feat: ✨ Update reports module (#1136)

* fix: 🚸 change 'max_nfev' from 1000 to None

This change goes back to `None` to allow `lmfit` to allows again to evualte the required number of fits based on the proposed model.

* feat: ✨ Add `warnings` for informing about fitting exceptions

* feat: ✨ Add fit insights to fit report

* ci: 💚 Update release file path in labeler.yml

* ci: 💚 Remove unused codeowners in labeler.yml

* Revert "ci: 💚 Remove unused codeowners in labeler.yml"

This reverts commit 5845c02.

* ci: ⬇️ Update labeler version back to `v4`

* Revert "ci: ⬇️ Update labeler version back to `v4`"

This reverts commit e4767aa.

* feat: ✨ Switch to default value for max iterations

* ci: ♻️ Update labeler.yml to v5 standard

* from tools import transform_numpy_dictionary

* fix: 🐛 condition for setting computional message

* ci: 💚 Update labeler.yml with changed file patterns

* test: ✅ Add `np.int64` for converting to int

.github/labeler.yml

@@ -1,54 +1,82 @@
+root:
+- changed-files:
+  - any-glob-to-any-file: '*'
 codeowners:
-  - .github/CODEOWNERS
+- changed-files:
+  - any-glob-to-any-file: .github/CODEOWNERS
 codespaces:
-  - .devcontainer/**
+- changed-files:
+  - any-glob-to-any-file:  .devcontainer/**
 dependencies:
-  - poetry.lock
-  - github/dependabot.yml
+- changed-files:
+  - any-glob-to-any-file:
+    - poetry.lock
+    - github/dependabot.yml
 documentation:
-  - docs/**
-  - Examples/**
-  - mkdocs.yml
-  - README.md
-  - INSTALLATION.md
+- changed-files:
+  - any-glob-to-any-file:
+    - docs/**
+    - Examples/**
+    - mkdocs.yml
+    - README.md
+    - INSTALLATION.md
 forms:
-  - .github/ISSUE_TEMPLATE/**
-  - .github/pull_request_template.md
+- changed-files:
+  - any-glob-to-any-file:
+    - .github/ISSUE_TEMPLATE/**
+    - .github/pull_request_template.md
 github-actions:
-  - .github/workflows/**
+- changed-files:
+  - any-glob-to-any-file: .github/workflows/**
 pre-commit:
-  - .pre-commit-config.yaml
-  - .pre-commit-hooks.yaml
+- changed-files:
+  - any-glob-to-any-file:
+    - .pre-commit-config.yaml
+    - .pre-commit-hooks.yaml
 python:
-  - "spectrafit/**/*.py"
+- changed-files:
+  - any-glob-to-any-file: "spectrafit/**/*.py"
 testing:
-  - "spectrafit/**/test_*.py"
+- changed-files:
+  - any-glob-to-any-file: "spectrafit/**/test_*.py"
 docker:
-  - Dockerfile
-  - .dockerignore
-  - .devcontainer/Dockerfile
+- changed-files:
+  - any-glob-to-any-file:
+    - Dockerfile
+    - .dockerignore
+    - .devcontainer/Dockerfile
 release:
-  - "spectrafit/__init__.py"
+- changed-files:
+    - any-glob-to-any-file: spectrafit/__init__.py
 vendor:
-  - vendor/**
+- changed-files:
+  - any-glob-to-any-file: vendor/**
 maintenance:
-  - .gitignore
-  - .github/dependabot.yml
-  - .github/release-drafter.yml
-  - .github/labeler.yml
-  - .github/workflows/label.yml
-  - .sonarcloud.properties
-  - .pre-commit-config.yaml
-  - .prettierignore
-  - .pylintrc
-  - .sonarcloud.properties
-  - .sourcery.yaml
-  - "pyproject.toml"
+- changed-files:
+  - any-glob-to-any-file:
+    - .gitignore
+    - .github/dependabot.yml
+    - .github/release-drafter.yml
+    - .github/labeler.yml
+    - .github/workflows/label.yml
+    - .sonarcloud.properties
+    - .pre-commit-config.yaml
+    - .prettierignore
+    - .pylintrc
+    - .sonarcloud.properties
+    - .sourcery.yaml
+    - "pyproject.toml"
 license:
-  - LICENSE
+- changed-files:
+  - any-glob-to-any-file:
+    - LICENSE
+    - THIRD_PARTY_LICENSES
 security:
-  - SECURITY.md
+- changed-files:
+  - any-glob-to-any-file: SECURITY.md
 code-of-conduct:
-  - CODE_OF_CONDUCT.md
+- changed-files:
+  - any-glob-to-any-file: CODE_OF_CONDUCT.md
 changelog:
-  - CHANGELOG.md
+- changed-files:
+  - any-glob-to-any-file: CHANGELOG.md

spectrafit/api/report_model.py

@@ -106,6 +106,10 @@ class SolverAPI(BaseModel):
         default={},
         description="Error bar comment if values reach initial value or boundary",
     )
+    computional: Dict[str, Any] = Field(
+        ...,
+        description="Computional information like number of function evaluations",
+    )
 
 
 class OutputAPI(BaseModel):

spectrafit/api/tools_model.py

@@ -80,7 +80,7 @@ class SolverModelsAPI(BaseModel):
         description="Minimizer options",
     )
     optimizer: Dict[str, Any] = Field(
-        default={"max_nfev": 1000, "method": "leastsq"},
+        default={"max_nfev": None, "method": "leastsq"},
         description="Optimzer options",
     )
 

spectrafit/models.py

@@ -753,7 +753,7 @@ def model_check(self, model: str) -> None:
             model (str): Model name.
 
