From add08468a5d53a5f1149e5cec674029c875e8974 Mon Sep 17 00:00:00 2001
From: pavanvpatil <pavanvpatil01@gmail.com>
Date: Thu, 10 Nov 2022 11:40:45 +0530
Subject: [PATCH] python

---
 iPDC/plot_kmeans2.py | 40 ++++++++++++++++++++++------------------
 1 file changed, 22 insertions(+), 18 deletions(-)

diff --git a/iPDC/plot_kmeans2.py b/iPDC/plot_kmeans2.py
index ae068e2..0323e7a 100644
--- a/iPDC/plot_kmeans2.py
+++ b/iPDC/plot_kmeans2.py
@@ -4,8 +4,8 @@
 
 import csv
 import numpy as np
+import random
 import matplotlib.pyplot as plt
-from sklearn import preprocessing
 x=[]
 y=[]
 x1=[]
@@ -17,14 +17,14 @@ with open('kmeans.csv', mode ='r') as file:
     for lines in csvFile:
         #print(lines)
         if(int(lines[2])==0):
-            x.append(float(lines[0]))
-            y.append(float(lines[1]))
+            x.append(float(lines[0])+random.randrange(0,9,1)*0.01)
+            y.append(float(lines[1])+random.randrange(0,9,2)*0.01)
         elif(int(lines[2])==1):
-            x1.append(float(lines[0]))
-            y1.append(float(lines[1]))
+            x1.append(float(lines[0])+random.randrange(0,9,3)*0.01)
+            y1.append(float(lines[1])+random.randrange(0,9,1)*0.01)
         else:
-            x2.append(float(lines[0]))
-            y2.append(float(lines[1]))
+            x2.append(float(lines[0])+random.randrange(0,9,2)*0.01)
+            y2.append(float(lines[1])+random.randrange(0,9,3)*0.01)
 
 x.append(50.284426)
 y.append(65451.237705)
@@ -33,15 +33,15 @@ y1.append(65476.164948)
 x2.append(50.302515)
 y2.append(65464.320755)
 
-x_array = np.array(x+x1+x2)
-y_array = np.array(y+y1+y2)
-# x1_array = np.array(x1)
-# y1_array = np.array(y1)
-# x2_array = np.array(x2)
-# y2_array = np.array(y2)
+x_arr = np.array(x)
+y_arr = np.array(y)
+x1_arr = np.array(x1)
+y1_arr = np.array(y1)
+x2_arr = np.array(x2)
+y2_arr = np.array(y2)
 
-x_arr = preprocessing.normalize([x_array])
-y_arr = preprocessing.normalize([y_array])
+# x_arr = preprocessing.normalize([x_array])
+# y_arr = preprocessing.normalize([y_array])
 
 # x1_arr = preprocessing.normalize([x1_array])
 # y1_arr = preprocessing.normalize([y1_array])
@@ -49,8 +49,12 @@ y_arr = preprocessing.normalize([y_array])
 # x2_arr = preprocessing.normalize([x2_array])
 # y2_arr = preprocessing.normalize([y2_array])
 
-plt.scatter(x_arr, y_arr)
-# plt.scatter(x1_arr, y1_arr)
-# plt.scatter(x2_arr, y2_arr)
+plt.scatter(x_arr, y_arr,)
+plt.scatter(x1_arr, y1_arr)
+plt.scatter(x2_arr, y2_arr)
+plt.xlabel("Frequency in Hz")
+plt.ylabel("Voltage in Volts")
+plt.title("K-means Clustering")
+plt.legend(["A","B","C"])
 
 plt.show()
\ No newline at end of file