Model view restructure (#10)

* Improve the structure of the main page

* Forgot one file

* Cleanup imports

* more cleanup

* cleaner naming

* cleaner naming

* cleaner naming

* added atmopsheric and immersion corrosion pages

* referecnes fixed

---------

Co-authored-by: Aravinth Ravikumar <aravinth.ravikumar@hereon.de>

web_app.dockerfile

@@ -47,4 +47,4 @@ HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health || exit 1
 WORKDIR /app/web_app
 
 # Run the application
-ENTRYPOINT ["pipenv", "run", "streamlit", "run", "website.py", "--server.port=8501", "--server.address=0.0.0.0"]
+ENTRYPOINT ["pipenv", "run", "streamlit", "run", "Home.py", "--server.port=8501", "--server.address=0.0.0.0"]

web_app/website.py → web_app/Home.py

@@ -5,8 +5,7 @@
 from model_view import model_view
 from helper import local_css
 
-
-st.set_page_config(page_title="CorWiz", page_icon=":material/rainy:", layout="wide", initial_sidebar_state="collapsed")
+st.set_page_config(page_title="CorWiz", page_icon=":material/rainy:", layout="wide", initial_sidebar_state="auto")
 
 local_css('style/style.css')
 

web_app/model_view.py

@@ -1,140 +1,119 @@
-import matplotlib.pyplot as plt
-import plotly.express as px
+import os
+import json
 import numpy as np
 import streamlit as st
-from streamlit_extras.stylable_container import stylable_container
+import plotly.express as px
 import streamlit.components.v1 as components
 
-from models import AC_model_fileu1993, AC_model_iso9223, AC_model_ma2010, AC_model_benarie1986, AC_model_soares1999, AC_model_klinesmith2007, IC_model_ali2020, IC_model_kovalenko2016, IC_model_garbatov2011, IC_model_hicks2012
-import os
-import json
+from models import (
+    AC_model_fileu1993, AC_model_iso9223, AC_model_ma2010,
+    AC_model_benarie1986, AC_model_soares1999, AC_model_klinesmith2007,
+    IC_model_ali2020, IC_model_kovalenko2016, IC_model_garbatov2011,
+    IC_model_hicks2012
+)
 
 
-def extract_model_details_from_json(path):
-    model_infos = {
+def extract_model_details_from_json(directory_path):
+    """Extracts model details from JSON files in the specified directory."""
+    model_details = {
         'names': [],
         'kadi_identifiers': [],
         'descriptions': [],
         'special_notes': [],
         'parameters': [],
         'formulas': [],
-        'article_identifier' : []
-        }
+        'article_identifiers': []
+    }
 
-    # Iterate over each file in the specified path
-    for file_name in os.listdir(path):
-
-        # model_info = [model name, kadi identifier, description, special notes, parameteres, formula]
+    for file_name in os.listdir(directory_path):
         if file_name.endswith('.json'):
-            json_file_path = os.path.join(path, file_name)
-
+            json_file_path = os.path.join(directory_path, file_name)
             with open(json_file_path, 'r', encoding='utf-8') as file:
                 data = json.load(file)
 
-            # Access the 'extras' array in the JSON data
-            model_infos['descriptions'].append(data.get('description', []))
-            model_infos['names'].append(data.get('title', []))
-            model_infos['kadi_identifiers'].append(data.get('identifier', []))
-            model_infos['special_notes'].append(data.get('special notes', []))
-            model_infos['article_identifier'].append(data.get('links', [])[0]['record_to']['identifier'])
+            model_details['names'].append(data.get('title', ''))
+            model_details['kadi_identifiers'].append(data.get('identifier', ''))
+            model_details['descriptions'].append(data.get('description', ''))
+            model_details['special_notes'].append(data.get('special notes', ''))
+            model_details['article_identifiers'].append(data.get('links', [{}])[0].get('record_to', {}).get('identifier', ''))
 
