배열¶
- class Array(dtype: str, shape: list[int], stype: str, data: bytes)[소스]¶
- class Array(ndarray: ndarray[Any, dtype[Any]])
기반 클래스:
object
배열 유형.
A dataclass containing serialized data from an array-like or tensor-like object along with metadata about it. The class can be initialized in one of two ways:
By specifying explicit values for dtype, shape, stype, and data.
By providing a NumPy ndarray (via the ndarray argument).
In scenario (2), the dtype, shape, stype, and data are automatically derived from the input. In scenario (1), these fields must be specified manually.
- 매개변수:
dtype (Optional[str] (default: None)) – A string representing the data type of the serialized object (e.g. “float32”). Only required if you are not passing in a ndarray.
shape (Optional[list[int]] (default: None)) – A list representing the shape of the unserialized array-like object. Only required if you are not passing in a ndarray.
stype (Optional[str] (default: None)) – A string indicating the serialization mechanism used to generate the bytes in data from an array-like or tensor-like object. Only required if you are not passing in a ndarray.
data (Optional[bytes] (default: None)) – A buffer of bytes containing the data. Only required if you are not passing in a ndarray.
ndarray (Optional[NDArray] (default: None)) – A NumPy ndarray. If provided, the dtype, shape, stype, and data fields are derived automatically from it.
예제
Initializing by specifying all fields directly:
>>> arr1 = Array( >>> dtype="float32", >>> shape=[3, 3], >>> stype="numpy.ndarray", >>> data=b"serialized_data...", >>> )
Initializing with a NumPy ndarray:
>>> import numpy as np >>> arr2 = Array(np.random.randn(3, 3))
메소드
from_numpy_ndarray
(ndarray)NumPy에서 배열을 만듭니다.
numpy
()배열을 NumPy 배열로 반환합니다.
속성
dtype
shape
stype
data