错误：“numpy.ndarray”对象没有属性“exp”

vnjpjtjt 于 2023-08-05 发布在其他

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我使用scipy.optimize.fsolve函数，代码如下：
我试图求解obj函数的值x_1，保持x_2的值不变。应当注意，x_1和x_2的值在0和1之间。我将w_xx、b_xx和y_test的值相加。

import numpy as np
from scipy.optimize import fsolve
y_test = np.array([3.448 ,11.071,3.602 ,11.838,3.512 ,13.78,4.013,15.209,3.339,13.15,3.387,17.419,3.793,15.303,3.92,11.683,3.655 ,14.317]).reshape(9,2)
#weight matrix
w_01 = np.array([0.5524624,0.72511494,0.51372594,-0.6308459]).reshape(2,2)
w_T2 = np.array([[-0.59752214, -0.5804831,   1.4108963,  -0.2634158,  -0.5614638,  -1.0390981, 0.65243214,  0.7106961, -0.5652963,  -0.0601576,   0.90772694, -1.3798463,  -0.40833127, -0.7003734, -0.21786042,  0.27037245]]).reshape(2,8)
w_02 = np.transpose(w_T2)
w_03 = np.array([[-1.0097426,0.32732514,0.24015452,-1.0950012,0.24607354,-0.21128657,-0.89929247,0.5828309,-1.4573368,-1.0770408,0.62045175,-1.2865094,-1.3986484,-1.2846812, 0.9638692 ,1.5144163]]).reshape(2,8)
#Bais matrix
b_01 = np.array([0.859291,0.59829414]).reshape(2,1)
b_02 = np.array([-0.5619188,-0.57078356,0.5717453,-0.5602762,-0.61745477,-0.6130685,0.56874627,0.55697656]).reshape(8,1)
b_03 = np.array([0.23421602,0.48550755]).reshape(2,1)
def sigmoid(x):
    return 1 / (1 + np.exp(-x))
### Defining Obj function
### inp is 2x1 matrix and out is also 2x1 matrix
def objfunction(x1,x2,y):
    inp = np.array([x1,x2]).reshape(2,1)
    out = y.reshape(2,1)
    f = (np.dot(w_03,(np.dot(w_02,(sigmoid(np.dot(w_01,inp) + b_01))) + b_02)) + b_03) - out # value of y
    return f.flatten()
### Calculating Solution
x_1 = 0 ### Inital guess
x_2 = 0.5 
sol = np.zeros((len(y_test),2))
for i,value in enumerate(y_test):
    sol[i] = fsolve(objfunction,x_1,args=(x_2,value))

字符串
错误代码：

p:\python\mimo_fsolve.py:46: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
  inp = np.array([x1,x2]).reshape(2,1)

AttributeError: 'numpy.ndarray' object has no attribute 'exp'

loop of ufunc does not support argument 0 of type numpy.ndarray which has no callable exp method

型

numpy

来源：https://stackoverflow.com/questions/76740350/error-numpy-ndarray-object-has-no-attribute-exp

1条答案

按热度按时间

t30tvxxf1#

为了回答你的主要问题，你得到这个错误的原因是因为fsolve为objfunction提供了一个看起来像x1的np.array([x1])的numpy数组。当您尝试将其与x2（浮点型）组合以生成inp时，会创建一个不规则的数组，因为第一个元素是数组，第二个元素只是一个数字。Numpy不喜欢这样，所以它将数组转换为object数据类型。如果你尝试下面的代码，你可以看到这一点：

print(np.array([np.array([0]), 0]).dtype) # object

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当您尝试在对象数组上执行np.exp时（因为inp是对象数据类型，np.dot(w_01, inp) + b_01也将是），numpy会抛出错误，因为在对象数组上没有np.exp的实现（重读错误，您会看到这就是错误的内容）。
要解决这个问题，可以将inp定义中的x1替换为x1[0]。但是你最终会遇到另一个问题，因为你返回的是f.flatten()，它的形状是(2,)，因为它包含x2，而fsolve期望返回的是(1,)，因为这是它给出的函数。您可以通过获取第一个元素（即f.flatten()[0]）。最后一个问题是，您将sol定义为(n,2)，但您似乎只想存储x_1，因此只需将其设置为1D数组。

def objfunction(x1, x2, y):
    inp = np.array([x1[0], x2]).reshape(2, 1)
    out = y.reshape(2, 1)
    f = (np.dot(w_03, (np.dot(w_02, (sigmoid(np.dot(w_01, inp) + b_01))) +
         b_02)) + b_03) - out  # value of y
    return f.flatten()[0]

x_1 = 0  # Inital guess
x_2 = 0.5
sol = np.zeros((len(y_test)))
for i, value in enumerate(y_test):
    sol[i] = fsolve(objfunction, x_1, args=(x_2, value))

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错误：“numpy.ndarray”对象没有属性“exp”

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