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Viewing changes to cogent/evolve/discrete_markov.py

  • Committer: Bazaar Package Importer
  • Author(s): Steffen Moeller
  • Date: 2010-12-04 22:30:35 UTC
  • mfrom: (1.1.1 upstream)
  • Revision ID: james.westby@ubuntu.com-20101204223035-j11kinhcrrdgg2p2
Tags: 1.5-1
* Bumped standard to 3.9.1, no changes required.
* New upstream version.
  - major additions to Cookbook
  - added AlleleFreqs attribute to ensembl Variation objects.
  - added getGeneByStableId method to genome objects.
  - added Introns attribute to Transcript objects and an Intron class.
  - added Mann-Whitney test and a Monte-Carlo version
  - exploratory and confirmatory period estimation techniques (suitable for
    symbolic and continuous data)
  - Information theoretic measures (AIC and BIC) added
  - drawing of trees with collapsed nodes
  - progress display indicator support for terminal and GUI apps
  - added parser for illumina HiSeq2000 and GAiix sequence files as 
    cogent.parse.illumina_sequence.MinimalIlluminaSequenceParser.
  - added parser to FASTQ files, one of the output options for illumina's
    workflow, also added cookbook demo.
  - added functionality for parsing of SFF files without the Roche tools in
    cogent.parse.binary_sff
  - thousand fold performance improvement to nmds
  - >10-fold performance improvements to some Table operations

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cogent/evolve/discrete_markov.py
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import numpy
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from cogent.util.warning import deprecated
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from cogent.recalculation.definition import (NonParamDefn, CalcDefn, 
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    EvaluatedCell, PartitionDefn, ConstCell, ConstDefn,
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    DictArrayTemplate)
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from cogent.evolve.substitution_model import _SubstitutionModel
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__author__ = "Peter Maxwell"
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__copyright__ = "Copyright 2007-2009, The Cogent Project"
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__credits__ = ["Peter Maxwell"]
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__license__ = "GPL"
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__version__ = "1.4.1"
 
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__version__ = "1.5.0"
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__maintainer__ = "Peter Maxwell"
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__email__ = "pm67nz@gmail.com"
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__status__ = "Production"
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            uniq_cells.append(matrix)
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        return (all_cells, uniq_cells)
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class DiscreteSubstitutionModel(_SubstitutionModel):
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    _default_expm_setting = None
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    def _isInstantaneous(self, x, y):
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        return True
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    def getParamList(self):
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        return []
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    def makePsubsDefn(self, **kw):
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        motifs = tuple(self.getAlphabet())
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        psub = PsubMatrixDefn(
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            name="psubs", dimension = ('motif', motifs), default=None, 
 
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def DiscreteSubstitutionModel(*args, **kw):
 
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    deprecated("class",
 
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        "cogent.evolve.discrete_markov.DiscreteSubstitutionModel",
 
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        "cogent.evolve.substitution_model.DiscreteSubstitutionModel",
 
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        '1.6')
 
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    from cogent.evolve.substitution_model import DiscreteSubstitutionModel
 
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    return DiscreteSubstitutionModel(*args, **kw)
 
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class PartialyDiscretePsubsDefn(object):
 
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    def __init__(self, alphabet, psubs, discrete_edges):
 
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        motifs = tuple(alphabet)
 
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        dpsubs = PsubMatrixDefn(
 
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            name="dpsubs", dimension = ('motif', motifs), default=None, 
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            dimensions=('locus', 'edge'))
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        return psub
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    def makeFundamentalParamControllerDefns(self, bin_names):                
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        (input_probs, word_probs, mprobs_matrix) = \
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                self.mprob_model.makeMotifWordProbDefns()
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        # XXX absorb 1 unneeded input
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        word_probs = CalcDefn(
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                lambda x,y:x, name='hack')(
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                word_probs, mprobs_matrix)
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        defns = {
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            'motif_probs': input_probs,  
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            'word_probs': word_probs,
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            'bprobs': None,
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            }
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        return defns
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        self.choices = [psubs, dpsubs]
 
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        self.discrete_edges = discrete_edges
 
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    def selectFromDimension(self, dimension, category):
 
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        assert dimension == 'edge', dimension
 
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        special = category in self.discrete_edges
 
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        return self.choices[special].selectFromDimension(dimension, category)
 
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