Anselmoo · Anselmoo · Mar 22, 2023 · Mar 20, 2023 · Mar 20, 2023 · Mar 20, 2023
@@ -20,9 +20,9 @@ pre-commit:
   - .pre-commit-config.yaml
   - .pre-commit-hooks.yaml
 python:
-  - all: ["./spectrafit/**/*.py", "!./spectrafit/**/test_*.py"]
+  - any: ["./spectrafit/**/*.py", "!./spectrafit/**/test_*.py"]
 testing:
-  - all: ["./spectrafit/**/test_*.py"]
+  - "./spectrafit/**/test_*.py"
 docker:
   - Dockerfile
   - .dockerignore

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "SpectraFit"
-version = "1.0.0b2"
+version = "0.16.6"
 description = "Fast fitting of 2D- and 3D-Spectra with established routines"
 readme = "README.md"
 authors = ["Anselm Hahn <[email protected]>"]
@@ -101,7 +101,7 @@ exclude = ["docs/", "tools/"]
   mkdocs-minify-plugin = "^0.6.2"
   mkdocs-material = "^9.1.2"
   jupytext = "^1.14.5"
-  mkdocs-jupyter = "^0.23.1"
+  mkdocs-jupyter = "^0.24.0"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]

@@ -1,2 +1,2 @@
 """SpectraFit, fast command line tool for fitting data."""
-__version__ = "1.0.0b2"
+__version__ = "0.16.6"
@@ -47,7 +47,7 @@ class FitMethodAPI(BaseModel):
         default=False,
         description="Fitting in the global fashion",
     )
-    confidence_interval: Dict[str, Any] = Field(
+    confidence_interval: Union[bool, Dict[str, Any]] = Field(
         ...,
         description="Settings for the confidence interval calculation",
     )

@@ -569,21 +569,29 @@ def get_linear_correlation(self) -> Dict[str, Any]:
         return self.args_out["linear_correlation"]
 
     @property
-    def settings_conf_interval(self) -> Dict[str, Any]:
+    def settings_conf_interval(self) -> Union[bool, Dict[str, Any]]:
         """Confidence interval settings.
 
         Returns:
-            Dict[str, Any]: Confidence interval settings.
+            Union[bool, Dict[str, Any]]: Confidence interval settings.
         """
+        if isinstance(self.args_out["conf_interval"], dict):
+            self.args_out["conf_interval"] = {
+                key: value if value is not None else {}
+                for key, value in self.args_out["conf_interval"].items()
+            }
         return self.args_out["conf_interval"]
 
     @property
     def get_confidence_interval(self) -> Dict[Any, Any]:
         """Get the confidence interval.
 
         Returns:
-            Dict[Any, Any]: Confidence interval as dictionary.
+            Dict[Any, Any]: Confidence interval as dictionary with or without the
+                    confidence interval results.
         """
+        if self.args_out["conf_interval"] is False:
+            return {}
         return self.args_out["confidence_interval"]
 
     @property

@@ -571,6 +571,26 @@ def test_conv_2(
 
             mock_show.assert_called_once()
 
+    def test_conv_no(
+        self,
+        class_spectrafit_fit: SpectraFitNotebook,
+        initial_model: List[Dict[str, Dict[str, Dict[str, Any]]]],
+    ) -> None:
+        """Test conf interval via bool for false."""
+        sp = class_spectrafit_fit
+
+        with mock.patch(__plotly_io_show__) as mock_show:
+            sp.solver_model(
+                initial_model=initial_model,
+                show_plot=False,
+                show_df=True,
+                show_metric=True,
+                show_peaks=True,
+                conf_interval=False,
+            )
+
+            mock_show.assert_called_once()
+
     def test_display_current_df(
         self,
         class_spectrafit_fit: SpectraFitNotebook,
@@ -583,3 +603,20 @@ def test_display_current_df(
         sp.display_original_df()
         sp.display_preprocessed_df()
         sp.display_fit_df()
+
+    def test_confidence_interval_false_expot(
+        self,
+        class_spectrafit_fit: SpectraFitNotebook,
+        initial_model: List[Dict[str, Dict[str, Dict[str, Any]]]],
+    ) -> None:
+        """Test the confidence interval function."""
+        sp = class_spectrafit_fit
+        sp.solver_model(
+            initial_model=initial_model,
+            show_plot=False,
+            show_df=False,
+            show_metric=False,
+            show_peaks=False,
+            conf_interval=False,
+        )
+        sp.generate_report