def _load_embeddings(self, trial_folder):
X = []
for embed_json in Tools.search(trial_folder, ('embed_', ),
substr=True):
with open(embed_json, 'r') as f:
D = json.load(f)
x = np.zeros((len(list(D)), Config.TCN_EMB_SIZE), dtype=float)
for ii, key in enumerate(sorted(list(D))):
x[ii, :] = np.array(D[key])
X.append(np.copy(x))
X = np.stack(X, axis=0)
X = np.mean(X, axis=0)
return (trial_folder, X)
def _init_dimred(self, data_root, n_components):
Y = []
pbar = tqdm(Tools.search(data_root, ('embed_left.json',
'embed_middle.json',
'embed_right.json',
'embed_steady.json',
'embed_mobile.json')))
pbar.set_description('load tcn embeddings')
for embed_file in pbar:
with open(embed_file, 'r') as f:
embed_dict = json.load(f)
for k, embedding in embed_dict.items():
if np.isnan(embedding).any():
pyout(k, embed_file)
sys.exit(0)
Y.append(embedding)
Y = np.array(Y)
return self._dimred_fit(Y, n_components=n_components)