/usr/lib/python2.7/dist-packages/cogent/app/cove.py is in python-cogent 1.9-9.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 | #!/usr/bin/env python
from cogent.app.util import CommandLineApplication,\
CommandLineAppResult, ResultPath
from cogent.app.parameters import Parameter, FlagParameter, ValuedParameter,\
MixedParameter,Parameters, _find_synonym, is_not_None
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2016, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.9"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class Covet(CommandLineApplication):
"""Application controller for Covet
Generate new models, by training them on example sequences.
where options are:
-a <alignfile> : make starting model from alignment
-A <filename> : save alignments to filename.1, etc., for animation
-b <backupfile> : each iteration, back up curr model to <backupfile>
-f : use flat text save formats, portable but clumsy
-G <GOP> : gap-open prob 0 < gop < 1 for random alignment generation
-h : print short help and version info
-i <cm file> : take start model from <cm file>
-m : do maximum likelihood model construction (slow!)
-p <prior file> : use prior in <file>; default is Laplace plus-one
-s <seed> : set random() seed
-X <GEX> : gap-extend prob 0 < gex < 1 for random alignment generation
"""
_parameters = {
'-a':ValuedParameter(Prefix='-',Name='a',Delimiter=' '),
'-A':ValuedParameter(Prefix='-',Name='A',Delimiter=' '),
'-b':ValuedParameter(Prefix='-',Name='b',Delimiter=' '),
'-f':FlagParameter(Prefix='-',Name='f'),
'-G':ValuedParameter(Prefix='-',Name='G',Delimiter=' '),
'-i':ValuedParameter(Prefix='-',Name='i',Delimiter=' '),
'-m':FlagParameter(Prefix='-',Name='m'),
'-p':ValuedParameter(Prefix='-',Name='p',Delimiter=' '),
'-s':ValuedParameter(Prefix='-',Name='s',Delimiter=' '),
'-X':ValuedParameter(Prefix='-',Name='X',Delimiter=' ')}
_command = 'covet'
_input_handlar = '_input_as_string'
def _input_as_string(self,filename):
"""Returns 'modelname' and 'filename' to redirect input to stdin"""
return ' '.join([filename+'.cm',super(Covet,self)._input_as_string(filename)])
def _input_as_lines(self,data):
"""Returns 'temp_filename to redirect input to stdin"""
filename = self._input_filename = self.getTmpFilename(self.WorkingDir)
data_file = open(filename,'w')
data_to_file = '\n'.join([str(d).strip('\n') for d in data])
data_file.write(data_to_file)
data_file.write('\n') #must end with new line
data_file.close()
return ' '.join([filename+'.cm',filename])
def _get_result_paths(self,data):
"""Specifies the paths of output files generated by the application
data: the data the instance of the application is called on
CMfinder produces it's output in two files .align and .motif
it also prints an output to sdtout.
"""
result={}
if not isinstance(data,list):
inputPath=data
else:
inputPath=''.join([self._input_filename])
result['cm'] =\
ResultPath(Path=(inputPath+'.cm'))
if self._input_filename is not None:
result['_input_filename'] = ResultPath(self._input_filename)
return result
class Coves(CommandLineApplication):
"""Application controller for Coves
Computes the score of each whole sequence individually, and prints the scores.
You might use it to detect sequences which, according to the model, don't belong
to the same structural consensus; sequences which don't fit the model get negative
scores.
where options are:
-a : show all pairs, not just Watson-Crick
-g <gcfrac> : set expected background GC composition (default 0.5)
-m : mountain representation of structural alignment
-s : secondary structure string representation of
structural alignment
"""
_parameters = {
'-a':FlagParameter(Prefix='-',Name='a'),
'-g':ValuedParameter(Prefix='-',Name='g',Delimiter=' '),
'-m':FlagParameter(Prefix='-',Name='m'),
'-s':FlagParameter(Prefix='-',Name='s',Value=True)}
_command = 'coves'
_input_handler = '_input_as_string'
def _input_as_string(self,filename):
"""Returns 'modelname' and 'filename' to redirect input to stdin"""
return ' '.join([filename+'.cm',super(Coves,self)._input_as_string(filename)])
class Covee(CommandLineApplication):
"""Application controller for Covee
emits a consensus structure prediction for the family.
where options are:
-a : annotate all pairs, not just canonical ones
-b : emit single most probable sequence
-l : print as mountain landscape
-s <seed> : set seed for random()
EXPERIMENTAL OPTIONS:
-L : calculate expected length distributions for states
"""
_parameters = {
'-a':FlagParameter(Prefix='-',Name='a'),
'-b':FlagParameter(Prefix='-',Name='b',Value=True),
'-l':FlagParameter(Prefix='-',Name='l'),
'-s':ValuedParameter(Prefix='-',Name='s',Delimiter=' '),
'-L':FlagParameter(Prefix='-',Name='L')}
_command = 'covee'
_input_handler = '_input_as_string'
def _input_as_string(self,filename):
"""Returns 'modelname' and 'filename' to redirect input to stdin"""
return ' '.join([filename+'.cm',super(Covee,self)._input_as_string(filename)])
def _input_as_lines(self,data):
"""Returns 'temp_filename to redirect input to stdin"""
return ''.join([data+'.cm',super(Covee,self)._input_as_lines(data)])
class Covea(CommandLineApplication):
"""Application controller for Covea
here supported options are:
-a : annotate all base pairs, not just canonical ones
-h : print short help and version info
-o <outfile> : write alignment to <outfile> in SELEX format
-s <scorefile> : save individual alignment scores to <scorefile>
Experimental options:
-S : use small-memory variant of alignment algorithm
"""
_parameters = {
'-a':FlagParameter(Prefix='-',Name='a'),
'-o':ValuedParameter(Prefix='-',Name='o',Delimiter=' '),
'-s':ValuedParameter(Prefix='-',Name='s',Delimiter=' '),
'-S':FlagParameter(Prefix='-',Name='S')}
_command = 'covea'
_input_handler = '_input_as_string'
def _input_as_string(self,filename):
"""Returns 'modelname' and 'filename' to redirect input to stdin"""
return ' '.join([filename+'.cm',super(Covea,self)._input_as_string(filename)])
def _input_as_lines(self,data):
"""Returns 'temp_filename to redirect input to stdin"""
return ''.join([data+'.cm',super(Covea,self)._input_as_lines(data)])
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