feat: elevation to master (#205)

* feat: delete testing files * feat: visualisation * feat: utils.py * feat: stochastic.py * feat: resilience.py * feat: stochastic.py * feat: rm report.py * feat: preprocessing.py * feat: NetworkGraphs.py * feat: metrics.py * feat: machineLearning.py * feat: deepLearning.py * feat: embedding.py * feat: rm classification.ipynb * feat: metrics_visualisation.py * feat: ML_visualisation.py * feat: utils_visualisation.py * refactor: cleaned up the codebase (#198) * fix: issue with non-temporal graph in visualisation.html * feat: stochastic api * feat: Documentation (#201) * chore: documentation * feat: created documentation * feat: created documentation * feat: created documentation * feat: created documentation * feat: stochastic analysis integration (#203) * Update resilience_routes.py * feat: stochastic analysis * Update stochastic.js * feat: add tooltips * fix: gtfs duplicate stations preprocess --------- Co-authored-by: sferez <[email protected]> Co-authored-by: Tejas Patil <[email protected]>
airscholar · May 1, 2023 · 604cd92 · 604cd92
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commit 604cd92
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diff --git a/.gitignore b/.gitignore
@@ -3,6 +3,7 @@ venv/
 .vscode/
 .ipynb_checkpoints/
 __pycache__/
+application/__pycache__/
 *.mp4
 .env
 .DS_Store
@@ -17,3 +18,4 @@ application/flask_session/
 application/__pycache__/app.cpython-311.pyc
 *.pyc
 *.pyc
+flask_session/
diff --git a/Dockerfile b/Dockerfile
@@ -20,7 +20,7 @@ WORKDIR /alpha-team
 
 # Install GDAL and pygraphviz
 RUN pip install GDAL pygraphviz
-
+RUN pip3 install torch --index-url https://download.pytorch.org/whl/cpu
 # Copy the current directory contents into the container at /AlphaTeam
 COPY requirements.txt .
 

diff --git a/README.md b/README.md
@@ -34,5 +34,7 @@ the command in step 3 above.
 
 # Documentation
 
-On the frontend of the application, you can find the documentation for the API endpoints once the frontend application
-is started at `http://localhost:{chosen port}/docs`
+You can view the documentation in the `docs/` directory. The documentation is generated using Sphinx.
+
+### To regenerate the documentation
+In the root directory of the project, run `sh generate_docs.sh` to regenerate the documentation.
diff --git a/analysis/CryptoData.ipynb b/analysis/CryptoData.ipynb
diff --git a/analysis/Rail.ipynb b/analysis/Rail.ipynb
diff --git a/application/app.py b/application/app.py
@@ -14,6 +14,7 @@
 from application.routes.hotspot.hotspot_routes import hotspot_routes
 from application.routes.metrics.global_metrics_routes import global_metrics_routes
 from application.routes.visualisation.visualisation_routes import visualisation_routes
+from application.routes.stochastic.stochastic_routes import stochastic_routes
 
 sys.path.insert(1, '../')
 from src.NetworkGraphs import *
@@ -40,6 +41,7 @@
 app.register_blueprint(hotspot_routes)
 app.register_blueprint(global_metrics_routes)
 app.register_blueprint(visualisation_routes)
+app.register_blueprint(stochastic_routes)
 
 BASE_URL = 'http://localhost:8000/api/v1'
 

diff --git a/application/dictionary/__init__.py b/application/dictionary/__init__.py
diff --git a/application/dictionary/information.py b/application/dictionary/information.py
@@ -78,6 +78,7 @@
 
     'list_of_nodes': 'Enter a list of nodes to remove from the network for a personalized resilience analysis, '
                      'allowing you to evaluate the impact of specific node deletions on the overall network stability.',
+
 }
 
 description = {
@@ -141,7 +142,8 @@
                      "<b>closed loop of three nodes</b>. By examining the number of triangles a node participates in, "
                      "one can assess its tendency to form tightly connected groups. This metric helps identify nodes "
                      "that contribute to the network's <b>cohesion and community structure</b>, revealing potential "
-                     "subgroups or areas of high connectivity.",
+                     "subgroups or areas of high connectivity.  <i>Triangle computation is not allow for Directed and "
+                     "Multi graphs.</i>",
 
