added papers.py and implemented basic test + confusion matrix printing

scripts/paper.py

@@ -0,0 +1,34 @@
+#!/usr/bin/env python
+from tabulate import tabulate
+import algorithm
+import database
+import analysis
+import numpy as np
+
+
+def base_test(protocol, variables, setname='csh101', nb_tree_per_forest=50, max_depth=10):
+    # get train data
+    train = database.get(protocol, 'train', database.CLASSES, variables, setname)
+    # make and train model
+    model = algorithm.Model(nb_tree_per_forest, max_depth)
+    model.train(train)
+    # get test data
+    test = database.get(protocol, 'test', database.CLASSES, variables, setname)
+    test_labels = algorithm.make_labels(test).astype(int)
+    # make prediction on test
+    test_predictions = model.predict(test)
+    # get and return confusion matrix
+    cm = analysis.get_confusion_matrix(test_predictions, test_labels)
+    return cm
+
+
+def pretty_confusion_matrix(cm):
+    classes = np.array([database.CLASSES])
+    table = tabulate(np.vstack((np.hstack(([[""]], classes)),
+                                np.hstack((classes.T, cm)))))
+    return table
+
+
+if __name__ == '__main__':
+    print("Main script for Human Activity Recognition with Random Forest classifier")
+    print(pretty_confusion_matrix(base_test('proto1', database.VARIABLES)))