diff --git a/spectral/algorithms/algorithms.py b/spectral/algorithms/algorithms.py
index ab14505..a7c6f6c 100644
--- a/spectral/algorithms/algorithms.py
+++ b/spectral/algorithms/algorithms.py
@@ -567,7 +567,7 @@ def principal_components(image):
     (L, V) = np.linalg.eig(stats.cov)
 
     # numpy says eigenvalues may not be sorted so we'll sort them, if needed.
-    if not np.alltrue(np.diff(L) <= 0):
+    if not np.all(np.diff(L) <= 0):
         ii = list(reversed(np.argsort(L)))
         L = L[ii]
         V = V[:, ii]
@@ -1683,7 +1683,7 @@ def mnf(signal, noise):
     C = noise.sqrt_inv_cov.dot(signal.cov).dot(noise.sqrt_inv_cov)
     (L, V) = np.linalg.eig(C)
     # numpy says eigenvalues may not be sorted so we'll sort them, if needed.
-    if not np.alltrue(np.diff(L) <= 0):
+    if not np.all(np.diff(L) <= 0):
         ii = list(reversed(np.argsort(L)))
         L = L[ii]
         V = V[:, ii]
diff --git a/spectral/tests/spatial.py b/spectral/tests/spatial.py
index 882c136..6b58539 100644
--- a/spectral/tests/spatial.py
+++ b/spectral/tests/spatial.py
@@ -158,7 +158,7 @@ def test_map_classes_isomorphic(self):
         gt2 = gt + 1
         d = map_class_ids(gt2, gt)
         result = map_classes(gt2, d)
-        assert (np.alltrue(result == gt))
+        assert (np.all(result == gt))
 
     def test_map_fails_allow_unmapped_false(self):
         '''map_classes should raise ValueError if image has unmapped value.'''
@@ -180,7 +180,7 @@ def test_map_allow_unmapped_true(self):
         d = map_class_ids(gt2, gt)
         d.pop(1)
         result = map_classes(gt2, d, allow_unmapped=True)
-        assert (np.alltrue(result[gt2 == 1] == 1))
+        assert (np.all(result[gt2 == 1] == 1))
 
 
 def run():
diff --git a/spectral/tests/spymath.py b/spectral/tests/spymath.py
index 3be5618..649542c 100644
--- a/spectral/tests/spymath.py
+++ b/spectral/tests/spymath.py
@@ -73,7 +73,7 @@ def setup(self):
 
     def test_evals_sorted(self):
         '''Eigenvalues should be sorted in descending order.'''
-        assert (np.alltrue(np.diff(self.pc.eigenvalues) <= 0))
+        assert (np.all(np.diff(self.pc.eigenvalues) <= 0))
 
     def test_evecs_orthonormal(self):
         '''Eigenvectors should be orthonormal.'''