Update docs with user defined settings

docs/Gettingstarted.rst

@@ -105,8 +105,24 @@ User-defined settings
 ----------------------
 Below you can find a list of all user-defined settings that are included in the `jarkus.yml` file. For each setting a link to the documentation of the corresponding function is provided which explains how the setting is used.
 
-Upcoming!
-
+	* filter1: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Transects.save_elevation_dataframes`
+	* filter2: :py:mod:`JAT.Filtering_functions.availability_locations_filter`
+	* primary dune: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_primary_dune_top`
+	* secondary dune: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_secondary_dune_top`
+	* mean sea level: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_sea_level`
+	* mean high water: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_high_water_fixed`
+	* mean low water: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_low_water_fixed`
+	* landward variance threshold: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_variance`
+	* landward derivative: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_derivative`
+	* landward bma: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_bma`
+	* seaward foreshore: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_foreshore`
+	* seaward active profile: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_activeprofile`
+	* seaward DoC: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_doc`
+	* dune toe fixed: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_dune_toe_fixed`
+	* dune toe classifier: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_dune_toe_derivative`
+	* normalization: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.normalize_dimensions(`
+
+
 Dependencies
 ---------------
 The JAT has specific dependencies that are managed through the `setup.py` file, the packages needed are as follows::

docs/_build/Examples.html

@@ -183,8 +183,8 @@ <h2>2. Regional analysis<a class="headerlink" href="#regional-analysis" title="P
 <h2>3. Extract all<a class="headerlink" href="#extract-all" title="Permalink to this headline">¶</a></h2>
 <p>This Example shows how to extract all characteristic parameters from all transect locations. For this, include the correct directories in the <cite>jarkus_03.yml</cite> file and run the code in <cite>JAT_use_extract_all.py</cite>. The analysis can take a long time, around 10 hours. Thus, it is recommended to download the input files and store them locally to reduce the run time.</p>
 <p>The <cite>Filtering_execution.py</cite> file provides an example of how the filtering functionalities of the JAT can be used.</p>
-<p>To create distribution plots that show the values of the characteristic parameters through time and space use <cite>Distribution_plots.py</cite>. This script can only be used after the output of <cite>JAT_use_extract_all.py</cite> and <cite>Filtering_execution.py</cite> are available. <cite>Distribution_plots.py</cite> creates the distribution plots for both the filtered and unfiltered dataframes. The distribution plots of the unfiltered dataframes are available on the <a class="reference external" href="https://github.com/christavanijzendoorn/JAT">4TU repository</a> to show what the characteristic parameters look like.</p>
-<p><cite>Creation_netcdf.py</cite> was used to produce the netcdf file that is available on the <a class="reference external" href="https://github.com/christavanijzendoorn/JAT">4TU repository</a>. The output of <cite>Creation_netcdf.py</cite>, which is <cite>extracted_parameters.nc</cite> is saved in the Input directory because it serves as the input for Example 5.</p>
+<p>To create distribution plots that show the values of the characteristic parameters through time and space use <cite>Distribution_plots.py</cite>. This script can only be used after the output of <cite>JAT_use_extract_all.py</cite> and <cite>Filtering_execution.py</cite> are available. <cite>Distribution_plots.py</cite> creates the distribution plots for both the filtered and unfiltered dataframes. The distribution plots of the unfiltered dataframes are available on the <a class="reference external" href="https://doi.org/10.4121/14514213">4TU repository</a> to show what the characteristic parameters look like.</p>
+<p><cite>Creation_netcdf.py</cite> was used to produce the netcdf file that is available on the <a class="reference external" href="https://doi.org/10.4121/14514213">4TU repository</a>. The output of <cite>Creation_netcdf.py</cite>, which is <cite>extracted_parameters.nc</cite> is saved in the Input directory because it serves as the input for Example 5.</p>
 </div>
 <div class="section" id="dune-toe-analysis">
 <h2>4. Dune toe analysis<a class="headerlink" href="#dune-toe-analysis" title="Permalink to this headline">¶</a></h2>
@@ -212,7 +212,7 @@ <h2>4. Dune toe analysis<a class="headerlink" href="#dune-toe-analysis" title="P
 </div>
 <div class="section" id="use-netcdf-file">
 <h2>5. Use NetCDF file<a class="headerlink" href="#use-netcdf-file" title="Permalink to this headline">¶</a></h2>
-<p>The output of Example 3 was converted into a netcdf file that is publicly available. This makes sure that the characteristic parameters can be accessed directly without having to use the Jarkus Analysis Toolbox. Thus, to work with this example you can choose to work through example 3 or just simply download <cite>extracted_parameters.nc</cite> from the <a class="reference external" href="https://github.com/christavanijzendoorn/JAT">4TU repository</a>.</p>
+<p>The output of Example 3 was converted into a netcdf file that is publicly available. This makes sure that the characteristic parameters can be accessed directly without having to use the Jarkus Analysis Toolbox. Thus, to work with this example you can choose to work through example 3 or just simply download <cite>extracted_parameters.nc</cite> from the <a class="reference external" href="https://doi.org/10.4121/14514213">4TU repository</a>.</p>
 <p>The <cite>Load_data_from_netcdf.py</cite> script shows how to load the extracted characteristic parameters from the netcdf file and gives a first glimpse of how to work with these data.</p>
 </div>
 </div>