         Raises:
-            KeyError: If the model is not supported.
+            NotImplementedError: If the model is not implemented.
         """
         if model.split("_")[0] not in self.__models__:
             raise NotImplementedError(f"{model} is not supported!")
@@ -1532,12 +1532,11 @@ def __call__(self) -> Tuple[Minimizer, Any]:
                 **self.args_solver["minimizer"],
             )
 
-        return (
-            minimizer,
-            minimizer.minimize(
-                **self.args_solver["optimizer"],
-            ),
+        result = minimizer.minimize(
+            **self.args_solver["optimizer"],
         )
+        self.args_solver["optimizer"]["max_nfev"] = minimizer.max_nfev
+        return minimizer, result
 
     @staticmethod
     def solve_local_fitting(

spectrafit/plugins/notebook.py

@@ -43,6 +43,8 @@
 from spectrafit.models import SolverModels
 from spectrafit.tools import PostProcessing
 from spectrafit.tools import PreProcessing
+from spectrafit.tools import exclude_none_dictionary
+from spectrafit.tools import transform_numpy_dictionary
 from spectrafit.utilities.transformer import list2dict
 
 
@@ -595,6 +597,15 @@ def get_linear_correlation(self) -> Dict[str, Any]:
         """
         return self.args_out["linear_correlation"]
 
+    @property
+    def get_computional(self) -> Dict[str, Any]:
+        """Get the computational time.
+
+        Returns:
+            Dict[str, Any]: Computational time as dictionary.
+        """
+        return self.args_out["fit_insights"]["computional"]
+
     @property
     def settings_conf_interval(self) -> Union[bool, Dict[str, Any]]:
         """Confidence interval settings.
@@ -705,7 +716,7 @@ def make_input_contribution(self) -> InputAPI:
                 global_fitting=self.settings_global_fitting,
                 confidence_interval=self.settings_conf_interval,
                 configurations=self.settings_configurations,
-                settings_solver_models=self.settings_solver_models.dict(
+                settings_solver_models=self.settings_solver_models.model_dump(
                     exclude_none=True
                 ),
             ),
@@ -728,6 +739,7 @@ def make_solver_contribution(self) -> SolverAPI:
             covariance_matrix=self.get_covariance_matrix,
             variables=self.get_variables,
             errorbars=self.get_errorbars,
+            computional=self.get_computional,
         )
 
     @property
@@ -742,15 +754,26 @@ def make_output_contribution(self) -> OutputAPI:
     def __call__(self) -> Dict[str, Any]:
         """Get the complete report as dictionary.
 
+        !!! info "About the report and `exclude_none_dictionary`"
+
+            The report is generated by using the `ReportAPI` class, which is a
+            `Pydantic`-definition of the report. The `Pydantic`-definition is
+            converted to a dictionary by using the `.model_dump()` option of `Pydantic`.
+            The `recursive_exclude_none` function is used to remove all `None` values
+            from the dictionary, which are hidden in the nested dictionaries.
+
         Returns:
             Dict[str, Any]: Report as dictionary by using the `.dict()` option of
                  pydantic. `None` is excluded.
         """
-        return ReportAPI(
+        report = ReportAPI(
             input=self.make_input_contribution,
             solver=self.make_solver_contribution,
             output=self.make_output_contribution,
-        ).dict(exclude_none=True)
+        ).model_dump(exclude_none=True)
+        report = exclude_none_dictionary(report)
+        report = transform_numpy_dictionary(report)
+        return report
 
 
 class SpectraFitNotebook(DataFramePlot, DataFrameDisplay, ExportResults):
@@ -1129,7 +1152,7 @@ def solver_model(
                     "column": list(self.df.columns),
                     "autopeak": self.autopeak,
                     **list2dict(peak_list=self.initial_model),
-                    **self.settings_solver_models.dict(),
+                    **self.settings_solver_models.model_dump(),
                 },
             )(),
         )()

spectrafit/plugins/test/test_notebook.py

@@ -111,6 +111,7 @@ def args_out_fixture() -> Dict[str, Any]:
                 "error_a": {"value": 1, "std": 2},
                 "error_b": {"value": 3, "std": 4},
             },
+            "computional": {"optmizer": "leastsq", "nfev": 1000},
         },
         "descriptive_statistic": pd.DataFrame({"mean": [1, 2], "std": [1, 2]}).to_dict(
             orient="list"