Notice that the strides attribute of the ndarray object referenced by x$,$ y$,$ and z are all different. You should understand why. For example, if you print y$,$ the $3$

and $7$

elements are swapped from how they appear in the figure above:

$>>>$ y

array$([[-2.,-7.],$

$[-3.,-8.]],$ dtype$=$float$32)$

$>>>$ z

array$([[-2.,-7.],$

$[-3.,-8.]],$ dtype$=$float$32)$

Write Python code that creates objects in memory as depicted in the diagram. Write your code in the cell below. Do NOT create any Python list objects in your solution, not even temporarily or as arguments to the np$.$array function. Hint: You should use the arange, slicing, transpose $($T$),$ negation, assignment, and copy operations provided by Numpy. keep in mind that this is x $=$ # Create the base array $\text{'}$x$\text{'}$ with the specified values and shape $(3,5)$

x$\_$values $=[0,1,-2,-3,4,5,6,-7,-8,9,10,11,12,13,14]$

x $=$ np$.$array$($x$\_$values, dtype$=$np$.$float$32).$reshape$(3,5)$