def save(self, dirname): utils.find_or_create(dirname) if self.s.size > 0: np.savetxt(dirname + '/cps.txt', self.s, fmt='%d') if self.h.size > 0: np.savetxt(dirname + '/states.txt', self.h, fmt='%.6f') if self.v.size > 0: np.savetxt(dirname + '/obs.txt', self.v, fmt='%.6f')
def save(self, dirname): utils.find_or_create(dirname) if len(self.mean) > 0: np.savetxt(dirname + '/mean.txt', self.mean, fmt='%.6f') if len(self.cpp) > 0: np.savetxt(dirname + '/cpp.txt', self.cpp, fmt='%.6f') if len(self.ll) > 0: np.savetxt(dirname + '/ll.txt', self.ll, fmt='%.6f') if len(self.score) > 0: np.savetxt(dirname + '/score.txt', self.score, fmt='%.6f')
# Change Point Estimations print('filtering...') result = model.filter(data.v) result.evaluate(data.s) result.save(work_dir + '/filtering') print('\tF-score : ' + str(result.score)) print('smoothing...') result = model.smooth(data.v) result.evaluate(data.s) result.save(work_dir + '/smoothing') print('\tF-score : ' + str(result.score)) print('online smoothing...') result = model.online_smooth(data.v, lag=10) result.evaluate(data.s) result.save(work_dir + '/online_smoothing') print('\tF-score : ' + str(result.score)) # Visualization visualize_data(work_dir + '/data', m, n) print('done.') if __name__ == '__main__': find_or_create(work_dir) experiment()