[](https://badge.fury.io/py/fpzip)
# fpzip
fpzip is a compression algorithm supporting lossless and lossy encoding for up to 4 dimensional floating point data. This package contains Python C++ bindings for the fpzip algorithm (version 1.3.0). The version number for this package is independent. Python 3.7+ is supported.
```python
import fpzip
import numpy as np
data = np.array(..., dtype=np.float32) # up to 4d float or double array
# Compress data losslessly, interpreting the underlying buffer in C (default) or F order.
compressed_bytes = fpzip.compress(data, precision=0, order='C') # returns byte string
# Back to 3d or 4d float or double array, decode as C (default) or F order.
data_again = fpzip.decompress(compressed_bytes, order='C')
```
## Installation
#### `pip` Binary Installation
```bash
pip install fpzip
```
If we have a precompiled binary available the above command should just work. However, if you have to compile from sounce, it's unfortunately necessary to install numpy first because of a quirk in the Python installation procedure that won't easily recognize when a numpy installation completes in the same process. There are some hacks, but I haven't gotten them to work.
#### `pip` Source Installation
*Requires C++ compiler.*
```bash
pip install numpy
pip install fpzip
```
#### Direct Installation
*Requires C++ compiler.*
```bash
$ pip install numpy
$ python setup.py develop
```
## References
Algorithm and C++ code by Peter Lindstrom and Martin Isenburg. Cython interface code by William Silversmith. Check out [Dr. Lindstrom's site](https://computing.llnl.gov/projects/fpzip) or the [fpzip Github page](https://github.com/LLNL/fpzip).
1. Peter Lindstrom and Martin Isenburg, "[Fast and Efficient Compression of Floating-Point Data,](https://www.researchgate.net/publication/6715625_Fast_and_Efficient_Compression_of_Floating-Point_Data)" IEEE Transactions on Visualization and Computer Graphics, 12(5):1245-1250, September-October 2006, doi:[10.1109/TVCG.2006.143](http://dx.doi.org/10.1109/TVCG.2006.143).
Raw data
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"description": "[](https://badge.fury.io/py/fpzip)\n\n# fpzip\n\nfpzip is a compression algorithm supporting lossless and lossy encoding for up to 4 dimensional floating point data. This package contains Python C++ bindings for the fpzip algorithm (version 1.3.0). The version number for this package is independent. Python 3.7+ is supported.\n\n```python\nimport fpzip\nimport numpy as np\n\ndata = np.array(..., dtype=np.float32) # up to 4d float or double array\n# Compress data losslessly, interpreting the underlying buffer in C (default) or F order.\ncompressed_bytes = fpzip.compress(data, precision=0, order='C') # returns byte string\n# Back to 3d or 4d float or double array, decode as C (default) or F order.\ndata_again = fpzip.decompress(compressed_bytes, order='C') \n```\n\n## Installation\n\n#### `pip` Binary Installation \n\n```bash\npip install fpzip\n```\n\nIf we have a precompiled binary available the above command should just work. However, if you have to compile from sounce, it's unfortunately necessary to install numpy first because of a quirk in the Python installation procedure that won't easily recognize when a numpy installation completes in the same process. There are some hacks, but I haven't gotten them to work.\n\n#### `pip` Source Installation\n\n*Requires C++ compiler.*\n\n```bash\npip install numpy\npip install fpzip\n```\n\n#### Direct Installation\n\n*Requires C++ compiler.* \n\n```bash\n$ pip install numpy\n$ python setup.py develop\n```\n\n## References\n\nAlgorithm and C++ code by Peter Lindstrom and Martin Isenburg. Cython interface code by William Silversmith. Check out [Dr. Lindstrom's site](https://computing.llnl.gov/projects/fpzip) or the [fpzip Github page](https://github.com/LLNL/fpzip).\n\n1. Peter Lindstrom and Martin Isenburg, \"[Fast and Efficient Compression of Floating-Point Data,](https://www.researchgate.net/publication/6715625_Fast_and_Efficient_Compression_of_Floating-Point_Data)\" IEEE Transactions on Visualization and Computer Graphics, 12(5):1245-1250, September-October 2006, doi:[10.1109/TVCG.2006.143](http://dx.doi.org/10.1109/TVCG.2006.143).\n\n",
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