             extras = data.get('extras', [])
-            # Iterate through each model in the 'extras' array
-            parameters_found = False
-            formula_found = False
-            for item in extras:
-                if item['key'] == 'Parameters':
-                    model_infos['parameters'].append(item['value'])
-                    parameters_found = True
-                if item['key'] == 'Formula':
-                    model_infos['formulas'].append(item['value'])
-                    formula_found = True
-            if not parameters_found:
-                model_infos['parameters'].append('')
-            if not formula_found:
-                model_infos['formulas'].append('')
-
-
-    return model_infos
-
-
-def display_model_info(model_info, model):
+            parameters = next((item['value'] for item in extras if item['key'] == 'Parameters'), '')
+            formula = next((item['value'] for item in extras if item['key'] == 'Formula'), '')
+
+            model_details['parameters'].append(parameters)
+            model_details['formulas'].append(formula)
+
+    return model_details
+
+
+def display_model_info(model_info, model_name):
     # st.markdown("#### Model developed by: \n" + model_info['model_developers'][model_info['model_names'].index(model)])
-    st.markdown("#### Model Description: \n" + str(model_info['descriptions'][model_info['names'].index(model)]))
+    st.markdown(str(model_info['descriptions'][model_info['names'].index(model_name)]))
     try:
-        st.markdown("#### Model Notes: \n" + model_info['special_notes'][model_info['names'].index(model)])
+        st.markdown("#### Model Notes: \n" + model_info['special_notes'][model_info['names'].index(model_name)])
     except:
         pass
 
 
 def run_model(model_identifier, model_functions, article_identifier):
-    with st.container():
-        model, time = model_functions[model_identifier](article_identifier)
-    return model, time
+    return  model_functions[model_identifier](article_identifier)
+
+def plot_mass_loss_over_time(model, time_range):
+    """Generates and returns a Plotly figure for mass loss over time."""
+    t = np.linspace(0, time_range, 400)
+    D = model.eval_material_loss(t)
+    fig = px.line(x=t, y=D, labels={'x': 'Time [years]', 'y': 'Mass loss [um]'}, title="Mass Loss Over Time", height=700)
+    return fig
 
 
 def model_view(model_view_container):
+    immersion_corrosion_models = extract_model_details_from_json('../data/kadi4mat_json/immersion_corrosion_models/')
+    atmospheric_corrosion_models = extract_model_details_from_json(
+        '../data/kadi4mat_json/atmospheric_corrosion_models/')
+
     with model_view_container:
         st.write("---")
         st.header("Corrosion Mass Loss Models")
 
