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FuzzyCorr

This repository contains the work developed for a Master Thesis on fuzzy map comparison methods to evaluate the performance of hydro-morphodynamic numerical models. Please read the License terms for code usage and re-distribution.

Sediment transport and hydraulic processes can be reproduced with numerical models such as SSIIMM, Hydro_AS_2D, TELEMAC and many more. The accuracy of numerical models is assessed through comparing the simulated and the observed datasets, which constitutes a model validation. With the purpose of analyzing simulated and observed bed elevation change, two methods of comparison can be applied:

  1. Comparison via statistical methods such as RMSE (Root Mean Squared Error) or visual human comparison. However, local measures of similarity (or a similarity) like the RMSE are very sensible to uncertainty of location and amount, thus indicating low agreement even when overall patterns were adequately simulated.
  2. Visual comparison captures global similarity, which is one of the reasons why modelers often use it for model validation. Humans are capable of finding patterns without deliberately trying, and therefore, this type of comparison provides substantial advantages over local similarity measures. Nevertheless, more research has to be done to implement automated validation tools that emulate human thinking. This is necessary because human comparison is not transparent, prone to subjective interpretations, time consuming, and hardly reproducible.

In this context, the concept of fuzzy set theory has capacities to consider similarity of spatial pattern analogous to human thinking. For instance, fuzziness of location introduces a tolerance regarding spatial uncertainty in the results of hydro-morphodynamic models. To this end, fuzzy logic enables an objective validation of such models by overcoming uncertainties in the model structure, parameters and input data.

The algorithms provided with fuzzycorr address the necessity in evaluating (or validating) model performance through the use of fuzzy map comparison. Future developments aim to go beyond a one-way validation towards a two-way communication between the validation algorithms and the models. The two-way communication represents a feedback loop that will eventually enable an automated calibration of numerical hydro-morphodynamic models.

Install dependencies

The necessary modules for running this repo are specified in environment.yml. To install all packages in the environment:

  • Navigate ( cd) with the Anaconda Prompt through your directories to the .yml file
  • Type conda env create -f environment.yml
  • Active the new environment with conda activate env-fuzzycorr

Usage

The best way to learn the usage is by examples. In the directory examples, the usage of the modules are demonstrated in a case study. Inside the folder salzach_case, the results from a hydro-morphodynamic numerical simulation ( i.e., simulated bed elevation change, deltaZ) are located in raw_data. For more details on the hydro-morphodynamic numerical refer to Beckers et al. (2020).

  • prepro_salzach.py: example of the usage of the class PreProFuzzy of the module prepro.py, where vector data is interpolated and rasterized.
  • classification_salzach.py: example of the usage of the class PreProCategorization of the module prepro.py.
  • fuzzycomparison_salzach.py: example of the usage of the class FuzzyComparison of the module fuzzycomp.py, which creates a correlation (similarity) measure between simulated and observed datasets.
  • plot_salzach.py, plot_class_rasters.py and performance_salzach: example of the usage of the module plotter.py.
  • random_map: example of generating a raster following a uniform random distribution, which uses the module prepro.py.

Structure

This package contains the following modules, which were designed in Python 3.6:

  • prepro.py: Includes functions for reading, normalizing and rasterizing vector data. These are preprocessing steps for fuzzy map comparison (module fuzzycomp).
  • fuzzycomp.py: Provides routines for fuzzy map comparison in continuous valued rasters. The reader is referred to Hagen(2006) for more details (more to come).
  • plotter.py: Visualization routines for output and input rasters.
  • The package documentation is located in the folder docs.

Pre- and post-processing: prepro.py

prepro

Fuzzy map comparison core: fuzzycomp.py

fuzzycomp

Plot routines: plotter.py

plotter

References

Disclaimer and License

Disclaimer (general)

No warranty is expressed or implied regarding the usefulness or completeness of the information provided for fuzzycorr and its documentation. References to commercial products do not imply endorsement by the Authors of fuzzycorr. The concepts, materials, and methods used in the codes and described in the docs are for informational purposes only. The Authors have made substantial effort to ensure the accuracy of the code and the docs and the Authors shall not be held liable, nor their employers or funding sponsors, for calculations and/or decisions made on the basis of application of fuzzycorr. The information is provided "as is" and anyone who chooses to use the information is responsible for her or his own choices as to what to do with the code, docs, and data and the individual is responsible for the results that follow from their decisions.

BSD 3-Clause License

Copyright (c) 2020, Beatriz Negreiros and all other the Authors of fuzzycorr. All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

  1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
  2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
  3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.