def json_numpy_obj_hook(dct):
"""
Decodes a previously encoded numpy ndarray with proper shape and dtype,
or an encoded KeywordRegistry.
:param dct: (dict) json encoded ndarray
:return: (ndarray) if input was an encoded ndarray
"""
if isinstance(dct, dict) and '__ndarray__' in dct:
# data = base64.b64decode(dct['__ndarray__'])
data = dct['__ndarray__']
return np.asarray(data, dct['dtype']).reshape(dct['shape'])
special_keys = ['level', 'coefficients', 'amplitude', 'kappa',
'base', 'shift', 'mean', 'sd', 'u', 'tau', 'offset']
if isinstance(dct, dict) and any(k in special_keys for k in dct):
# print("json_numpy_obj_hook: {0} type {1}".format(dct,type(dct)))
for k in dct:
if type(dct[k]) is list:
dct[k] = np.asarray(dct[k])
if '_KWR_ARGS' in dct:
return KeywordRegistry.from_json(dct)
if '_KWR_ARGS' in dct:
return KeywordRegistry.from_json(dct)
return dct
def test_jsonify(model_registry):
json = model_registry.to_json()
unjson = KeywordRegistry.from_json(json)
unjson.keywords == model_registry.keywords