

In [1]:

    
import numpy as np
import matplotlib.pyplot as plt
import twpca
from twpca import TWPCA
%matplotlib inline

%load_ext autoreload
%autoreload 2

check identity warp does not change data appreciably



In [2]:

    
_, _, data = twpca.datasets.jittered_neuron()
model = TWPCA(data, n_components=1, warpinit='identity')



In [3]:

    
np.all(np.isclose(model.params['warp'], np.arange(model.shared_length), atol=1e-5, rtol=2))









    Out[3]:





True



In [4]:

    
np.nanmax(np.abs(model.transform() - data)) < 1e-5









    Out[4]:





True

check that shift initialization for warp solves the simple toy problem



In [5]:

    
model = TWPCA(data, n_components=1, warpinit='shift')



In [6]:

    
plt.imshow(np.squeeze(model.transform()))









    Out[6]:





<matplotlib.image.AxesImage at 0x1209ebb70>