Numpy Vector (N,1) dimension -> (N,) dimension conversion

by

reshape works for this

a  = np.arange(3)        # a.shape  = (3,)
b  = a.reshape((3,1))    # b.shape  = (3,1)
b2 = a.reshape((-1,1))   # b2.shape = (3,1)
c  = b.reshape((3,))     # c.shape  = (3,)
c2 = b.reshape((-1,))    # c2.shape = (3,)

note also that reshape doesn’t copy the data unless it needs to for the new shape (which it doesn’t need to do here):

a.__array_interface__['data']   # (22356720, False)
b.__array_interface__['data']   # (22356720, False)
c.__array_interface__['data']   # (22356720, False)

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