Example and fix

examples/undocumented/python_modular/clustering_gmm_modular.py

@@ -0,0 +1,44 @@
+from numpy import array, append
+from shogun.Distribution import GMM
+from shogun.Library import Math_init_random
+
+Math_init_random(5)
+
+real_gmm=GMM(2)
+
+real_gmm.set_nth_mean(array([1.0, 1.0]), 0)
+real_gmm.set_nth_mean(array([-1.0, -1.0]), 1)
+
+real_gmm.set_nth_cov(array([[1.0, 0.2],[0.2, 0.1]]), 0)
+real_gmm.set_nth_cov(array([[0.3, 0.1],[0.1, 1.0]]), 1)
+
+real_gmm.set_coef(array([0.3, 0.7]))
+
+generated=array([real_gmm.sample()])
+for i in range(199):
+    generated=append(generated, array([real_gmm.sample()]), axis=0)
+
+generated=generated.transpose()
+
+parameter_list = [generated]
+
+def clustering_gmm_modular (fm_train=generated,n=2,min_cov=1e-9,max_iter=1000,min_change=1e-9,cov_type=0):
+
+	from shogun.Distribution import GMM
+	from shogun.Features import RealFeatures
+	from shogun.Library import Math_init_random
+
+	Math_init_random(5)
+
+	feat_train=RealFeatures(generated)
+
+	est_gmm=GMM(n, cov_type)
+	est_gmm.train(feat_train)
+	est_gmm.train_em(min_cov, max_iter, min_change)
+
+	return est_gmm
+
+if __name__=='__main__':
+	print 'GMM'
+	clustering_gmm_modular(*parameter_list[0])
+

examples/undocumented/python_modular/graphical/em_2d_gmm.py

@@ -11,8 +11,6 @@
 min_change=1e-9
 cov_type=0
 
-gaus1=Gaussian(array([1.0, 1.0]), array([[1.0, 0.2],[0.2, 0.1]]))
-gaus2=Gaussian(array([-1.0, -1.0]), array([[0.3, 0.1],[0.1, 1.0]]))
 real_gmm=GMM(2)
 
 real_gmm.set_nth_mean(array([1.0, 1.0]), 0)