1 files changed, 0 insertions, 32 deletions

diff --git a/Metrics/Metrics-Calculation/metrics_plot/src/test.py b/Metrics/Metrics-Calculation/metrics_plot/src/test.py
deleted file mode 100644
index 0212cc2a..00000000
--- a/Metrics/Metrics-Calculation/metrics_plot/src/test.py
+++ /dev/null
@@ -1,32 +0,0 @@
-from pyclustering.cluster.kmedoids import kmedoids
-from pyclustering.utils import read_sample
-from pyclustering.samples.definitions import FCPS_SAMPLES
-from pyclustering.utils.metric import distance_metric, type_metric
-import matplotlib.pyplot as plt 
-
-# metric = distance_metric(type_metric.MINKOWSKI, degree=2)
-# print(metric([1,1], [2,2]))
-
-# Load list of points for cluster analysis.
-sample = [[1,1,1], [2,2,2],[3,3,3]]
-
-# Set random initial medoids.
-initial_medoids = [1, 1 ,1]
-# Create instance of K-Medoids algorithm.
-kmedoids_instance = kmedoids(sample, initial_medoids)
-# Run cluster analysis and obtain results.
-kmedoids_instance.process()
-centoids = kmedoids_instance.get_medoids()
-clusters = kmedoids_instance.get_clusters()
-# Show allocated clusters.
-for cluster_id in range(len(clusters)):
-    for index in clusters[cluster_id]:
-        if(cluster_id == 0):
-            plt.plot(sample[index][0], sample[index][1], 'ro')
-            print(sample[index][0])
-        else:
-            plt.plot(sample[index][0], sample[index][1], 'bo')
-
-plt.plot(sample[centoids[0]][0], sample[centoids[0]][1], 'bo')
-# plt.plot(sample[centoids[1]][0], sample[centoids[1]][1], 'ro')
-plt.show()
\ No newline at end of file