Merge pull request #9 from munechika-koyo/develop

Refactor MFR loop
munechika-koyo · Nov 18, 2023 · bdfea95 · bdfea95
2 parents a409dc8 + c9dc517
commit bdfea95
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Showing 5 changed files with 62 additions and 42 deletions.
diff --git a/cherab/inversion/__init__.py b/cherab/inversion/__init__.py
@@ -5,4 +5,4 @@
 from .mfr import Mfr
 
 __all__ = ["compute_svd", "_SVDBase", "Lcurve", "GCV", "Mfr"]
-__version__ = "0.1.2.dev0"
+__version__ = "0.1.2"
diff --git a/cherab/inversion/mfr.py b/cherab/inversion/mfr.py
@@ -194,6 +194,10 @@ def solve(
         if not issubclass(regularizer, _SVDBase):
             raise TypeError("regularizer must be a subclass of _SVDBase")
 
+        # check data attribute
+        if self._data is None:
+            raise ValueError("data attribute is not set")
+
         # check initial solution
         if x0 is None:
             x0 = np.ones(self._gmat.shape[1])
@@ -212,50 +216,66 @@ def solve(
             else:
                 path: Path = Path(path)
 
-        # MFR loop
+        # set iteration counter and status
         niter = 0
         status = {}
         self._converged = False
         errors = []
+        reg = None
+        x = None
+
+        # set timer
         start_time = time()
+
+        # start MFR iteration
         while niter < miter and not self._converged:
             with Spinner(f"{niter:02}-th MFR iteration", timer=True) as sp:
-                sp_base_text = sp.text + " "
-
-                # compute regularization matrix
-                hmat = self.regularization_matrix(
-                    x0, eps=eps, derivative_weights=derivative_weights
-                )
-
-                # compute SVD components
-                spinner = sp if verbose else None
-                singular, u_vecs, basis = compute_svd(self._gmat, hmat, use_gpu=use_gpu, sp=spinner)
-
-                # find optimal solution using regularizer class
-                sp.text = sp_base_text + " (Solving regularizer)"
-                reg = regularizer(singular, u_vecs, basis, data=self._data)
-                x, _ = reg.solve(bounds=bounds, **kwargs)
-
-                # check convergence
-                diff = np.linalg.norm(x - x0)
-                errors.append(diff)
-                self._converged = bool(diff < tol)
-
-                # update solution
-                x0 = x
-
-                # store regularizer object at each iteration
-                if store_regularizers:
-                    with (path / f"regularizer_{niter}.pickle").open("wb") as f:
-                        pickle.dump(reg, f)
-
-                # print iteration information
-                _text = f"(Diff: {diff:.3e}, Tolerance: {tol:.3e}, lambda: {reg.lambda_opt:.3e})"
-                sp.text = sp_base_text + _text
-                sp.ok()
-
-                # update iteration counter
-                niter += 1
+                try:
+                    sp_base_text = sp.text + " "
+
+                    # compute regularization matrix
+                    hmat = self.regularization_matrix(
+                        x0, eps=eps, derivative_weights=derivative_weights
+                    )
+
+                    # compute SVD components
+                    spinner = sp if verbose else None
+                    singular, u_vecs, basis = compute_svd(
+                        self._gmat, hmat, use_gpu=use_gpu, sp=spinner
+                    )
+
+                    # find optimal solution using regularizer class
+                    sp.text = sp_base_text + " (Solving regularizer)"
+                    reg = regularizer(singular, u_vecs, basis, data=self._data)
+                    x, _ = reg.solve(bounds=bounds, **kwargs)
+
+                    # check convergence
+                    diff = np.linalg.norm(x - x0)
+                    errors.append(diff)
+                    self._converged = bool(diff < tol)
+
+                    # update solution
+                    x0 = x
+
+                    # store regularizer object at each iteration
+                    if store_regularizers:
+                        with (path / f"regularizer_{niter}.pickle").open("wb") as f:
+                            pickle.dump(reg, f)
+
+                    # print iteration information
+                    _text = (
+                        f"(Diff: {diff:.3e}, Tolerance: {tol:.3e}, lambda: {reg.lambda_opt:.3e})"
+                    )
+                    sp.text = sp_base_text + _text
+                    sp.ok()
+
+                    # update iteration counter
+                    niter += 1
+
+                except Exception as e:
+                    sp.fail()
+                    print(e)
+                    break
 
         elapsed_time = time() - start_time
 

diff --git a/docs/source/_static/switcher.json b/docs/source/_static/switcher.json
@@ -5,8 +5,8 @@
   },
   {
     "name": "0.1",
-    "version": "v0.1.1",
-    "url": "https://cherab-inversion.readthedocs.io/en/v0.1.1/",
+    "version": "v0.1.2",
+    "url": "https://cherab-inversion.readthedocs.io/en/v0.1.2/",
     "preferred": true
   }
 ]
diff --git a/meson.build b/meson.build
@@ -2,7 +2,7 @@ project(
   'cherab-inversion',
   'cython',
   # Note that version cannot dinamically changed now.
-  version: '0.1.2.dev0',
+  version: '0.1.2',
   meson_version: '>= 0.64.0',
   default_options: [
     'cython_args=-3',

diff --git a/pyproject.toml b/pyproject.toml
@@ -10,7 +10,7 @@ build-backend = "mesonpy"
 [project]
 name = "cherab-inversion"
 description = "Cherab inversion framework"
-version = "0.1.2.dev0"
+version = "0.1.2"
 readme = "README.md"
 authors = [
     { name = "Koyo Munechika", email = "[email protected]" },