import numpy as np
from scipy.optimize import minimize
# 定义一个简单的目标函数,例如 f(x) = (x-3)^2
def objective_function(x):
return (x - 3) ** 2
# 初始猜测
initial_guess = [0]
# 使用 minimize 优化
result = minimize(objective_function, initial_guess)
# 输出结果
print("最优解(result.x):", result.x)
print("最小函数值(result.fun):", result.fun)
print("优化成功吗?(result.success):", result.success)
print("结束原因(result.message):", result.message)
print("迭代次数(result.nit):", result.nit)
print("函数调用次数(result.nfev):", result.nfev)
打印内容:
最优解(result.x): [2.99999998]
最小函数值(result.fun): 2.5388963550532293e-16
优化成功吗?(result.success): True
结束原因(result.message): Optimization terminated successfully.
迭代次数(result.nit): 2
函数调用次数(result.nfev): 6