NumPy错误:具有多个元素的数组的真值不明确.使用a.any()或a.all() [英] NumPy Error: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

问题描述

我正在使用numpy处理图像卷积代码:

I am working on an Image Convolution code using numpy:

def CG(A, b, x, imax=10, epsilon = 0.01):
    steps=np.asarray(x)
    i = 0
    r = b - A * x
    d = r.copy()
    delta_new = r.T * r
    delta_0 = delta_new
    while i < imax and delta_new > epsilon**2 * delta_0:
        q = A * d
        alpha = float(delta_new / (d.T * q))
        x = x + alpha * d
        if i%50 == 0:
            r = b - A * x
        else:
            r = r - alpha * q
        delta_old = delta_new
        delta_new = r.T * r
        beta = float(delta_new / delta_old)
        d = r + beta * d
        i = i + 1
        steps = np.append(steps, np.asarray(x), axis=1)
    return steps

我收到以下错误:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

在线while i < imax and delta_new > epsilon**2 * delta_0:

任何人都可以告诉我我做错了什么吗?

Could anyone please tell me what am I doing wrong ?

推荐答案

delta_new和delta_0看起来像是Numpy数组，而Numpy不知道如何比较它们.

It looks like delta_new and delta_0 are Numpy arrays, and Numpy doesn't know how to compare them.

作为一个例子，假设您是否采用了两个随机的Numpy数组并尝试进行比较:

As an example, imagine if you took two random Numpy arrays and tried to compare them:

>>> a = np.array([1, 3, 5])
>>> b = np.array([5, 3, 1])
>>> print(a<b)
array([True, False, False])
>>> bool(a<b)
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

您必须基本上选择"如何将所有数组中所有值的比较折叠成一个布尔值.

You have to basically "pick" how to collapse the comparisons of all of the values across all of your arrays down to a single bool.

>>> (a<b).any()
True

>>> (a<b).all()
False

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