numpoly.vstack

numpoly.vstack(tup: Sequence[numpoly.typing.PolyLike]) → numpoly.baseclass.ndpoly

Stack arrays in sequence vertically (row wise).

This is equivalent to concatenation along the first axis after 1-D arrays of shape (N,) have been reshaped to (1,N). Rebuilds arrays divided by vsplit.

This function makes most sense for arrays with up to 3 dimensions. For instance, for pixel-data with a height (first axis), width (second axis), and r/g/b channels (third axis). The functions concatenate, stack and block provide more general stacking and concatenation operations.

Args:

tup:

The arrays must have the same shape along all but the first axis. 1-D arrays must have the same length.

Return:

The array formed by stacking the given arrays, will be at least 2-D.

Example:

>>> poly1 = numpoly.variable(3)
>>> const1 = numpoly.polynomial([1, 2, 3])
>>> numpoly.vstack([poly1, const1])
polynomial([[q0, q1, q2],
            [1, 2, 3]])
>>> const2 = numpoly.polynomial([[1], [2], [3]])
>>> poly2 = poly1.reshape(3, 1)
>>> numpoly.vstack([const2, poly2])
polynomial([[1],
            [2],
            [3],
            [q0],
            [q1],
            [q2]])