv = Interval(4, 7, (4, 7))
               >>> iv.begin
               4
               >>> iv.end
               7
               >>> iv.data
               (4, 7)
        
               >>> begin, end, data = iv
               >>> begin
               4
               >>> end
               7
               >>> data
               (4, 7)
        
        -  Constructing from lists of intervals
        
           We could have made a similar tree this way:
        
           .. code:: python
        
               >>> ivs = [(1, 2), (4, 7), (5, 9)]
               >>> t = IntervalTree(
               ...    Interval(begin, end, "%d-%d" % (begin, end)) for begin, end in ivs
               ... )
        
           Or, if we don't need the data fields:
        
           .. code:: python
        
               >>> t2 = IntervalTree(Interval(*iv) for iv in ivs)
        
        -  Removing intervals
        
           .. code:: python
        
               >>> t.remove( Interval(1, 2, "1-2") )
               >>> sorted(t)
               [Interval(4, 7, '4-7'), Interval(5, 9, '5-9')]
        
               >>> t.remove( Interval(500, 1000, "Doesn't exist"))  # raises ValueError
               Traceback (most recent call last):
               ValueError
        
               >>> t.discard(Interval(500, 1000, "Doesn't exist"))  # quietly does nothing
        
               >>> del t[5]  # same as t.remove_overlap(5)
               >>> t
               IntervalTree()
        
           We could also empty a tree entirely:
        
           .. code:: python
        
               >>> t2.clear()
               >>> t2
               IntervalTree()
        
           Or remove intervals that overlap a range:
        
           .. code:: python
        
               >>> t = IntervalTree([
               ...     Interval(0, 10), 
               ...     Interval(10, 20), 
               ...     Interval(20, 30), 
               ...     Interval(30, 40)])
               >>> t.remove_overlap(25, 35)
               >>> sorted(t)
               [Interval(0, 10), Interval(10, 20)]
        
           We can also remove only those intervals completely enveloped in a
           range:
        
           .. code:: python
        
               >>> t.remove_envelop(5, 20)
               >>> sorted(t)
               [Interval(0, 10)]
        
        -  Chopping
        
           We could also chop out parts of the tree:
        
           .. code:: python
        
               >>> t = IntervalTree([Interval(0, 10)])
               >>> t.chop(3, 7)
               >>> sorted(t)
               [Interval(0, 3), Interval(7, 10)]
        
           To modify the new intervals' data fields based on which side of the
           interval is being chopped:
        
           .. code:: python
        
               >>> def datafunc(iv, islower):
               ...     oldlimit = iv[islower]
               ...     return "oldlimit: {0}, islower: {1}".format(oldlimit, islower)
               >>> t = IntervalTree([Interval(0, 10)])
               >>> t.chop(3, 7, datafunc)
               >>> sorted(t)[0]
               Interval(0, 3, 'oldlimit: 10, islower: True')
               >>> sorted(t)[1]
               Interval(7, 10, 'oldlimit: 0, islower: False')
        
        -  Slicing
        
           You can also slice intervals in the tree without removing them:
        
           .. code:: python
        
               >>> t = IntervalTree([Interval(0, 10), Interval(5, 15)])
               >>> t.slice(3)
               >>> sorted(t)
               [Interval(0, 3), Interval(3, 10), Interval(5, 15)]
        
           You can also set the data fields, for example, re-using
           ``datafunc()`` from above:
        
           .. code:: python
        
               >>> t = IntervalTree([Interval(5, 15)])
               >>> t.slice(10, datafunc)
               >>> sorted(t)[0]
               Interval(5, 10, 'oldlimit: 15, islower: True')
               >>> sorted(t)[1]
               Interval(10, 15, 'oldlimit: 5, islower: False')
        
        Future improvements
        -------------------
        
        See the issue tracker on GitHub.
        
        Based on
        --------
        
        -  Eternally Confuzzled's AVL tree
        -  Wikipedia's Interval Tree
        -  Heavily modified from Tyler Kahn's Interval Tree implementation in
           Python (GitHub project)
        -  Incorporates contributions from:
        
           -  konstantint/Konstantin Tretyakov of the University of Tartu
              (Estonia)
           -  siniG/Avi Gabay
           -  lmcarril/Luis M. Carril of the Karlsruhe Institute for Technology
              (Germany)
        
        Copyright
        ---------
        
        -  Chaim-Leib Halbert, 2013-2015
        -  Modifications, Konstantin Tretyakov, 2014
        
        Licensed under the Apache License, version 2.0.
        
