Metadata-Version: 2.1
Name: uncertainty-framework
Version: 0.1.3
Summary: Framework for propagating uncertainties through V-FOR-WaTer
Home-page: UNKNOWN
Author: Mirko Mälicke
Author-email: mirko.maelicke@kit.edu
License: MIT license
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
        ```
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
