From 36700a13ee46d2f4bb01d00df2d66f72393d96a9 Mon Sep 17 00:00:00 2001
From: tkgowtham <tkgowthamkamal@gmail.com>
Date: Wed, 2 Oct 2024 21:14:43 +0530
Subject: [PATCH] Update dbscan.py with more test cases

---
 machine_learning/dbscan.py | 73 +++++++++++++++++++++++++++++++++++++-
 1 file changed, 72 insertions(+), 1 deletion(-)

diff --git a/machine_learning/dbscan.py b/machine_learning/dbscan.py
index 90fec1c0a..744ef69b8 100644
--- a/machine_learning/dbscan.py
+++ b/machine_learning/dbscan.py
@@ -7,6 +7,7 @@ LinkedIn : https://www.linkedin.com/in/gowtham-kamalasekar/
 
 import math
 
+import matplotlib.patches as mpatches
 import matplotlib.pyplot as plt
 import pandas as pd
 
@@ -118,6 +119,38 @@ class DbScan:
         11 [2, 10, 11, 12]
         12 [9, 11, 12]
 
+        >>> result = DbScan(3, 2.5).perform_dbscan()
+        >>> for key in sorted(result):
+        ...     print(key, sorted(result[key]))
+        1 [1, 2, 10, 11]
+        2 [1, 2, 3, 10, 11]
+        3 [2, 3, 4, 11]
+        4 [3, 4, 5, 6, 7, 8]
+        5 [4, 5, 6, 7, 8]
+        6 [4, 5, 6, 7]
+        7 [4, 5, 6, 7, 8]
+        8 [4, 5, 7, 8]
+        9 [9, 11, 12]
+        10 [1, 2, 10, 11, 12]
+        11 [1, 2, 3, 9, 10, 11, 12]
+        12 [9, 10, 11, 12]
+
+        >>> result = DbScan(5, 2.5).perform_dbscan()
+        >>> for key in sorted(result):
+        ...     print(key, sorted(result[key]))
+        1 [1, 2, 10, 11]
+        2 [1, 2, 3, 10, 11]
+        3 [2, 3, 4, 11]
+        4 [3, 4, 5, 6, 7, 8]
+        5 [4, 5, 6, 7, 8]
+        6 [4, 5, 6, 7]
+        7 [4, 5, 6, 7, 8]
+        8 [4, 5, 7, 8]
+        9 [9, 11, 12]
+        10 [1, 2, 10, 11, 12]
+        11 [1, 2, 3, 9, 10, 11, 12]
+        12 [9, 10, 11, 12]
+
         """
         if type(self.file) is str:
             data = pd.read_csv(self.file)
@@ -159,6 +192,35 @@ class DbScan:
         10   [1, 10, 11] ---> Noise ---> Border
         11   [2, 10, 11, 12] ---> Core
         12   [9, 11, 12] ---> Noise ---> Border
+
+        >>> DbScan(5,2.5).print_dbscan()
+        1   [1, 2, 10, 11] ---> Noise ---> Border
+        2   [1, 2, 3, 10, 11] ---> Core
+        3   [2, 3, 4, 11] ---> Noise ---> Border
+        4   [3, 4, 5, 6, 7, 8] ---> Core
+        5   [4, 5, 6, 7, 8] ---> Core
+        6   [4, 5, 6, 7] ---> Noise ---> Border
+        7   [4, 5, 6, 7, 8] ---> Core
+        8   [4, 5, 7, 8] ---> Noise ---> Border
+        9   [9, 11, 12] ---> Noise ---> Border
+        10   [1, 2, 10, 11, 12] ---> Core
+        11   [1, 2, 3, 9, 10, 11, 12] ---> Core
+        12   [9, 10, 11, 12] ---> Noise ---> Border
+
+        >>> DbScan(2,0.5).print_dbscan()
+        1   [1] ---> Noise
+        2   [2] ---> Noise
+        3   [3] ---> Noise
+        4   [4] ---> Noise
+        5   [5] ---> Noise
+        6   [6] ---> Noise
+        7   [7] ---> Noise
+        8   [8] ---> Noise
+        9   [9] ---> Noise
+        10   [10] ---> Noise
+        11   [11] ---> Noise
+        12   [12] ---> Noise
+
         """
         for i in self.dict1:
             print(i, " ", self.dict1[i], end=" ---> ")
@@ -185,6 +247,13 @@ class DbScan:
 
         >>> DbScan(4,1.9).plot_dbscan()
         Plotted Successfully
+
+        >>> DbScan(5,2.5).plot_dbscan()
+        Plotted Successfully
+
+        >>> DbScan(5,2.5).plot_dbscan()
+        Plotted Successfully
+
         """
         if type(self.file) is str:
             data = pd.read_csv(self.file)
@@ -214,10 +283,12 @@ class DbScan:
                     ha="center",
                     va="bottom",
                 )
+        core_legend = mpatches.Patch(color="red", label="Core")
+        noise_legend = mpatches.Patch(color="green", label="Noise")
         plt.xlabel("X")
         plt.ylabel("Y")
         plt.title("DBSCAN Clustering")
-        plt.legend(["Core", "Noise"])
+        plt.legend(handles=[core_legend, noise_legend])
         plt.show()
         print("Plotted Successfully")