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Dynamic mode decompositon in python.

Project description

Documentation Status MIT License

Dynamic mode decomposition (DMD)is a tool for analyzing the dynamics of nonlinear systems.

This is an experimental DMD codebase for research purposes.

Alternatively, check out PyDMD, a professionally maintained open source DMD codebase for Python.

Installation:

pip install dmdlab

Usage:

from dmdlab import DMD, plot_eigs
import numpy as np
from scipy.linalg import logm

# Generate toy data
ts = np.linspace(0,6,50)

theta = 1/10
A_dst = np.array([[np.cos(theta), -np.sin(theta)],
                  [np.sin(theta), np.cos(theta)]])
A_cts = logm(A_dst)/(ts[1]-ts[0])

x0 = np.array([1,0])
X = np.vstack([expm(A_cts*ti)@x0 for ti in ts]).T

# Fit model
model = DMD.from_full(X, ts)

# Print the eigenvalue phases
print(np.angle(model.eigs))

>>> [0.1, -0.1]

For a technical reference, check out the DMD book.

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