numpy.trapz

# numpy.cross¶

`numpy.``cross`(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None)[source]

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

The cross product of a and b in 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.

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 axisa, axisb and axisc. c : ndarray Vector cross product(s). ValueError When the dimension of the vector(s) in a and/or b does not equal 2 or 3.

`inner`
Inner product
`outer`
Outer product.
`ix_`
Construct index arrays.

Notes

New in version 1.9.0.

Supports full broadcasting of the inputs.

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)
-3
```

Multiple vector cross-products. Note that the direction of the cross product vector is defined by the 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 axisc keyword.

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

Change the vector definition of x and y using axisa and 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]])
```