-        immersion_corrosion_models = extract_model_details_from_json('../data/kadi4mat_json/immersion_corrosion_models/')
-        atmospheric_corrosion_models = extract_model_details_from_json('../data/kadi4mat_json/atmospheric_corrosion_models/')
-
-        models = ['Atmospheric corrosion models', 'Immersed corrosion models']
-        ac_or_ic = st.selectbox(
-            'Is your problem atmospheric corrosion or immersed corrosion?',
-            models
-        )
-
-        if ac_or_ic == models[0]:
-            model_info = atmospheric_corrosion_models
-            model_functions = {'model_feliu1993': AC_model_fileu1993, 
-                               'din-corrosion-protection-model-iso-9223-compliant': AC_model_iso9223, 
-                               'model_ma2010': AC_model_ma2010, 
-                               'model_benarie1986': AC_model_benarie1986, 
-                               'model_soares1999': AC_model_soares1999, 
-                               'model_klinesmith2007': AC_model_klinesmith2007}
-        else:
-            model_info = immersion_corrosion_models
-            model_functions = {'model_ali2020': IC_model_ali2020, 
-                               'model_kovalenko2016': IC_model_kovalenko2016, 
-                               'model_garbatov2011': IC_model_garbatov2011, 
-                               'model_hicks2012': IC_model_hicks2012}  
-
-        model = st.selectbox(
-            'Please select model',
-            model_info['names']
-        )
-
-        model_identifier = model_info['kadi_identifiers'][model_info['names'].index(model)]
-        article_identifier = model_info['article_identifier'][model_info['names'].index(model)]
-        formulas = model_info['formulas'][model_info['names'].index(model)]
-        st.subheader("Selected model: " + model)
-
-        image_column, data_column = st.columns((1, 1))
-        fig = plt.figure(figsize=(10, 6))
-
-        with data_column:
-            print('\n\n\n')
-            print(article_identifier)
-            display_model_info(model_info, model)
-            model, time = run_model(model_identifier, model_functions, article_identifier)
-
-
-        for formula in formulas:
-            st.write(r'' + formula['key'] + ': ' + formula['value'])
-
-        if model is not None:
-            t = np.linspace(0, time, 400)
-            D = model.eval_material_loss(t)
-
-            # Create the plot using Plotly Express
-            fig = px.line(x=t, y=D, labels={'x': 'Time [years]', 'y': 'Mass loss [um]'}, title="Mass Loss Over Time", height=700)
+        main_view = st.container()
+        description_box = st.container()
+        model_info = None
+        selected_model_name = None
+
+        with main_view:
+            image_column, data_column = st.columns((1, 1))
+            with data_column:
+                model_categories = ['Atmospheric corrosion', 'Immersion corrosion']
+
+                model_category_selection = st.selectbox('**Corrosion Type**', model_categories)
+
+                if model_category_selection == 'Atmospheric corrosion':
+                    model_info = atmospheric_corrosion_models
+                    model_functions = {'model_feliu1993': AC_model_fileu1993,
+                                       'din-corrosion-protection-model-iso-9223-compliant': AC_model_iso9223,
+                                       'model_ma2010': AC_model_ma2010,
+                                       'model_benarie1986': AC_model_benarie1986,
+                                       'model_soares1999': AC_model_soares1999,
+                                       'model_klinesmith2007': AC_model_klinesmith2007}
+                else:
+                    model_info = immersion_corrosion_models
+                    model_functions = {'model_ali2020': IC_model_ali2020,
+                                       'model_kovalenko2016': IC_model_kovalenko2016,
+                                       'model_garbatov2011': IC_model_garbatov2011,
+                                       'model_hicks2012': IC_model_hicks2012}
+
+                selected_model_name = st.selectbox('**Model**', model_info['names'])
+
+                model_identifier = model_info['kadi_identifiers'][model_info['names'].index(selected_model_name)]
+                article_identifier = model_info['article_identifiers'][model_info['names'].index(selected_model_name)]
+                formulas = model_info['formulas'][model_info['names'].index(selected_model_name)]
+
+                model, time = run_model(model_identifier, model_functions, article_identifier)
 
             with image_column:
                 chart_container = st.container()
-                plot_html = fig.to_html(full_html=False, include_plotlyjs='cdn')
+                plot_html = plot_mass_loss_over_time(model, time).to_html(full_html=False, include_plotlyjs='cdn')
 
                 with chart_container:
                     components.html(
@@ -146,5 +125,13 @@ def model_view(model_view_container):
                         height=800,
                         scrolling=True
                     )
-        else:
-            st.write("No model selected.")
+
+        with description_box:
+            description = st.expander("**Model Description**", expanded=False)
+
+            with description:
+                display_model_info(model_info, selected_model_name)
+
+                st.write("### Model Formulas")
+                for formula in formulas:
+                    st.write(r'' + formula['key'] + ': ' + formula['value'])

