Add graph visuals

requirements.txt

@@ -1,8 +1,9 @@
 streamlit>=1.2.0
-plotly>=5.4.0
-scikit-learn>=1.0.1
 spacy-streamlit>=1.0.2
 spacy>=3.1.4
 benepar>=0.2.0
+pyvis
+numpy
+pandas
 
 https://huggingface.co/edichief/en_healthsea/resolve/main/en_healthsea-any-py3-none-any.whl

support_functions.py

@@ -2,10 +2,12 @@ import pandas as pd
 import difflib
 from spacy.tokens import Doc
 
-import plotly
-import plotly.graph_objs as go
-from sklearn.manifold import TSNE
 import numpy as np
+from numpy import dot
+from numpy.linalg import norm
+
+from pyvis.network import Network
+import streamlit.components.v1 as components
 
 
 class HealthseaSearch:
@@ -149,52 +151,44 @@ class HealthseaSearch:
                 mode="lines+markers+text",
                 marker={
                     "size": 10,
-                    "opacity": 0.8,
+                    "opacity": 1,
+                    "colorscale":'Viridis',
                 },
             )
 
             # Configure the layout.
             layout = go.Layout(
-                margin={"l": 0, "r": 0, "b": 0, "t": 0}, font={"color": "#DF55E2"}
+                margin={"l": 0, "r": 0, "b": 0, "t": 0}, font={"color": "#DF55E2", "size":20}
             )
 
             data = [trace]
 
             return go.Figure(data=data, layout=layout)
 
-        else:
-            tsne_model = TSNE(
-                perplexity=40, n_components=2, init="pca", n_iter=2500, random_state=23
-            )
+    def pyvis(self, vectors):
+        net = Network(height='500px', width='700px', bgcolor="#0E1117", font_color="#ffffff")
+        net.barnes_hut(central_gravity = 0.8, spring_length = 100)
 
-            new_values = tsne_model.fit_transform(tokens)
-
-            x = []
-            y = []
-            for value in new_values:
-                x.append(value[0])
-                y.append(value[1])
+        net.add_node(vectors[0][0], label=vectors[0][0], color="#4EA0DB", value=100) # node id = 1 and label = Node 1
 
-            trace = go.Scatter(
-                x=x,
-                y=y,
-                text=labels,
-                textposition="top right",
-                mode="lines+markers+text",
-                marker={
-                    "size": 10,
-                    "opacity": 0.8,
-                },
-            )
+        for vector in vectors[1:]:
+            net.add_node(vector[0], label=vector[0], color="#FE51B9", value=70) # node id = 1 and label = Node 1
 
-            # Configure the layout.
-            layout = go.Layout(
-                margin={"l": 0, "r": 0, "b": 0, "t": 0}, font={"color": "#DF55E2"}
-            )
+        for i, vector in enumerate(vectors):
+            current_vector = vectors[i]
+            if i < len(vectors):
+                for _vector in vectors[i+1:]:
+                    sim = self.calculate_cosine_sim(current_vector[1],_vector[1])
+                    net.add_edge(current_vector[0],_vector[0], weight=sim, value=sim*0.1, title=sim)
 
-            data = [trace]
+        net.save_graph("viz.html")
+        HtmlFile = open("viz.html", 'r', encoding='utf-8')
+        source_code = HtmlFile.read() 
+        components.html(source_code, height = 500, width=700)
 
-            return go.Figure(data=data, layout=layout)
+    def calculate_cosine_sim(self,a,b):
+        cos_sim = dot(a, b)/(norm(a)*norm(b))
+        return cos_sim
 
     # Load substance meta
     def get_substances(self, _aspect, n):
@@ -266,24 +260,31 @@ class HealthseaSearch:
     def get_all_conditions(self):
         condition_list = []
         for condition_key in self.conditions:
-            condition_list.append((self.conditions[condition_key]["frequency"],condition_key))
+            if condition_key in self.health_aspects:
+                alias = len(self.health_aspects[condition_key]["alias"])
+            else:
+                alias = 0
+            condition_list.append((self.conditions[condition_key]["frequency"],condition_key,alias))
 
         condition_list = sorted(condition_list, key=lambda tup: tup[0], reverse=True)
         return condition_list
 
     def get_all_conditions_df(self):
-        condition_list = self.get_all_conditions()[:1000]
+        condition_list = self.get_all_conditions()[:100]
         condition_data = {
             "Condition": [],
-            "Frequency": []
+            "Frequency": [],
+            "Alias": []
         }
         for condition in condition_list:
             condition_data["Frequency"].append(condition[0])
             condition_data["Condition"].append(condition[1])
+            condition_data["Alias"].append(condition[2])
 
