numpy.ones() in Python

The Python numpy.ones() function generates a fresh array with specific size and data type, where each element is assigned a value of 1. This function closely resembles the numpy zeros() function.

arguments of the numpy.ones() function

The syntax for the numpy.ones() function is as follows:

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.
  • 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.
  • The order defines the whether to store multi-dimensional array in row-major (C-style) or column-major (Fortran-style) order in memory.

Here is an example of how the Python numpy.ones() function can be used.

Let’s examine a few instances of building arrays using the numpy ones() function.

Creating an array with a single dimension, filled with 1s.

import numpy as np

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

Result:

[1. 1. 1.]

Take note that the elements in the array have a default data type of float, which is why the values for “one” are displayed as 1.

2. Forming an array with multiple dimensions.

import numpy as np

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

Result:

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

A NumPy array with integer data type, consisting of all ones.

import numpy as np

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

The result:

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

4. Creating a NumPy array with a tuple data type and filled with ones.

We have the option to define the array elements as a tuple, along with their respective data types.

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)

Give me one option to paraphrase the following sentence natively: “Output.”

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

Source: Documentation for Application Programming Interface (API)

Paraphrased: Documentation about the Application Programming Interface (API) is being referenced.

 

 

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