     'node_pagerank': "Node PageRank is a metric that estimates a node's <b>relative importance</b> within a network, "
                      "considering both the <b>quantity and quality</b> of its connections. Inspired by the algorithm "
@@ -322,4 +324,17 @@
                           "groups similar nodes using their embeddings. This combination provides a more "
                           "comprehensive understanding of network organization, relationships between communities, "
                           "and individual node roles, unveiling shared interests or functional clusters.",
+
+    'clustering_coefficient': "The <b>Clustering Coefficient Estimator</b> provides a robust and efficient method for "
+                              "computing the clustering coefficient in complex networks, without the computational "
+                              "overhead of traditional techniques. Leveraging a <b>stochastic Monte Carlo "
+                              "approach</b>, our algorithm performs the metrics computation over <b>10,"
+                              "000 iterations</b>, ensuring accurate estimations while <b>significantly reducing "
+                              "processing time</b>. ",
+
+    'shortest_path': "The <b>Shortest Path Length Estimator</b> provides an efficient and accurate estimation of the "
+                     "shortest path length in complex networks, without the computational burden of traditional "
+                     "methods. Utilizing a <b>stochastic Monte Carlo approach</b>, our algorithm samples the metrics "
+                     "computation over <b>10,000 iterations</b>, ensuring reliable estimations while <b>significantly "
+                     "reducing processing time</b>.",
 }
diff --git a/application/routes/centrality_routes.py b/application/routes/centrality_routes.py
diff --git a/application/routes/cluster_routes.py b/application/routes/cluster_routes.py
diff --git a/application/routes/clusters/__init__.py b/application/routes/clusters/__init__.py
diff --git a/application/routes/clusters/cluster_routes.py b/application/routes/clusters/cluster_routes.py
@@ -1,8 +1,8 @@
 import sys
 
-import requests
+from flask import Blueprint, render_template, session
+
 from application.dictionary.information import *
-from flask import Blueprint, render_template, session, request
 
 sys.path.insert(1, '../../')
 from src.metrics import *
@@ -12,8 +12,14 @@
 # -------------------------------------------ML-CLUSTERING-----------------------------------
 BASE_URL = 'http://localhost:8000/api/v1/clusters/'
 
+
 @cluster_routes.route('/clustering/louvain', endpoint='clustering_louvanian', methods=['GET', 'POST'])
 def clustering_louvanian():
+    """
+    :Function: Visualise the clusters using Louvain algorithm
+    :return: the cluster page
+    
+    """
     filename2 = session['filename2']
     clusterType = 'louvain'
     networkGraphs = get_networkGraph(filename2)
@@ -22,14 +28,20 @@ def clustering_louvanian():
     else:
         is_spatial = 'no'
 
-    return render_template('clusters/clustering_louvanian.html', session_id=filename2, clusterType=clusterType, method_name='Louvain', is_spatial=is_spatial,
-    #tooltips starts from here
-    description=description['louvain'], tooltip_dynamic=tooltips['dynamic'],
-    tooltip_layout=tooltips['layout_dropdown'], tooltip_number_of_clusters=tooltips['number_of_clusters'])
+    return render_template('clusters/clustering_louvanian.html', session_id=filename2, clusterType=clusterType,
+                           method_name='Louvain', is_spatial=is_spatial,
+                           description=description['louvain'], tooltip_dynamic=tooltips['dynamic'],
+                           tooltip_layout=tooltips['layout_dropdown'],
+                           tooltip_number_of_clusters=tooltips['number_of_clusters'])
 
 
 @cluster_routes.route('/clustering/greedy_modularity', endpoint='clustering_greedy_modularity', methods=['GET', 'POST'])
 def clustering_greedy_modularity():
+    """
+    :Function: Visualise the clusters using Greedy Modularity algorithm
+    :return: the clusters page
+    
+    """
     filename2 = session['filename2']
     clusterType = 'greedy_modularity'
     networkGraphs = get_networkGraph(filename2)
@@ -38,15 +50,20 @@ def clustering_greedy_modularity():
     else:
         is_spatial = 'no'
 
-    return render_template('clusters/clustering_greedy_modularity.html', session_id=filename2, clusterType=clusterType, method_name='Greedy Modularity', is_spatial=is_spatial,
-    #tooltips starts from here
-    description=description['greedy_modularity'], tooltip_dynamic=tooltips['dynamic'],
-    tooltip_layout=tooltips['layout_dropdown'], tooltip_number_of_clusters=tooltips['number_of_clusters'])
-
+    return render_template('clusters/clustering_greedy_modularity.html', session_id=filename2, clusterType=clusterType,
+                           method_name='Greedy Modularity', is_spatial=is_spatial,
+                           description=description['greedy_modularity'], tooltip_dynamic=tooltips['dynamic'],
+                           tooltip_layout=tooltips['layout_dropdown'],
+                           tooltip_number_of_clusters=tooltips['number_of_clusters'])
 
