Svariati aggiornamenti

geo2net.py

 import sys
 import numpy as np
 from scipy.ndimage import distance_transform_edt
-from skimage.morphology import watershed
+from skimage.segmentation import watershed
 from skimage.future.graph import RAG,rag_boundary
 from sklearn.cluster import KMeans
 from sklearn.decomposition import PCA
@@ -15,8 +15,8 @@ from skimage.measure import regionprops
 from skfuzzy.cluster import cmeans
 import hdbscan
 
-sys.path.append('D:\Mes donnees\__WORK__\Developpement\pycharm-workspace\moringa')
-#sys.path.append('/home/raffaele/Develop/PycharmProjects/moringa')
+#sys.path.append('D:\Mes donnees\__WORK__\Developpement\pycharm-workspace\moringa')
+sys.path.append('/Users/raffaele/python/moringa')
 from sitsproc_c_modules.obiatools import zonalstats,OSTAT_MEAN,OSTAT_COUNT,OSTAT_SUM
 
 def objectStats(seg,img,stats,nodata_value=-9999.0):
@@ -36,7 +36,7 @@ def objectStats(seg,img,stats,nodata_value=-9999.0):
                                          np.arange(seg.shape[0]).astype(np.int32),
                                          np.arange(seg.shape[1]).astype(np.int32),
                                          np.array(stats).astype(np.int32),
-                                         np.array([nodata_value] * img.shape[0], np.float32))
+                                         np.array([nodata_value] * img.shape[0]).astype(np.float32))
     return zstat
 
 def objectLabelPropagation(map):
@@ -78,7 +78,7 @@ def objectKMeans(seg,img,nc,nodata_value=-9999.0,return_cluster_map = False):
 def objectCMeans(seg,img,nc,pc=0,nodata_value=-9999.0):
     print("Running CMeans")
     zstat = objectStats(seg,img,OSTAT_MEAN,nodata_value)
-    data = np.array(zstat.values()).swapaxes(0,1)
+    data = np.array(list(zstat.values())).swapaxes(0,1)
     cntr, u, u0, d, jm, p, fpc = cmeans(data,nc,2, error=0.005, maxiter=1000, init=None)
 
     clust_dict = {}
@@ -465,7 +465,7 @@ def generateClusterGraphs_tfidf(seg,tfidf):
 
 def thresholdGraph(gr, th, dir='ge', key='weight'):
     ggr = gr.copy()
-    for u,v,d in ggr.edges(data=True):
+    for u,v,d in gr.edges(data=True):
         if dir=='ge' and d[key] >= th:
             ggr.remove_edge(u, v)
         elif dir=='le' and d[key] <= th: