MISC Using np.finfo(float).eps instead of 1e-10 in Matern kernel

Jan Hendrik Metzen · Jan Hendrik Metzen · commit 0b035a8f8ad6 · 2014-12-20T10:00:15.000+01:00
Furthmore, fixed typo and increased readability of test_matern_kernel.
diff --git a/examples/svm/plot_svm_matern_kernel.py b/examples/svm/plot_svm_matern_kernel.py
@@ -10,7 +10,7 @@
 is compared on a (discontinuous) step-function:
  * The Matern kernel for coef0==1.5, learning a once differentiable function
  * The Matern kernel for coef0==2.5, learning a twice differentiable function
- * The Matern kernel for coef0==3.5, learning a three-rimes differentiable 
+ * The Matern kernel for coef0==3.5, learning a three-times differentiable 
    function
  * The absolute-exponential kernel which corresponds to a Matern kernel
    with coef0==0.5
diff --git a/sklearn/metrics/pairwise.py b/sklearn/metrics/pairwise.py
@@ -792,7 +792,7 @@ def matern_kernel(X, Y=None, gamma=None, coef0=1.5):
         K *= np.sqrt(5) * gamma
         K = (1 + K + K ** 2 / 3.0) * np.exp(-K)
     else:  # general case; expensive to evaluate
-        K[K == 0.0] += 1e-10  # strict zeros would result in nan
+        K[K == 0.0] += np.finfo(float).eps  # strict zeros would result in nan
         tmp = (np.sqrt(2 * coef0) * gamma * K)
         K[:] = (2 ** (1 - coef0)) / scipy.special.gamma(coef0)
         K *= tmp ** coef0
diff --git a/sklearn/metrics/tests/test_pairwise.py b/sklearn/metrics/tests/test_pairwise.py
@@ -421,7 +421,7 @@ def test_matern_kernel():
     X = rng.random_sample((5, 4))
     K = matern_kernel(X, X)
     # the diagonal elements of a matern kernel are 1
-    assert_array_almost_equal(K.flat[::6], np.ones(5))
+    assert_array_almost_equal(np.diag(K), np.ones(5))
     # matern kernel for coef0==inf is equal to rbf kernel
     K_rbf = rbf_kernel(X, X)
     K = matern_kernel(X, X, coef0=np.inf)
