python中numpy.zeros(np.zeros)的使用方法

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翻译：

用法：zeros(shape, dtype=float, order='C')

返回：返回来一个给定形状和类型的用0填充的数组；

参数：shape:形状

dtype:数据类型，可选参数，默认numpy.float64

dtype类型：

t ,位域,如t4代表4位

b,布尔值，true or false

i,整数,如i8(64位）

u,无符号整数，u8(64位）

f,浮点数，f8（64位）

c,浮点负数，

o,对象，

s,a，字符串，s24

u,unicode,u24

order:可选参数，c代表与c语言类似，行优先；F代表列优先

例子：

复制代码

np.zeros(5)
array([ 0., 0., 0., 0., 0.])

np.zeros((5,), dtype=np.int)
array([0, 0, 0, 0, 0])

np.zeros((2, 1))
array([[ 0.],
    [ 0.]])

s = (2,2)
np.zeros(s)
array([[ 0., 0.],
    [ 0., 0.]])

np.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) # custom dtype
array([(0, 0), (0, 0)],
   dtype=[('x', '<i4'), ('y', '<i4')])

########################################################

zeros(shape, dtype=float, order='C')

Return a new array of given shape and type, filled with zeros.

Parameters
----------
shape : int or sequence of ints
  Shape of the new array, e.g., ``(2, 3)`` or ``2``.
dtype : data-type, optional
  The desired data-type for the array, e.g., `numpy.int8`. Default is
  `numpy.float64`.
order : {'C', 'F'}, optional
  Whether to store multidimensional data in C- or Fortran-contiguous
  (row- or column-wise) order in memory.

Returns
-------
out : ndarray
  Array of zeros with the given shape, dtype, and order.

See Also
--------
zeros_like : Return an array of zeros with shape and type of input.
ones_like : Return an array of ones with shape and type of input.
empty_like : Return an empty array with shape and type of input.
ones : Return a new array setting values to one.
empty : Return a new uninitialized array.

Examples
--------
np.zeros(5)
array([ 0., 0., 0., 0., 0.])

np.zeros((5,), dtype=np.int)
array([0, 0, 0, 0, 0])

np.zeros((2, 1))
array([[ 0.],
    [ 0.]])

s = (2,2)
np.zeros(s)
array([[ 0., 0.],
    [ 0., 0.]])

np.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) # custom dtype
array([(0, 0), (0, 0)],
   dtype=[('x', '<i4'), ('y', '<i4')])
Type:   builtin_function_or_method

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np.zeros(5)
array([ 0., 0., 0., 0., 0.])


np.zeros((5,), dtype=np.int)
array([0, 0, 0, 0, 0])


np.zeros((2, 1))
array([[ 0.],
    [ 0.]])


s = (2,2)
np.zeros(s)
array([[ 0., 0.],
    [ 0., 0.]])


np.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) # custom dtype
array([(0, 0), (0, 0)],
   dtype=[('x', '<i4'), ('y', '<i4')])


########################################################

zeros(shape, dtype=float, order='C')



Return a new array of given shape and type, filled with zeros.


Parameters
----------
shape : int or sequence of ints
  Shape of the new array, e.g., ``(2, 3)`` or ``2``.
dtype : data-type, optional
  The desired data-type for the array, e.g., `numpy.int8`. Default is
  `numpy.float64`.
order : {'C', 'F'}, optional
  Whether to store multidimensional data in C- or Fortran-contiguous
  (row- or column-wise) order in memory.


Returns
-------
out : ndarray
  Array of zeros with the given shape, dtype, and order.


See Also
--------
zeros_like : Return an array of zeros with shape and type of input.
ones_like : Return an array of ones with shape and type of input.
empty_like : Return an empty array with shape and type of input.
ones : Return a new array setting values to one.
empty : Return a new uninitialized array.


Examples
--------
np.zeros(5)
array([ 0., 0., 0., 0., 0.])


np.zeros((5,), dtype=np.int)
array([0, 0, 0, 0, 0])


np.zeros((2, 1))
array([[ 0.],
    [ 0.]])


s = (2,2)
np.zeros(s)
array([[ 0., 0.],
    [ 0., 0.]])


np.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) # custom dtype
array([(0, 0), (0, 0)],
   dtype=[('x', '<i4'), ('y', '<i4')])
Type:   builtin_function_or_method