Merge branch 'feature/lixin/hyper-parameters_merge' into master

mir-group · Nov 19, 2019 · f57194e · f57194e
2 parents e0e8632 + c755bec
commit f57194e
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Showing 17 changed files with 4,332 additions and 1,124 deletions.
diff --git a/flare/gp.py b/flare/gp.py
diff --git a/flare/gp_algebra.py b/flare/gp_algebra.py
diff --git a/flare/gp_algebra_multi.py b/flare/gp_algebra_multi.py
diff --git a/flare/gp_from_aimd.py b/flare/gp_from_aimd.py
@@ -92,6 +92,8 @@ def __init__(self, frames: List[Structure],
         self.skip = skip
         assert (skip >= 1), "skip needs to be an integer >= 1"
         self.validate_ratio = validate_ratio
+        assert (validate_ratio>=0 and validate_ratio<=1), \
+                "validate_ratio needs to be [0,1]"
         self.max_trains = max_trains
         self.curr_step = 0
         self.max_atoms_from_frame = max_atoms_from_frame
@@ -212,11 +214,19 @@ def pre_run(self):
         if self.verbose >= 3 and atom_count > 0:
             print(f"Added {atom_count} atoms to pretrain")
 
-        if self.seed_envs or atom_count or self.seed_frames:
+        if (self.seed_envs or atom_count or self.seed_frames) and self.max_trains>0:
             if self.verbose >= 3:
                 print("Now commencing pre-run training of GP (which has "
                       "non-empty training set)")
             self.train_gp(max_iter=self.pre_train_max_iter)
+        else:
+            if self.verbose >= 3:
+                print("Now commencing pre-run set up of GP (which has "
+                      "non-empty training set)")
+            self.gp.set_L_alpha()
+
+        if self.model_write:
+            self.gp.write_model(self.model_write, self.model_format)
 
     def run(self):
         """
@@ -229,10 +239,7 @@ def run(self):
             print("Commencing run with pre-run...")
         self.pre_run()
 
-        if self.validate_ratio > 0:
-            train_frame = int(len(self.frames) * (1 - self.validate_ratio))
-        else:
-            train_frame = len(self.frames)
+        train_frame = int(len(self.frames) * (1 - self.validate_ratio))
 
         # Loop through trajectory
         nsample = 0
@@ -292,6 +299,10 @@ def run(self):
                         else:
                             self.gp.update_L_alpha()
                         nsample = 0
+                        if self.checkpoint_interval \
+                                and self.train_count % self.checkpoint_interval == 0 \
+                                and self.model_write:
+                            self.gp.write_model(self.model_write, self.model_format)
                     else:
                         self.gp.update_L_alpha()
 
@@ -357,4 +368,4 @@ def train_gp(self, max_iter: int = None):
         if self.checkpoint_interval \
                 and self.train_count % self.checkpoint_interval == 0 \
                 and self.model_format:
-            self.gp.write_model(self.output_name+'_model', self.model_format)
+            self.gp.write_model(self.output_name+'_model', self.model_format)
diff --git a/flare/kernels.py b/flare/kernels.py
@@ -362,7 +362,7 @@ def three_body_jit(bond_array_1, bond_array_2,
 
                     fj = fj1*fj2*fj3
                     fdj = fdj1*fj2*fj3+fj1*fdj2*fj3
-                    
+
                     kern += triplet_kernel(ci1, ci2, cj1, cj2, ri1, ri2, ri3,
                                            rj1, rj2, rj3, fi, fj, fdi, fdj,
                                            ls1, ls2, ls3, sig2)