The pieces seem to work, but getting NaNs for center coordinates afte…

…r iterating...hmmm...

k_means_plus_plus.py

@@ -4,14 +4,17 @@
 from numbers import Integral
 
 class KMeansPlusPlus:
- def __init__(self,data_frame,k,columns=None,max_iterations=None):
+ def __init__(self,data_frame,k
+ ,columns=None
+ ,max_iterations=None
+ ,tolerance = 1e-5):
  if not isinstance(data_frame,DataFrame):
  raise Exception("data_frame argument is not a pandas DataFrame")
  elif data_frame.empty:
  raise Exception("The given data frame is empty")
 
  if max_iterations is not None and max_iterations <= 0:
- raise Exception("")
+ raise Exception("max_iterations must be positive!")
 
 
  self.data_frame = data_frame # m x n
@@ -21,6 +24,7 @@ def __init__(self,data_frame,k,columns=None,max_iterations=None):
  # from point i to center j (where i and j start at 0)
  self.clusters = None # Series of length m, consisting of integers 0,1,...,k-1
  self.previous_clusters = None
+ self.max_iterations = max_iterations
 
  if not isinstance(k,Integral) or k <= 0:
  raise Exception("The value of k must be a positive integer")
@@ -74,13 +78,16 @@ def _get_clusters(self):
 
  min_distances = self.distance_matrix.min(axis=1)
 
- cluster_list = [
- boolean_series.index[j][0]
- for boolean_series in [
- self.distance_matrix.iloc[i,:] == min_distances[i]
- for i in list(range(len(self.columns)))
- ]
- for j in list(range(self.k))
+ #We need to make sure the index 
+ min_distances.index = list(range(self.numRows))
+
+ cluster_list = [boolean_series.index[j]
+ for boolean_series in
+ [
+ self.distance_matrix.iloc[i,:] == min_distances.iloc[i]
+ for i in list(range(self.numRows))
+ ]
+ for j in list(range(self.k))
  if boolean_series[j]
  ]
 
@@ -113,7 +120,7 @@ def cluster(self):
  self._compute_distances()
  self._get_clusters()
 
- if max_iterations is not None and counter >= max_iterations:
+ if self.max_iterations is not None and counter >= self.max_iterations:
  break
  elif all(self.clusters == self.previous_clusters):
  break