fix: changing ckmeans to sklearn kmeans

Loop3D · Mar 7, 2022 · 60f3ec5 · 60f3ec5
1 parent 2242bf2
commit 60f3ec5
Showing 1 changed file with 6 additions and 9 deletions.
diff --git a/LoopStructural/modelling/intrusions/intrusion_frame_builder.py b/LoopStructural/modelling/intrusions/intrusion_frame_builder.py
@@ -6,7 +6,7 @@
 
 import numpy as np
 import pandas as pd
-import ckwrap
+from sklearn.cluster import KMeans
 
 try:
     import skfmm as fmm
@@ -160,10 +160,6 @@ def add_contact_anisotropies(self, series_list=None, **kwargs):
         if self.intrusion_network_type == "shortest path":
             n_clusters = self.number_of_contacts
 
-            # if "number_contacts" in kwargs:
-            #     n_clusters = kwargs["number_contacts"]
-            # else:
-            #     n_clusters = [1]*len(series_list)
 
         if series_list == None:
             self.anisotropies_series_list = None
@@ -188,15 +184,16 @@ def add_contact_anisotropies(self, series_list=None, **kwargs):
                 n_contacts = n_clusters[i]
 
                 # use scalar field values to find different contacts
-                contact_clustering = ckwrap.ckmeans(series_i_vals, n_contacts)
+                series_i_vals_mod = series_i_vals.reshape(len(series_i_vals),1)
+                contact_clustering = KMeans(n_clusters = n_contacts, random_state=0).fit(series_i_vals_mod)
 
                 for j in range(n_contacts):
-                    series_ij_name = series_list[i].name + "_" + str(j)
-                    z = np.ma.masked_not_equal(contact_clustering.labels, j)
+                    z = np.ma.masked_not_equal(contact_clustering.labels_, j)
                     y = np.ma.masked_array(series_i_vals, z.mask)
                     series_ij_vals = np.ma.compressed(y)
                     series_ij_mean = np.mean(series_ij_vals)
                     series_ij_std = np.std(series_ij_vals)
+                    series_ij_name = series_list[i].name + "_" + str(series_ij_mean)
 
                     series_parameters[series_ij_name] = [
                         series_list[i],
@@ -354,7 +351,7 @@ def indicator_function_contacts(self, delta=None):
         #     for j in range(len(self.anisotropies_series_parameters)):
         #         delta_list.append(delta[i])
 
-        for i, contact_id in enumerate(self.anisotropies_series_parameters.keys()):
+        for i, contact_id in enumerate(sorted(self.anisotropies_series_parameters)):
             series_id = self.anisotropies_series_parameters[contact_id][0]
             seriesi_mean = self.anisotropies_series_parameters[contact_id][1]
             seriesi_std = self.anisotropies_series_parameters[contact_id][2]