xorbits.numpy.fromfunction#
- xorbits.numpy.fromfunction(function, shape, *, dtype=<class 'float'>, like=None, **kwargs)#
Construct an array by executing a function over each coordinate.
The resulting array therefore has a value
fn(x, y, z)
at coordinate(x, y, z)
.- 参数
function (callable) – The function is called with N parameters, where N is the rank of shape. Each parameter represents the coordinates of the array varying along a specific axis. For example, if shape were
(2, 2)
, then the parameters would bearray([[0, 0], [1, 1]])
andarray([[0, 1], [0, 1]])
shape ((N,) tuple of ints) – Shape of the output array, which also determines the shape of the coordinate arrays passed to function.
dtype (data-type, optional) – Data-type of the coordinate arrays passed to function. By default, dtype is float.
like (array_like, optional) –
Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as
like
supports the__array_function__
protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.1.20.0(numpy) 新版功能.
- 返回
fromfunction – The result of the call to function is passed back directly. Therefore the shape of fromfunction is completely determined by function. If function returns a scalar value, the shape of fromfunction would not match the shape parameter.
- 返回类型
any
提示
Keywords other than dtype and like are passed to function.
实际案例
>>> np.fromfunction(lambda i, j: i, (2, 2), dtype=float) array([[0., 0.], [1., 1.]])
>>> np.fromfunction(lambda i, j: j, (2, 2), dtype=float) array([[0., 1.], [0., 1.]])
>>> np.fromfunction(lambda i, j: i == j, (3, 3), dtype=int) array([[ True, False, False], [False, True, False], [False, False, True]])
>>> np.fromfunction(lambda i, j: i + j, (3, 3), dtype=int) array([[0, 1, 2], [1, 2, 3], [2, 3, 4]])
警告
This method has not been implemented yet. Xorbits will try to execute it with numpy.
This docstring was copied from numpy.