ensure compatibility

fgcz · Oct 17, 2024 · 2554fac · 2554fac
1 parent a5a2935
commit 2554fac
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Showing 3 changed files with 10 additions and 5 deletions.
diff --git a/src/depiction/tools/calibrate/config.py b/src/depiction/tools/calibrate/config.py
@@ -2,13 +2,14 @@
 
 from typing import Literal, Annotated
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, ConfigDict
 
 from depiction.tools.calibrate.spatial_smoothing_config import GaussianSpatialSmoothingConfig, SpatialSmoothingConfig
 from depiction.tools.filter_peaks.config import FilterPeaksConfig
 
 
 class CalibrationRegressShiftConfig(BaseModel):
+    model_config = ConfigDict(extra="forbid")
     calibration_method: Literal["RegressShift"] = "RegressShift"
 
     max_distance: float
@@ -44,7 +45,8 @@ class CalibrationConstantGlobalShiftConfig(BaseModel):
     calibration_method: Literal["ConstantGlobalShift"] = "ConstantGlobalShift"
 
 
-class CalibrationConfig(BaseModel, use_enum_values=True, validate_default=True):
+class CalibrationConfig(BaseModel):
+    model_config = ConfigDict(extra="forbid", use_enum_values=True, validate_default=True)
     method: (
         Annotated[
             CalibrationRegressShiftConfig

diff --git a/src/depiction_targeted_preproc/app/config_presets/dev_presets.yml b/src/depiction_targeted_preproc/app/config_presets/dev_presets.yml
@@ -25,8 +25,9 @@ calibration:
     max_distance_unit: ppm
     reg_model_type: linear_siegelslopes
     reg_model_unit: mz
-    input_smoothing_activated: yes
-    input_smoothing_kernel_size: 5
-    input_smoothing_kernel_std: 1.0
+    spatial_smoothing:
+      type: Gaussian
+      kernel_size: 5
+      kernel_std: 1.0
     min_points: 3
   n_jobs: 10
diff --git a/src/depiction_targeted_preproc/pipeline_config/model.py b/src/depiction_targeted_preproc/pipeline_config/model.py
@@ -43,6 +43,8 @@ class PipelineArtifact(str, Enum):
 # TODO we have some redundancy in the peak picker allowing filtering... it should be removed there, since sometimes you
 #      might want peak filtering without peak picking -> TODO create task
 class PipelineParametersPreset(Model, use_enum_values=True, validate_default=True):
+    model_config = ConfigDict(extra="forbid")
+
     baseline_correction: BaselineCorrectionConfig | None
     filter_peaks: FilterPeaksConfig | None
     calibration: CalibrationConfig | None