         datatypes = {
             "Frequency": int,
-            "Condition": str
+            "Condition": str,
+            "Alias": int
         }
 
         df = pd.DataFrame(data=condition_data)
@@ -295,24 +296,32 @@ class HealthseaSearch:
     def get_all_benefits(self):
         benefit_list = []
         for benefit_key in self.benefits:
-            benefit_list.append((self.benefits[benefit_key]["frequency"],benefit_key))
+            if benefit_key in self.health_aspects:
+                alias = len(self.health_aspects[benefit_key]["alias"])
+            else:
+                alias = 0
+            benefit_list.append((self.benefits[benefit_key]["frequency"],benefit_key,alias))
 
         benefit_list = sorted(benefit_list, key=lambda tup: tup[0], reverse=True)
         return benefit_list
 
     def get_all_benefits_df(self):
-        benefit_list = self.get_all_benefits()[:1000]
+        benefit_list = self.get_all_benefits()[:100]
         benefit_data = {
             "Benefit": [],
-            "Frequency": []
+            "Frequency": [],
+            "Alias": []
         }
         for benefit in benefit_list:
             benefit_data["Frequency"].append(benefit[0])
             benefit_data["Benefit"].append(benefit[1])
+            benefit_data["Alias"].append(benefit[2])
+
 
         datatypes = {
             "Frequency": int,
-            "Benefit": str
+            "Benefit": str,
+            "Alias": int
         }
 
         df = pd.DataFrame(data=benefit_data)

visualize_dataset.py

@@ -119,7 +119,8 @@ def visualize_dataset():
             vectors.append((current_aspect["name"], current_aspect["vector"]))
         st.markdown("\n")
         st.info("""To improve the search, the table also shows results of other health aspects with a high similarity""")
-        st.write(search_engine.tsne_plot(vectors))
+        #st.write(search_engine.tsne_plot(vectors))
+        search_engine.pyvis(vectors)
 
     else:
         kpi_mentions, kpi_product_mentions = st.columns(2)

