feat: refactoring model quality dtos (#92)

* fix: edit model quality dto

* feat: (api) classification model quality refactoring

api/app/models/metrics/model_quality_dto.py

@@ -9,19 +9,43 @@
 from app.models.model_dto import ModelType
 
 
-class MetricsBase(BaseModel):
-    f1: Optional[float] = None
-    accuracy: Optional[float] = None
+class Distribution(BaseModel):
+    timestamp: str
+    value: Optional[float] = None
+
+
+class BaseClassificationMetrics(BaseModel):
     precision: Optional[float] = None
     recall: Optional[float] = None
     f_measure: Optional[float] = None
+    true_positive_rate: Optional[float] = None
+    false_positive_rate: Optional[float] = None
+
+    model_config = ConfigDict(
+        populate_by_name=True, alias_generator=to_camel, protected_namespaces=()
+    )
+
+
+class GroupedBaseClassificationMetrics(BaseModel):
+    precision: List[Distribution]
+    recall: List[Distribution]
+    f_measure: List[Distribution]
+    true_positive_rate: List[Distribution]
+    false_positive_rate: List[Distribution]
+
+    model_config = ConfigDict(
+        populate_by_name=True, alias_generator=to_camel, protected_namespaces=()
+    )
+
+
+class AdditionalMetrics(BaseModel):
+    f1: Optional[float] = None
+    accuracy: Optional[float] = None
     weighted_precision: Optional[float] = None
     weighted_recall: Optional[float] = None
     weighted_f_measure: Optional[float] = None
     weighted_true_positive_rate: Optional[float] = None
     weighted_false_positive_rate: Optional[float] = None
-    true_positive_rate: Optional[float] = None
-    false_positive_rate: Optional[float] = None
     area_under_roc: Optional[float] = None
     area_under_pr: Optional[float] = None
 
@@ -30,53 +54,56 @@ class MetricsBase(BaseModel):
     )
 
 
-class BinaryClassificationModelQuality(MetricsBase):
+class AdditionalGroupedMetrics(GroupedBaseClassificationMetrics):
+    f1: List[Distribution]
+    accuracy: List[Distribution]
+    weighted_precision: List[Distribution]
+    weighted_recall: List[Distribution]
+    weighted_f_measure: List[Distribution]
+    weighted_true_positive_rate: List[Distribution]
+    weighted_false_positive_rate: List[Distribution]
+    area_under_roc: Optional[List[Distribution]] = None
+    area_under_pr: Optional[List[Distribution]] = None
+
+    model_config = ConfigDict(
+        populate_by_name=True, alias_generator=to_camel, protected_namespaces=()
+    )
+
+
+class GlobalBinaryMetrics(BaseClassificationMetrics, AdditionalMetrics):
     true_positive_count: int
     false_positive_count: int
     true_negative_count: int
     false_negative_count: int
 
-
-class Distribution(BaseModel):
-    timestamp: str
-    value: Optional[float] = None
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
 
-class GroupedMetricsBase(BaseModel):
-    f1: Optional[List[Distribution]] = None
-    accuracy: Optional[List[Distribution]] = None
-    precision: List[Distribution]
-    recall: List[Distribution]
-    f_measure: List[Distribution]
-    weighted_precision: Optional[List[Distribution]] = None
-    weighted_recall: Optional[List[Distribution]] = None
-    weighted_f_measure: Optional[List[Distribution]] = None
-    weighted_true_positive_rate: Optional[List[Distribution]] = None
-    weighted_false_positive_rate: Optional[List[Distribution]] = None
-    true_positive_rate: List[Distribution]
-    false_positive_rate: List[Distribution]
-    area_under_roc: Optional[List[Distribution]] = None
-    area_under_pr: Optional[List[Distribution]] = None
-
-    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+class BinaryClassificationModelQuality(GlobalBinaryMetrics):
+    pass
 
 
 class CurrentBinaryClassificationModelQuality(BaseModel):
-    global_metrics: BinaryClassificationModelQuality
-    grouped_metrics: GroupedMetricsBase
+    global_metrics: GlobalBinaryMetrics
+    grouped_metrics: AdditionalGroupedMetrics
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
 
 class ClassMetrics(BaseModel):
     class_name: str
-    metrics: MetricsBase
-    grouped_metrics: Optional[GroupedMetricsBase] = None
+    metrics: BaseClassificationMetrics
+
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+
+
+class AdditionalClassMetrics(ClassMetrics):
+    grouped_metrics: GroupedBaseClassificationMetrics
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
 
