How do I make a matrix from multiple lists of matrices?

Question

Hi I am trying to figure out how to create a matrix from other matrices. I have created 3 matrixes from certain calculations and have arrived at 3 matrices of shape (1200,3) each. 1200 represents the rows of number of data set. What I want to extract from each of this Matrix (A, B, C) is to put them in this order for the first of 1200 data points:

[[A[0][0], B[0][0], C[0][0]],    
 [A[0][1], B[0][1], C[0][1]],    
 [A[0][2], B[0][2], C[0][2]]]

This is what I have written so far:

def getRotationMatrix(acc_x_sample, acc_y_sample, acc_z_sample, mag_x_sample, mag_y_sample, mag_z_sample):
    a = np.transpose(np.array([acc_x_sample,acc_y_sample,acc_z_sample]))
    m = np.transpose(np.array([mag_x_sample,mag_y_sample,mag_z_sample]))

    B = np.cross(a,m) # (a x m)
    A = np.cross(B,a) 
    C = a

    R =[]
    for i in range(2):
        R.append(A[i],B[i],C[i])
    return R

To clarify, do you want an output array of shape (1200, 3,3) where each item of shape (1,3,3) is like you are showing in your question? — Gilad Green
– Gilad Green, Commented Sep 18, 2021 at 13:05

Mohamed abdelmagid · Accepted Answer · 2021-09-18 13:25:35Z

5

This seems like a job for np.stack, it can be used to do just that

result = np.stack([A, B, C], axis=2);

You can change the value of axis depending on how you want to merge them.

edited Sep 18, 2021 at 13:25

answered Sep 18, 2021 at 13:21

Mohamed abdelmagid

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3 Comments

Gilad Green Over a year ago

For output as seen in question axis should be 2, but this is a cleaner way of doing this compared to my answer

Mohamed abdelmagid Over a year ago

Thanks, I'll update it right away.

Clarence Chan Over a year ago

Yes! But this works well!

Gilad Green · Accepted Answer · 2021-09-18 13:15:07Z

2

One way to achieve this is as follows:

np.c_[A,B,C].reshape((-1,3,3)).transpose((0,2,1))

First, stack (as columns) the three arrays yielding an array of shape (1200,9). Then, reshape it to the desired shape of (1200,3,3) and lastly, transpose the last two dimensions so each column in the nested 2D array is from either A,B or C.

Example input:

A = np.array([[1,2,3],[4,5,6]])
B = np.array([[-1,-2,-3],[-4,-5,-6]])
C = np.array([[11,12,13],[14,15,16]])
np.c_[A,B,C].reshape((-1,3,3)).transpose((0,2,1))

Output:

array([[[ 1, -1, 11],
        [ 2, -2, 12],
        [ 3, -3, 13]],
       [[ 4, -4, 14],
        [ 5, -5, 15],
        [ 6, -6, 16]]])

answered Sep 18, 2021 at 13:15

Gilad Green

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Comments

Andre · Accepted Answer · 2021-09-18 13:45:49Z

1

The other answers might already be enough for you make it work but here's a small function that does what you want (as I understand):

def new_mat(*arrs):
    
    combined =  np.concatenate([arrs])
    
    return combined[:,0,:].T

edited Sep 18, 2021 at 13:45

answered Sep 18, 2021 at 13:37

Andre

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