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1 2 """Reads in the output of l_classifier.py and prepares it for display. 3 NOTE: this only makes sense for two classes. 4 """ 5 6 import numpy 7 import read_classified 8 9 12 1315 fd = open(fn, 'r') 16 hdr, classifiers = read_classified.read_classes(fd) 17 dbar = None 18 for classifier in classifiers: 19 dsum = None 20 for model in classifier.models.values(): 21 if dsum is None: 22 dsum = numpy.array(model.dir, numpy.double) 23 else: 24 dsum += model.dir 25 dsum /= len(classifier.models) 26 for model in classifier.models.values(): 27 model.dir -= dsum 28 29 if dbar is None: 30 dbar = numpy.array(classifier.models['P'].dir, numpy.double) 31 else: 32 dbar += classifier.models['P'].dir 33 34 print fn, hdr['K'], ssv(dbar/len(classifiers))35 36 37 38 if __name__ == '__main__': 39 import sys 40 doit(sys.argv[1]) 41
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