Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN: 9780133594140
Author: James Kurose, Keith Ross
Publisher: PEARSON
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Generate equally spaced coordinates
We wish to generate n +1 equally-spaced x coordinates in [a, b].
0.0
0.5
1.0
Compose a function linspace( a,b,n ) which accepts a left-hand bound a, a right-hand boundb (both float S), and a number of intervals n (an int ), and returns a
list containing the coordinates dividing the space equally. n should have the default value of 10.
For instance, linspace( 0,1,10 ) and linspace( 0,1 ) should both return the list:
[ 0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0 ]
Note that the length of this list is n +1= 11 and that both the left- and right-hand bounds are included. You may use a for loop or a while loop to implement the solution to this
question. You may also assume that a < b, so don't worry about testing or swapping those values. Finally, please note that small numerical errors are permissible, e.g., 1.00000004 or
similar.
Note that this is not the default behavior of numpy.linspace in some particulars. Please don't confuse these later on in the course.
Answer*
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Transcribed Image Text:Generate equally spaced coordinates We wish to generate n +1 equally-spaced x coordinates in [a, b]. 0.0 0.5 1.0 Compose a function linspace( a,b,n ) which accepts a left-hand bound a, a right-hand boundb (both float S), and a number of intervals n (an int ), and returns a list containing the coordinates dividing the space equally. n should have the default value of 10. For instance, linspace( 0,1,10 ) and linspace( 0,1 ) should both return the list: [ 0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0 ] Note that the length of this list is n +1= 11 and that both the left- and right-hand bounds are included. You may use a for loop or a while loop to implement the solution to this question. You may also assume that a < b, so don't worry about testing or swapping those values. Finally, please note that small numerical errors are permissible, e.g., 1.00000004 or similar. Note that this is not the default behavior of numpy.linspace in some particulars. Please don't confuse these later on in the course. Answer*
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