[Solved] What is the output of this code snippet? from scipy.optimize import minimize obj_fun = lambda x: (x[0]-2)**2 + (x[1]-3)**2 constraint = {'type':... What is the output of this code snippet? | SciPy

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What is the output of this code snippet?

from scipy.optimize import minimize

obj_fun = lambda x: (x[0]-2)**2 + (x[1]-3)**2
constraint = {'type': 'ineq', 'fun': lambda x: x[0] + x[1] - 4}
result = minimize(obj_fun, [0, 0], constraints=constraint, method='SLSQP')
print(round(result.fun, 2))

A0.00

B1.00

C2.00

D4.00

Step-by-Step Solution

Solution:

Step 1: Understand the objective function
The function measures distance squared from point (2,3).
Step 2: Apply the constraint and minimize
The constraint requires x[0] + x[1] >= 4. The closest point to (2,3) on this line is (1,3), giving value (1-2)^2+(3-3)^2=1.
Final Answer:
1.00 -> Option B
Quick Check:
Minimum distance squared with constraint = 1.00 [OK]

Quick Trick: Check closest point on constraint line to target point [OK]

Common Mistakes:

Ignoring the constraint
Rounding incorrectly
Confusing objective function value with variables

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What is the output of this code snippet?

Step 1: Understand the objective function

Step 2: Apply the constraint and minimize

Final Answer:

Quick Check:

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