docs/_build/Gettingstarted.html

@@ -267,7 +267,26 @@ <h2>Input files<a class="headerlink" href="#input-files" title="Permalink to thi
 <div class="section" id="user-defined-settings">
 <h2>User-defined settings<a class="headerlink" href="#user-defined-settings" title="Permalink to this headline">¶</a></h2>
 <p>Below you can find a list of all user-defined settings that are included in the <cite>jarkus.yml</cite> file. For each setting a link to the documentation of the corresponding function is provided which explains how the setting is used.</p>
-<p>Upcoming!</p>
+<blockquote>
+<div><ul class="simple">
+<li><p>filter1: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Transects.save_elevation_dataframes" title="JAT.Jarkus_Analysis_Toolbox.Transects.save_elevation_dataframes"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Transects.save_elevation_dataframes</span></code></a></p></li>
+<li><p>filter2: <a class="reference internal" href="Functionalities.html#JAT.Filtering_functions.availability_locations_filter" title="JAT.Filtering_functions.availability_locations_filter"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Filtering_functions.availability_locations_filter</span></code></a></p></li>
+<li><p>primary dune: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_primary_dune_top" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_primary_dune_top"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_primary_dune_top</span></code></a></p></li>
+<li><p>secondary dune: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_secondary_dune_top" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_secondary_dune_top"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_secondary_dune_top</span></code></a></p></li>
+<li><p>mean sea level: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_sea_level" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_sea_level"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_sea_level</span></code></a></p></li>
+<li><p>mean high water: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_high_water_fixed" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_high_water_fixed"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_high_water_fixed</span></code></a></p></li>
+<li><p>mean low water: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_low_water_fixed" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_low_water_fixed"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_low_water_fixed</span></code></a></p></li>
+<li><p>landward variance threshold: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_variance" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_variance"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_variance</span></code></a></p></li>
+<li><p>landward derivative: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_derivative" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_derivative"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_derivative</span></code></a></p></li>
+<li><p>landward bma: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_bma" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_bma"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_bma</span></code></a></p></li>
+<li><p>seaward foreshore: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_foreshore" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_foreshore"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_foreshore</span></code></a></p></li>
+<li><p>seaward active profile: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_activeprofile" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_activeprofile"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_activeprofile</span></code></a></p></li>
+<li><p>seaward DoC: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_doc" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_doc"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_doc</span></code></a></p></li>
+<li><p>dune toe fixed: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_dune_toe_fixed" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_dune_toe_fixed"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_dune_toe_fixed</span></code></a></p></li>
+<li><p>dune toe classifier: <a class="reference internal" href="Functionalities.html#JAT.Jarkus_Analysis_Toolbox.Extraction.get_dune_toe_derivative" title="JAT.Jarkus_Analysis_Toolbox.Extraction.get_dune_toe_derivative"><code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.get_dune_toe_derivative</span></code></a></p></li>
+<li><p>normalization: <code class="xref py py-mod docutils literal notranslate"><span class="pre">JAT.Jarkus_Analysis_Toolbox.Extraction.normalize_dimensions(</span></code></p></li>
+</ul>
+</div></blockquote>
 </div>
 <div class="section" id="dependencies">
 <h2>Dependencies<a class="headerlink" href="#dependencies" title="Permalink to this headline">¶</a></h2>

docs/_build/Method.html

@@ -172,7 +172,7 @@ <h1>Method<a class="headerlink" href="#method" title="Permalink to this headline
 <p>The Jarkus Analysis Toolbox helps to analyse the Jarkus dataset. This dataset is stored on an online repository and made available by Rijkswaterstaat and Deltares.</p>
 <p>Based on user input the necessary data is retrieved from this dataset by the JAT for certain years and locations. The JAT contains the option to save the elevation information of the requested coastal transects and to create a quickplot that shows all measured years per requested transect.</p>
 <p>The core of the JAT is in the parameter extraction. This means that characteristic parameters are extracted from the elevation profile of each requested coastal transect. User input determines which characteristic parameters are extracted and it is expected that more extraction methods will be added to the JAT in the future. A guide on how to add a new method is provided in the <a class="reference internal" href="Development.html"><span class="doc">Development</span></a> section.</p>
-<p>The raw output parameters that were extracted by using the currently available methods are made avaiable through <a class="reference external" href="https://github.com/christavanijzendoorn/JAT">4TU repository</a>.</p>
+<p>The raw output parameters that were extracted by using the currently available methods are made avaiable through <a class="reference external" href="https://doi.org/10.4121/14514213">4TU repository</a>.</p>
 <p>Within the examples provided along with the JAT there are examples of filtering and visualisation that can be executed based on the raw output parameters. These examples provide suggestions which help to kick-start further analysis, but this is where the user can apply their own methods.</p>
 </div>
 

