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src/c/o/cogent-1.5.3/cogent/phylo/distance.py   cogent(Download)
from cogent.util import parallel, table, warning, progress_display as UI
from cogent.maths.stats.util import Numbers
from cogent import LoadSeqs, LoadTree
 
from warnings import warn
    def __make_pair_alignment(self, seqs, opt_kwargs):
        lf = self.__sm.makeLikelihoodFunction(\
                    LoadTree(tip_names=seqs.getSeqNames()),
                    aligned=False)
        lf.setSequences(seqs.NamedSeqs)
 
        # create the tree object
        tree = LoadTree(tip_names = sequence_names)
 
        # make the parameter controller

src/c/o/cogent-1.5.3/cogent/phylo/tree_collection.py   cogent(Download)
def LoadTrees(filename):
    """Parse a file of (score, tree) lines. Scores can be positive probabilities
    or negative log likelihoods."""
    from cogent import LoadTree
    infile = open(filename, 'r')
            assert klass in [list,  LogLikelihoodScoredTreeCollection]
            klass = LogLikelihoodScoredTreeCollection
        tree = LoadTree(treestring=line[1])
        trees.append((lnL, tree))
    trees.sort(reverse=True)

src/p/y/pycogent-HEAD/cogent/phylo/distance.py   pycogent(Download)
from cogent.util import parallel, table, warning, progress_display as UI
from cogent.maths.stats.util import Numbers
from cogent import LoadSeqs, LoadTree
 
__author__ = "Gavin Huttley"
    def _make_pair_alignment(self, seqs, opt_kwargs):
        lf = self._sm.makeLikelihoodFunction(\
                    LoadTree(tip_names=seqs.getSeqNames()),
                    aligned=False)
        lf.setSequences(seqs.NamedSeqs)
 
        # create the tree object
        tree = LoadTree(tip_names = sequence_names)
 
        # make the parameter controller

src/p/y/pycogent-HEAD/cogent/phylo/tree_collection.py   pycogent(Download)
def LoadTrees(filename):
    """Parse a file of (score, tree) lines. Scores can be positive probabilities
    or negative log likelihoods."""
    from cogent import LoadTree
    infile = open(filename, 'r')
            assert klass in [list,  LogLikelihoodScoredTreeCollection]
            klass = LogLikelihoodScoredTreeCollection
        tree = LoadTree(treestring=line[1])
        trees.append((lnL, tree))
    trees.sort(reverse=True)

src/e/e/eebprogramming-HEAD/lec10review/9lscore.py   eebprogramming(Download)
#!/usr/bin/env python
# taken from http://pycogent.sourceforge.net/
from cogent.evolve.models import HKY85
from cogent import LoadSeqs, LoadTree
model = HKY85()
aln = LoadSeqs("data/primate_cdx2_promoter.fasta")
tree = LoadTree(tip_names=aln.Names)

src/e/e/eebprogramming-HEAD/lec10review/10rr.py   eebprogramming(Download)
#!/usr/bin/env python
# taken from http://pycogent.sourceforge.net/
from cogent import LoadSeqs, LoadTree
from cogent.evolve.models import HKY85
from cogent.maths import stats
aln = LoadSeqs(filename = "data/long_testseqs.fasta")
t = LoadTree(filename = "data/test.tree")

src/c/l/CladeCompare-0.2/cladecomparelib/ancestrallrt.py   CladeCompare(Download)
import tempfile
 
from cogent import LoadSeqs, LoadTree
from cogent.evolve.models import WG01
from cogent.maths import stats
 
    # Null model: character states at root of tree
    tree = LoadTree(filename=fulltreefname)
    aln = LoadSeqs(cog_full_fname, format='fasta')
 
    # Alternative model: character states at root of foreground
    # ENH: get the alt model w/o rerunning with a subtree?
    subtree = LoadTree(filename=subtreefname)
    subaln = LoadSeqs(cog_fg_fname, format='fasta')
    # or: 

src/c/o/cogent-1.5.3/cogent/phylo/consensus.py   cogent(Download)
#! /usr/bin/env python
"""This module implements methods for generating consensus trees from a list of trees"""
 
from cogent.core.tree import TreeBuilder
from cogent import LoadTree
    for filename in sys.argv[1:]:
        for tree in open(filename):
            trees.append(LoadTree(treestring=tree))
    print "Consensus of %s trees from %s" % (len(trees),sys.argv[1:])
    outtrees = majorityRule(trees, strict=True)

src/c/o/cogent-1.5.3/cogent/align/progressive.py   cogent(Download)
#!/usr/bin/env python
 
from __future__ import with_statement
from cogent import LoadTree
from cogent.phylo import nj as NJ
        ests_from_pairwise = False
    elif two_seqs:
        tree = LoadTree(tip_names=seqs.getSeqNames())
        ests_from_pairwise = False
    else:

src/p/y/pycogent-HEAD/cogent/phylo/consensus.py   pycogent(Download)
#! /usr/bin/env python
"""This module implements methods for generating consensus trees from a list of trees"""
 
from cogent.core.tree import TreeBuilder
from cogent import LoadTree
    for filename in sys.argv[1:]:
        for tree in open(filename):
            trees.append(LoadTree(treestring=tree))
    print "Consensus of %s trees from %s" % (len(trees),sys.argv[1:])
    outtrees = majorityRule(trees, strict=True)

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