finding centroid of cluster

Question

i have done the final project of Data Science course.
my code has solved 4 test cases and 1 gives error. unfortunately it's a hidden case, so i cannot understand what should I do.

that is the problem:
https://www.sololearn.com/learning/eom-project/1093/108

here is my code:

import numpy as np

n = int(input())

data = [[float(i) for i in input().split()] for j in range(n) ]

def dist(a, b):
x = a[0]-b[0]
y = a[1]-b[1]
res = np.sqrt(x**2+y**2)
return res

clus_1 = []
clus_2 = []

for point in data:
if(dist(point,[0,0])<=dist(point,[2,2])):
clus_1.append(point)
else:
clus_2.append(point)

res_1 = np.array(clus_1, dtype=np.float32)
res_1 = res_1.mean(axis=0)
res_1 = np.round(res_1, decimals=2)

res_2 = np.array(clus_2, dtype=np.float32)
res_2 = res_2.mean(axis=0)
res_2 = np.round(res_2, decimals=2)

print(res_1)
print(res_2)

Answer 1

"If none of the data points were assigned to the given centroid, return None."

...print(None)

Answer 2

Tnx for answering Paul K Sadler . What does it mean by givencentroid? I tried every permutation of checking empty lists to print None, its not clear to me

Answer 3

For example...

import numpy as np

first = np.array([[0., 0.]])
second = np.array([[2., 2.]])
n = int(input())

data = []

for i in range(n):
data.append([float(i) for i in input().split()])

data = np.array(data).reshape((-1,2))

for i in range(n):
dist1 = np.sqrt(((data[i]-first[0])**2).sum())

dist2 = np.sqrt(((data[i]-second[0])**2).sum())

if (dist1) <= (dist2):
first = np.vstack((first,data[i]))

else:
second = np.vstack((second,data[i]))

if first.size > 2:
mean1 = np.mean(first[1:], axis=0)
print(np.around(mean1, decimals=2))
else:
print(None)

if second.size > 2:
mean2 = np.mean(second[1:], axis=0)
print(np.around(mean2, decimals=2))
else:
print(None)

Answer 4

Paul that's great, your code works very well. but i'm confused what's wrong with my modified code? can you see whats its problem? it made me frustrated.

here it is:

import numpy as np

n = int(input())

data = [[float(i) for i in input().split()] for j in range(n) ]

def dist(a, b):
x = a[0]-b[0]
y = a[1]-b[1]
res = np.sqrt(x**2+y**2)
return res

clus_1 = []
clus_2 = []

for point in data:
if(dist(point,[0,0])<=dist(point,[2,2])):
clus_1.append(point)
else:
clus_2.append(point)

res_1 = np.array(clus_1, dtype=np.float32)
res_1 = res_1.mean(axis=0)
res_1 = np.round(res_1, decimals=2)

res_2 = np.array(clus_2, dtype=np.float32)
res_2 = res_2.mean(axis=0)
res_2 = np.round(res_2, decimals=2)

if (len(clus_1)==0):
print(None)
else:
print(res_1)

if (len(clus_2)==0):
print(None)
else:
print(res_2)

Answer 5

I found my code bug, it was trying to get mean of empty array, if statement solves this bug, tnx Paul K Sadler again

Answer 6

Glad you were able to resolve it, sorry I was not able to look before now.

Answer 7

Paul K Sadler U helped a lot

Answer 8

finding centroid of cluster
In this last project
If test 3 is giving error
Then include these below points in your code

If any of the cluster is empty(either cluster 0 or cluster 1)
Then your programme must print None for that cluster