从磁盘加载 NumPy 的 .npz 格式的稀疏矩阵。注意：这与 SciPy 的 save_npz() 输出不进行二进制兼容。此二进制格式目前不稳定。仅加载本包保存的文件。
参数
| 名称 |
类型 |
描述 |
默认值 |
filename
|
类文件对象、字符串或 pathlib.Path
|
要读取的文件。类文件对象必须支持 seek() 和 read() 方法。
|
必需
|
返回值
示例
有关用法示例，请参阅 sparse.save_npz。
另请参阅
源代码位于 sparse/numba_backend/_io.py
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132 | def load_npz(filename):
"""Load a sparse matrix in numpy's `.npz` format from disk.
Note: This is not binary compatible with scipy's `save_npz()`
output. This binary format is not currently stable.
Will only load files saved by this package.
Parameters
----------
filename : file-like object, string, or pathlib.Path
The file to read. File-like objects must support the
`seek()` and `read()` methods.
Returns
-------
SparseArray
The sparse matrix at path `filename`.
Examples
--------
See [`sparse.save_npz`][] for usage examples.
See Also
--------
- [`sparse.save_npz`][]
- [`scipy.sparse.save_npz`][]
- [`scipy.sparse.load_npz`][]
- [`numpy.savez`][]
- [`numpy.load`][]
"""
with np.load(filename) as fp:
try:
coords = fp["coords"]
data = fp["data"]
shape = tuple(fp["shape"])
fill_value = fp["fill_value"][()]
return COO(
coords=coords,
data=data,
shape=shape,
sorted=True,
has_duplicates=False,
fill_value=fill_value,
)
except KeyError:
pass
try:
data = fp["data"]
indices = fp["indices"]
indptr = fp["indptr"]
comp_axes = fp["compressed_axes"]
shape = tuple(fp["shape"])
fill_value = fp["fill_value"][()]
return GCXS(
(data, indices, indptr),
shape=shape,
fill_value=fill_value,
compressed_axes=comp_axes,
)
except KeyError as e:
raise RuntimeError(f"The file {filename!s} does not contain a valid sparse matrix") from e
|