urban/data_mining_algorithms
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General Bugfixes

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- Rewrote certain numGen functions
- Removed ++ functions
This commit is contained in:
Conrad
2018-06-05 16:58:05 +02:00
parent 667e7881cc
commit 54f81b2291
4 changed files with 26 additions and 80 deletions
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31
src/algorithms/dmlib.py
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@@ -1,27 +1,26 @@
# Calculate the difference between two points giving the indexes of these xdata entries
import math
def calcdiff(point1, point2, data):
# Calculate the difference between two points giving the indexes of these xdata entries
def calcdiff(point1, point2):
if int(point2) > int(point1):
difference = int(point2) - int(point1)
else:
difference = int(point1) - int(point2)
# print("Datapoint: " + str(xdata[point1]) + " | Cluster: " + str(xdata[point2]) + " | Difference: " + str(difference))
return betrag(difference)
return difference
# Calculate the difference between two points in 2D space
def calcdiff2d(point1, point2):
point1 = [int(i) for i in point1]
point2 = [int(i) for i in point2]
difference = math.sqrt(((point2[0])-(point1[0]))**2+((point2[0])-(point1[0]))**2)
difference = math.sqrt(((point2[0]) - (point1[0])) ** 2 + ((point2[1]) - (point1[1])) ** 2)
return betrag(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
@@ -29,21 +28,3 @@ def findHighest(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
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