docs/_build/_sources/Examples.rst.txt

@@ -56,5 +56,5 @@ The output of Example 3 was converted into a netcdf file that is publicly availa
 The `Load_data_from_netcdf.py` script shows how to load the extracted characteristic parameters from the netcdf file and gives a first glimpse of how to work with these data. 
 
 
-.. _4TU repository: https://github.com/christavanijzendoorn/JAT
-.. _repository: https://github.com/christavanijzendoorn/JAT
+.. _4TU repository: https://doi.org/10.4121/14514213
+.. _repository: https://doi.org/10.4121/14514213

docs/_build/_sources/Gettingstarted.rst.txt

@@ -105,8 +105,24 @@ User-defined settings
 ----------------------
 Below you can find a list of all user-defined settings that are included in the `jarkus.yml` file. For each setting a link to the documentation of the corresponding function is provided which explains how the setting is used.
 
-Upcoming!
-
+	* filter1: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Transects.save_elevation_dataframes`
+	* filter2: :py:mod:`JAT.Filtering_functions.availability_locations_filter`
+	* primary dune: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_primary_dune_top`
+	* secondary dune: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_secondary_dune_top`
+	* mean sea level: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_sea_level`
+	* mean high water: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_high_water_fixed`
+	* mean low water: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_mean_low_water_fixed`
+	* landward variance threshold: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_variance`
+	* landward derivative: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_derivative`
+	* landward bma: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_landward_point_bma`
+	* seaward foreshore: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_foreshore`
+	* seaward active profile: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_activeprofile`
+	* seaward DoC: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_seaward_point_doc`
+	* dune toe fixed: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_dune_toe_fixed`
+	* dune toe classifier: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.get_dune_toe_derivative`
+	* normalization: :py:mod:`JAT.Jarkus_Analysis_Toolbox.Extraction.normalize_dimensions(`
+
+
 Dependencies
 ---------------
 The JAT has specific dependencies that are managed through the `setup.py` file, the packages needed are as follows::

docs/_build/_sources/Method.rst.txt

@@ -8,15 +8,15 @@ Method
 
 The Jarkus Analysis Toolbox helps to analyse the Jarkus dataset. This dataset is stored on an online repository and made available by Rijkswaterstaat and Deltares.
 
-.. _online repository: http://opendap.deltares.nl/thredds/catalog/opendap/rijkswaterstaat/jarkus/profiles/catalog.html?dataset=varopendap/rijkswaterstaat/jarkus/profiles/transect.nc 
+.. _online repository: https://opendap.deltares.nl/thredds/fileServer/opendap/rijkswaterstaat/jarkus/profiles/transect.nc
 
 Based on user input the necessary data is retrieved from this dataset by the JAT for certain years and locations. The JAT contains the option to save the elevation information of the requested coastal transects and to create a quickplot that shows all measured years per requested transect.
 
 The core of the JAT is in the parameter extraction. This means that characteristic parameters are extracted from the elevation profile of each requested coastal transect. User input determines which characteristic parameters are extracted and it is expected that more extraction methods will be added to the JAT in the future. A guide on how to add a new method is provided in the :doc:`Development` section.
 
 The raw output parameters that were extracted by using the currently available methods are made avaiable through `4TU repository`_. 
 
-.. _4TU repository: https://github.com/christavanijzendoorn/JAT
+.. _4TU repository: https://doi.org/10.4121/14514213
 
 Within the examples provided along with the JAT there are examples of filtering and visualisation that can be executed based on the raw output parameters. These examples provide suggestions which help to kick-start further analysis, but this is where the user can apply their own methods.
 

docs/_build/_sources/index.rst.txt

@@ -6,7 +6,8 @@ The Jarkus Analysis Toolbox (JAT) is a Python-based open-source software, that c
 The software that is described in this documentation can be found in this `Github repository`_. Additionally, the extracted parameters for the entire Jarkus dataset are made available through the `4TU repository`_. Please use the `issues`_ page to raise questions and suggest improvements.
 
 .. _Github repository: https://github.com/christavanijzendoorn/JAT
-.. _4TU repository: https://github.com/christavanijzendoorn/JAT
+.. _4TU repository: https://doi.org/10.4121/14514213
+
 .. _issues: https://github.com/christavanijzendoorn/JAT/issues