TypeError: minimize() missing 1 required positional argument: 'x0'
时间: 2023-08-18 14:38:59 浏览: 88
这个错误提示是因为`minimize()`函数需要传入初始点`x0`参数,但是你没有提供。你需要在调用`minimize()`函数时传入`x0`参数,例如:
```python
import numpy as np
from scipy.optimize import minimize
def objective(x):
return x[0]**2 + x[1]**2
x0 = np.array([0, 0]) # 初始点
sol = minimize(objective, x0, method='SLSQP')
print(sol)
```
在上面的代码中,`x0`是一个包含两个元素的数组,表示初始点的坐标。你可以根据具体问题设置初始点的值。注意,`minimize()`函数的第一个参数是目标函数,第二个参数是初始点,第三个参数是优化算法的名称。
相关问题
TypeError: minimize() missing 1 required positional argument: 'var_list'
This error occurs when the `minimize` function is called without providing the required argument `var_list`.
The `minimize` function is used to minimize a scalar function of one or more variables using optimization algorithms. The `var_list` argument is used to specify the variables that the function should be minimized with respect to.
To fix this error, make sure to provide the `var_list` argument when calling the `minimize` function. The `var_list` argument should be a list of variables that the function should be minimized with respect to.
Here is an example of how to use the `minimize` function with the `var_list` argument:
```
import tensorflow as tf
# Define the function to be minimized
def f(x, y):
return x**2 + y**2
# Define the variables to be minimized with respect to
x = tf.Variable(1.0)
y = tf.Variable(2.0)
var_list = [x, y]
# Define the optimizer
optimizer = tf.optimizers.Adam()
# Minimize the function
minimizer = optimizer.minimize(lambda: f(x, y), var_list=var_list)
# Run the minimizer
for i in range(100):
minimizer.run()
# Print the final values of x and y
print("x =", x.numpy())
print("y =", y.numpy())
```
typeerror: minimize() missing 1 required positional argument: 'var_list'
看起来您遇到了一个 TypeError 错误,该错误提示 minimize() 函数缺少必需的位置参数 'var_list'。这通常意味着您需要在函数调用中提供一个名为 var_list 的变量列表参数,以便 minimize() 函数能够正常运行。请检查您的代码,确保您正确传递了必需的参数,并使用正确的参数名称和格式。如果您需要更多的帮助,请提供更多的代码和上下文详细信息,我会尽力帮助您解决这个问题。
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