Update to be backwards compatible with python 3.8 and 3.9

ovito-org · Apr 29, 2024 · fb76461 · fb76461
1 parent 51c5f1a
commit fb76461
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Showing 2 changed files with 50 additions and 38 deletions.
diff --git a/.github/workflows/python-tests.yml b/.github/workflows/python-tests.yml
@@ -18,7 +18,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.10", "3.11"]
+        python-version: ["3.8", "3.9", "3.10", "3.11"]
     steps:
     - uses: actions/checkout@v3
     - name: Install apt dependencies

diff --git a/src/scoreBasedDenoising/__init__.py b/src/scoreBasedDenoising/__init__.py
@@ -110,30 +110,36 @@ def getModelPath(self):
                 raise FileNotFoundError(f"{path} does not exist.")
             return Path(self.model_path)
         modelDir = impRes.files("graphite.pretrained_models.denoiser")
-        match self.structure:
-            case "SiO2":
-                return modelDir.joinpath("SiO2-denoiser.pt")
-            case "FCC" | "BCC" | "HCP":
-                return modelDir.joinpath("Cu-denoiser.pt")
-            case _:
-                raise NotImplementedError(
-                    f"No default model path available for: {self.structure}"
-                )
+        if self.structure == "SiO2":
+            return modelDir.joinpath("SiO2-denoiser.pt")
+        elif (
+            self.structure == "FCC"
+            or self.structure == "BCC"
+            or self.structure == "HCP"
+        ):
+            return modelDir.joinpath("Cu-denoiser.pt")
+        else:
+            raise NotImplementedError(
+                f"No default model path available for: {self.structure}"
+            )
 
     def estimateNearestNeighborsDistance(self, data):
         finder = NearestNeighborFinder(
             ScoreBasedDenoising.numNearestNeigh[self.structure], data
         )
-        match self.structure:
-            case "SiO2":
-                idx = np.where(
-                    data.particles["Particle Type"]
-                    == data.particles["Particle Type"].type_by_name("Si").id
-                )[0]
-            case "FCC" | "BCC" | "HCP":
-                idx = None
-            case _:
-                raise NotImplementedError
+        if self.structure == "SiO2":
+            idx = np.where(
+                data.particles["Particle Type"]
+                == data.particles["Particle Type"].type_by_name("Si").id
+            )[0]
+        elif (
+            self.structure == "FCC"
+            or self.structure == "BCC"
+            or self.structure == "HCP"
+        ):
+            idx = None
+        else:
+            raise NotImplementedError
         _, neighVec = finder.find_all(idx)
         return np.mean(np.linalg.norm(neighVec, axis=2))
 
@@ -180,15 +186,18 @@ def writeTable(data, y, ylabel, title):
         table.y = table.create_property(ylabel, data=y)
 
     def _modify(self, data, frame, **kwargs):
-        match self.structure:
-            case "SiO2":
-                model = self.setupSiO2model(data)
-            case "FCC" | "BCC" | "HCP":
-                model = self.setupFccBccHcpModel(data)
-            case "Custom":
-                model = self.setupCustomModel()
-            case _:
-                raise NotImplementedError
+        if self.structure == "SiO2":
+            model = self.setupSiO2model(data)
+        elif (
+            self.structure == "FCC"
+            or self.structure == "BCC"
+            or self.structure == "HCP"
+        ):
+            model = self.setupFccBccHcpModel(data)
+        elif self.structure == "Custom":
+            model = self.setupCustomModel()
+        else:
+            raise NotImplementedError
 
         model = model.to(self.device)
         model.eval()
@@ -214,15 +223,18 @@ def _modify(self, data, frame, **kwargs):
         )
         data.particles_["Position_"][...] = denoised_atoms
 
-        match self.structure:
-            case "SiO2":
-                pass
-            case "FCC" | "BCC" | "HCP":
-                self.teardownFccBccHcpModel(data)
-            case "Custom":
-                pass
-            case _:
-                raise NotImplementedError
+        if self.structure == "SiO2":
+            pass
+        elif (
+            self.structure == "FCC"
+            or self.structure == "BCC"
+            or self.structure == "HCP"
+        ):
+            self.teardownFccBccHcpModel(data)
+        elif self.structure == "Custom":
+            pass
+        else:
+            raise NotImplementedError
 
         ScoreBasedDenoising.writeTable(data, convergence, "Convergence", "Convergence")
         ScoreBasedDenoising.writeTable(