Different Ways to Calculate Magnitude Using Numpy in Python (2025)

We can calculate the magnitude of the vector and magnitude of complex numbers in Python using Numpy. There are different functions available to calculate the magnitude of a vector. Here we are using only three different ways and abs() to calculate the magnitude of the complex number.

Using Numpy functions, it is easy to calculate the magnitude in Python. To find the magnitude of the vector, we need to calculate the length of the vector. So we can say that here we are going to calculate the length of the given vector. To find the magnitude of the complex number, we are using the “absmethod.

Contents

How to get the magnitude of a complex number?

Let us first know how to declare the complex number. There are two possible ways to declare a complex number.

a=4+3i

In the above method, 4 is a real part, and 3 is an imaginary part.

We can also declare the complex numbers in another way. By declaring it as a complex and giving real part and imaginary part as a parameter.

a=complex(4,3)

This is another method to declare complex numbers.

Here we will use the abs() function to calculate the magnitude of a given complex number.

What is abs() function?

Python abs() is a built-in function that returns an absolute value of a number. The argument may be an integer, floating number, or complex number. If we give an integer, it returns an integer. If the given is a floating number, it returns a floating number.

What are the syntax, parameter, and return type of a abs() function?

Syntax

The syntax for abs() function is

abs(value)

Parameters

The input value is given to get an absolute value.

Returns

It will return the absolute value for the given number.

InputReturn value
integerinteger
floatfloat
complex numberthe magnitude of the complex number

Code

a=complex(5,6) print(complex)

Here we are simply assigning a complex number. A variable “a” holds the complex number. Using abs() function to get the magnitude of a complex number.

Output

7.810249675906654

How to get the magnitude of a vector in numpy?

Finding the length of the vector is known as calculating the magnitude of the vector. We can calculate the magnitude using three different functions. They are, linalg.norm(), numpy.dot(), and numpy.einsum() functions. These are useful functions to calculate the magnitude of a given vector.

What is numpy.linalg.norm()?

In Python, it contains a standard library called Numpy. The Numpy contains many functions. Among them, linalg.norm() is one of the functions used to calculate the magnitude of a vector.

What are the syntax, parameters, and return type of a linalg.norm() function?

Syntax

The syntax for linalg.norm() function is

linalg.norm(x, ord=None, axis=None, keepdims=False)

Parameters

  1. x : array_like.
  2. ord : {non-zero, int, inf, -inf, ‘fro’, ‘nuc’}
  3. axis : {None, int, 2-tuple of ints}
  4. keepdims : bool

Returns

It returns the magnitude of a given vector.

Code

import numpy as npa=np.array([1,2,3,4])magnitude=np.linalg.norm(a)print("The given vector is:",a)print("The Magnitude of the given vector is :",magnitude)

First, we need to import the library Numpy. Here we are using linalg.norm to calculate the magnitude of a given vector. A variable “a” holds an array. Using “linalg.norm()” we calculated the magnitude of a vector, and we got the output.

Output

The given vector is: [1 2 3 4]The Magnitude of the given vector is : 5.477225575051661

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What is numpy.dot()?

Numpy.dot() is a function used to calculate the dot product of the vector. It is also possible to calculate the magnitude of the given vector. Here we are using numpy.dot() function to calculate the magnitude of the given vector.

What are the syntax, parameters, and return type of numpy.dot() function?

Syntax

The syntax for numpy.dot() is

numpy.dot(a, b, out=None)

Parameters

  1. a : array_like.
  2. b : array_like.
  3. out : ndarray, optional.

Returns

It returns the magnitude of a given array.

Code

import numpy as npa=np.array([1,2,3,4])magnitude=np.sqrt(a.dot(a))print("The given vector is:",a)print("The Magnitude of the given vector is :",magnitude)

First, we need to import the library Numpy. Here we are using numpy.dot() along with the numpy.sqrt() to calculate the magnitude of a vector. A variable “a” holds an array. Using “numpy.dot()” we calculated the magnitude of the given vector and got the output.

Output

The given vector is: [1 2 3 4]The Magnitude of the given vector is : 5.477225575051661

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What is numpy.einsum()?

numpy.einsum() is used to find the Einstein summation convention. If parameters are provided, we can calculate the Einstein summation convention using this function. Here we are using this function as one possible way to calculate the magnitude of the given vector.

What are the syntax, parameters, and return type of numpy.einsum() function?

Syntax

The syntax for numpy.einsum() is

numpy.einsum(subscripts,*operands,out=None,dtype=None,order='K',casting='safe',optimize=False)

Parameters

  1. subscripts : str.
  2. operands : list of array_like.
  3. out ; ndarray
  4. dtype : {data-type, None}
  5. order : {‘C’, ‘F’, ‘A’, ‘K’}
  6. casting : {‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}
  7. optimize : {False, True, ‘greedy’, ‘optimal’}

Returns

It returns the magnitude of a given array.

Code

import numpy as npa=np.array([1,2,3,4])magnitude=np.sqrt(np.einsum('i,i',a,a))print("The given vector is:",a)print("The Magnitude of the given vector is :",magnitude)

First, we need to import the library Numpy. Here we are using numpy.einsum() along with the numpy.sqrt() to calculate the magnitude of a vector. A variable “a” holds an array. Using “numpy.einsum()” we calculated the magnitude of the given vector and got the output.

Output

The given vector is: [1 2 3 4]The Magnitude of the given vector is : 5.477225575051661

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1.What is the syntax for linalg.norm() function?

