# PARSE: Physical Attribute Representativity and Stationarity Evaluator
## General information
PARSE is an open source package for representativity analysis of 3D binary images. It aims at representativity analysis for different scalar and vector metrics. Using PARSE library, one can estimate determenistic and statistical representative elementary volumes (dREV and sREV) for these metrics. Stationarity analysis and comparison of different images using vector metrics are also possible.
Currently, we provide the following metrics for REV analysis:
- Porosity.
- Permeability.
- Euler density.
- Correlation functions (two-point probabilty $S_2$, lineal path function $L_2$, cluster function $C_2$, surface-surface function $F_{ss}$, surface-void function $F_{sv}$, pore-size function $P$,
chord length function $p$).
- Pore-network model characterstics (pore and throat numbers, pore and throat radii, connectivity, mean pore and throat radii, mean connectivity).
- Persistence diagrams.
## Prerequisites
Python 3.x and Julia 1.x with packages StatsBase.jl, LinearAlgebra.jl, CorrelationFunctions.jl (version=0.11.0)
and EulerCharacteristic.jl should be installed.
## Installation
To install the latest PyPI release as a library run
```
python3 -m pip install revanalyzer
```
or you can clone this repository and run from local folder
```
python3 -m pip install .
```
## Documentation
Documentation is available here on
[GitHub Pages](https://fatimp.github.io/REVAnalyzer/index.html).
To build the documentation locally clone this repository, then read /docs/README.md
## Tutorials
Numerous Jupiter notebooks with examples which show the functionality of PARSE library are available here:
- [REV analysis for porosity](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_porosity.ipynb)
- [REV analysis for permeability](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_permeability.ipynb)
- [REV analysis for Euler density](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_Euler.ipynb)
- [REV analysis for correlation functions](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_CF.ipynb)
- [REV analysis for pore-network model characteristics](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_PNM_characteristics.ipynb)
- [REV analysis for persistence diagrams](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_PD.ipynb)
- [Comparison of two images using vector metric](https://github.com/fatimp/REVAnalyzer/blob/main/examples/image_compare.ipynb)
- [Stationarity analysis](https://github.com/fatimp/REVAnalyzer/blob/main/examples/stationarity_analysis.ipynb)
## Describing scientific papers
Mathematical backgound for REV analysis, description of metrics used in 'REVAnalyzer' and application evamples with real
porous image data:
[Andrey S. Zubov, Aleksey N. Khlyupin, Marina V. Karsanina, Kirill M. Gerke (2024). En search for representative elementary volume (REV) within heterogeneous materials: A survey of scalar and vector metrics using porous media as an example. Advances in Water Resources, 19, 104762.](https://www.sciencedirect.com/science/article/abs/pii/S0309170824001490)
## Authors
Andrey S. Zubov, Digital Core group, MIPT.
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"description": "# PARSE: Physical Attribute Representativity and Stationarity Evaluator\n\n## General information\n\nPARSE is an open source package for representativity analysis of 3D binary images. It aims at representativity analysis for different scalar and vector metrics. Using PARSE library, one can estimate determenistic and statistical representative elementary volumes (dREV and sREV) for these metrics. Stationarity analysis and comparison of different images using vector metrics are also possible.\n\nCurrently, we provide the following metrics for REV analysis:\n- Porosity.\n- Permeability.\n- Euler density.\n- Correlation functions (two-point probabilty $S_2$, lineal path function $L_2$, cluster function $C_2$, surface-surface function $F_{ss}$, surface-void function $F_{sv}$, pore-size function $P$,\nchord length function $p$).\n- Pore-network model characterstics (pore and throat numbers, pore and throat radii, connectivity, mean pore and throat radii, mean connectivity).\n- Persistence diagrams.\n\n## Prerequisites\n\nPython 3.x and Julia 1.x with packages StatsBase.jl, LinearAlgebra.jl, CorrelationFunctions.jl (version=0.11.0)\nand EulerCharacteristic.jl should be installed.\n\n## Installation\n\nTo install the latest PyPI release as a library run\n\n```\npython3 -m pip install revanalyzer\n```\n\nor you can clone this repository and run from local folder\n\n```\npython3 -m pip install .\n```\n\n## Documentation\n\t\nDocumentation is available here on\n[GitHub Pages](https://fatimp.github.io/REVAnalyzer/index.html).\n\nTo build the documentation locally clone this repository, then read /docs/README.md\n\n## Tutorials\n\nNumerous Jupiter notebooks with examples which show the functionality of PARSE library are available here:\n- [REV analysis for porosity](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_porosity.ipynb)\n- [REV analysis for permeability](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_permeability.ipynb)\n- [REV analysis for Euler density](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_Euler.ipynb)\n- [REV analysis for correlation functions](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_CF.ipynb)\n- [REV analysis for pore-network model characteristics](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_PNM_characteristics.ipynb)\n- [REV analysis for persistence diagrams](https://github.com/fatimp/REVAnalyzer/blob/main/examples/REV_PD.ipynb)\n- [Comparison of two images using vector metric](https://github.com/fatimp/REVAnalyzer/blob/main/examples/image_compare.ipynb)\n- [Stationarity analysis](https://github.com/fatimp/REVAnalyzer/blob/main/examples/stationarity_analysis.ipynb)\n\n## Describing scientific papers\n\nMathematical backgound for REV analysis, description of metrics used in 'REVAnalyzer' and application evamples with real \nporous image data:\n\n[Andrey S. Zubov, Aleksey N. Khlyupin, Marina V. Karsanina, Kirill M. Gerke (2024). En search for representative elementary volume (REV) within heterogeneous materials: A survey of scalar and vector metrics using porous media as an example. Advances in Water Resources, 19, 104762.](https://www.sciencedirect.com/science/article/abs/pii/S0309170824001490)\n\n## Authors\n\nAndrey S. Zubov, Digital Core group, MIPT.\n",
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