HODLR in_place bug

Author: dfm

george/hodlr.pyx

@@ -88,7 +88,7 @@ cdef class HODLRSolver:
         # Do an in-place solve if requested.
         if in_place:
             self.solver.apply_inverse(n, nrhs, <double*>y.data, <double*>y.data)
-            return y
+            return y.reshape(y0.shape)
 
         # Do the standard solve.
         cdef np.ndarray[DTYPE_t, ndim=2] alpha = np.empty_like(y, dtype=DTYPE)

george/testing/test_gp.py

@@ -56,22 +56,22 @@ def _test_prediction(solver=BasicSolver):
     mu, cov = gp.predict(y, x)
 
     assert np.allclose(y, mu), \
-        "GP must predict noise-free training data exactly ({0})." \
-        .format(solver.__name__)
+        "GP must predict noise-free training data exactly ({0}).\n({1})" \
+        .format(solver.__name__, y - mu)
 
     assert np.all(cov > -1e-15), \
-        "Covariance matrix must be nonnegative ({}).\n{}" \
+        "Covariance matrix must be nonnegative ({0}).\n{1}" \
         .format(solver.__name__, cov)
 
     var = np.diag(cov)
     assert np.allclose(var, 0), \
-        "Variance must vanish at noise-free training points ({}).\n{}" \
+        "Variance must vanish at noise-free training points ({0}).\n{1}" \
         .format(solver.__name__, var)
 
     t = np.array((-.5, .3, 1.2))
     var = np.diag(gp.predict(y, t)[1])
     assert np.all(var > 0), \
-        "Variance must be positive away from training points ({}).\n{}" \
+        "Variance must be positive away from training points ({0}).\n{1}" \
         .format(solver.__name__, var)