        The source code for this project is at
        https://github.com/chaimleib/intervaltree
        
        Change log
        ==========
        
        Version 2.1.0
        -------------
        
        -  Added:
        
           -  ``merge_overlaps()`` method and tests
           -  ``merge_equals()`` method and tests
           -  ``range()`` method
           -  ``span()`` method, for returning the difference between ``end()``
              and ``begin()``
        
        -  Fixes:
        
           -  Development version numbering is changing to be compliant with
              PEP440. Version numbering now contains major, minor and micro
              release numbers, plus the number of builds following the stable
              release version, e.g. 2.0.4b34
           -  Speed improvement: ``begin()`` and ``end()`` methods used
              iterative ``min()`` and ``max()`` builtins instead of the more
              efficient ``iloc`` member available to ``SortedDict``
           -  ``overlaps()`` method used to return ``True`` even if provided
              null test interval
        
        -  Maintainers:
        
           -  Added coverage test (``make coverage``) with html report
              (``htmlcov/index.html``)
           -  Tests run slightly faster
        
        Version 2.0.4
        -------------
        
        -  Fix: Issue #27: README incorrectly showed using a comma instead of a
           colon when querying the ``IntervalTree``: it showed
           ``tree[begin, end]`` instead of ``tree[begin:end]``
        
        Version 2.0.3
        -------------
        
        -  Fix: README showed using + operator for setlike union instead of the
           correct \| operator
        -  Removed tests from release package to speed up installation; to get
           the tests, download from GitHub
        
        Version 2.0.2
        -------------
        
        -  Fix: Issue #20: performance enhancement for large trees.
           ``IntervalTree.search()`` made a copy of the entire
           ``boundary_table`` resulting in linear search time. The
           ``sortedcollections`` package is now the sole install dependency
        
        Version 2.0.1
        -------------
        
        -  Fix: Issue #26: failed to prune empty ``Node`` after a rotation
           promoted contents of ``s_center``
        
        Version 2.0.0
        -------------
        
        -  ``IntervalTree`` now supports the full ``collections.MutableSet`` API
        -  Added:
        
           -  ``__delitem__`` to ``IntervalTree``
           -  ``Interval`` comparison methods ``lt()``, ``gt()``, ``le()`` and
              ``ge()`` to ``Interval``, as an alternative to the comparison
              operators, which are designed for sorting
           -  ``IntervalTree.from_tuples(iterable)``
           -  ``IntervalTree.clear()``
           -  ``IntervalTree.difference(iterable)``
           -  ``IntervalTree.difference_update(iterable)``
           -  ``IntervalTree.union(iterable)``
           -  ``IntervalTree.intersection(iterable)``
           -  ``IntervalTree.intersection_update(iterable)``
           -  ``IntervalTree.symmetric_difference(iterable)``
           -  ``IntervalTree.symmetric_difference_update(iterable)``
           -  ``IntervalTree.chop(a, b)``
           -  ``IntervalTree.slice(point)``
        
        -  Deprecated ``IntervalTree.extend()`` -- use ``update()`` instead
        -  Internal improvements:
        
           -  More verbose tests with progress bars
           -  More tests for comparison and sorting behavior
           -  Code in the README is included in the unit tests
        
        -  Fixes
        
           -  BACKWARD INCOMPATIBLE: On ranged queries where ``begin >= end``,
              the query operated on the overlaps of ``begin``. This behavior was
              documented as expected in 1.x; it is now changed to be more
              consistent with the definition of ``Interval``\ s, which are
              half-open.
           -  Issue #25: pruning empty Nodes with staggered descendants could
              result in invalid trees
           -  Sorting ``Interval``\ s and numbers in the same list gathered all
              the numbers at the beginning and the ``Interval``\ s at the end
           -  ``IntervalTree.overlaps()`` and friends returned ``None`` instead
              of ``False``
           -  Maintainers: ``make install-testpypi`` failed because the ``pip``
              was missing a ``--pre`` flag
        
        Version 1.1.1
        -------------
        
        -  Removed requirement for pyandoc in order to run functionality tests.
        