-class GlobalMetrics(MetricsBase):
+class GlobalMulticlassMetrics(AdditionalMetrics):
     confusion_matrix: List[List[int]]
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
@@ -85,7 +112,15 @@ class GlobalMetrics(MetricsBase):
 class MultiClassificationModelQuality(BaseModel):
     classes: List[str]
     class_metrics: List[ClassMetrics]
-    global_metrics: GlobalMetrics
+    global_metrics: GlobalMulticlassMetrics
+
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+
+
+class CurrentMultiClassificationModelQuality(BaseModel):
+    classes: List[str]
+    class_metrics: List[AdditionalClassMetrics]
+    global_metrics: GlobalMulticlassMetrics
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
@@ -143,6 +178,7 @@ class ModelQualityDTO(BaseModel):
         BinaryClassificationModelQuality
         | CurrentBinaryClassificationModelQuality
         | MultiClassificationModelQuality
+        | CurrentMultiClassificationModelQuality
         | RegressionModelQuality
         | CurrentRegressionModelQuality
     ]
@@ -187,7 +223,10 @@ def _create_model_quality(
                 model_quality_data=model_quality_data,
             )
         if model_type == ModelType.MULTI_CLASS:
-            return MultiClassificationModelQuality(**model_quality_data)
+            return ModelQualityDTO._create_multiclass_model_quality(
+                dataset_type=dataset_type,
+                model_quality_data=model_quality_data,
+            )
         if model_type == ModelType.REGRESSION:
             return ModelQualityDTO._create_regression_model_quality(
                 dataset_type=dataset_type, model_quality_data=model_quality_data
@@ -206,12 +245,24 @@ def _create_binary_model_quality(
             return CurrentBinaryClassificationModelQuality(**model_quality_data)
         raise MetricsInternalError(f'Invalid dataset type {dataset_type}')
 
+    @staticmethod
+    def _create_multiclass_model_quality(
+        dataset_type: DatasetType,
+        model_quality_data: Dict,
+    ) -> MultiClassificationModelQuality | CurrentMultiClassificationModelQuality:
+        """Create a multiclass model quality instance based on dataset type."""
+        if dataset_type == DatasetType.REFERENCE:
+            return MultiClassificationModelQuality(**model_quality_data)
+        if dataset_type == DatasetType.CURRENT:
+            return CurrentMultiClassificationModelQuality(**model_quality_data)
+        raise MetricsInternalError(f'Invalid dataset type {dataset_type}')
+
     @staticmethod
     def _create_regression_model_quality(
         dataset_type: DatasetType,
         model_quality_data: Dict,
     ) -> RegressionModelQuality | CurrentRegressionModelQuality:
-        """Create a binary model quality instance based on dataset type."""
+        """Create a regression model quality instance based on dataset type."""
         if dataset_type == DatasetType.REFERENCE:
             return RegressionModelQuality(**model_quality_data)
         if dataset_type == DatasetType.CURRENT:

api/tests/commons/db_mock.py

@@ -323,7 +323,7 @@ def get_sample_current_dataset(
     'mape': 35.19314237273801,
     'rmse': 202.23194752188695,
     'adj_r2': 0.9116805380966796,
-    'variance': 0.23
+    'variance': 0.23,
 }
 
 grouped_regression_model_quality_dict = {

sdk/radicalbit_platform_sdk/apis/model_current_dataset.py

@@ -10,14 +10,14 @@
     ClassificationDataQuality,
     CurrentBinaryClassificationModelQuality,
     CurrentFileUpload,
+    CurrentMultiClassificationModelQuality,
     CurrentRegressionModelQuality,
     DataQuality,
     DatasetStats,
     Drift,
     JobStatus,
     ModelQuality,
     ModelType,
-    MultiClassificationModelQuality,
     RegressionDataQuality,
 )
 
@@ -241,7 +241,7 @@ def __callback(
                         case ModelType.MULTI_CLASS:
                             return (
                                 job_status,
-                                MultiClassificationModelQuality.model_validate(
+                                CurrentMultiClassificationModelQuality.model_validate(
                                     response_json['modelQuality']
                                 ),
                             )

sdk/radicalbit_platform_sdk/models/__init__.py

@@ -23,6 +23,7 @@
 from .dataset_model_quality import (
     BinaryClassificationModelQuality,
     CurrentBinaryClassificationModelQuality,
+    CurrentMultiClassificationModelQuality,
     CurrentRegressionModelQuality,
     ModelQuality,
     MultiClassificationModelQuality,
@@ -52,6 +53,7 @@
     'ModelQuality',
     'BinaryClassificationModelQuality',
     'CurrentBinaryClassificationModelQuality',
+    'CurrentMultiClassificationModelQuality',
     'MultiClassificationModelQuality',
     'RegressionModelQuality',
     'CurrentRegressionModelQuality',

