Numpy.dot()尺寸未对齐 [英] Numpy.dot() dimensions not aligned

问题描述

我无法为scipy.signal.dlsim方法提供正确的输入.

I'm having trouble giving the right input to the scipy.signal.dlsim method.

该方法需要4个状态空间矩阵:

The method requires the 4 state space matrices:

A = np.array([
    [0.9056, -0.1908, 0.0348, 0.0880],
    [0.0973, 0.8728, 0.4091, -0.0027],
    [0.0068, -0.1694, 0.9729, -0.6131],
    [-0.0264, 0.0014, 0.1094, 0.6551]
    ])

B = np.array([
    [0, -0.0003, -0.0330, -0.0042, -0.0037],
    [0, -0.0005, 0.0513, -0.0869, -0.1812],
    [0, 0.0003, -0.0732, 1.1768, -1.1799],
    [0, -0.0002, -0.0008, 0.2821, -0.4797]
    ])

C = np.array([-0.01394, -0.0941, 0.0564, 0.0435])

D = np.array([0, 0.0004, -0.0055, 0.3326, 0.5383])

和我以以下方式构建的输入向量:

and an input vector which I build in the following way:

inputs = np.array([
    data['input1'].values(),
    data['input2'].values(),
    data['input3'].values(),
    data['input4'].values(),
    data['input5'].values()
])

这将创建一个尺寸为(5x752)的输入矩阵(我有752个数据点).因此，我使用输入矩阵的转置来预处理我的数据:

This creates an inputs matrix with (5x752) dimensions (I have 752 data points). So I take the transpose of the inputs matrix to preprocess my data:

inputs = np.transpose(inputs)

输入矩阵现在具有(752x5)的维数，我认为这对于scipy的仿真算法是必需的.

The inputs matrix now has the (752x5) dimensions I presume are necessary for the simulation algorithm of scipy.

执行该方法时，出现以下错误:

When I execute the method, I get the following error:

    110     # Simulate the system
    111     for i in range(0, out_samples - 1):
--> 112         xout[i+1,:] = np.dot(a, xout[i,:]) + np.dot(b, u_dt[i,:])
    113         yout[i,:] = np.dot(c, xout[i,:]) + np.dot(d, u_dt[i,:])
    114 

ValueError: shapes (4,5) and (1,5) not aligned: 5 (dim 1) != 1 (dim 0)

我知道scipy无法进行这种乘法，但是我不知道我应该以哪种格式将输入数组提供给该方法.如果我不转置矩阵，则尺寸会更糟(1x752).

I understand scipy is unable to make this multiplication but I do not know in which format I should give my inputs array to the method. If I would not transpose the matrix the dimensions would be even worse (1x752).

我在这里错过了什么吗?

Am I missing something here?

推荐答案

numpy.dot()方法分别适用于矩阵和数组.我将数组转换为矩阵，以便能够轻松读取引起此错误的尺寸.如果将向量解释为矩阵，则Numpy会将其视为行向量.这样会出现尺寸错误:(4x5) x (1x5).

The numpy.dot() method works separately for a matrix and an array. I converted the array somewhere to a matrix to be able to easily read the dimensions which caused this error. If the vector is interpreted as a matrix, it is seen by Numpy as a row vector. This gives the dimensions error: (4x5) x (1x5).

当numpy将向量视为数组时，numpy.dot()自动执行正确的乘法运算，因为将向量视为列向量并且可以正确计算np.dot():(4x5) x (5x1)

When numpy sees the vector as an array, numpy.dot() automatically does the right multiplication because the vector is seen as a column vector and the np.dot() can be calculated correctly: (4x5) x (5x1)

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