Python get_spectrum_data Examples

Example #1

File: InDomainTest.py Project: shwetabhandare/HuR_TTP

def createSpectrumData(testSeqFile, resultsConf):

	filename_list = string.split(testSeqFile, "_")
	list_len = len(filename_list)


	testPosLen = int(filename_list[list_len - 3])
	testNegLen = int(filename_list[list_len - 2])

	k1 = int(resultsConf["results"]["k1"])
	k2 = int(resultsConf["results"]["k2"])

	testSpectrumData = demo_utils.get_spectrum_data(testSeqFile, k1, k2, 
		testPosLen, testNegLen, True);

	return testSpectrumData;

Example #2

File: demo_test.py Project: shwetabhandare/PySG

Cs = [ 10**x for x in xrange( -3, 4 ) ]
k1 = int(sys.argv[1])
k2 = int(sys.argv[2])
trainFile = sys.argv[3];
testFile = sys.argv[4];

trainPosLen = int(sys.argv[5])
trainNegLen = int(sys.argv[6])

testPosLen = int(sys.argv[7])
testNegLen = int(sys.argv[8])

trainFeatureData = sys.argv[9];
testFeatureData = sys.argv[10];
	
trainData = demo_utils.get_spectrum_data(trainFile, k1, k2, trainPosLen, trainNegLen, True);
trainData.save(featureData);
for C in Cs:

   print C;
   #print "Train for C : " + str(C);
   s = svm.SVM(C=C);
   s.train(trainData);
   testData = demo_utils.get_spectrum_data(testFile, k1, k2, testPosLen, testNegLen, True);
   results = s.test(testData);

exit(1);

for C in Cs:

   print "Train for C : " + C;

Example #3

File: demo_test_with_features.py Project: shwetabhandare/PySG

bestTP = None
K1 = [7, 8, 9, 10, 11, 12, 13]
K2 = [7, 8, 9, 10, 11, 12, 13]

result_file = open("K-spectrum.txt", "w")
for k1 in K1:
    for k2 in K2:
        for C in Cs:
            print "**** Train/Test with K1: " + str(k1) + ", k2: " + str(k2) + ", C: " + str(C)
            trainData = generate_model.get_spectrum_data(trainSeqFile, k1, k2, trainLen, trainLen, True)
            folds = []
            s = svm.SVM(C=C)
            s.train(trainData)

            # testData = SparseDataSet(testFeatureFile);
            testData = demo_utils.get_spectrum_data(testSeqFile, k1, k2, testLen, testLen, True)

            results = s.test(testData)
            labels = results.getGivenClass()
            dvals = results.getDecisionFunction()
            folds.append((dvals, labels))

            demo_utils.print_results(results)
            print "Results Log: "
            results.getLog()
            fpc, tpc, area = roc_mod.roc_VA(folds, None)
            print "Area: " + str(area)
            if area > bestAUC:
                bestAUC = area
                bestFP = fpc
                bestTP = tpc