Data_Driven_Science_Python_Demos
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dylewsky
IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by J. Nathan Kutz and Steven L. Brunton
The `scipy.optimize.minimize` method tends to be really slow for solving the basis pursuit problem (ex. in the compressed sensing context) especially when we are dealing with less sparse vectors. A...
In the notebook here https://github.com/dylewsky/Data_Driven_Science_Python_Demos/blob/master/CH09/CH09_SEC03_ERA_OKID.ipynb OKID errors if the system is not square, i.e., if `q != p` The error happens in the indexing here ``` for i in range(LL):...
As an example, the following code, from `CH01_SEC04_1_Linear.ipynb`, plt.plot(a, x*a, Color='k', LineWidth=2, label='True line') # True relationship plt.plot(a, b, 'x', Color='r', MarkerSize = 10, label='Noisy data') # Noisy measurements should...
