Semantic Linking: Created Classes for semantic linking logic

data-hub/semantic-linking-microservice/app/initialdemo/HyperGraph.py

-import networkx as nx
-import matplotlib.pyplot as plt
-import pandas as pd
 import json
 
+nodeIds = []
+destIds = []
+clusterlabels = []
+destclusterlabel = []
+cluster = []
+labalvlues = []
 
+def classify():
 
-with open("mult_in_out.json", "r") as json_file:
+    with open("mult_in_out.json", "r") as json_file:
         df_nodes = json.load(json_file)
 
 
-nodeIds = []
-destIds= []
-clusterlabels= []
-destclusterlabel = []
-cluster= []
-labalvlues = []
-i = 0
-
 
-for row in df_nodes:
+    for row in df_nodes:
 
         for j in range(len(row['TransactionFrom'])):
             print("   Input Ids:  ", row['TransactionFrom'][j])
@@ -26,23 +22,24 @@ for row in df_nodes:
         print("This is nodes:  ", nodeIds)
 
 
-for row in df_nodes:
+    for row in df_nodes:
        destIds.append(row['TransactionTo'])
 
 
-for row in range(len(nodeIds)):
+    for row in range(len(nodeIds)):
         print(nodeIds[row])
 
-print("Finish InputIDs")
-for row in range(len(nodeIds)):
+    print("Finish InputIDs")
+    i = 0
+    for row in range(len(nodeIds)):
 
         clusterlabels.append(row)
         i += 1
-print(i)
+    print(i)
 
-"""" classifying Inputs"""
-"""" Labaling inputs"""
-for row in range(len(nodeIds)):
+    """" classifying Inputs"""
+    """" Labaling inputs"""
+    for row in range(len(nodeIds)):
 
         for rown in range(len(nodeIds[row])):
 
@@ -63,16 +60,16 @@ for row in range(len(nodeIds)):
                           clusterlabels[row] = clusterlabels[row1]
 
 
-print(clusterlabels)
-print("cluster labels:", len(clusterlabels))
-print("NodeIDs:   ", len(nodeIds))
+    print(clusterlabels)
+    print("cluster labels:", len(clusterlabels))
+    print("NodeIDs:   ", len(nodeIds))
 
 
 
-"""" Calculating the number of clusters"""
-clusternum = 1
-labalvlues.append(clusterlabels[0])
-for row in range(len(clusterlabels)):
+    """" Calculating the number of clusters"""
+    clusternum = 1
+    labalvlues.append(clusterlabels[0])
+    for row in range(len(clusterlabels)):
         flag = True
         for row1 in range(len(labalvlues)):
           if(clusterlabels[row]== labalvlues[row1]):
@@ -82,26 +79,26 @@ for row in range(len(clusterlabels)):
             clusternum = + 1
             labalvlues.append(clusterlabels[row])
 
-print("label values (source Ids in the network):  ", labalvlues, " and the number of clusters is: ", len(labalvlues))
+    print("label values (source Ids in the network):  ", labalvlues, " and the number of clusters is: ", len(labalvlues))
 
 
 
 
-"""" clustering Ids according to their labels"""
+    """" clustering Ids according to their labels"""
 
-for row in range(len(labalvlues)):
+    for row in range(len(labalvlues)):
         cluster.append([])
         for row3 in range(len(nodeIds)):
             if (labalvlues[row] == clusterlabels[row3]):
                 cluster[row].extend(nodeIds[row3])
-print("clusters:   ", cluster)
+    print("clusters:   ", cluster)
 
 
 
-""" Removing duplicating items in cluster"""
+    """ Removing duplicating items in cluster"""
 
-flag = True
-while(flag):
+    flag = True
+    while(flag):
       for row in range(len(cluster)):
 
         flag= False
@@ -118,13 +115,13 @@ while(flag):
         if(flag):
             break
 
-print("cluster:", cluster)
+    print("cluster:", cluster)
 
 
 
 
-"""" Clustering  Destination Ids """
-for row in range(len(destIds)):
+    """" Clustering  Destination Ids """
+    for row in range(len(destIds)):
         destclusterlabel.append([])
         for row2 in range(len(destIds[row])):
             flag = True
@@ -137,4 +134,4 @@ for row in range(len(destIds)):
             if(flag):
                 destclusterlabel.append(destIds[row][row2])
 
-print("destination labels (destination Ids):  ", destclusterlabel)
+    print("destination labels (destination Ids):  ", destclusterlabel)