 
 @cluster_routes.route('/clustering/label_propagation', endpoint='clustering_label_propagation', methods=['GET', 'POST'])
 def clustering_label_propagation():
+    """
+    :Function: Visualise the clusters using Label Propagation algorithm
+    :return: the clusters page
+    
+    """
     filename2 = session['filename2']
     clusterType = 'label_propagation'
     networkGraphs = get_networkGraph(filename2)
@@ -55,14 +72,20 @@ def clustering_label_propagation():
     else:
         is_spatial = 'no'
 
-    return render_template('clusters/clustering_label_propagation.html', session_id=filename2, clusterType=clusterType, method_name='Label Propagation', is_spatial=is_spatial,
-    #tooltips starts from here
-    description=description['label_propagation'], tooltip_dynamic=tooltips['dynamic'],
-    tooltip_layout=tooltips['layout_dropdown'], tooltip_number_of_clusters=tooltips['number_of_clusters'])
+    return render_template('clusters/clustering_label_propagation.html', session_id=filename2, clusterType=clusterType,
+                           method_name='Label Propagation', is_spatial=is_spatial,
+                           description=description['label_propagation'], tooltip_dynamic=tooltips['dynamic'],
+                           tooltip_layout=tooltips['layout_dropdown'],
+                           tooltip_number_of_clusters=tooltips['number_of_clusters'])
 
 
 @cluster_routes.route('/clustering/asyn_lpa', endpoint='clustering_asyn_lpa', methods=['GET', 'POST'])
 def clustering_asyn_lpa():
+    """
+    :Function: Visualise the clusters using Asyn Lpa algorithm
+    :return: the clusters page
+    
+    """
     filename2 = session['filename2']
     clusterType = 'asyn_lpa'
     networkGraphs = get_networkGraph(filename2)
@@ -71,13 +94,20 @@ def clustering_asyn_lpa():
     else:
         is_spatial = 'no'
 
-    return render_template('clusters/clustering_asyn_lpa.html', session_id=filename2, clusterType=clusterType, method_name='Asyn Lpa', is_spatial=is_spatial,
-    #tooltips starts from here
-    description=description['asyn_lpa'], tooltip_dynamic=tooltips['dynamic'],
-    tooltip_layout=tooltips['layout_dropdown'], tooltip_number_of_clusters=tooltips['number_of_clusters'])
+    return render_template('clusters/clustering_asyn_lpa.html', session_id=filename2, clusterType=clusterType,
+                           method_name='Asyn Lpa', is_spatial=is_spatial,
+                           description=description['asyn_lpa'], tooltip_dynamic=tooltips['dynamic'],
+                           tooltip_layout=tooltips['layout_dropdown'],
+                           tooltip_number_of_clusters=tooltips['number_of_clusters'])
+
 
 @cluster_routes.route('/clustering/k_clique', endpoint='clustering_k_clique', methods=['GET', 'POST'])
 def clustering_k_clique():
+    """
+    :Function: Visualise the clusters using K Clique algorithm
+    :return: the clusters page
+    
+    """
     filename2 = session['filename2']
     clusterType = 'k_clique'
     networkGraphs = get_networkGraph(filename2)
@@ -86,13 +116,20 @@ def clustering_k_clique():
     else:
         is_spatial = 'no'
 
-    return render_template('clusters/clustering_k_clique.html', session_id=filename2, clusterType=clusterType, method_name='K Clique', is_spatial=is_spatial,
-    #tooltips starts from here
-    description=description['k_clique'], tooltip_dynamic=tooltips['dynamic'],
-    tooltip_layout=tooltips['layout_dropdown'], tooltip_number_of_clusters=tooltips['number_of_clusters'])
+    return render_template('clusters/clustering_k_clique.html', session_id=filename2, clusterType=clusterType,
+                           method_name='K Clique', is_spatial=is_spatial,
+                           description=description['k_clique'], tooltip_dynamic=tooltips['dynamic'],
+                           tooltip_layout=tooltips['layout_dropdown'],
+                           tooltip_number_of_clusters=tooltips['number_of_clusters'])
+
 
 @cluster_routes.route('/clustering/spectral', endpoint='clustering_spectral', methods=['GET', 'POST'])
 def clustering_spectral():
+    """
+    :Function: Visualise the clusters using Spectral algorithm
+    :return: the clusters page
+    
+    """
     filename2 = session['filename2']
     clusterType = 'spectral'
     networkGraphs = get_networkGraph(filename2)
@@ -101,13 +138,20 @@ def clustering_spectral():
     else:
         is_spatial = 'no'
 
-    return render_template('clusters/clustering_spectral.html', session_id=filename2, clusterType=clusterType, method_name='Spectral', is_spatial=is_spatial,
-    #tooltips starts from here
-    description=description['spectral'], tooltip_dynamic=tooltips['dynamic'],
-    tooltip_layout=tooltips['layout_dropdown'], tooltip_number_of_clusters=tooltips['number_of_clusters'])
+    return render_template('clusters/clustering_spectral.html', session_id=filename2, clusterType=clusterType,
+                           method_name='Spectral', is_spatial=is_spatial,
+                           description=description['spectral'], tooltip_dynamic=tooltips['dynamic'],
+                           tooltip_layout=tooltips['layout_dropdown'],
+                           tooltip_number_of_clusters=tooltips['number_of_clusters'])
+
 
 @cluster_routes.route('/clustering/kmeans', endpoint='clustering_kmeans', methods=['GET', 'POST'])
 def clustering_kmeans():
+    """
+    :Function: Visualise the clusters using KMeans algorithm
+    :return: the clusters page
+    
+    """
     filename2 = session['filename2']
     clusterType = 'kmeans'
     networkGraphs = get_networkGraph(filename2)
@@ -116,13 +160,20 @@ def clustering_kmeans():
     else:
         is_spatial = 'no'
 
-    return render_template('clusters/clustering_kmeans.html', session_id=filename2, clusterType=clusterType, method_name='KMeans', is_spatial=is_spatial,
-    #tooltips starts from here
-    description=description['kmeans'], tooltip_dynamic=tooltips['dynamic'],
-    tooltip_layout=tooltips['layout_dropdown'], tooltip_number_of_clusters=tooltips['number_of_clusters'])
+    return render_template('clusters/clustering_kmeans.html', session_id=filename2, clusterType=clusterType,
+                           method_name='KMeans', is_spatial=is_spatial,
+                           description=description['kmeans'], tooltip_dynamic=tooltips['dynamic'],
+                           tooltip_layout=tooltips['layout_dropdown'],
+                           tooltip_number_of_clusters=tooltips['number_of_clusters'])
+
 
 @cluster_routes.route('/clustering/agglomerative', endpoint='clustering_agglomerative', methods=['GET', 'POST'])
 def clustering_agglomerative():
+    """
+    :Function: Visualise the clusters using Agglomerative algorithm
+    :return: the clusters page
+    
+    """
     filename2 = session['filename2']
     clusterType = 'agglomerative'
     networkGraphs = get_networkGraph(filename2)
@@ -131,14 +182,20 @@ def clustering_agglomerative():
     else:
         is_spatial = 'no'
 
-    return render_template('clusters/clustering_agglomerative.html', session_id=filename2, clusterType=clusterType, method_name='Agglomerative', is_spatial=is_spatial,
-    #tooltips starts from here
-    description=description['agglomerative'], tooltip_dynamic=tooltips['dynamic'],
-    tooltip_layout=tooltips['layout_dropdown'], tooltip_number_of_clusters=tooltips['number_of_clusters'])
+    return render_template('clusters/clustering_agglomerative.html', session_id=filename2, clusterType=clusterType,
+                           method_name='Agglomerative', is_spatial=is_spatial,
+                           description=description['agglomerative'], tooltip_dynamic=tooltips['dynamic'],
+                           tooltip_layout=tooltips['layout_dropdown'],
+                           tooltip_number_of_clusters=tooltips['number_of_clusters'])
 
 
 @cluster_routes.route('/clustering/dbscan', endpoint='clustering_dbscan', methods=['GET', 'POST'])
 def clustering_dbscan():
+    """
+    :Function: Visualise the clusters using Dbscan algorithm
+    :return: the clusters page
+    
+    """
     filename2 = session['filename2']
     clusterType = 'dbscan'
     networkGraphs = get_networkGraph(filename2)
@@ -147,7 +204,8 @@ def clustering_dbscan():
     else:
         is_spatial = 'no'
 
-    return render_template('clusters/clustering_dbscan.html', session_id=filename2, clusterType=clusterType, method_name='Dbscan', is_spatial=is_spatial,
-    #tooltips starts from here
-    description=description['dbscan'], tooltip_dynamic=tooltips['dynamic'],
-    tooltip_layout=tooltips['layout_dropdown'], tooltip_number_of_clusters=tooltips['number_of_clusters'])
+    return render_template('clusters/clustering_dbscan.html', session_id=filename2, clusterType=clusterType,
+                           method_name='Dbscan', is_spatial=is_spatial,
+                           description=description['dbscan'], tooltip_dynamic=tooltips['dynamic'],
+                           tooltip_layout=tooltips['layout_dropdown'],
+                           tooltip_number_of_clusters=tooltips['number_of_clusters'])
diff --git a/application/routes/deepLearning/__init__.py b/application/routes/deepLearning/__init__.py