| Name | PyCZINV JSON |
| Version |
0.1.4
JSON |
| download |
| home_page | None |
| Summary | Python package for geophysical inversion tailored to Critical Zone Science. |
| upload_time | 2024-10-11 17:46:21 |
| maintainer | None |
| docs_url | None |
| author | Hang Chen |
| requires_python | None |
| license | MIT |
| keywords |
geophysical
inversion
critical
zone
science
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# PyCZINV
PyCZINV is a Python package designed for facilitating geophysical inversion processes, with a focus on applications within critical zone science. It aims to simplify and streamline the execution of joint inversion, coupled inversion, and time-lapse inversion to help researchers and practitioners easily derive the subsurface properties they are interested in.
## Features
- **Joint Inversion**: Combine data from different geophysical methods to improve inversion results.
- **Coupled Inversion**: Link inversion processes to consider mutual constraints.
- **Time-Lapse Inversion**: Analyze changes over time to observe dynamic processes.
- **Rock Physics**: Rock Physics models for hydrologic and geophysical properties transformation
- **Data Preprocessing**: Utilities for preparing your geophysical data for inversion.
- **Visualization**: Tools for visualizing inversion results and data.
## Installation
PyCZINV requires Python 3.6 or newer. You can install PyCZINV using pip:
```bash
pip install pyczinv
## Rock Physics Models
### 1. Voigt-Reuss-Hill (VRH) Mixing Model
The VRH model is used to estimate the effective bulk modulus, shear modulus, and density of composite materials made of different minerals.
**Usage**:
```python
from PyCZINV import VRH_model
# Fraction, Bulk modulus (K), Shear modulus (G), and Density (rho) of minerals
f = [0.35, 0.25, 0.2, 0.125, 0.075]
K = [55.4, 36.6, 75.6, 46.7, 50.4]
G = [28.1, 45, 25.6, 23.65, 27.4]
rho = [2560, 2650, 2630, 2540, 3050]
Km, Gm, rho_b = VRH_model(f=f, K=K, G=G, rho=rho)
print(Km, Gm, rho_b)
Raw data
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"description": "# PyCZINV\r\n\r\nPyCZINV is a Python package designed for facilitating geophysical inversion processes, with a focus on applications within critical zone science. It aims to simplify and streamline the execution of joint inversion, coupled inversion, and time-lapse inversion to help researchers and practitioners easily derive the subsurface properties they are interested in.\r\n\r\n## Features\r\n\r\n- **Joint Inversion**: Combine data from different geophysical methods to improve inversion results.\r\n- **Coupled Inversion**: Link inversion processes to consider mutual constraints.\r\n- **Time-Lapse Inversion**: Analyze changes over time to observe dynamic processes.\r\n- **Rock Physics**: Rock Physics models for hydrologic and geophysical properties transformation\r\n- **Data Preprocessing**: Utilities for preparing your geophysical data for inversion.\r\n- **Visualization**: Tools for visualizing inversion results and data.\r\n\r\n## Installation\r\n\r\nPyCZINV requires Python 3.6 or newer. You can install PyCZINV using pip:\r\n\r\n```bash\r\npip install pyczinv\r\n\r\n\r\n\r\n\r\n## Rock Physics Models\r\n\r\n### 1. Voigt-Reuss-Hill (VRH) Mixing Model\r\nThe VRH model is used to estimate the effective bulk modulus, shear modulus, and density of composite materials made of different minerals. \r\n\r\n**Usage**:\r\n```python\r\nfrom PyCZINV import VRH_model\r\n\r\n# Fraction, Bulk modulus (K), Shear modulus (G), and Density (rho) of minerals\r\nf = [0.35, 0.25, 0.2, 0.125, 0.075]\r\nK = [55.4, 36.6, 75.6, 46.7, 50.4]\r\nG = [28.1, 45, 25.6, 23.65, 27.4]\r\nrho = [2560, 2650, 2630, 2540, 3050]\r\n\r\nKm, Gm, rho_b = VRH_model(f=f, K=K, G=G, rho=rho)\r\nprint(Km, Gm, rho_b)\r\n",
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