本文整理匯總了Python中numpy.byte_bounds方法的典型用法代碼示例。如果您正苦於以下問題：Python numpy.byte_bounds方法的具體用法？Python numpy.byte_bounds怎麽用？Python numpy.byte_bounds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.byte_bounds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: _reduce_memmap_backed
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import byte_bounds [as 別名]
def _reduce_memmap_backed(a, m):
"""Pickling reduction for memmap backed arrays.
a is expected to be an instance of np.ndarray (or np.memmap)
m is expected to be an instance of np.memmap on the top of the ``base``
attribute ancestry of a. ``m.base`` should be the real python mmap object.
"""
# offset that comes from the striding differences between a and m
a_start, a_end = np.byte_bounds(a)
m_start = np.byte_bounds(m)[0]
offset = a_start - m_start
# offset from the backing memmap
offset += m.offset
if m.flags['F_CONTIGUOUS']:
order = 'F'
else:
# The backing memmap buffer is necessarily contiguous hence C if not
# Fortran
order = 'C'
if a.flags['F_CONTIGUOUS'] or a.flags['C_CONTIGUOUS']:
# If the array is a contiguous view, no need to pass the strides
strides = None
total_buffer_len = None
else:
# Compute the total number of items to map from which the strided
# view will be extracted.
strides = a.strides
total_buffer_len = (a_end - a_start) // a.itemsize
return (_strided_from_memmap,
(m.filename, a.dtype, m.mode, offset, order, a.shape, strides,
total_buffer_len)) 示例2: _reduce_memmap_backed
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import byte_bounds [as 別名]
def _reduce_memmap_backed(a, m):
"""Pickling reduction for memmap backed arrays
a is expected to be an instance of np.ndarray (or np.memmap)
m is expected to be an instance of np.memmap on the top of the ``base``
attribute ancestry of a. ``m.base`` should be the real python mmap object.
"""
# offset that comes from the striding differences between a and m
a_start, a_end = np.byte_bounds(a)
m_start = np.byte_bounds(m)[0]
offset = a_start - m_start
# offset from the backing memmap
offset += m.offset
if m.flags['F_CONTIGUOUS']:
order = 'F'
else:
# The backing memmap buffer is necessarily contiguous hence C if not
# Fortran
order = 'C'
if a.flags['F_CONTIGUOUS'] or a.flags['C_CONTIGUOUS']:
# If the array is a contiguous view, no need to pass the strides
strides = None
total_buffer_len = None
else:
# Compute the total number of items to map from which the strided
# view will be extracted.
strides = a.strides
total_buffer_len = (a_end - a_start) // a.itemsize
return (_strided_from_memmap,
(m.filename, a.dtype, m.mode, offset, order, a.shape, strides,
total_buffer_len)) 示例3: byte_bounds
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import byte_bounds [as 別名]
def byte_bounds(a):
"""
Returns pointers to the end-points of an array.
Parameters
----------
a : ndarray
Input array. It must conform to the Python-side of the array
interface.
Returns
-------
(low, high) : tuple of 2 integers
The first integer is the first byte of the array, the second
integer is just past the last byte of the array. If `a` is not
contiguous it will not use every byte between the (`low`, `high`)
values.
Examples
--------
>>> I = np.eye(2, dtype='f'); I.dtype
dtype('float32')
>>> low, high = np.byte_bounds(I)
>>> high - low == I.size*I.itemsize
True
>>> I = np.eye(2, dtype='G'); I.dtype
dtype('complex192')
>>> low, high = np.byte_bounds(I)
>>> high - low == I.size*I.itemsize
True
"""
ai = a.__array_interface__
a_data = ai['data'][0]
astrides = ai['strides']
ashape = ai['shape']
bytes_a = asarray(a).dtype.itemsize
a_low = a_high = a_data
if astrides is None:
# contiguous case
a_high += a.size * bytes_a
else:
for shape, stride in zip(ashape, astrides):
if stride < 0:
a_low += (shape-1)*stride
else:
a_high += (shape-1)*stride
a_high += bytes_a
return a_low, a_high
#-----------------------------------------------------------------------------
# Function for output and information on the variables used.
#----------------------------------------------------------------------------- 示例4: byte_bounds
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import byte_bounds [as 別名]
def byte_bounds(a):
"""
Returns pointers to the end-points of an array.
Parameters
----------
a : ndarray
Input array. It must conform to the Python-side of the array interface.
Returns
-------
(low, high) : tuple of 2 integers
The first integer is the first byte of the array, the second integer is
just past the last byte of the array. If `a` is not contiguous it
will not use every byte between the (`low`, `high`) values.
Examples
--------
>>> I = np.eye(2, dtype='f'); I.dtype
dtype('float32')
>>> low, high = np.byte_bounds(I)
>>> high - low == I.size*I.itemsize
True
>>> I = np.eye(2, dtype='G'); I.dtype
dtype('complex192')
>>> low, high = np.byte_bounds(I)
>>> high - low == I.size*I.itemsize
True
"""
ai = a.__array_interface__
a_data = ai['data'][0]
astrides = ai['strides']
ashape = ai['shape']
bytes_a = int(ai['typestr'][2:])
a_low = a_high = a_data
if astrides is None: # contiguous case
a_high += a.size * bytes_a
else:
for shape, stride in zip(ashape, astrides):
if stride < 0:
a_low += (shape-1)*stride
else:
a_high += (shape-1)*stride
a_high += bytes_a
return a_low, a_high
#-----------------------------------------------------------------------------
# Function for output and information on the variables used.
#-----------------------------------------------------------------------------