@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",