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I wont create a matrix of matrix with numpy.array, this matrix only need two elements, the comand is:

numpy.array([m1,m2])

this work fine indpendently of the matrices size, except when a matrix have a dimension in one. Example:

m1 = numpy.ones((2,2))
m2 = numpy.ones((2,1))
numpy.array([m1,m2])

In this case show error... and the shape for the matrices are (2,2) and (2,1) but for some reason i think that the dimension 1 is the problem. Someone know as fix this problem. Thanks!

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  • The arrays differ in size, so it can't make a neat 3d array. If the arrays differ in the first dimension it can make a (2,) shape object dtype array. But with the same 1st dimension, np.array throws an error. Maybe you shouldn't be creating such an array! Commented Dec 10, 2019 at 23:15
  • What exactly are you expecting? Can you get there without using np.array? Remember, an object dtype array is little better than a list, and in some ways, worse. Commented Dec 10, 2019 at 23:19
  • Another way to phrase this - np.array([m1,m2]) is an unreliable way of making a (2,) shape object dtype array. Better M=np.empty(2, object) and M[0]=m1 and M[1]=m2 (or some variation on that). Commented Dec 10, 2019 at 23:35

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This appears to be a known bug, or maybe just an undesirable behavior in numpy.

https://github.com/numpy/numpy/issues/7453

I would definitely question why this particular arrangement is appealing, though.
Obv not for the matrix arithmetic operations, since your arrays are of varying nth-dimension.

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