Numpy.dot() dimensions not aligned
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)
.
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)
arnoutaertgeerts
Updated on January 21, 2020Comments
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arnoutaertgeerts over 4 years
I'm having trouble giving the right input to the
scipy.signal.dlsim
method.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])
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() ])
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)
The inputs matrix now has the
(752x5)
dimensions I presume are necessary for the simulation algorithm of scipy.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)
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).
Am I missing something here?
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Muno almost 8 years"When numpy sees the vector as an array ... because the vector is seen as a column vector..." In other words, running
np.asarray(MatrixOrArray)
before usingnp.dot()
should do the trick? And this is so, becausenp.dot()
only works on columns? -
Jam1 about 6 yearscan you please show us what you did to get the solution?