[GRASS-SVN] r71062 - grass-addons/grass7/raster/r.object.activelearning

[svn_grass at osgeo.org]

Author: mlennert
Date: 2017-05-08 04:24:52 -0700 (Mon, 08 May 2017)
New Revision: 71062

Modified:
   grass-addons/grass7/raster/r.object.activelearning/r.object.activelearning.py
Log:
r.object.activelearning: lazy loading of scikit-learn in main() to allow compilation on server

Modified: grass-addons/grass7/raster/r.object.activelearning/r.object.activelearning.py
===================================================================
--- grass-addons/grass7/raster/r.object.activelearning/r.object.activelearning.py	2017-05-08 08:07:13 UTC (rev 71061)
+++ grass-addons/grass7/raster/r.object.activelearning/r.object.activelearning.py	2017-05-08 11:24:52 UTC (rev 71062)
@@ -101,16 +101,6 @@
 except ImportError :
 	pass
 
-try :
-	from sklearn import svm
-	from sklearn import preprocessing
-	from sklearn.model_selection import train_test_split
-	from sklearn.model_selection import RandomizedSearchCV
-	from sklearn.model_selection import StratifiedKFold
-	from sklearn.metrics.pairwise import rbf_kernel
-except ImportError :
-	gcore.fatal("This module requires the scikit-learn python package. Please install it.")
-
 import numpy as np 
 import scipy 
 import os.path
@@ -535,6 +525,18 @@
 	global nbr_uncertainty
 	global search_iter
 
+        global svm, preprocessing, train_test_split, RandomizedSearchCV
+        global StratifiedKFold, rbf_kernel
+        try :
+                from sklearn import svm
+                from sklearn import preprocessing
+                from sklearn.model_selection import train_test_split
+                from sklearn.model_selection import RandomizedSearchCV
+                from sklearn.model_selection import StratifiedKFold
+                from sklearn.metrics.pairwise import rbf_kernel
+        except ImportError :
+                gcore.fatal("This module requires the scikit-learn python package. Please install it.")
+
 	learning_steps = int(options['learning_steps']) if options['learning_steps'] != '0' else 5
 	search_iter = int(options['search_iter']) if options['search_iter'] != '0' else 10					# Number of samples to label at each iteration
 	diversity_lambda = float(options['diversity_lambda']) if options['diversity_lambda'] != '' else 0.25		# Lambda parameter used in the diversity heuristic