viz.html

@@ -0,0 +1,116 @@
+<html>
+<head>
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/vis/4.16.1/vis.css" type="text/css" />
+<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/vis/4.16.1/vis-network.min.js"> </script>
+<center>
+<h1></h1>
+</center>
+
+<!-- <link rel="stylesheet" href="../node_modules/vis/dist/vis.min.css" type="text/css" />
+<script type="text/javascript" src="../node_modules/vis/dist/vis.js"> </script>-->
+
+<style type="text/css">
+
+        #mynetwork {
+            width: 700px;
+            height: 500px;
+            background-color: #0E1117;
+            border: 1px solid lightgray;
+            position: relative;
+            float: left;
+        }
+
+        
+
+        
+
+        
+</style>
+
+</head>
+
+<body>
+<div id = "mynetwork"></div>
+
+
+<script type="text/javascript">
+
+    // initialize global variables.
+    var edges;
+    var nodes;
+    var network; 
+    var container;
+    var options, data;
+
+    
+    // This method is responsible for drawing the graph, returns the drawn network
+    function drawGraph() {
+        var container = document.getElementById('mynetwork');
+        
+        
+
+        // parsing and collecting nodes and edges from the python
+        nodes = new vis.DataSet([{"color": "#4EA0DB", "font": {"color": "#ffffff"}, "id": "knee pain", "label": "knee pain", "shape": "dot", "value": 100}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "joint pain", "label": "joint pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "foot pain", "label": "foot pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "hip pain", "label": "hip pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "shoulder pain", "label": "shoulder pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "knee joint pain", "label": "knee joint pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "knee pains", "label": "knee pains", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "ankle pain", "label": "ankle pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "neck pain", "label": "neck pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "knees pain", "label": "knees pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "wrist pain", "label": "wrist pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "shoulder pains", "label": "shoulder pains", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "forearm pain", "label": "forearm pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "leg pain", "label": "leg pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "legs pain", "label": "legs pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "chest pain", "label": "chest pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "elbow pain", "label": "elbow pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "spine pain", "label": "spine pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "finger joint pain", "label": "finger joint pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "toe pain", "label": "toe pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "arm pain", "label": "arm pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "hip joint pain", "label": "hip joint pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "wrist joint pain", "label": "wrist joint pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "head pain", "label": "head pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "knee swelling", "label": "knee swelling", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "groin pain", "label": "groin pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "feet pain", "label": "feet pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "jaw pain", "label": "jaw pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "shoulders pain", "label": "shoulders pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "tendon pain", "label": "tendon pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "thigh pain", "label": "thigh pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "arms pain", "label": "arms pain", "shape": "dot", "value": 70}, {"color": "#FE51B9", "font": {"color": "#ffffff"}, "id": "hip knee pain", "label": "hip knee pain", "shape": "dot", "value": 70}]);
+        edges = new vis.DataSet([{"from": "knee pain", "title": 0.9572226566398652, "to": "joint pain", "value": 0.09572226566398652, "weight": 0.9572226566398652}, {"from": "knee pain", "title": 0.9721691627688442, "to": "foot pain", "value": 0.09721691627688443, "weight": 0.9721691627688442}, {"from": "knee pain", "title": 0.9728595739961694, "to": "hip pain", "value": 0.09728595739961694, "weight": 0.9728595739961694}, {"from": "knee pain", "title": 0.9886381450225392, "to": "shoulder pain", "value": 0.09886381450225393, "weight": 0.9886381450225392}, {"from": "knee pain", "title": 0.9633261170891145, "to": "knee joint pain", "value": 0.09633261170891146, "weight": 0.9633261170891145}, {"from": "knee pain", "title": 0.9641970662920486, "to": "knee pains", "value": 0.09641970662920486, "weight": 0.9641970662920486}, {"from": "knee pain", "title": 0.9852088102259774, "to": "ankle pain", "value": 0.09852088102259775, "weight": 0.9852088102259774}, {"from": "knee pain", "title": 0.9775551384003314, "to": "neck pain", "value": 0.09775551384003314, "weight": 0.9775551384003314}, {"from": "knee pain", "title": 0.9527260826829039, "to": "knees pain", "value": 0.0952726082682904, "weight": 0.9527260826829039}, {"from": "knee pain", "title": 0.9668905460143599, "to": "wrist pain", "value": 0.096689054601436, "weight": 0.9668905460143599}, {"from": "knee pain", "title": 0.9506593292143222, "to": "shoulder pains", "value": 0.09506593292143223, "weight": 0.9506593292143222}, {"from": "knee pain", "title": 0.9694992428145469, "to": "forearm pain", "value": 0.0969499242814547, "weight": 0.9694992428145469}, {"from": "knee pain", "title": 0.980168245352133, "to": "leg pain", "value": 0.0980168245352133, "weight": 0.980168245352133}, {"from": "knee pain", "title": 0.9505274489621832, "to": "legs pain", "value": 0.09505274489621833, "weight": 0.9505274489621832}, {"from": "knee pain", "title": 0.9721296071055993, "to": "chest pain", "value": 0.09721296071055993, "weight": 0.9721296071055993}, {"from": "knee pain", "title": 0.9839312972552418, "to": "elbow pain", "value": 0.09839312972552418, "weight": 0.9839312972552418}, {"from": "knee pain", "title": 0.9584609544116655, "to": "spine pain", "value": 0.09584609544116655, "weight": 0.9584609544116655}, {"from": "knee pain", "title": 0.9519111501913806, "to": "finger joint pain", "value": 0.09519111501913807, "weight": 0.9519111501913806}, {"from": "knee pain", "title": 0.9609345812503135, "to": "toe pain", "value": 0.09609345812503135, "weight": 0.9609345812503135}, {"from": "knee pain", "title": 0.974981705771776, "to": "arm pain", "value": 0.0974981705771776, "weight": 0.974981705771776}, {"from": "knee pain", "title": 0.9537760229169574, "to": "hip joint pain", "value": 0.09537760229169574, "weight": 0.9537760229169574}, {"from": "knee pain", "title": 0.9545163508269806, "to": "wrist joint pain", "value": 0.09545163508269806, "weight": 0.9545163508269806}, {"from": "knee pain", "title": 0.958708042693945, "to": "head pain", "value": 0.09587080426939451, "weight": 0.958708042693945}, {"from": "knee pain", "title": 0.9545507396519165, "to": "knee swelling", "value": 0.09545507396519165, "weight": 0.9545507396519165}, {"from": "knee pain", "title": 0.9557324494770963, "to": "groin pain", "value": 0.09557324494770963, "weight": 0.9557324494770963}, {"from": "knee pain", "title": 0.952505866119859, "to": "feet pain", "value": 0.0952505866119859, "weight": 0.952505866119859}, {"from": "knee pain", "title": 0.9703174913222936, "to": "jaw pain", "value": 0.09703174913222937, "weight": 0.9703174913222936}, {"from": "knee pain", "title": 0.9529714904579305, "to": "shoulders pain", "value": 0.09529714904579306, "weight": 0.9529714904579305}, {"from": "knee pain", "title": 0.9576092078570831, "to": "tendon pain", "value": 0.09576092078570832, "weight": 0.9576092078570831}, {"from": "knee pain", "title": 0.9677445817935832, "to": "thigh pain", "value": 0.09677445817935833, "weight": 0.9677445817935832}, {"from": "knee pain", "title": 0.9506022576954113, "to": "arms pain", "value": 0.09506022576954114, "weight": 0.9506022576954113}, {"from": "knee pain", "title": 0.9606641167811792, "to": "hip knee pain", "value": 0.09606641167811793, "weight": 0.9606641167811792}, {"from": "joint pain", "title": 0.9244428549530791, "to": "foot pain", "value": 0.09244428549530792, "weight": 0.9244428549530791}, {"from": "joint pain", "title": 0.9550355502713094, "to": "hip pain", "value": 0.09550355502713094, "weight": 0.9550355502713094}, {"from": "joint pain", "title": 0.9410141085943581, "to": "shoulder pain", "value": 0.09410141085943581, "weight": 0.9410141085943581}, {"from": "joint pain", "title": 0.9483466241569839, "to": "knee joint pain", "value": 0.09483466241569839, "weight": 0.9483466241569839}, {"from": "joint pain", "title": 0.9018196317633977, "to": "knee pains", "value": 0.09018196317633978, "weight": 0.9018196317633977}, {"from": "joint pain", "title": 0.9255280047665597, "to": "ankle pain", "value": 0.09255280047665598, "weight": 0.9255280047665597}, {"from": "joint pain", "title": 0.9343239075808237, "to": "neck pain", "value": 0.09343239075808238, "weight": 0.9343239075808237}, {"from": "joint pain", "title": 0.8790642776719283, "to": "knees pain", "value": 0.08790642776719283, "weight": 0.8790642776719283}, {"from": "joint pain", "title": 0.9004978597329176, "to": "wrist pain", "value": 0.09004978597329177, "weight": 0.9004978597329176}, {"from": "joint pain", "title": 0.8838578611724158, "to": "shoulder pains", "value": 0.08838578611724159, "weight": 0.8838578611724158}, {"from": "joint pain", "title": 0.9216961499753696, "to": "forearm pain", "value": 0.09216961499753697, "weight": 0.9216961499753696}, {"from": "joint pain", "title": 0.9378619158732041, "to": "leg pain", "value": 0.09378619158732042, "weight": 0.9378619158732041}, {"from": "joint pain", "title": 0.8798352710030111, "to": "legs pain", "value": 0.0879835271003011, "weight": 0.8798352710030111}, {"from": "joint pain", "title": 0.9268068797624519, "to": "chest pain", "value": 0.0926806879762452, "weight": 0.9268068797624519}, {"from": "joint pain", "title": 0.9421524468267243, "to": "elbow pain", "value": 0.09421524468267244, "weight": 0.9421524468267243}, {"from": "joint pain", "title": 0.9352659055908789, "to": "spine pain", "value": 0.0935265905590879, "weight": 0.9352659055908789}, {"from": "joint pain", "title": 0.9198614060170138, "to": "finger joint pain", "value": 0.09198614060170139, "weight": 0.9198614060170138}, {"from": "joint pain", "title": 0.9013564915153371, "to": "toe pain", "value": 0.09013564915153371, "weight": 0.9013564915153371}, {"from": "joint pain", "title": 0.9275325362246755, "to": "arm pain", "value": 0.09275325362246756, "weight": 0.9275325362246755}, {"from": "joint pain", "title": 0.9549502924292922, "to": "hip joint pain", "value": 0.09549502924292923, "weight": 0.9549502924292922}, {"from": 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"to": "hip knee pain", "value": 0.09372469971999134, "weight": 0.9372469971999133}, {"from": "arms pain", "title": 0.9213338932213619, "to": "hip knee pain", "value": 0.0921333893221362, "weight": 0.9213338932213619}]);
+
+        // adding nodes and edges to the graph
+        data = {nodes: nodes, edges: edges};
+
+        var options = {
+    "configure": {
+        "enabled": false
+    },
+    "edges": {
+        "color": {
+            "inherit": true
+        },
+        "smooth": {
+            "enabled": false,
+            "type": "continuous"
+        }
+    },
+    "interaction": {
+        "dragNodes": true,
+        "hideEdgesOnDrag": false,
+        "hideNodesOnDrag": false
+    },
+    "physics": {
+        "barnesHut": {
+            "avoidOverlap": 0,
+            "centralGravity": 0.8,
+            "damping": 0.09,
+            "gravitationalConstant": -80000,
+            "springConstant": 0.001,
+            "springLength": 100
+        },
+        "enabled": true,
+        "stabilization": {
+            "enabled": true,
+            "fit": true,
+            "iterations": 1000,
+            "onlyDynamicEdges": false,
+            "updateInterval": 50
+        }
+    }
+};
+        
+        
+
+        
+
+        network = new vis.Network(container, data, options);
+	 
+        
+
+
+        
+
+        return network;
+
+    }
+
+    drawGraph();
+
+</script>
+</body>
+</html>