def main():
data = loadtxt("eemd_example.out")
orig = data[0]
imfs = data[1:]
plot(orig, label="Original data")
plot_imfs(imfs)
show()
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with libeemd. If not, see <http://www.gnu.org/licenses/>.
from pyeemd import ceemdan
from pyeemd.utils import plot_imfs
from matplotlib.pyplot import plot, show, title
import numpy as np
# Decompose a delta-function signal
N = 512
signal = np.zeros(N)
signal[N // 2] = 1
# Plot the original data using Matplotlib
title("Original signal")
plot(signal)
# Calculate IMFs and the residual by CEEMDAN
imfs = ceemdan(signal, noise_strength=0.2, ensemble_size=500)
# Plot the results using the plot_imfs helper function from pyeemd.utils
plot_imfs(imfs, plot_splines=False)
show()
# You can compare the results with Fig. 1 in the original CEEMDAN paper at
# http://dx.doi.org/10.1109/ICASSP.2011.5947265