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numpy.ndarray.flat() in Python

  • Difficulty Level : Basic
  • Last Updated : 21 Jun, 2021

The numpy.ndarray.flat() function is used as a 1_D iterator over N-dimensional arrays. 
It is not a subclass of, Python’s built-in iterator object, otherwise it a numpy.flatiter instance. 
Syntax : 

numpy.ndarray.flat()

Parameters : 

index : [tuple(int)] index of the values to iterate

Return : 
 

1-D iteration of array

Code 1 : Working on 2D array 
 

Python




# Python Program illustrating
# working of ndarray.flat()
 
import numpy as geek
 
# Working on 1D iteration of 2D array
array = geek.arange(15).reshape(3, 5)
print("2D array : \n",array )
 
# Using flat() : 1D iterator over range
print("\nUsing Array : ", array.flat[2:6])
 
# Using flat() to Print 1D represented array
print("\n1D representation of array : \n ->", array.flat[0:15])

Output : 
 

2D array : 
 [[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]]

Using Array :  [2 3 4 5]

1D representation of array : 
 -> [ 0  1  2 ..., 12 13 14]

Code 2 : Changing the values of array 
 

Python




# Python Program illustrating
# working of ndarray.flat()
 
import numpy as geek
 
# Working on 1D iteration of 2D array
array = geek.arange(15).reshape(3, 5)
print("2D array : \n",array )
 
# All elements set to 1
array.flat = 1
print("\nAll Values set to 1 : \n", array)
 
array.flat[3:6] = 8
array.flat[8:10] = 9
print("Changing values in a range : \n", array)   

Output : 
 

2D array : 
 [[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]]

All Values set to 1 : 
 [[1 1 1 1 1]
 [1 1 1 1 1]
 [1 1 1 1 1]]

Changing values in a range : 
 [[1 1 1 8 8]
 [8 1 1 9 9]
 [1 1 1 1 1]]

What actually numpy.flatiter is ? 
A flatiter iterator is returned by x.flat for any array x. It allows iterating(in row-major manner)over N-dimensional arrays, either in a for-loop or by calling its next method.
Code 3 : Role of numpy.flatitter() 
 

Python




# Python Program illustrating
# working of ndarray.flat()
 
import numpy as geek
 
# Working on 1D iteration of 2D array
array = geek.arange(15).reshape(3, 5)
print("2D array : \n",array )
 
print("\nID array : \n", array.flat[0:15])        
 
print("\nType of array,flat() : ", type(array.flat))
 
for i in array.flat:
    print(i, end = ' ')

Output : 
 

2D array : 
 [[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]]

ID array : 
 [ 0  1  2 ..., 12 13 14]

Type of array,flat() :  
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 

References : 
https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.flat.html#numpy.ndarray.flat
Note : 
These codes won’t run on online-ID. Please run them on your systems to explore the working. 
This article is contributed by Mohit Gupta_OMG 😀. If you like GeeksforGeeks and would like to contribute, you can also write an article using write.geeksforgeeks.org or mail your article to review-team@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
 


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