Python Numpy.dot() 尺寸未对齐
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Numpy.dot() dimensions not aligned
提问by arnoutaertgeerts
I'm having trouble giving the right input to the scipy.signal.dlsimmethod.
我无法为该scipy.signal.dlsim方法提供正确的输入。
The method requires the 4 state space matrices:
该方法需要 4 个状态空间矩阵：
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])
and an input vector which I build in the following way:
以及我以下列方式构建的输入向量：
inputs = np.array([
data['input1'].values(),
data['input2'].values(),
data['input3'].values(),
data['input4'].values(),
data['input5'].values()
])
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:
这将创建一个具有(5x752)维度的输入矩阵（我有 752 个数据点）。所以我对输入矩阵进行转置来预处理我的数据：
inputs = np.transpose(inputs)
The inputs matrix now has the (752x5)dimensions I presume are necessary for the simulation algorithm of scipy.
输入矩阵现在具有(752x5)我认为 scipy 的模拟算法所必需的维度。
When I execute the method, I get the following error:
当我执行该方法时，出现以下错误：
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)
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).
我知道 scipy 无法进行这种乘法运算，但我不知道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，尺寸会更糟（1x752）。
Am I missing something here?
我在这里错过了什么吗？
采纳答案by arnoutaertgeerts
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).
该numpy.dot()方法分别适用于矩阵和数组。我将某个地方的数组转换为矩阵，以便能够轻松读取导致此错误的维度。如果向量被解释为矩阵，则 Numpy 将其视为行向量。这给出了尺寸错误：(4x5) x (1x5)。
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)
当 numpy 将向量视为数组时，会numpy.dot()自动进行正确的乘法，因为向量被视为列向量并且np.dot()可以正确计算：(4x5) x (5x1)
