Welcome to Data fusion tools’ documentation!
Contents
Welcome to Data fusion tools’ documentation!#
DataFusionTools is a collection of tools that can be used to perform data fusion tasks. The tools are developed by the consortium of Deltares, TNO, HKV, Fugro and Geodan. The tools are developed in the context of the project DigiTwin Waterkering en Ondergrond. The tools are developed in Python and are available as a package on the following link.
Installation#
DataFusionTools is a collection of several subpackages or distributions that can be either installed separately or as a whole project. Each subpackage may have a few heavy dependencies attached, therefore it is not recommended to install the whole DataFusionTools package if only a subpackage is needed in a project.
It is recommended to install DataFusionTools in a python virtual environment. The main purpose of Python virtual environments is to create an isolated environment for Python projects. This means that each project can have its own dependencies, regardless of what dependencies every other project has. This avoids issues with packages dependencies. The virtual environment should be installed and activated before the installation of DataFusionTools. To create a virtual environment with python/pip follow this link. To create a virtual environment with conda follow this link.
Installing DataFusionTools as a package#
To install DataFusionTools, run the following code:
pip install git+https://bitbucket.org/DeltaresGEO/datafusiontools.git
Installing a subpackage#
To install a specific subpackage (sensitivity in this example), run the following:
pip install git+https://bitbucket.org/DeltaresGEO/datafusiontools.git@master#subdirectory=DataFusionTools/sensitivity
The subpackage is then imported in python:
import datafusiontools.sensitivity
The installable sukpackages are: interpolation, machine_learning, sensitivity, spatial_utils, d_series_parser and visualisation.
Using the package as a developer#
To install the package as a developer, you need first to check out the repository. Then, run the following command in the root of the repository:
pip install -e .[testing]
This will install the package in editable mode, so that any changes you make to the code will be reflected in the installed package. The [testing] flag will also install the dependencies needed for running the tests.
Developers#
Consortium consists of:
The Tutorials#
This part of the documentation includes the tutorials.
- Tutorial neural network
- How to get a 2d interpolated slice from a list of data
- Get ahn values from a list of points
- Bayesian Neural Networks
- reate D-Stability .sli file from the DataFusionTools
- Sensitivity analysis on a model
- Cluster 2d surface to create polygons for DSeries models
Indices and tables#
Package documentation#
- DataFusionTools package
- Subpackages
- DataFusionTools.interpolation package
- DataFusionTools.machine_learning package
- Submodules
- DataFusionTools.machine_learning.baseclass module
- DataFusionTools.machine_learning.convolutional module
- DataFusionTools.machine_learning.enumeration_classes module
- DataFusionTools.machine_learning.mpl module
- DataFusionTools.machine_learning.neural_networks module
- DataFusionTools.machine_learning.random_forest module
- DataFusionTools.machine_learning.support_vector_machine module
- DataFusionTools.machine_learning.bayesian_neural_network module
- Module contents
- DataFusionTools.d_series_parser
- DataFusionTools.sensitivity
- DataFusionTools.visualization
- Submodules