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src/c/o/cogent-1.5.3/cogent/evolve/pairwise_distance.py   cogent(Download)
from __future__ import division
from numpy import log, zeros, float64, int32, array, sqrt, dot, diag, where
from numpy.linalg import det, norm, inv
 
from cogent import DNA, RNA, LoadTable
            rows.append(row)
        header = [r'Seq1 \ Seq2'] + self.Names
        table = LoadTable(header=header, rows=rows, row_ids = True,
                missing_data='*', **kwargs)
        return table

src/p/y/pycogent-HEAD/cogent/evolve/pairwise_distance.py   pycogent(Download)
from __future__ import division
from numpy import log, zeros, float64, int32, array, sqrt, dot, diag, eye
from numpy.linalg import det, norm, inv, LinAlgError
 
from cogent import DNA, RNA, LoadTable
            rows.append(row)
        header = [r'Seq1 \ Seq2'] + self.Names
        table = LoadTable(header=header, rows=rows, row_ids = True,
                missing_data='*', **kwargs)
        return table

src/c/o/cogent-1.5.3/cogent/maths/stats/jackknife.py   cogent(Download)
from __future__ import division
 
import numpy as np
from cogent import LoadTable
 
            header.append('Stat-i')
 
        return LoadTable(rows=rows, header=header,title=title)
 
    @property
            header.append('Pseudovalue-i')
 
        return LoadTable(rows=rows, header=header,title=title)
 
    @property
                self._jackknifed_stat, self._standard_error))
        rows = rows.transpose()
        return LoadTable(header=header, rows=rows, title=title)
 
 

src/p/y/pycogent-HEAD/cogent/maths/stats/jackknife.py   pycogent(Download)
from __future__ import division
 
import numpy as np
from cogent import LoadTable
 
            header.append('Stat-i')
 
        return LoadTable(rows=rows, header=header,title=title)
 
    @property
            header.append('Pseudovalue-i')
 
        return LoadTable(rows=rows, header=header,title=title)
 
    @property
                self._jackknifed_stat, self._standard_error))
        rows = rows.transpose()
        return LoadTable(header=header, rows=rows, title=title)
 
 

src/p/i/picrust-HEAD/picrust/ancestral_state_reconstruction.py   picrust(Download)
from picrust.count import wagner_for_picrust
from picrust.ace import ace_for_picrust
from cogent import LoadTable
from cogent.util.table import Table
from cogent.app.util import get_tmp_filename
 
    #load in the first column (containing row ids). File doesn't matter since they should all have identical first columns.
    table=LoadTable(filename=output_files[0],header=True,sep='\t')
    row_ids = table.getRawData(columns=[table.Header[0]])
    combined_table.append([table.Header[0]])
            print "Combining file {0} of {1}: {2}".format(i,len(output_files),output_file)
        #pull out the second column (first column with actual preditions)
        table=LoadTable(filename=output_file,header=True,sep='\t')
        predictions = table.getRawData(columns=[table.Header[1]])
 
 
    #foreach trait in the table, create a new tmp file with just that trait, and create the job command and add it a tmp jobs file
    table=LoadTable(filename=table, header=True, sep='\t')
 
    #get dimensions of the table

src/p/i/picrust-HEAD/picrust/ace.py   picrust(Download)
from cogent.app.parameters import ValuedParameter, FilePath
from cogent import LoadTree
from cogent import LoadTable
from picrust.util import get_picrust_project_dir
from os.path import join
    #Load the output into Table objects
    try:
        asr_table=LoadTable(filename=tmp_output_count_path,header=True,sep='\t')
    except IOError:
        raise RuntimeError,\
         ("R reported an error on stderr:"
          " %s" % "\n".join(result["StdErr"].readlines()))
 
    asr_prob_table=LoadTable(filename=tmp_output_prob_path,header=True,sep='\t')

src/c/o/cogent-1.5.3/cogent/parse/psl.py   cogent(Download)
"""
 
from cogent import LoadTable
from cogent.parse.table import ConvertFields
 
    header = parser.next()
    rows = [row for row in parser]
    table = LoadTable(header=header, rows=rows, title=version)
    return table
 

src/c/o/cogent-1.5.3/cogent/evolve/likelihood_tree.py   cogent(Download)
from cogent.util.modules import importVersionedModule, ExpectedImportError
from cogent.util.parallel import MPI
from cogent import LoadTable
 
import numpy
            rows = zip(motifs, observed, expected)
            rows.sort(key=lambda row:(-row[1], row[0]))
            table = LoadTable(header=['Pattern', 'Observed', 'Expected'], rows=rows, row_ids=True)
            return (G, table)
        else:

src/p/y/pycogent-HEAD/cogent/parse/psl.py   pycogent(Download)
"""
 
from cogent import LoadTable
from cogent.parse.table import ConvertFields
 
    header = parser.next()
    rows = [row for row in parser]
    table = LoadTable(header=header, rows=rows, title=version)
    return table
 

src/p/y/pycogent-HEAD/cogent/evolve/likelihood_tree.py   pycogent(Download)
from cogent.util.modules import importVersionedModule, ExpectedImportError
from cogent.util.parallel import MPI
from cogent import LoadTable
 
import numpy
            rows = zip(motifs, observed, expected)
            rows.sort(key=lambda row:(-row[1], row[0]))
            table = LoadTable(header=['Pattern', 'Observed', 'Expected'], rows=rows, row_ids=True)
            return (G, table)
        else:

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