题目
题目
单项选择题

Question at position 14 You want to minmize a differentiable function f(x,y) but decide to use scipy.optimize.fsolve instead of scipy.optimize.minimize. Which of the following equations, or systems of equations, would you need to solve using fsolve to find the minimum of f(x,y)? Let fx(x,y) and fy(x,y) denote the partial derivatives of f with respect to x and y, respectively. fy(x,y)=0fx(x,y)=0 and fy(x,y)=0fx(x,y)=0f(x,y)=0You cannot find the minimum of f(x,y) using fsolve.

选项
A.𝑓 𝑦 ( 𝑥 , 𝑦 ) = 0
B.𝑓 𝑥 ( 𝑥 , 𝑦 ) = 0 and 𝑓 𝑦 ( 𝑥 , 𝑦 ) = 0
C.𝑓 𝑥 ( 𝑥 , 𝑦 ) = 0
D.𝑓 ( 𝑥 , 𝑦 ) = 0
E.You cannot find the minimum of 𝑓 ( 𝑥 , 𝑦 ) using fsolve.
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标准答案
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思路分析
The problem asks which equations you would need to solve with fsolve in order to locate the minimum of a differentiable function f(x, y). This hinges on finding stationary points where the gradient is zero. Option A: "f_y(x, y) = 0". This only sets the partial derivative with respect to y to zero. It ignores the x-direction, so you could miss critical points wh......Login to view full explanation

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位置14的问题 You want to minmize a differentiable function f(x,y) but decide to use scipy.optimize.fsolve instead of scipy.optimize.minimize. Which of the following equations, or systems of equations, would you need to solve using fsolve to find the minimum of f(x,y)? Let fx(x,y) and fy(x,y) denote the partial derivatives of f with respect to x and y, respectively. fy(x,y)=0fx(x,y)=0 and fy(x,y)=0fx(x,y)=0f(x,y)=0You cannot find the minimum of f(x,y) using fsolve.

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