Merge branch 'update.interface' into update

extra/leed/src/leed/leed.py

@@ -106,11 +106,20 @@ def check_keywords(key, segment, registered_list):
     def name(self) -> str:
         return self._name
 
-    def prepare(self, message: py2dmat.Message) -> None:
+    def evaluate(self, x: np.ndarray, args = (), nprocs: int = 1, nthreads: int = 1) -> float:
+        self.prepare(x, args)
+        cwd = os.getcwd()
+        os.chdir(self.work_dir)
+        self.run(nprocs, nthreads)
+        os.chdir(cwd)
+        result = self.get_results()
+        return result
+
+    def prepare(self, x: np.ndarray, args) -> None:
         self.work_dir = self.proc_dir
         for dir in [self.path_to_base_dir]:
             copy_tree(os.path.join(self.root_dir, dir), os.path.join(self.work_dir))
-        self.input.prepare(message)
+        self.input.prepare(x, args)
 
     def run(self, nprocs: int = 1, nthreads: int = 1) -> None:
         self._run_by_subprocess([str(self.path_to_solver)])
@@ -149,10 +158,11 @@ def __init__(self, info):
             self.root_dir = info.base["root_dir"]
             self.output_dir = info.base["output_dir"]
 
-        def prepare(self, message: py2dmat.Message):
-            x_list = message.x
-            step = message.step
-            extra = message.set > 0
+        def prepare(self, x: np.ndarray, args):
+            x_list = x
+            #step, iset = args
+            #extra = iset > 0
+
             # Delete output files
             delete_files = ["search.s", "gleed.o"]
             for file in delete_files:

extra/sim-trhepd-rheed/src/sim_trhepd_rheed/sim_trhepd_rheed.py

@@ -122,8 +122,18 @@ def command(self) -> List[str]:
         """Command to invoke solver"""
         return [str(self.path_to_solver)]
 
-    def prepare(self, message: py2dmat.Message) -> None:
-        fitted_x_list, subdir = self.input.prepare(message)
+    def evaluate(self, x: np.ndarray, args = (), nprocs: int = 1, nthreads: int = 1) -> float:
+        self.prepare(x, args)
+        cwd = os.getcwd()
+        os.chdir(self.work_dir)
+        self.run(nprocs, nthreads)
+        os.chdir(cwd)
+        result = self.get_results()
+        return result
+
+    def prepare(self, x: np.ndarray, args) -> None:
+        # fitted_x_list, subdir = self.input.prepare(message)
+        fitted_x_list, subdir = self.input.prepare(x, args)
         self.work_dir = self.proc_dir / Path(subdir)
 
         self.output.prepare(fitted_x_list)
@@ -306,13 +316,15 @@ def load_bulk_output_file(self, filename):
             bulk_f = np.array(bulk_file)
             return bulk_f
 
-        def prepare(self, message: py2dmat.Message):
+        def prepare(self, x: np.ndarray, args):
             if self.isLogmode:
                 time_sta = time.perf_counter()
 
-            x_list = message.x
-            step = message.step
-            iset = message.set
+            # x_list = message.x
+            # step = message.step
+            # iset = message.set
+            x_list = x
+            step, iset = args
 
             dimension = self.dimension
             string_list = self.string_list

extra/sxrd/src/sxrd/sxrd.py

@@ -122,9 +122,18 @@ def check_keywords(key, segment, registered_list):
     def name(self) -> str:
         return self._name
 
-    def prepare(self, message: py2dmat.Message) -> None:
+    def evaluate(self, x: np.ndarray, args = (), nprocs: int = 1, nthreads: int = 1) -> float:
+        self.prepare(x, args)
+        cwd = os.getcwd()
+        os.chdir(self.work_dir)
+        self.run(nprocs, nthreads)
+        os.chdir(cwd)
+        result = self.get_results()
+        return result
+
+    def prepare(self, x: np.ndarray, args) -> None:
         self.work_dir = self.proc_dir
-        self.input.prepare(message)
+        self.input.prepare(x, args)
         import shutil
 
         for file in ["lsfit.in", self.path_to_f_in, self.path_to_bulk]:
@@ -180,10 +189,10 @@ def __init__(self, info):
                 info_s["config"], info_s["reference"], info_s["param"]["domain"]
             )
 
-        def prepare(self, message: py2dmat.Message):
-            x_list = message.x
-            step = message.step
-            extra = message.set > 0
+        def prepare(self, x: np.ndarray, args):
+            x_list = x
+            #step, iset = args
+            #extra = iset > 0
 
             # Generate fit file
             # Add variables by numpy array.(Variables are updated in optimization process).

src/py2dmat/__init__.py

@@ -17,7 +17,6 @@
 # Pay attention to the dependencies and the order of imports!
 # For example, Runner depends on solver.
 
-from ._message import Message
 from ._info import Info
 from . import solver
 from ._runner import Runner

src/py2dmat/_info.py

@@ -18,7 +18,10 @@
 
 from typing import MutableMapping, Optional
 from pathlib import Path
+from fnmatch import fnmatch
 
+from .util import toml
+from . import mpi
 from . import exception
 
 
@@ -61,3 +64,15 @@ def _cleanup(self) -> None:
         self.algorithm = {}
         self.solver = {}
         self.runner = {}
+
+    @classmethod
+    def from_file(cls, file_name, fmt="", **kwargs):
+        if fmt == "toml" or fnmatch(file_name.lower(), "*.toml"):
+            inp = {}
+            if mpi.rank() == 0:
+                inp = toml.load(file_name)
+            if mpi.size() > 1:
+                inp = mpi.comm().bcast(inp, root=0)
+            return cls(inp)
+        else:
+            raise ValueError("unsupported file format: {}".format(file_name))

src/py2dmat/_main.py

@@ -36,12 +36,13 @@ def main():
     args = parser.parse_args()
 
     file_name = args.inputfile
-    inp = {}
-    if py2dmat.mpi.rank() == 0:
-        inp = py2dmat.util.toml.load(file_name)
-    if py2dmat.mpi.size() > 1:
-        inp = py2dmat.mpi.comm().bcast(inp, root=0)
-    info = py2dmat.Info(inp)
+    # inp = {}
+    # if py2dmat.mpi.rank() == 0:
+    #     inp = py2dmat.util.toml.load(file_name)
+    # if py2dmat.mpi.size() > 1:
+    #     inp = py2dmat.mpi.comm().bcast(inp, root=0)
+    # info = py2dmat.Info(inp)
+    info = py2dmat.Info.from_file(file_name)
 
     algname = info.algorithm["name"]
     if algname == "mapper":