xorbits.numpy.fromiter#
- xorbits.numpy.fromiter(iter, dtype, count=- 1, *, like=None)#
Create a new 1-dimensional array from an iterable object.
- 参数
iter (iterable object) – An iterable object providing data for the array.
dtype (data-type) –
The data-type of the returned array.
在 1.23(numpy) 版更改: Object and subarray dtypes are now supported (note that the final result is not 1-D for a subarray dtype).
count (int, optional) – The number of items to read from iterable. The default is -1, which means all data is read.
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
out – The output array.
- 返回类型
ndarray
提示
Specify count to improve performance. It allows
fromiter
to pre-allocate the output array, instead of resizing it on demand.实际案例
>>> iterable = (x*x for x in range(5)) >>> np.fromiter(iterable, float) array([ 0., 1., 4., 9., 16.])
A carefully constructed subarray dtype will lead to higher dimensional results:
>>> iterable = ((x+1, x+2) for x in range(5)) >>> np.fromiter(iterable, dtype=np.dtype((int, 2))) array([[1, 2], [2, 3], [3, 4], [4, 5], [5, 6]])
警告
This method has not been implemented yet. Xorbits will try to execute it with numpy.
This docstring was copied from numpy.