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import base64 import json import numpy as np
''' Implementation taken from: http://stackoverflow.com/a/24375113 '''
class NumpyEncoder(json.JSONEncoder): def default(self, obj): """ if input object is a ndarray it will be converted into a dict holding dtype, shape and the data base64 encoded """ if isinstance(obj, np.ndarray): if np.prod(obj.shape) <= 16 and obj.dtype == np.float64: return dict(__ndarray__=obj.tolist()) else: data_b64 = base64.b64encode(obj.data) return dict(__ndarray__=data_b64, dtype=str(obj.dtype), shape=obj.shape) return json.JSONEncoder.default(self, obj)
class NumpyConvertEncoder(json.JSONEncoder): def default(self, obj): """ if input object is a ndarray it will be converted to a Python list with ndarray.tolist """ if isinstance(obj, np.ndarray): return obj.tolist() return json.JSONEncoder.default(self, obj)
def NumpyDecoder(dct): """ Decodes a previously encoded numpy ndarray with proper shape and dtype :param dct: (dict) json encoded ndarray :return: (ndarray) if input was an encoded ndarray """ if isinstance(dct, dict) and '__ndarray__' in dct:
if 'dtype' in dct: data = base64.b64decode(dct['__ndarray__']) return np.frombuffer(data, dct['dtype']).reshape(dct['shape']) else: return np.array(dct['__ndarray__']) return dct
def encode(dataObj): return json.dumps(dataObj, cls=NumpyEncoder)
def decode(dataStream): return json.loads(dataStream, object_hook=NumpyDecoder)
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