| Name | h5max JSON |
| Version |
0.3.1
JSON |
| download |
| home_page | https://github.com/jdcla/h5max |
| Summary | scipy.sparse support on h5py |
| upload_time | 2022-12-01 09:07:35 |
| maintainer | |
| docs_url | None |
| author | Jim Clauwaert |
| requires_python | >=3.9 |
| license | |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<div align="center">
<h1>h5max</h1>
A utility package built upon `h5py` for easier data saving and loading of sparse data objects.
[](https://pypi.python.org/pypi/h5max/)
[](https://github.com/jdcla/h5max/blob/main/LICENSE.md)
[](https://github.com/jdcla/h5max/issues)
[](https://github.com/jdcla/h5max/stargazers)
</div>
`h5max` handles storing and loading of `scipy.sparse` data structures in `h5py` file objects, which is not natively supported. It assumes a simple data structure where information of individual samples are stored according to the index they occupy within datasets.
<div align="center">
<img src="https://github.com/jdcla/h5max/raw/main/h5max.png" width="600">
</div>
## Installation
```bash
pip install h5max
```
## Usage
```python
import h5py
import h5max
import numpy as np
fh = h5py.File('my_data.h5', 'w')
a = np.zeros((100,100))
b = np.zeros((1000,50))
a[7,1] = 1
b[1,0] = 10
Ms = [a, b]
# store both a, b
h5max.store_sparse(fh, Ms, format='csr')
# load only a (index 0)
a_out = h5max.load_sparse(fh, 0, format='csr')
# load [a,b]
Ms_out = h5max.load_sparse(fh, [0, 1], format='csr')
fh.close()
```
# Package features
- [x] Support for `csr`, `csc`, `coo` sparse types
- [ ] Support for `bsr`, `dia`, `dok`, `lil` sparse types
- [x] Support for overwriting
- [x] Flexible data loading and saving (both as sparse and numpy arrays.)
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