Parameters ---------- dims : str or sequence of str Name(s) of the the data dimension(s). Must be either a string (only for 1D data) or a sequence of strings with length equal to the number of dimensions. data : array_like
(
self,
dims,
data: T_DuckArray | np.typing.ArrayLike,
attrs=None,
encoding=None,
fastpath=False,
)
| 368 | __slots__ = ("_attrs", "_data", "_dims", "_encoding") |
| 369 | |
| 370 | def __init__( |
| 371 | self, |
| 372 | dims, |
| 373 | data: T_DuckArray | np.typing.ArrayLike, |
| 374 | attrs=None, |
| 375 | encoding=None, |
| 376 | fastpath=False, |
| 377 | ): |
| 378 | """ |
| 379 | Parameters |
| 380 | ---------- |
| 381 | dims : str or sequence of str |
| 382 | Name(s) of the the data dimension(s). Must be either a string (only |
| 383 | for 1D data) or a sequence of strings with length equal to the |
| 384 | number of dimensions. |
| 385 | data : array_like |
| 386 | Data array which supports numpy-like data access. |
| 387 | attrs : dict_like or None, optional |
| 388 | Attributes to assign to the new variable. If None (default), an |
| 389 | empty attribute dictionary is initialized. |
| 390 | (see FAQ, :ref:`approach to metadata`) |
| 391 | encoding : dict_like or None, optional |
| 392 | Dictionary specifying how to encode this array's data into a |
| 393 | serialized format like netCDF4. Currently used keys (for netCDF) |
| 394 | include '_FillValue', 'scale_factor', 'add_offset' and 'dtype'. |
| 395 | Well-behaved code to serialize a Variable should ignore |
| 396 | unrecognized encoding items. |
| 397 | """ |
| 398 | super().__init__( |
| 399 | dims=dims, data=as_compatible_data(data, fastpath=fastpath), attrs=attrs |
| 400 | ) |
| 401 | |
| 402 | self._encoding: dict[Any, Any] | None = None |
| 403 | if encoding is not None: |
| 404 | self.encoding = encoding |
| 405 | |
| 406 | def _new( |
| 407 | self, |
no test coverage detected