# numpy.einsum() Method

• Last Updated : 10 Aug, 2020

In NumPy, we can find Einstein’s summation convention of two given multidimensional arrays with the help of numpy.einsum(). We will pass two arrays as a parameter and it will return the Einstein’s summation convention.

Syntax: numpy.einsum()

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning - Basic Level Course

Parameter: Two arrays.

Return : It will return the Einstein’s summation convention.

Example 1:

## Python

 `import` `numpy as np`` ` ` ` `array1 ``=` `np.array([``1``, ``2``, ``3``])``array2 ``=` `np.array([``4``, ``5``, ``6``])`` ` `# Original 1-d arrays``print``(array1)``print``(array2)``r ``=` `np.einsum(``"n,n"``, a, b)`` ` `# Einstein’s summation convention of ``# the said arrays``print``(r)`

Output:

```[1 2 3]
[4 5 6]
32
```

Example 2:

## Python

 `import` `numpy as np`` ` ` ` `ar1 ``=` `np.arange(``9``).reshape(``3``, ``3``)``ar2 ``=` `np.arange(``10``, ``19``).reshape(``3``, ``3``)`` ` `# Original Higher dimension``print``(ar1)`` ` `print``(ar2)``print``("")``r ``=` `np.einsum(``"mk,kn"``, ar1, ar2)`` ` `# Einstein’s summation convention of ``# the said arrays``print``(r)`

Output:

```[[0 1 2]
[3 4 5]
[6 7 8]]
[[10 11 12]
[13 14 15]
[16 17 18]]

[[ 45  48  51]
[162 174 186]
[279 300 321]]```

My Personal Notes arrow_drop_up