Framework for propagating uncertainties through V-FOR-WaTer
Project description
uncertainty-framework
Framework for propagating uncertainties through V-FOR-WaTer
Install
pip install uncertainty-framework
Examples
The examples are implemeted as a python module. The main function imports fire
to
have a nice command line interface. Currently there is only one example.
Variogram estimation
This example illustrates, how the MonteCarlo simulation can be used to simulate
measurement uncertainties on a variogram estimation. It replaces the observations by
a gaussian distribution around the observation using a scale of 5
. The observation
value range is [0, 256[
.
The uncertainty_framework.examples.variograms
example has additional dependencies that
need to be installed separatly:
pip install scikit-gstat plotly
Then, you can run it through the command line. It is recommended to decrease the default number of iterations for this example.
python -m uncertainty_framework.examples.variograms --num-iter=500 --verbose
It is possbile to increase the used scale for generating new observations and also some of the variogram parameters are exposed:
python -m uncertainty_framework.examples.variograms --num-iter=500 --estimator=cressie --ons-scale=15 --verbose
Project details
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