Given an array of locations in memory of n dimensions we want to find out what ordering it has in memory.  For example, given the following input array [[[ 0 4 8 12] [16 20 24 28] [32 36 40 44]] [[48 52 56 60] [64 68 72 76] [80 84 88 92]]] your function has to return the tuple: [2,1,0] As a suggestion: - Loop through the number of dimensions - For each dimension generate a list of slices equivalent to the above indexing notation - Get the first two elements of each axis - Order the axes by the difference between those two elements Complete the code: def get_storage_order(r): import numpy as np return to check the code manually: r = np.array([[[ 0, 4, 8, 12], [32, 36, 40, 44], [64, 68, 72, 76]], [[16, 20, 24, 28], [48, 52, 56, 60], [80, 84, 88, 92]]])   get_storage_order(r)

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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Given an array of locations in memory of n dimensions we want to find out what ordering it has in memory. 

For example, given the following input array

[[[ 0 4 8 12] [16 20 24 28] [32 36 40 44]]

[[48 52 56 60] [64 68 72 76] [80 84 88 92]]]

your function has to return the tuple: [2,1,0]

As a suggestion:

- Loop through the number of dimensions

- For each dimension generate a list of slices equivalent to the above indexing notation

- Get the first two elements of each axis

- Order the axes by the difference between those two elements

Complete the code:

def get_storage_order(r):

import numpy as np

return

to check the code manually:

r = np.array([[[ 0, 4, 8, 12], [32, 36, 40, 44], [64, 68, 72, 76]], [[16, 20, 24, 28], [48, 52, 56, 60], [80, 84, 88, 92]]])
 
get_storage_order(r)
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