Darcy scale image analysis toolbox
Visit pmgbergen.github.io/DarSIA
If you use DarSIA in your research, we ask you to cite the following publication:
Nordbotten, J. M., Benali, B., Both, J. W., Brattekås, B., Storvik, E., & Fernø, M. A. (2023). DarSIA: An open-source Python toolbox for two-scale image processing of dynamics in porous media. Transport in Porous Media, https://doi.org/10.1007/s11242-023-02000-9
The first release can be also found on Zenodo: 10.5281/zenodo.7515016
DarSIA is developed under Python 3.10. Clone the repository from github and enter the DarSIA folder. Then, run the following command to install:
pip install .To install DarSIA as editable (recommended), along with the tools to develop and run tests, run the following in your virtual environment:
$ pip install -e .[dev]The following Python script can be applied to the test image in the examples/images folder.
import numpy as np
# Create a darsia Image: An image that also contains information of physical entities
image = darsia.imread("images/baseline.jpg", width=2.8, height=1.5)
# Use the show method to take a look at the imported image.
image.show()
# Copy the image and adds a grid on top of it.
grid_image = image.add_grid(dx=0.1, dy=0.1)
grid_image.show()
# Extract region of interest (ROI) from image (box defined by two corners):
ROI_image = image.subregion(coordinates=np.array([[1.5, 0], [2.8, 0.7]]))
ROI_image.show()Furthermore, we encourage any user to checkout the examples in the examples folder and the jupyter notebooks in the examples/notebooks folder.
Use black (version 22.3.0), flake8 and isort formatting.