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numpy.ravel () in Python

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Parameters :

  array:  [array_like] Input array.  order:  [C-contiguous, F-contiguous, A-contiguous; optional] C-contiguous order in memory (last index varies the fastest) C order means that operating row-rise on the array will be slightly quicker FORTRAN-contiguous order in memory (first index varies the fastest). F order means that column-wise operations will be faster. ’A’ means to read / write the elements in Fortran-like index order if, array is Fortran contiguous in memory, C-like order otherwise 

Return:

 Flattened array having same type as the Input array and and order as per choice. 

Code 1: Shows that array.ravel is equivalent to reshaping (-1, order = order)

# Python program illustrating
# numpy.ravel () method

  

import numpy as geek

 

array = geek.arange ( 15 ). reshape ( 3 , 5 )

print ( "Original array:" , array)

  
# Outpue comes as [0 1 2 ..., 12 13 14]
# as long output, so this is the path
# shows output in Python

print ( "ravel ():" , array.ravel () )

 
# This shows that array.ravel is equivalent to changing the form (- 1, order = order).

print ( " numpy.ravel () == numpy.reshape (-1) " )

print ( "Reshaping array:" , array.reshape ( - 1 ))

 

Output:

 Original array: [[0 1 2 3 4] [5 6 7 8 9] [10 11 12 13 14]] ravel (): [0 1 2 ..., 12 13 14] numpy.ravel () == numpy.reshape (-1) Reshaping array: [0 1 2 ..., 12 13 14] 

Code 2: Shows order manipulation

Output:

 Original array: [[0 1 2 3 4] [5 6 7 8 9] [10 11 12 13 14]] About numpy.ravel (): numpy.ravel (): [0 1 2 ..., 12 13 14] Maintains A Order: [0 1 2 ..., 12 13 14] array2 [[[0 2 4] [1 3 5]] [[6 8 10] [7 9 11]]] Maintains A Order: [0 1 2 ..., 9 10 11] 

Links:
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.ravel.html#numpy.ravel

Notes:
These codes will not work for online ID. Please run them on your systems to see how they work

This article is provided by Mohit Gupta_OMG

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# Python program illustrating
# numpy.ravel () method

 

import numpy as geek

  

array = geek.arange ( 15 ). Reshape ( 3 , 5 )

print ( "Original array:" , array)

 
# Outpue comes as [0 1 2 ... , 12 13 14]
# as long output, so this is the way
# shows output in Python

 
# Near:

print ( "About numpy.ravel ():" , array.ravel)

 

print ( "numpy.ravel ():" , array.ravel ())

 
# Maintain the order of “A” and “F”

print ( "Maintains A Order:" , array.ravel (order = ’A’ ))

 
# K-order to save order
# "K" means it is not "A" or "F"

array2 = geek.arange ( 12 ). reshape ( 2 , 3 , 2 ). swapaxes ( 1 , 2 )

print ( " ar ray2 " , array2)

print ( "Maintains A Order:" , array2.ravel (order = ’K’ ))