        Version 1.1.0
        -------------
        
        -  Added ability to use ``Interval.distance_to()`` with points, not just
           ``Intervals``
        -  Added documentation on return types to ``IntervalTree`` and
           ``Interval``
        -  ``Interval.__cmp__()`` works with points too
        -  Fix: ``IntervalTree.score()`` returned maximum score of 0.5 instead
           of 1.0. Now returns max of subscores instead of avg
        -  Internal improvements:
        
           -  Development version numbering scheme, based on ``git describe``
              the "building towards" release is appended after a hyphen, eg.
              1.0.2-37-g2da2ef0-1.10. The previous tagged release is 1.0.2, and
              there have been 37 commits since then, current tag is g2da2ef0,
              and we are getting ready for a 1.1.0 release
           -  Optimality tests added
           -  ``Interval`` overlap tests for ranges, ``Interval``\ s and points
              added
        
        Version 1.0.2
        -------------
        
        | -Bug fixes:
        |  - ``Node.depth_score_helper()`` raised ``AttributeError``
        |  - README formatting
        
        Version 1.0.1
        -------------
        
        -  Fix: pip install failure because of failure to generate README.rst
        
        Version 1.0.0
        -------------
        
        -  Renamed from PyIntervalTree to intervaltree
        -  Speed improvements for adding and removing Intervals (~70% faster
           than 0.4)
        -  Bug fixes:
        
           -  BACKWARD INCOMPATIBLE: ``len()`` of an ``Interval`` is always 3,
              reverting to default behavior for ``namedtuples``. In Python 3,
              ``len`` returning a non-integer raises an exception. Instead, use
              ``Interval.length()``, which returns 0 for null intervals and
              ``end - begin`` otherwise. Also, if the ``len() === 0``, then
              ``not iv`` is ``True``.
           -  When inserting an ``Interval`` via ``__setitem__`` and improper
              parameters given, all errors were transformed to ``IndexError``
           -  ``split_overlaps`` did not update the ``boundary_table`` counts
        
        -  Internal improvements:
        
           -  More robust local testing tools
           -  Long series of interdependent tests have been separated into
              sections
        
        Version 0.4
        -----------
        
        -  Faster balancing (~80% faster)
        -  Bug fixes:
        
           -  Double rotations were performed in place of a single rotation when
              presented an unbalanced Node with a balanced child.
           -  During single rotation, kept referencing an unrotated Node instead
              of the new, rotated one
        
        Version 0.3.3
        -------------
        
        -  Made IntervalTree crash if inited with a null Interval (end <= begin)
        -  IntervalTree raises ValueError instead of AssertionError when a null
           Interval is inserted
        
        Version 0.3.2
        -------------
        
        -  Support for Python 3.2+ and 2.6+
        -  Changed license from LGPL to more permissive Apache license
        -  Merged changes from https://github.com/konstantint/PyIntervalTree to
           https://github.com/chaimleib/PyIntervalTree
        
           -  Interval now inherits from a namedtuple. Benefits: should be
              faster.
              Drawbacks: slight behavioural change (Intervals not mutable
              anymore).
           -  Added float tests
           -  Use setup.py for tests
           -  Automatic testing via travis-ci
           -  Removed dependency on six
        
        -  Interval improvements:
        
           -  Intervals without data have a cleaner string representation
           -  Intervals without data are pickled more compactly
           -  Better hashing
           -  Intervals are ordered by begin, then end, then by data. If data is
              not
              orderable, sorts by type(data)
        
        -  Bug fixes:
        
           -  Fixed crash when querying empty tree
           -  Fixed missing close parenthesis in examples
           -  Made IntervalTree crash earlier if a null Interval is added
        
        -  Internals:
        
           -  New test directory
           -  Nicer display of data structures for debugging, using custom
              test/pprint.py (Python 2.6, 2.7)
           -  More sensitive exception handling
           -  Local script to test in all supported versions of Python
           -  Added IntervalTree.score() to measure how optimally a tree is
              structured
        
        Version 0.2.3
        -------------
        
        -  Slight changes for inclusion in PyPI.
        -  Some documentation changes
        -  Added tests
        -  Bug fix: interval addition via [] was broken in Python 2.7 (see
           http://bugs.python.org/issue21785)
        -  Added intervaltree.bio subpackage, adding some utilities for use in
           bioinformatics
        
        Version 0.2.2b
        --------------
        
        -  Forked from https://github.com/MusashiAharon/PyIntervalTree
        
Keywords: interval-tree data-structure intervals tree
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Text Processing :: General
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Topic :: Text Processing :: Markup