@author Norman MacDonald
@date 2010-03-12
"""
import os,sys
from optparse import OptionParser, OptionGroup
from pica.Sample import SampleSet, ClassLabelSet
from pica.io.FileIO import FileIO
from pica.AssociationRule import load_rules
from pica.utils.ProgramTimer import ProgramTimer
from pica.AssociationRule import load_rules,AssociationRuleSet
if __name__ == "__main__":
pt = ProgramTimer()
parser = OptionParser(version="%prog 0.8")
parser.add_option("-s","--samples_filename",help="Read samples from FILE",metavar="FILE")
parser.add_option("-m","--model_filename",help="Read rules from FILE",metavar="FILE")
parser.add_option("-t","--target_sample",help="Set the target SAMPLE for selecting",metavar="SAMPLE")
parser.add_option("-f","--target_samples_filename",help="Read target samples from filename, one per line")
parser.add_option("-o","--output_filename",help="Write selected rules to FILE",metavar="FILE")
parser.add_option("-g","--output_genomes",action="store_true",default=False,help="Output genomes that satisfy rules instead")
(options, args) = parser.parse_args()
pt.start()
fileio = FileIO()
samples = fileio.load_samples(options.samples_filename)
target_samples = []
seta = {}
for keya in sample_rulesets.keys():
if not seta.has_key(keya):
seta[keya] = [keya]
for keyb in sample_rulesets.keys():
if not seta.has_key(keyb):
equality = is_equal(sample_rulesets[keya],
sample_rulesets[keyb])
if equality:
seta[keya].append(keyb)
seta[keyb] = [keya]
return seta
if __name__ == "__main__":
pt = ProgramTimer()
parser = OptionParser(version="%prog 0.8")
parser.add_option("-s",
"--samples_filename",
help="Read samples from FILE",
metavar="FILE")
parser.add_option("-m",
"--model_filename",
help="Read rules from FILE",
metavar="FILE")
parser.add_option("-o",
"--output_filename",
help="Write selected organisms to FILE",
metavar="FILE")
parser.add_option("-c",
"--classes_filename",
Train a classifier with a sample set.
@author Norman MacDonald
@date 2010-02-16
"""
import os,sys
from optparse import OptionParser
from pica.io.FileIO import FileIO
from pica.utils.ProgramTimer import ProgramTimer
from pica.io.FileIO import error
import pickle # RVF
if __name__ == "__main__":
pt = ProgramTimer()
parser = OptionParser(version="PICA %prog 1.0.1")
parser.add_option("-a","--algorithm",action="store",dest="algorithm",
help="Training algorithm [default = %default]",metavar="ALG",default="libsvm.libSVMTrainer")
parser.add_option("-k","--svm_cost",action="store",dest="C",metavar="FLOAT",help="Set the SVM misclassification penalty parameter C to FLOAT")
parser.add_option("-s","--samples",action="store",dest="input_samples_filename",help="Read samples from FILE",metavar="FILE")
parser.add_option("-c","--classes",action="store",dest="input_classes_filename",help="Read class labels from FILE",metavar="FILE")
parser.add_option("-t","--targetclass",action="store",dest="target_class",help="Set the target CLASS for testing",metavar="CLASS")
parser.add_option("-o","--output",action="store",dest="output_filename",help="Write rules to FILE",metavar="FILE",default=None)
parser.add_option("-p","--parameters",action="store",dest="parameters",help="FILE with additional, classifier-specific parameters. (confounders for CWMI)",metavar="FILE",default="taxonomic_confounders.txt")
parser.add_option("-f","--feature_select",help="Model file (currently only association rule files) with features to select from [default: %default]",metavar="FILE",default=None)
parser.add_option("-1","--feature_select_score",help="Order features by (feature selection option)", default="order_cwmi")
parser.add_option("-n","--feature_select_top_n",help="Take the top n features(feature selection option)", type="int", default=20)
(options, args) = parser.parse_args()
import os, sys
from optparse import OptionParser
from pica.io.FileIO import FileIO
from pica.utils.ProgramTimer import ProgramTimer
from pica.io.FileIO import error
import pickle # RVF
"""
Train a classifier with a sample set.
@author Norman MacDonald
@date 2010-02-16
"""
if __name__ == "__main__":
pt = ProgramTimer()
parser = OptionParser(version="PICA %prog 1.0.1")
parser.add_option("-a",
"--algorithm",
action="store",
dest="algorithm",
help="Training algorithm [default = %default]",
metavar="ALG",
default="libsvm.libSVMTrainer")
parser.add_option(
"-k",
"--svm_cost",
action="store",
dest="C",
metavar="FLOAT",
help="Set the SVM misclassification penalty parameter C to FLOAT",
