Write a function solveNLEs (coefficients) to solve the following set of nonlinear equations where coefficients is a list that contains values for a, b, c. The function should return a list containing the the solutions x, y, z. x² + y² = a xy+yz² = b y²2² +z = c Your function should make use of fsolve from scipy.optimize. Optimisers can be sensitive to the starting estimates of the roots. Set these to [1,1,1] as we have confirmed that they work! For example: Test import numpy as np answer = solveNLEs (np.array([2,2,2])) print (np.round(answer, 5)) # Print rounded answer to avoid floating point errors. import numpy as np answer = solveNLEs (np. array([1,4, -2])) print (np.round(answer, 5)) # Print rounded answer to avoid floating point errors. Result [1. 1. 1.] [ 0.78553 0.61882 -2.38294]
Write a function solveNLEs (coefficients) to solve the following set of nonlinear equations where coefficients is a list that contains values for a, b, c. The function should return a list containing the the solutions x, y, z. x² + y² = a xy+yz² = b y²2² +z = c Your function should make use of fsolve from scipy.optimize. Optimisers can be sensitive to the starting estimates of the roots. Set these to [1,1,1] as we have confirmed that they work! For example: Test import numpy as np answer = solveNLEs (np.array([2,2,2])) print (np.round(answer, 5)) # Print rounded answer to avoid floating point errors. import numpy as np answer = solveNLEs (np. array([1,4, -2])) print (np.round(answer, 5)) # Print rounded answer to avoid floating point errors. Result [1. 1. 1.] [ 0.78553 0.61882 -2.38294]
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
Section: Chapter Questions
Problem 1PE
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write using python
![Write a function solveNLEs (coefficients) to solve the following set of nonlinear equations where coefficients is a list that contains values for a, b, c. The function
should return a list containing the the solutions x, y, z.
x² + y² = a
xy+yz² = b
y² + z = c
Your function should make use of fsolve from scipy.optimize. Optimisers can be sensitive to the starting estimates of the roots. Set these to [1,1,1] as we have
confirmed that they work!
For example:
Test
import numpy as np.
answer = solveNLEs (np.array([2,2,2]))
print (np.round(answer,5)) # Print rounded answer to avoid floating point errors.
import numpy as np
answer = solveNLEs (np.array([1,4, -2]))
print (np.round (answer, 5)) # Print rounded answer to avoid floating point errors.
Result
[1. 1. 1.]
[ 0.78553 0.61882 -2.38294]](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fac4bd707-1db8-4976-9f6d-8edf92850988%2Fe39d5d0d-02c9-4732-939a-5cc7a9847327%2Fsak97ys_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Write a function solveNLEs (coefficients) to solve the following set of nonlinear equations where coefficients is a list that contains values for a, b, c. The function
should return a list containing the the solutions x, y, z.
x² + y² = a
xy+yz² = b
y² + z = c
Your function should make use of fsolve from scipy.optimize. Optimisers can be sensitive to the starting estimates of the roots. Set these to [1,1,1] as we have
confirmed that they work!
For example:
Test
import numpy as np.
answer = solveNLEs (np.array([2,2,2]))
print (np.round(answer,5)) # Print rounded answer to avoid floating point errors.
import numpy as np
answer = solveNLEs (np.array([1,4, -2]))
print (np.round (answer, 5)) # Print rounded answer to avoid floating point errors.
Result
[1. 1. 1.]
[ 0.78553 0.61882 -2.38294]
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