本文整理汇总了Python中__builtin__.all方法的典型用法代码示例。如果您正苦于以下问题:Python __builtin__.all方法的具体用法?Python __builtin__.all怎么用?Python __builtin__.all使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类__builtin__
的用法示例。
在下文中一共展示了__builtin__.all方法的11个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: load
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def load(file):
"""
Wrapper around cPickle.load which accepts either a file-like object or
a filename.
Note that the NumPy binary format is not based on pickle/cPickle anymore.
For details on the preferred way of loading and saving files, see `load`
and `save`.
See Also
--------
load, save
"""
if isinstance(file, type("")):
file = open(file, "rb")
return pickle.load(file)
# These are all essentially abbreviations
# These might wind up in a special abbreviations module
示例2: __init__
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def __init__(self):
# The tree, which should be built.
self._tree = []
# List of all open constructs
self._open_blocks = []
# Nodes to which the open blocks have to be appended when closed
self._path = []
# Nr. of open blocks when file was opened. Used for checking whether all
# blocks have been closed, when file processing finishes.
self._nr_prev_blocks = []
# Current node, to which content should be added
self._curnode = self._tree
# Current file
self._curfile = None
示例3: _validate_axis
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def _validate_axis(axis, ndim, argname):
try:
axis = [operator.index(axis)]
except TypeError:
axis = list(axis)
axis = [a + ndim if a < 0 else a for a in axis]
if not builtins.all(0 <= a < ndim for a in axis):
raise ValueError('invalid axis for this array in `%s` argument' %
argname)
if len(set(axis)) != len(axis):
raise ValueError('repeated axis in `%s` argument' % argname)
return axis
示例4: _maketup
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def _maketup(descr, val):
dt = dtype(descr)
# Place val in all scalar tuples:
fields = dt.fields
if fields is None:
return val
else:
res = [_maketup(fields[name][0], val) for name in dt.names]
return tuple(res)
示例5: identity
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def identity(n, dtype=None):
"""
Return the identity array.
The identity array is a square array with ones on
the main diagonal.
Parameters
----------
n : int
Number of rows (and columns) in `n` x `n` output.
dtype : data-type, optional
Data-type of the output. Defaults to ``float``.
Returns
-------
out : ndarray
`n` x `n` array with its main diagonal set to one,
and all other elements 0.
Examples
--------
>>> np.identity(3)
array([[ 1., 0., 0.],
[ 0., 1., 0.],
[ 0., 0., 1.]])
"""
from numpy import eye
return eye(n, dtype=dtype)
示例6: array_equal
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def array_equal(a1, a2):
"""
True if two arrays have the same shape and elements, False otherwise.
Parameters
----------
a1, a2 : array_like
Input arrays.
Returns
-------
b : bool
Returns True if the arrays are equal.
See Also
--------
allclose: Returns True if two arrays are element-wise equal within a
tolerance.
array_equiv: Returns True if input arrays are shape consistent and all
elements equal.
Examples
--------
>>> np.array_equal([1, 2], [1, 2])
True
>>> np.array_equal(np.array([1, 2]), np.array([1, 2]))
True
>>> np.array_equal([1, 2], [1, 2, 3])
False
>>> np.array_equal([1, 2], [1, 4])
False
"""
try:
a1, a2 = asarray(a1), asarray(a2)
except:
return False
if a1.shape != a2.shape:
return False
return bool(asarray(a1 == a2).all())
示例7: any
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def any(items):
for item in items:
if item:
return True
return False
# ---all() from Python 2.5 ---
示例8: all
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def all(items):
return reduce(operator.__and__, items)
# --- test if interpreter supports yield keyword ---
示例9: all
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def all(items):
return reduce(operator.__and__, items)
示例10: geterr
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def geterr():
"""
Get the current way of handling floating-point errors.
Returns
-------
res : dict
A dictionary with keys "divide", "over", "under", and "invalid",
whose values are from the strings "ignore", "print", "log", "warn",
"raise", and "call". The keys represent possible floating-point
exceptions, and the values define how these exceptions are handled.
See Also
--------
geterrcall, seterr, seterrcall
Notes
-----
For complete documentation of the types of floating-point exceptions and
treatment options, see `seterr`.
Examples
--------
>>> np.geterr()
{'over': 'warn', 'divide': 'warn', 'invalid': 'warn',
'under': 'ignore'}
>>> np.arange(3.) / np.arange(3.)
array([ NaN, 1., 1.])
>>> oldsettings = np.seterr(all='warn', over='raise')
>>> np.geterr()
{'over': 'raise', 'divide': 'warn', 'invalid': 'warn', 'under': 'warn'}
>>> np.arange(3.) / np.arange(3.)
__main__:1: RuntimeWarning: invalid value encountered in divide
array([ NaN, 1., 1.])
"""
maskvalue = umath.geterrobj()[1]
mask = 7
res = {}
val = (maskvalue >> SHIFT_DIVIDEBYZERO) & mask
res['divide'] = _errdict_rev[val]
val = (maskvalue >> SHIFT_OVERFLOW) & mask
res['over'] = _errdict_rev[val]
val = (maskvalue >> SHIFT_UNDERFLOW) & mask
res['under'] = _errdict_rev[val]
val = (maskvalue >> SHIFT_INVALID) & mask
res['invalid'] = _errdict_rev[val]
return res
示例11: geterrcall
# 需要导入模块: import __builtin__ [as 别名]
# 或者: from __builtin__ import all [as 别名]
def geterrcall():
"""
Return the current callback function used on floating-point errors.
When the error handling for a floating-point error (one of "divide",
"over", "under", or "invalid") is set to 'call' or 'log', the function
that is called or the log instance that is written to is returned by
`geterrcall`. This function or log instance has been set with
`seterrcall`.
Returns
-------
errobj : callable, log instance or None
The current error handler. If no handler was set through `seterrcall`,
``None`` is returned.
See Also
--------
seterrcall, seterr, geterr
Notes
-----
For complete documentation of the types of floating-point exceptions and
treatment options, see `seterr`.
Examples
--------
>>> np.geterrcall() # we did not yet set a handler, returns None
>>> oldsettings = np.seterr(all='call')
>>> def err_handler(type, flag):
... print("Floating point error (%s), with flag %s" % (type, flag))
>>> oldhandler = np.seterrcall(err_handler)
>>> np.array([1, 2, 3]) / 0.0
Floating point error (divide by zero), with flag 1
array([ Inf, Inf, Inf])
>>> cur_handler = np.geterrcall()
>>> cur_handler is err_handler
True
"""
return umath.geterrobj()[2]