xorbits.numpy.fromiter#
- xorbits.numpy.fromiter(iter, dtype, count=- 1, *, like=None)#
Create a new 1-dimensional array from an iterable object.
- Parameters
iter (iterable object) – An iterable object providing data for the array.
dtype (data-type) –
The data-type of the returned array.
Changed in version 1.23(numpy): 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.New in version 1.20.0(numpy).
- Returns
out – The output array.
- Return type
ndarray
Notes
Specify count to improve performance. It allows
fromiter
to pre-allocate the output array, instead of resizing it on demand.Examples
>>> 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]])
Warning
This method has not been implemented yet. Xorbits will try to execute it with numpy.
This docstring was copied from numpy.