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| -rw-r--r-- | test/test.py | 42 |
1 files changed, 42 insertions, 0 deletions
diff --git a/test/test.py b/test/test.py index 0a9633a..ab10737 100644 --- a/test/test.py +++ b/test/test.py @@ -12,6 +12,48 @@ def check_result(selected_features, n_relevant): success = False return success +def read_digits(fname='digit.txt'): + ''' + read_digits(fname='digit.txt') + + read a data file that contains the features and class labels. + each row of the file is a feature vector with the class + label appended. + ''' + import csv + import numpy as np + + fw = csv.reader(open(fname,'rb'), delimiter='\t') + data = [] + for line in fw: + data.append( [float(x) for x in line] ) + data = np.array(data) + labels = data[:,len(data.transpose())-1] + data = data[:,:len(data.transpose())-1] + return data, labels + +def uniform_data(n_observations = 1000, n_features = 50, n_relevant = 5): + import numpy as np + xmax = 10 + xmin = 0 + data = 1.0*np.random.randint(xmax + 1, size = (n_features, n_observations)) + labels = np.zeros(n_observations) + delta = n_relevant * (xmax - xmin) / 2.0 + + for m in range(n_observations): + zz = 0.0 + for k in range(n_relevant): + zz += data[k, m] + if zz > delta: + labels[m] = 1 + else: + labels[m] = 2 + data = data.transpose() + + return data, labels + + + n_relevant = 5 |