Code Rework

src/algorithms/dmlib.py

@@ -1,40 +1,27 @@
 # Calculate the difference between two points giving the indexes of these data entries
 def calcdiff(point1, point2):
-	if int(point2) > int(point1):
-		difference = int(point2) - int(point1)
-	else:
-		difference = int(point1) - int(point2)
-	# print("Datapoint: " + str(data[point1]) + " | Cluster: " + str(data[point2]) + " | Difference: " + str(difference))
-	return betrag(difference)
+    if int(point2) > int(point1):
+        difference = int(point2) - int(point1)
+    else:
+        difference = int(point1) - int(point2)
+    return abs(difference)
 
-# Get the absolute value of a number and returns it as int
-def betrag(number):
-	if number < 0:
-		number = int((-2 * number) / 2)
-	return number
-
-# Determine the highest int value in an array and returns is as an int
-def findHighest(data):
-	maximum = 0
-	for i in range(0, len(data)):
-		if int(data[i]) > maximum:
-			maximum = int(data[i])
-	return maximum
 
 def pp_calcdiff(data, clusterpoint):
-	max_diff = 0
-	new_cluster = 0
-	for item in range(0,len(data)):
-		if calcdiff(data[item], clusterpoint) > max_diff:
-			max_diff = calcdiff(data[item], clusterpoint)
-			new_cluster = data[item]
-	return new_cluster
+    max_diff = 0
+    new_cluster = 0
+    for item in range(0, len(data)):
+        if calcdiff(data[item], clusterpoint) > max_diff:
+            max_diff = calcdiff(data[item], clusterpoint)
+            new_cluster = data[item]
+    return new_cluster
+
 
 def pp_calcdiff_2(data, clusterpoint, clusterpoint_2):
-	max_diff = 0
-	new_cluster = 0
-	for item in range(0,len(data)):
-		if calcdiff(data[item], clusterpoint) + calcdiff(data[item], clusterpoint_2) > max_diff:
-			max_diff = calcdiff(data[item], clusterpoint)
-			new_cluster = data[item]
-	return new_cluster
+    max_diff = 0
+    new_cluster = 0
+    for item in range(0, len(data)):
+        if calcdiff(data[item], clusterpoint) + calcdiff(data[item], clusterpoint_2) > max_diff:
+            max_diff = calcdiff(data[item], clusterpoint)
+            new_cluster = data[item]
+    return new_cluster