Showing ValueError shapes 1 3 and 1 3 not aligned 3 dim 1 1 dim 0

Question

I am trying to use the following matrices and perform a dot product as shown in the code  I checked the size of the matrices and all are  3  1  but it is throwing me error for the last two dot products   coordinate1    -7 173  -2 314  2 811   coordinate2    -5 204  -3 598  3 323   coordinate3    -3 922  -3 881  4 044   coordinate4    -2 734  -3 794  3 085    import numpy as np  from numpy import matrix coordinate1i matrix coordinate1  coordinate2i matrix coordinate2  coordinate3i matrix coordinate3  coordinate4i matrix coordinate4   b0   coordinate1i - coordinate2i b1   coordinate3i - coordinate2i b2   coordinate4i - coordinate3i  n1   np cross b0  b1  n2   np cross b2  b1   n12cross   np cross n1 n2  x1  np cross n1 b1  np linalg norm b1  print np shape x1  print np shape n2  np asarray x1  np asarray n2   y   np dot x1 n2  x   np dot n1 n2   return np degrees np arctan2 y  x

User · Answer

The column of the first matrix and the row of the second matrix should be equal and the order should be like this only

column of first matrix = row of second matrix

and do not follow the below step

row of first matrix  = column of second matrix

it will throw an error

User · Answer

Unlike standard arithmetic  which desires matching dimensions  dot products require that the dimensions are one of     X     A  B  dot  Y     B  C  - gt   X     Y     A  C   where     means  0 or more different values  B   dot  B  C  - gt   C    A  B  dot  B   - gt   A    B   dot  B   - gt       Your problem is that you are using np matrix  which is totally unnecessary in your code - the main purpose of np matrix is to translate a   b into np dot a  b   As a general rule  np matrix is probably not a good choice

User · Answer

By converting the matrix to array by using     n12   np squeeze np asarray n2    X12   np squeeze np asarray x1     solved the issue

User · Answer

numpy dot a  b  out None    Dot product of two arrays   For N dimensions it is a sum product over the last axis of a and the second-to-last of b   Documentation  numpy dot

[python] Showing ValueError: shapes (1,3) and (1,3) not aligned: 3 (dim 1) != 1 (dim 0)

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