ValueError:对象的深度太小，不适合需要的数组

I've searched and find out this may be a problem concerning types. But I tried to force the array to float using astype didn't work out. This must be a simple error, however im a beginner. About the problem: im trying to form the spatial correlation matrix bewteen the signals of all mics.

我搜索并发现这可能是一个关于类型的问题。但我试图用astype来强制数组浮动，但没有成功。这一定是一个简单的错误，但我是初学者。关于这个问题:我正在尝试形成一个空间相关矩阵，在所有麦克风的信号中。

 R_a[k][l] = np.correlate(self.mic_list[k].delayed_signal,self.mic_list[l].delayed_signal)

where this class has a mic_list which is a list of mic, which is another class that has this method

这个类有一个mic_list，它是一个mic的列表，它是另一个有这个方法的类?

def add_delayed_signal (self, delayed_signal):
    self.delayed_signal = delayed_signal

Thanks you in advanced.

谢谢你在发达。

1 个解决方案

#1

I'm guessing R_a is a 2-dimensional array. What np.correlate does is to compute the cross-correlation between two signals, and gives you a vector as a result (not a scalar).

我猜R_a是一个二维数组。np。关联是计算两个信号之间的相互关系，并给出一个结果向量(而不是标量)。

What you're looking for is probably np.cov or np.corrcoef. These are also vectorized approaches to getting the result you want.

你要找的可能是np。浸或np.corrcoef。这些也是获取您想要的结果的矢量化方法。

For example:

例如:

>>> x = np.random.randn(10)
>>> y = np.random.randn(10)
>>> X = np.vstack((x, y))
>>> X
array([[ 1.45841294, -0.16430013, -0.20782822,  0.08979425, -1.38337166,
         0.36488053, -2.57135737,  0.81215918, -0.54081983,  0.30421112],
       [-0.79416305,  1.14511318, -0.4962483 , -0.42647021, -0.59925241,
        -0.45612051, -0.02566026, -1.7668091 , -1.63098627,  0.3761437 ]])
>>> np.cov(X)    
array([[ 1.28563113, -0.20563105],
       [-0.20563105,  0.74178773]])

Is this what you're looking for?

这就是你要找的吗?

#1