numpy.ones() in Python

Python numpy.ones() function returns a new array of given shape and data type, where the element’s value is set to 1. This function is very similar to numpy zeros() function.

The Python numpy.ones() function returns a new array of the given shape and data type, where the value of the elements is set to 1. This function is very similar to the numpy zeros() function.

numpy.ones() function arguments ( numpy.ones() function arguments )

The numpy.ones() function syntax is:

The syntax of the numpy.ones() function is:

ones(shape, dtype=None, order='C')

• The shape is an int or tuple of ints to define the size of the array. If we just specify an int variable, a one-dimensional array will be returned. For a tuple of ints, the array of given shape will be returned.
  shape is an int or a tuple of ints that defines the size of the array. If we specify only one int variable, a 1D array will be returned. For a tuple of integers, returns an array of the given shape.
• The dtype is an optional parameter with default value as a float. It’s used to specify the data type of the array, for example, int.
  dtype is an optional parameter and defaults to float. It is used to specify the data type of the array, such as int.
• The order defines the whether to store multi-dimensional array in row-major (C-style) or column-major (Fortran-style) order in memory.
  The order defines whether to store multidimensional arrays in memory in row-major (C-style) or column-major (Fortran-style) order.

Python numpy.ones（）示例 (Python numpy.ones() Examples)

Let’s look at some examples of creating arrays using the numpy ones() function.

Let's see some examples of creating arrays using the numpyones () function.

1. Creating one - dimensional array with ones

import numpy as np

array_1d = np.ones(3)
print(array_1d)

Output:

输出：

[1. 1. 1.]

Notice that the elements are having the default data type as the float. That’s why the ones are 1. in the array.

请注意，元素的默认数据类型为float。 这就是数组中1.的原因。

2.创建多维数组 (2. Creating Multi-dimensional array)

import numpy as np

array_2d = np.ones((2, 3))
print(array_2d)

Output:

输出：

[[1. 1. 1.]
 [1. 1. 1.]]

3.具有int数据类型的NumPy个数组 (3. NumPy ones array with int data type)

import numpy as np

array_2d_int = np.ones((2, 3), dtype=int)
print(array_2d_int)

Output:

输出：

[[1 1 1]
 [1 1 1]]

4.具有元组数据类型和一个的NumPy数组 (4. NumPy Array with Tuple Data Type and Ones)

We can specify the array elements as a tuple and specify their data types too.

我们可以将数组元素指定为元组 ，也可以指定其数据类型。

import numpy as np

array_mix_type = np.ones((2, 2), dtype=[('x', 'int'), ('y', 'float')])
print(array_mix_type)
print(array_mix_type.dtype)

Output:

输出：

[[(1, 1.) (1, 1.)]
 [(1, 1.) (1, 1.)]]
[('x', '<i8'), ('y', '<f8')]

Python numpy.ones() Example

Python numpy.ones（）示例

Reference: API Doc

参考 ： API文档

翻译自: https://www.journaldev.com/32792/numpy-ones-in-python