本文整理匯總了Python中numpy.loads方法的典型用法代碼示例。如果您正苦於以下問題：Python numpy.loads方法的具體用法？Python numpy.loads怎麽用？Python numpy.loads使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類numpy的用法示例。
在下文中一共展示了numpy.loads方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: read_qa_comat
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import loads [as 別名]
def read_qa_comat(filename):
qa_comat_dict = {}
print 'read qa_comat ...'
with open(filename) as fin:
for l in tqdm(fin):
to = l.strip().split('\t')
#print 'test len(to): ', len(to)
m = np.loads(base64.b32decode(to[1]))
# print 'test m: ', m
# to[0] key which is qid_uid_rid; to[1] is the corresponding
# 3-row numpy array to denote the qa co-occur matrix
m0 = np.asarray(m[0], dtype=np.int16)
m1 = np.asarray(m[1], dtype=np.int16)
qa_comat_dict[to[0]] = [m0,m1,m[2]]
return qa_comat_dict
# Convert Embedding Dict 2 numpy array 示例2: loads
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import loads [as 別名]
def loads(*args, **kwargs):
# NumPy 1.15.0, 2017-12-10
warnings.warn(
"np.loads is deprecated, use pickle.loads instead",
DeprecationWarning, stacklevel=2)
return pickle.loads(*args, **kwargs) 示例3: deserialise_nparr
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import loads [as 別名]
def deserialise_nparr(arr_str):
arr = np.loads(base64.b64decode(arr_str))
return np.array(arr, dtype=np.float32) 示例4: from_rpc_dict
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import loads [as 別名]
def from_rpc_dict(cls, d):
if d is None:
return None
data = numpy.loads(base64.b64decode(d["data"].encode('utf-8')))
data_shape_and_dtype = data.shape, data.dtype # TODO: DataAndMetadata from_rpc_dict fails for RGB
intensity_calibration = Calibration.from_rpc_dict(d.get("intensity_calibration"))
if "dimensional_calibrations" in d:
dimensional_calibrations = [Calibration.from_rpc_dict(dc) for dc in d.get("dimensional_calibrations")]
else:
dimensional_calibrations = None
metadata = d.get("metadata", {})
timestamp = datetime.datetime(*map(int, re.split('[^\d]', d.get("timestamp")))) if "timestamp" in d else None
return DataAndCalibration(lambda: data, data_shape_and_dtype, intensity_calibration, dimensional_calibrations, metadata, timestamp)