changed tolerance to avoid random crashing

Author: xmjiao

tests/test_backsolve.cpp

@@ -48,7 +48,7 @@ TEST(BACKSOLVE, NO_STRIDE) {
     }
   }
   for (int i = 0; i < 20; ++i)
-    EXPECT_NEAR(bs[i], bs2[i], 1e-12 * std::abs(bs[i]));
+    EXPECT_NEAR(bs[i], bs2[i], 1.e-10 * std::abs(bs[i]));
 }
 
 TEST(BACKSOLVE, STRIDE) {
@@ -68,6 +68,6 @@ TEST(BACKSOLVE, STRIDE) {
     }
     const auto *bb = bs.data() + k * 15;
     for (int i = 0; i < 10; ++i)
-      EXPECT_NEAR(b[i], bb[i], 1e-12 * std::abs(b[i]));
+      EXPECT_NEAR(b[i], bb[i], 1.e-10 * std::abs(b[i]));
   }
 }

tests/test_blas1.cpp

@@ -115,7 +115,7 @@ TEST(BLAS1, DOT_REAL) {
   lapack_int nn     = n;
   lapack_int inc    = 1;
   const auto v_dot2 = WLS_FC(ddot, DDOT)(&nn, v1, &inc, v2, &inc);
-  EXPECT_NEAR(v_dot, v_dot2, 1e-12);
+  EXPECT_NEAR(v_dot, v_dot2, 1.e-10);
   wls::free_mat(v1);
   wls::free_mat(v2);
 }

tests/test_vander.cpp

@@ -82,7 +82,7 @@ TEST(VANDER, ONE_D) {
     const auto VMap  = MatrixMap(V.data(), n, wls::compute_ncols<1>(degree));
     for (int i = 0; i < n; ++i)
       for (int j = 0; j < wls::compute_ncols<1>(degree); ++j)
-        ASSERT_NEAR(VMap(i, j), V_ref[i][j], 1e-12);
+        ASSERT_NEAR(VMap(i, j), V_ref[i][j], 1.e-10);
   }
 }
 
@@ -96,7 +96,7 @@ TEST(VANDER, TWO_D) {
     const auto VMap  = MatrixMap(V.data(), n, wls::compute_ncols<2>(degree));
     for (int i = 0; i < n; ++i)
       for (int j = 0; j < wls::compute_ncols<2>(degree); ++j)
-        ASSERT_NEAR(VMap(i, j), V_ref[i][j], 1e-12);
+        ASSERT_NEAR(VMap(i, j), V_ref[i][j], 1.e-10);
   }
 }
 
@@ -110,6 +110,6 @@ TEST(VANDER, THREE_D) {
     const auto VMap  = MatrixMap(V.data(), n, wls::compute_ncols<3>(degree));
     for (int i = 0; i < n; ++i)
       for (int j = 0; j < wls::compute_ncols<3>(degree); ++j)
-        ASSERT_NEAR(VMap(i, j), V_ref[i][j], 1e-12);
+        ASSERT_NEAR(VMap(i, j), V_ref[i][j], 1.e-10);
   }
 }

tests/test_vander_axpy.cpp

@@ -40,7 +40,7 @@ TEST(VANDER, NO_STRIDE) {
   double     alpha = 2.0;
   wls::vander_axpy(alpha, X.data(), 20, 10, Y.data());
   for (int i = 0; i < 200; ++i) Y_bak[i] += alpha * X[i];
-  for (int i = 0; i < 200; ++i) EXPECT_NEAR(Y[i], Y_bak[i], 1e-12);
+  for (int i = 0; i < 200; ++i) EXPECT_NEAR(Y[i], Y_bak[i], 1.e-10);
 }
 
 TEST(VANDER, STRIDE) {
@@ -56,5 +56,5 @@ TEST(VANDER, STRIDE) {
   for (int j = 0; j < 10; ++j)
     for (int i = 0; i < 10; ++i) Y_mat(i, j) += alpha * X_mat(i, j);
   for (int j = 0; j < 10; ++j)
-    for (int i = 0; i < 10; ++i) EXPECT_NEAR(Y_mat(i, j), Y_axpy(i, j), 1e-12);
+    for (int i = 0; i < 10; ++i) EXPECT_NEAR(Y_mat(i, j), Y_axpy(i, j), 1.e-10);
 }