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cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None)

The cross product of a and b in $R^3$ is a vector perpendicular to both a and b. If a and b are arrays of vectors, the vectors are defined by the last axis of a and b by default, and these axes can have dimensions 2 or 3. Where the dimension of either a or b is 2, the third component of the input vector is assumed to be zero and the cross product calculated accordingly. In cases where both input vectors have dimension 2, the z-component of the cross product is returned.

Notes

versionadded

Supports full broadcasting of the inputs.

Parameters

a : array_like: Components of the first vector(s).
b : array_like: Components of the second vector(s).
axisa : int, optional: Axis of a that defines the vector(s). By default, the last axis.
axisb : int, optional: Axis of b that defines the vector(s). By default, the last axis.
axisc : int, optional: Axis of c containing the cross product vector(s). Ignored if both input vectors have dimension 2, as the return is scalar. By default, the last axis.
axis : int, optional: If defined, the axis of a, b and c that defines the vector(s) and cross product(s). Overrides :None:None:`axisa`, :None:None:`axisb` and :None:None:`axisc`.

Raises

ValueError: When the dimension of the vector(s) in a and/or b does not equal 2 or 3.

Returns

c : ndarray: Vector cross product(s).

Return the cross product of two (arrays of) vectors.

Examples

Vector cross-product.

>>> x = [1, 2, 3]
... y = [4, 5, 6]
... np.cross(x, y)
array([-3,  6, -3])

One vector with dimension 2.

>>> x = [1, 2]
... y = [4, 5, 6]
... np.cross(x, y)
array([12, -6, -3])

Equivalently:

>>> x = [1, 2, 0]
... y = [4, 5, 6]
... np.cross(x, y)
array([12, -6, -3])

Both vectors with dimension 2.

>>> x = [1,2]
... y = [4,5]
... np.cross(x, y)
array(-3)

Multiple vector cross-products. Note that the direction of the cross product vector is defined by the :None:None:`right-hand rule`.

>>> x = np.array([[1,2,3], [4,5,6]])
... y = np.array([[4,5,6], [1,2,3]])
... np.cross(x, y)
array([[-3,  6, -3],
       [ 3, -6,  3]])

The orientation of c can be changed using the :None:None:`axisc` keyword.

>>> np.cross(x, y, axisc=0)
array([[-3,  3],
       [ 6, -6],
       [-3,  3]])

Change the vector definition of x and :None:None:`y` using :None:None:`axisa` and :None:None:`axisb`.

>>> x = np.array([[1,2,3], [4,5,6], [7, 8, 9]])
... y = np.array([[7, 8, 9], [4,5,6], [1,2,3]])
... np.cross(x, y)
array([[ -6,  12,  -6],
       [  0,   0,   0],
       [  6, -12,   6]])

>>> np.cross(x, y, axisa=0, axisb=0)
array([[-24,  48, -24],
       [-30,  60, -30],
       [-36,  72, -36]])

See :

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