Numpy concatenate 2D arrays with 1D array
Try concatenating X_Yscores[:, None] (or X_Yscores[:, np.newaxis] as imaluengo suggests). This creates a 2D array out of a 1D array.
Example:
A = np.array([1, 2, 3])print A.shapeprint A[:, None].shapeOutput:
(3,)(3,1)
I am not sure if you want something like:
a = np.array( [ [1,2],[3,4] ] )b = np.array( [ 5,6 ] )c = a.ravel()con = np.concatenate( (c,b ) )array([1, 2, 3, 4, 5, 6])OR
np.column_stack( (a,b) )array([[1, 2, 5], [3, 4, 6]])np.row_stack( (a,b) )array([[1, 2], [3, 4], [5, 6]])
You can try this one-liner:
concat = numpy.hstack([a.reshape(dim,-1) for a in [Cscores, Mscores, Tscores, Yscores]])The "secret" here is to reshape using the known, common dimension in one axis, and -1 for the other, and it automatically matches the size (creating a new axis if needed).