本文整理匯總了Python中numpy.core.numeric.longdouble方法的典型用法代碼示例。如果您正苦於以下問題：Python numeric.longdouble方法的具體用法？Python numeric.longdouble怎麽用？Python numeric.longdouble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.core.numeric的用法示例。
在下文中一共展示了numeric.longdouble方法的2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: stdout_automatic_parser
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import longdouble [as 別名]
def stdout_automatic_parser(result):
"""
Try and automatically convert strings formatted as tables into a matrix.
Under the hood, this function essentially applies the genfromtxt function
to the stdout.
Args:
result (dict): the result to parse.
"""
np.seterr(all='raise')
parsed = {}
# By default, if dtype is None, the order Numpy tries to convert a string
# to a value is: bool, int, float. We don't like this, since it would give
# us a mixture of integers and doubles in the output, if any integers
# existed in the data. So, we modify the StringMapper's default mapper to
# skip the int check and directly convert numbers to floats.
oldmapper = np.lib._iotools.StringConverter._mapper
np.lib._iotools.StringConverter._mapper = [(nx.bool_, np.lib._iotools.str2bool, False),
(nx.floating, float, nx.nan),
(nx.complexfloating, complex, nx.nan + 0j),
(nx.longdouble, nx.longdouble, nx.nan)]
file_contents = result['output']['stdout']
with warnings.catch_warnings():
warnings.simplefilter("ignore")
parsed = np.genfromtxt(io.StringIO(file_contents))
# Here we restore the original mapper, so no side-effects remain.
np.lib._iotools.StringConverter._mapper = oldmapper
return parsed 示例2: automatic_parser
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import longdouble [as 別名]
def automatic_parser(result, dtypes={}, converters={}):
"""
Try and automatically convert strings formatted as tables into nested
list structures.
Under the hood, this function essentially applies the genfromtxt function
to all files in the output, and passes it the additional kwargs.
Args:
result (dict): the result to parse.
dtypes (dict): a dictionary containing the dtype specification to perform
parsing for each available filename. See the numpy genfromtxt
documentation for more details on how to format these.
"""
np.seterr(all='raise')
parsed = {}
# By default, if dtype is None, the order Numpy tries to convert a string
# to a value is: bool, int, float. We don't like this, since it would give
# us a mixture of integers and doubles in the output, if any integers
# existed in the data. So, we modify the StringMapper's default mapper to
# skip the int check and directly convert numbers to floats.
oldmapper = np.lib._iotools.StringConverter._mapper
np.lib._iotools.StringConverter._mapper = [(nx.bool_, np.lib._iotools.str2bool, False),
(nx.floating, float, nx.nan),
(nx.complexfloating, complex, nx.nan + 0j),
(nx.longdouble, nx.longdouble, nx.nan)]
for filename, contents in result['output'].items():
if dtypes.get(filename) is None:
dtypes[filename] = None
if converters.get(filename) is None:
converters[filename] = None
with warnings.catch_warnings():
warnings.simplefilter("ignore")
parsed[filename] = np.genfromtxt(io.StringIO(contents),
dtype=dtypes[filename],
converters=converters[filename]
).tolist()
# Here we restore the original mapper, so no side-effects remain.
np.lib._iotools.StringConverter._mapper = oldmapper
return parsed