def get_diag(embbeded, diagramas):
homology_dimensions = (0, 1)
VR = hl.VietorisRipsPersistence(homology_dimensions=[0, 1], n_jobs=1)
sliding_window = ts.SlidingWindow(embbeded.shape[1] - 1, 4)
embedded_window = sliding_window.fit_transform(embbeded.T)
#sliding_window3 = ts.SlidingWindow(embbeded3.shape[1] - 1, 4)
#embedded_window3 = sliding_window3.fit_transform(embbeded3.T)
diagrams = VR.fit_transform(embedded_window)
#diagrams3 = VR.fit_transform(embedded_window3)
diagrams = diagrams[:, :, :-1]
#diagrams3 = diagrams3[:, :, :-1]
diagrams = [clean_ceros(item) for item in diagrams]
#diagrams3 = [clean_ceros(item) for item in diagrams3]
entropy = persistent_entropy.persistent_entropy(diagrams,
keep_inf=False,
val_inf=None,
normalize=False)
#z = np.zeros((len(diagrams[0]), 1), dtype=int)
#diagrams[0] = np.append(diagrams[0], z, 1)
#diagrams = [list(diagrams[0][item]) for item in range(len(diagrams[0]))]
diagramas.append(diagrams)
#entropy3 = persistent_entropy.persistent_entropy(diagrams3, keep_inf=False, val_inf=None, normalize=False)
entropy = pd.DataFrame(entropy)
#entropy3 = pd.DataFrame(entropy3)
return entropy, diagramas
def get_steps():
steps = [('embedding', ts.SingleTakensEmbedding()),
('window', ts.SlidingWindow(size=6, stride=1)),
('diagram', hl.VietorisRipsPersistence()),
('rescaler', diag.Scaler()),
('filter', diag.Filtering(epsilon=0.1)),
('entropy', diag.PersistenceEntropy(nan_fill_value=0.)),
('scaling', skprep.MinMaxScaler(copy=True))]
return steps
def get_diag2(diagramas):
homology_dimensions = (0, 1)
#Vietoris Rips filter applied
VR = hl.VietorisRipsPersistence(homology_dimensions = [0,1], n_jobs=1)
diagrams = VR.fit_transform(diagramas)
diagrams = diagrams[:, :, :-1]
#clean ceros elements
diagrams = [clean_ceros(item) for item in diagrams]
diagramas.append(diagrams)
return diagramas
def get_diag(embbeded, diagramas):
homology_dimensions = (0, 1)
#Vietoris Rips filter applied
VR = hl.VietorisRipsPersistence(homology_dimensions = [0,1], n_jobs=1)
sliding_window = ts.SlidingWindow(embbeded.shape[1]-1, 4)
embedded_window = sliding_window.fit_transform(embbeded.T)
diagrams = VR.fit_transform(embedded_window)
diagrams = diagrams[:, :, :-1]
#clean ceros elements
diagrams = [clean_ceros(item) for item in diagrams]
entropy = persistent_entropy.persistent_entropy(diagrams, keep_inf=False, val_inf=None, normalize=False)
diagramas.append(diagrams)
entropy = pd.DataFrame(entropy)
return entropy, diagramas