sdk/radicalbit_platform_sdk/models/dataset_model_quality.py

@@ -8,19 +8,43 @@ class ModelQuality(BaseModel):
     pass
 
 
-class MetricsBase(BaseModel):
-    f1: Optional[float] = None
-    accuracy: Optional[float] = None
+class Distribution(BaseModel):
+    timestamp: str
+    value: Optional[float] = None
+
+
+class BaseClassificationMetrics(BaseModel):
     precision: Optional[float] = None
     recall: Optional[float] = None
     f_measure: Optional[float] = None
+    true_positive_rate: Optional[float] = None
+    false_positive_rate: Optional[float] = None
+
+    model_config = ConfigDict(
+        populate_by_name=True, alias_generator=to_camel, protected_namespaces=()
+    )
+
+
+class GroupedBaseClassificationMetrics(BaseModel):
+    precision: List[Distribution]
+    recall: List[Distribution]
+    f_measure: List[Distribution]
+    true_positive_rate: List[Distribution]
+    false_positive_rate: List[Distribution]
+
+    model_config = ConfigDict(
+        populate_by_name=True, alias_generator=to_camel, protected_namespaces=()
+    )
+
+
+class AdditionalMetrics(BaseModel):
+    f1: Optional[float] = None
+    accuracy: Optional[float] = None
     weighted_precision: Optional[float] = None
     weighted_recall: Optional[float] = None
     weighted_f_measure: Optional[float] = None
     weighted_true_positive_rate: Optional[float] = None
     weighted_false_positive_rate: Optional[float] = None
-    true_positive_rate: Optional[float] = None
-    false_positive_rate: Optional[float] = None
     area_under_roc: Optional[float] = None
     area_under_pr: Optional[float] = None
 
@@ -29,53 +53,56 @@ class MetricsBase(BaseModel):
     )
 
 
-class BinaryClassificationModelQuality(ModelQuality, MetricsBase):
+class AdditionalGroupedMetrics(GroupedBaseClassificationMetrics):
+    f1: List[Distribution]
+    accuracy: List[Distribution]
+    weighted_precision: List[Distribution]
+    weighted_recall: List[Distribution]
+    weighted_f_measure: List[Distribution]
+    weighted_true_positive_rate: List[Distribution]
+    weighted_false_positive_rate: List[Distribution]
+    area_under_roc: Optional[List[Distribution]] = None
+    area_under_pr: Optional[List[Distribution]] = None
+
+    model_config = ConfigDict(
+        populate_by_name=True, alias_generator=to_camel, protected_namespaces=()
+    )
+
+
+class GlobalBinaryMetrics(BaseClassificationMetrics, AdditionalMetrics):
     true_positive_count: int
     false_positive_count: int
     true_negative_count: int
     false_negative_count: int
 
-
-class Distribution(BaseModel):
-    timestamp: str
-    value: Optional[float] = None
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
 
-class GroupedMetricsBase(BaseModel):
-    f1: Optional[List[Distribution]] = None
-    accuracy: Optional[List[Distribution]] = None
-    precision: List[Distribution]
-    recall: List[Distribution]
-    f_measure: List[Distribution]
-    weighted_precision: Optional[List[Distribution]] = None
-    weighted_recall: Optional[List[Distribution]] = None
-    weighted_f_measure: Optional[List[Distribution]] = None
-    weighted_true_positive_rate: Optional[List[Distribution]] = None
-    weighted_false_positive_rate: Optional[List[Distribution]] = None
-    true_positive_rate: List[Distribution]
-    false_positive_rate: List[Distribution]
-    area_under_roc: Optional[List[Distribution]] = None
-    area_under_pr: Optional[List[Distribution]] = None
-
-    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+class BinaryClassificationModelQuality(ModelQuality, GlobalBinaryMetrics):
+    pass
 
 
 class CurrentBinaryClassificationModelQuality(ModelQuality):
-    global_metrics: BinaryClassificationModelQuality
-    grouped_metrics: GroupedMetricsBase
+    global_metrics: GlobalBinaryMetrics
+    grouped_metrics: AdditionalGroupedMetrics
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
 
 class ClassMetrics(BaseModel):
     class_name: str
-    metrics: MetricsBase
-    grouped_metrics: Optional[GroupedMetricsBase] = None
+    metrics: BaseClassificationMetrics
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
 
-class GlobalMetrics(MetricsBase):
+class AdditionalClassMetrics(ClassMetrics):
+    grouped_metrics: GroupedBaseClassificationMetrics
+
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+
+
+class GlobalMulticlassMetrics(AdditionalMetrics):
     confusion_matrix: List[List[int]]
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
@@ -84,7 +111,15 @@ class GlobalMetrics(MetricsBase):
 class MultiClassificationModelQuality(ModelQuality):
     classes: List[str]
     class_metrics: List[ClassMetrics]
-    global_metrics: GlobalMetrics
+    global_metrics: GlobalMulticlassMetrics
+
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+
+
+class CurrentMultiClassificationModelQuality(ModelQuality):
+    classes: List[str]
+    class_metrics: List[AdditionalClassMetrics]
+    global_metrics: GlobalMulticlassMetrics
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)