sparsity logged in gp2Scale

lbl-camera · Sep 23, 2024 · bdce992 · bdce992
1 parent 03e28eb
commit bdce992
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Showing 2 changed files with 4 additions and 2 deletions.
diff --git a/fvgp/gp_lin_alg.py b/fvgp/gp_lin_alg.py
@@ -101,7 +101,7 @@ def calculate_sparse_minres(KV, vec, info=False, x0=None, M=None):
     if isinstance(x0, np.ndarray) and len(x0) < KV.shape[0]: x0 = np.append(x0, np.zeros(KV.shape[0] - len(x0)))
     res = np.zeros(vec.shape)
     for i in range(vec.shape[1]):
-        res[:, i], exit_code = minres(KV.tocsc(), vec[:, i], M=M, rtol=1e-8, x0=x0)
+        res[:, i], exit_code = minres(KV.tocsc(), vec[:, i], M=M, rtol=1e-5, x0=x0)
         if exit_code == 1: warnings.warn("MINRES not successful")
     if info: logger.info("MINRES compute time: {} seconds.",
                          time.time() - st)
@@ -116,7 +116,7 @@ def calculate_sparse_conj_grad(KV, vec, info=False, x0=None, M=None):
     if isinstance(x0, np.ndarray) and len(x0) < KV.shape[0]: x0 = np.append(x0, np.zeros(KV.shape[0] - len(x0)))
     res = np.zeros(vec.shape)
     for i in range(vec.shape[1]):
-        res[:, i], exit_code = cg(KV.tocsc(), vec[:, i], M=M, rtol=1e-8, x0=x0)
+        res[:, i], exit_code = cg(KV.tocsc(), vec[:, i], M=M, rtol=1e-5, x0=x0)
         if exit_code == 1: warnings.warn("CG not successful")
     if info: logger.info("CG compute time: {} seconds.", time.time() - st)
     return res

diff --git a/fvgp/gp_prior.py b/fvgp/gp_prior.py
@@ -190,6 +190,7 @@ def _compute_prior_covariance_gp2Scale(self, x_data, hyperparameters):
 
         logger.debug("        gp2Scale covariance matrix result written after {} seconds.", time.time() - st)
 
+
         # reshape the result set into COO components
         data, i_s, j_s = map(np.hstack, zip(*results))
         # mirror across diagonal
@@ -199,6 +200,7 @@ def _compute_prior_covariance_gp2Scale(self, x_data, hyperparameters):
             np.hstack([j_s, i_s[diagonal_mask]])
         K = sparse.coo_matrix((data, (i_s, j_s)), shape=(len(x_data), len(x_data)))
         logger.debug("        gp2Scale covariance matrix assembled after {} seconds.", time.time() - st)
+        logger.debug("        gp2Scale covariance matrix sparsity = {}.", float(K.nnz) / float(K.shape[0] ** 2))
         return K
 
     def _update_prior_covariance_gp2Scale(self, x_old, x_new, hyperparameters):