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()
