Merge branch 'update.interface.return_value' into update

sample/user_function/simple.py

@@ -3,6 +3,7 @@
 import py2dmat
 import py2dmat.util.toml
 import py2dmat.algorithm.mapper_mpi as pm_alg
+#import py2dmat.algorithm.min_search as pm_alg
 import py2dmat.solver.function
 
 
@@ -20,4 +21,6 @@ def my_objective_fn(x: np.ndarray) -> float:
 runner = py2dmat.Runner(solver, info)
 
 alg = pm_alg.Algorithm(info, runner)
-alg.main()
+retv = alg.main()
+
+print(retv)

src/py2dmat/algorithm/_algorithm.py

@@ -142,17 +142,18 @@ def run(self) -> None:
     def _run(self) -> None:
         pass
 
-    def post(self) -> None:
+    def post(self) -> Dict:
         if self.status < AlgorithmStatus.RUN:
             msg = "algorithm has not run yet"
             raise RuntimeError(msg)
         original_dir = os.getcwd()
         os.chdir(self.output_dir)
-        self._post()
+        result = self._post()
         os.chdir(original_dir)
+        return result
 
     @abstractmethod
-    def _post(self) -> None:
+    def _post(self) -> Dict:
         pass
 
     def main(self):
@@ -172,17 +173,22 @@ def main(self):
             self.mpicomm.Barrier()
 
         time_sta = time.perf_counter()
-        self.post()
+        result = self.post()
         time_end = time.perf_counter()
         self.timer["post"]["total"] = time_end - time_sta
 
-        with open(self.proc_dir / "time.log", "w") as fw:
+        self.write_timer(self.proc_dir / "time.log")
+
+        return result
+
+    def write_timer(self, filename: Path):
+        with open(filename, "w") as fw:
             fw.write("#in units of seconds\n")
 
             def output_file(type):
-                tmp_dict = self.timer[type]
-                fw.write("#{}\n total = {}\n".format(type, tmp_dict["total"]))
-                for key, t in tmp_dict.items():
+                d = self.timer[type]
+                fw.write("#{}\n total = {}\n".format(type, d["total"]))
+                for key, t in d.items():
                     if key == "total":
                         continue
                     fw.write(" - {} = {}\n".format(key, t))

src/py2dmat/algorithm/bayes.py

@@ -153,3 +153,4 @@ def _post(self) -> None:
             print("Best Solution:")
             for x, y in zip(label_list, self.xopt):
                 print(x, "=", y)
+        return {"x": self.xopt, "fx": self.best_fx}

src/py2dmat/algorithm/exchange.py

@@ -276,8 +276,10 @@ def _post(self) -> None:
             best_x = [self.best_x]
             best_istep = [self.best_istep]
             best_iwalker = [self.best_iwalker]
+
+        best_rank = np.argmin(best_fx)
+
         if self.mpirank == 0:
-            best_rank = np.argmin(best_fx)
             with open("best_result.txt", "w") as f:
                 f.write(f"nprocs = {self.nreplica}\n")
                 f.write(f"rank = {best_rank}\n")
@@ -293,3 +295,12 @@ def _post(self) -> None:
             print(f"  fx = {best_fx[best_rank]}")
             for label, x in zip(self.label_list, best_x[best_rank]):
                 print(f"  {label} = {x}")
+
+        return {
+            "x": best_x[best_rank],
+            "fx": best_fx[best_rank],
+            "nprocs": self.nreplica,
+            "rank": best_rank,
+            "step": best_istep[best_rank],
+            "walker": best_iwalker[best_rank],
+        }

src/py2dmat/algorithm/mapper_mpi.py

@@ -14,7 +14,7 @@
 # You should have received a copy of the GNU General Public License
 # along with this program. If not, see http://www.gnu.org/licenses/.
 
-from typing import List, Union
+from typing import List, Union, Dict
 
 from pathlib import Path
 from io import open
@@ -119,7 +119,7 @@ def _prepare(self) -> None:
         # do nothing
         pass
 
-    def _post(self) -> None:
+    def _post(self) -> Dict:
         if self.mpirank == 0:
             with open("ColorMap.txt", "w") as file_output:
                 for i in range(self.mpisize):
@@ -128,3 +128,4 @@ def _post(self) -> None:
                             line = line.lstrip()
                             if not line.startswith("#"):
                                 file_output.write(line)
+        return {}

src/py2dmat/algorithm/min_search.py

@@ -217,3 +217,4 @@ def _post(self):
             f.write(f"fx = {self.fopt}\n")
             for x, y in zip(label_list, self.xopt):
                 f.write(f"{x} = {y}\n")
+        return {"x": self.xopt, "fx": self.fopt}

src/py2dmat/algorithm/pamc.py

@@ -468,8 +468,8 @@ def _post(self) -> None:
             best_x = [self.best_x]
             best_istep = [self.best_istep]
             best_iwalker = [self.best_iwalker]
+        best_rank = np.argmin(best_fx)
         if self.mpirank == 0:
-            best_rank = np.argmin(best_fx)
             with open("best_result.txt", "w") as f:
                 f.write(f"nprocs = {self.mpisize}\n")
                 f.write(f"rank = {best_rank}\n")
@@ -500,3 +500,11 @@ def _post(self) -> None:
                     f.write(f" {self.logZs[i]}")
                     f.write(f" {self.acceptance_ratio[i]}")
                     f.write("\n")
+        return {
+            "x": best_x[best_rank],
+            "fx": best_fx[best_rank],
+            "nprocs": self.mpisize,
+            "rank": best_rank,
+            "step": best_istep[best_rank],
+            "walker": best_iwalker[best_rank],
+        }