web_app/pages/1_Atmospheric_Corrosion.py

@@ -0,0 +1,84 @@
+import streamlit as st
+
+st.title("Atmospheric Corrosion")
+
+text_column, image_column = st.columns((0.7, 0.3))
+
+with text_column:
+    st.write("""
+        ## What is Atmospheric Corrosion?
+
+        Atmospheric corrosion is the deterioration of a material, typically a metal, due to its interaction with the surrounding atmosphere. It is an electrochemical process that requires the presence of an electrolyte, which is usually a thin film of moisture on the metal surface[1][2].
+
+        ## Mechanism of Atmospheric Corrosion
+
+        The mechanism of atmospheric corrosion involves the following steps:
+
+        1. **Formation of an electrolyte layer**: When the relative humidity of the atmosphere exceeds a critical level (around 60% for iron in unpolluted atmospheres), a thin film of moisture forms on the metal surface[2].
+
+        2. **Anodic and cathodic reactions**: In the presence of the electrolyte, atmospheric corrosion proceeds through anodic and cathodic reactions. The anodic reaction involves the dissolution of the metal, while the cathodic reaction is often the reduction of oxygen from the atmosphere[2].
+
+        3. **Corrosion product formation**: The dissolved metal ions react with oxygen and water to form corrosion products, such as rust (iron oxide) on steel surfaces[1].
+
+        ## Factors Affecting Atmospheric Corrosion
+
+        Several factors influence the rate and severity of atmospheric corrosion:
+
+        1. **Relative humidity**: Higher relative humidity increases the likelihood of moisture condensation on the metal surface, facilitating the formation of an electrolyte layer[1][2].
+
+        2. **Temperature**: Increased temperature can accelerate the corrosion reactions and affect the properties of the electrolyte layer[1].
+
+        3. **Atmospheric pollutants**: Pollutants like sulfur dioxide (SO2) and chlorides can increase the conductivity of the electrolyte layer, leading to higher corrosion rates[1][3].
+
+        4. **Surface characteristics**: The roughness and cleanliness of the metal surface can influence the formation and properties of the electrolyte layer[5].
+
+        ## Mitigating Atmospheric Corrosion
+
+        Several methods are used to mitigate atmospheric corrosion, including:
+
+        1. **Coatings and paints**: Applying protective coatings or paints to the metal surface can create a barrier between the metal and the atmosphere[3].
+
+        2. **Cathodic protection**: This technique involves making the metal structure the cathode in an electrochemical cell, preventing the anodic dissolution of the metal[3].
+
+        3. **Alloying and surface treatments**: Modifying the metal composition or surface properties can enhance its resistance to atmospheric corrosion[5].
+
+        In conclusion, atmospheric corrosion is a complex electrochemical process that occurs when metals are exposed to the surrounding atmosphere. Understanding the mechanism and factors affecting atmospheric corrosion is crucial for developing effective prevention and mitigation strategies.
+
+        Citations:
+            
+        [1] https://www.corrosionpedia.com/definition/116/atmospheric-corrosion
+            
+        [2] https://corrosion-doctors.org/AtmCorros/mechani1.htm
+            
+        [3] https://www.dreiym.com/2023/01/25/atmospheric-corrosion-what-it-is-and-how-to-mitigate-it/
+            
+        [4] https://www.diva-portal.org/smash/get/diva2:12811/FULLTEXT01.pdf
+            
+        [5] https://www.sciencedirect.com/science/article/pii/S2352492823010851
+            
+        [6] https://www.db-thueringen.de/servlets/MCRFileNodeServlet/dbt_derivate_00051759/ilm1-2020000368.pdf
+            
+        [7] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5506901/
+            
+        [8] https://www.corrosionpedia.com/5-most-common-types-of-metal-coatings-that-everyone-should-know-about/2/6894
+             
+        [9] https://www.corrosionpedia.com/2/1525/corrosion/system-dependent-corrosion-in-piping-systems
+             
+        [10] https://link.springer.com/chapter/10.1007/978-3-319-97625-9_12
+             
+        [11] https://www.azom.com/article.aspx?ArticleID=97
+             
+        [12] https://www.corrosionpedia.com/2/1525/corrosion/system-dependent-corrosion-in-piping-systems
+    """)
+
+with image_column:
+
+    st.image('static/images/Atmospheric-corrosion-14_W640.jpg', use_column_width=True)
+    st.image('static/images/Crevice-corrosion-17_W640.jpg', use_column_width=True)
+    st.image('static/images/Erosion-corrosion-21_W640.jpg', use_column_width=True)
+    st.image('static/images/Pitting-corrosion-18_W640.jpg', use_column_width=True)
+
+    st.markdown(
+    '<div style="text-align: center;">Image credits [9], [10], [11], [12]</div>',
+    unsafe_allow_html=True
+    )