Fixed unit tests

psdr/opt/check_gradient.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-def check_gradient(f, x, grad, verbose = False):
+def check_gradient(f, x, grad, verbose = True):
 	grad_est_best = np.zeros(grad.shape)
 	for h in np.logspace(-14, -2,20):
 		grad_est = np.zeros(grad.shape)
@@ -20,5 +20,5 @@ def check_gradient(f, x, grad, verbose = False):
 		print "index, grad, grad est., ratio"
 		for i in np.ndindex(grad.shape):
 			print i, "%+5.2e %+5.2e  %+5.2e" %(grad[i], grad_est_best[i], grad[i]/grad_est_best[i])
-
-	return np.max(np.abs( (grad - grad_est_best)/grad ))
+	
+	np.max(np.abs( (grad - grad_est_best)/(np.abs(grad)+1e-10) ))

psdr/poly_ridge.py

@@ -6,7 +6,7 @@
 import scipy.linalg
 from scipy.linalg import norm
 from scipy.linalg import svd
-from scipy.misc import comb
+from scipy.special import comb
 from scipy.optimize import minimize, check_grad
 from scipy.spatial import Voronoi
 from copy import deepcopy

tests/test_ridge.py

@@ -1,6 +1,6 @@
 import numpy as np
 from psdr.poly_ridge import residual, build_J, LegendreTensorBasis  
-from psdr.util import check_gradient
+from psdr.opt import check_gradient
 
 
 def test_jacobian():