Metadata-Version: 2.1
Name: pyspde
Version: 0.0.5
Summary: PySPDE is a Python library for performing simulations and kriging of non-stationary spatial gaussian random fields with Matérn covariance, by solving the following Stochastic Partial Differential Equations (SPDEs)
Author-email: Esteban Jimenez <ejimenez@minerai.com.au>
Project-URL: Homepage, https://github.com/M1nerAI/pyspde
Project-URL: Issues, https://github.com/M1nerAI/pyspde/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: scipy
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: scikit-sparse==0.4.12

# PySPDE

PySPDE is a Python library for performing simulations and kriging of non-stationary spatial gaussian random fields with Matérn covariance, by solving the following Stochastic Partial Differential Equations (SPDEs):

$$ ({\kappa}^2 - {\nabla} {\cdot} H(x) {\nabla} )Z(x) = {\tau}W(x) \quad x \in \mathbb{R}^2
$$

The theory is proposed in Fuglstad (2014).

## Instalation

On Debian/Ubuntu systems:
```
sudo apt-get install libsuitesparse-dev
pip install pyspde
```

On Windows systems:
```
conda install -c conda-forge suitesparse
pip install pyspde
```

## Basic Usage

Imports:
```
from pyspde import anisotropy, Grid, Spde
```

Define the anisotropy and the grid:
```
atpy = anisotropy_from_svg(r'assets/anicline.svg', beta=10, gamma=0.1)
grid = Grid(nx=200, ny=100, anisotropy=atpy)
```

Define SPDE and Simulate:
```
sp = Spde(grid, sigma=1, a=25)
Z = sp.simulate()
```
