Cleaning up the software folder.

[pingpong.git] / python_ml / plotting.py

diff --git a/python_ml/plotting.py b/python_ml/plotting.py
deleted file mode 100644 (file)
index 0089d02..0000000
--- a/python_ml/plotting.py
+++ /dev/null
@@ -1,51 +0,0 @@
-from sklearn.cluster import KMeans
-import matplotlib.cm as cm
-import numpy as np
-import matplotlib.pyplot as plt
-
-# Create a subplot with 1 row and 2 columns
-fig, (ax2) = plt.subplots(1, 1)
-fig.set_size_inches(7, 7)
-
-
-# Read from file
-# TODO: Just change the following path and filename 
-#      when needed to read from a different file
-path = "/scratch/July-2018/Pairs/"
-filename = "dlink-off.txt"
-
-# Read and create an array of pairs
-with open(path + filename, "r") as pairs:
-       pairsArr = []
-       for line in pairs:
-               # We will see a pair and we need to split it into xpoint and ypoint
-               xpoint, ypoint = line.split(", ")
-               pair = [int(xpoint), int(ypoint)]
-               pairsArr.append(pair)
-
-# Formed array of pairs                
-#print(pairsArr)
-X = np.array(pairsArr);
-
-clusters = 6
-
-# Plot the data points based on the clusters
-clusterer = KMeans(n_clusters=clusters, random_state=10)
-cluster_labels = clusterer.fit_predict(X)
-# 2nd Plot showing the actual clusters formed
-colors = cm.nipy_spectral(cluster_labels.astype(float) / clusters)
-ax2.scatter(X[:, 0], X[:, 1], marker='o', s=50, lw=0, alpha=0.3,
-            c=colors, edgecolor='k')
-
-# Labeling the clusters
-centers = clusterer.cluster_centers_
-# Label with cluster centers and frequencies
-for i, c in enumerate(centers):
-       mark = '[' + str(int(c[0])) + ', ' + str(int(c[1])) + ']' + ', ' + str(clusterer.labels_.tolist().count(i))
-       ax2.scatter(c[0], c[1], marker='$%s$' % mark, alpha=1, s=3000, edgecolor='k')
-       print('[' + str(int(c[0])) + ', ' + str(int(c[1])) + ']' + ', ' + str(clusterer.labels_.tolist().count(i)))
-
-ax2.set_title("The visualization of the clustered data.")
-ax2.set_xlabel("Feature space for the 1st feature")
-ax2.set_ylabel("Feature space for the 2nd feature")
-plt.show()