The syntax for linalg.norm() function is
linalg.norm(x, ord=None, axis=None, keepdims=False)


2.What is the syntax for numpy.dot() function?

The syntax for numpy.dot() function is
numpy.dot(a, b, out=None)

3.What is the syntax for numpy.einsum() function?

The syntax for numpy.einsum() function is
numpy.einsum(subscripts,*operands,out=None,dtype=None,order=’K’,casting=’safe’,optimize=False)

4.What is the use of linalg.norm() function?

linalg.norm() function is used to find the magnitude of a given vector.

5.What are the different functions to calculate the magnitude?

linalg.norm(), numpy.dot(), and numpy.einsum() are the functions to calculate the magnitude of the vector.

6. What is abs() function?

It is a built-in function available in the python library. It returns an absolute value of a given integer.

7.What is the syntax for abs() function?

The syntax for the abs() function is
abs(value)

8.What the abs() function returns if the given input is a complex number?

The abs() function returns the magnitude of a complex number.

9.How do you find the magnitude of a complex number?

The built-in function abs() available in the Python library is used to calculate the magnitude of a complex number.

Conclusion

We can use those three functions to calculate the magnitude of the given vector. After that, we calculated the magnitude of the given vector. We have to note in this is that all the functions gave the same output as magnitude. Because we gave the same vector as an input. The conclusion is that three functions evaluate the same result only. We can use the abs() function to calculate the magnitude of a complex number.

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Different Ways to Calculate Magnitude Using Numpy in Python (2025)

FAQs

How to find magnitude using NumPy? ›

NumPy: Get the magnitude of a vector in NumPy

np. linalg. norm(x): Calculate the L2 (Euclidean) norm of the array 'x'. The L2 norm is the square root of the sum of the squared elements in the array.

How to get the magnitude of a number in Python? ›

Python abs()

The abs() function returns the absolute value of the given number. If the number is a complex number, abs() returns its magnitude.

What methods can you use to determine the number of dimensions that an NumPy array has? ›

You can get the number of dimensions, shape (length of each dimension), and size (total number of elements) of a NumPy array ( numpy. ndarray ) using the ndim , shape , and size attributes. The built-in len() function returns the size of the first dimension.

How many methods are there in NumPy? ›

Methods in Numpy:
all()diag()hypot()
nanargmin()arange()pv()
nanargmax()place()power()
amax()extract()float_power()
amin()compress()log()
23 more rows
Jul 15, 2024

How can you calculate magnitude? ›

the formula to determine the magnitude of a vector (in two-dimensional space) v = (x, y) is: |v| =√(x2 + y2).

What are the statistical methods available in NumPy? ›

Common NumPy Statistical Functions
FunctionsDescriptions
mean()return the mean of an array
std()return the standard deviation of an array
percentile()return the nth percentile of elements in an array
min()return the minimum element of an array
2 more rows

How to find order of magnitude in Python? ›

Order of magnitude
  1. convert(x, scale): returns the input values as float in the scale provided.
  2. order_of_magnitude(x): returns the order of magnitude exponent of the input values as float.
  3. power_of_ten(x): returns the power of ten corresponding to the order of magnitude of the input values as float.
Apr 29, 2021

How do you print magnitude in Python? ›

The abs() function is a built-in function in Python that returns the absolute value of a number, which means it returns the magnitude of a number without considering its sign. The abs() function returns a positive value, regardless of the input sign.

What is the NumPy size method? ›

size() function count the number of elements along a given axis.
  1. Syntax: numpy.size(arr, axis=None)
  2. Parameters:
  3. arr: [array_like] Input data.
  4. axis: [int, optional] Axis(x,y,z) along which the elements(rows or columns) are counted. ...
  5. Returns: [int] Return the number of elements along a given axis.
Jul 29, 2021

How do I find the dimension of an array in NumPy? ›

Use ndim attribute available with the NumPy array as numpy_array_name. ndim to get the number of dimensions. Alternatively, we can use the shape attribute to get the size of each dimension and then use len() function for the number of dimensions.

How to find the number of elements in a NumPy array? ›

Using the len() function

As you can see, we created a one-dimensional NumPy array called `arr` and then used the `len()` function to get its length. The output is `5`, which is the number of elements in the array.

What are various mathematical functions in NumPy? ›

Arithmetic Functions –
FUNCTIONDESCRIPTION
power()First array elements raised to powers from second array, element-wise.
subtract()Subtract arguments, element-wise.
true_divide()Returns a true division of the inputs, element-wise.
floor_divide()Return the largest integer smaller or equal to the division of the inputs.
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Jun 10, 2024

What are the disadvantages of NumPy? ›

However, NumPy is inefficient in handling such tasks, and routines designed to change, add, combine or delete data within the array can suffer performance limitations because of how NumPy allocates and uses memory.

What are the different data types in NumPy? ›

NumPy Data Types
  • strings - used to represent text data, the text is given under quote marks. e.g. "ABCD"
  • integer - used to represent integer numbers. e.g. -1, -2, -3.
  • float - used to represent real numbers. e.g. 1.2, 42.42.
  • boolean - used to represent True or False.
  • complex - used to represent complex numbers.

How to calculate the magnitude of a matrix? ›

As a matrix may be considered as a generalized number (for which certain computing rules hold), the question of a measure of its magnitude arises. Three methods are commonly used: (1) the maximum coefficient, (2) the norm, and (3) the maximum expansion or bound. |A| = maxN(Ax)/(N(x).

References

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