Merge pull request #27 from CESNET/feat-summary-improvement

Changed how much summary displays; Merged display_config and summary; Can save summary diagram to file

Author: milankures

cesnet_tszoo/configs/base_config.py

@@ -19,6 +19,7 @@
 import cesnet_tszoo.utils.anomaly_handler.factory as anomaly_handler_factories
 import cesnet_tszoo.utils.custom_handler.factory as custom_handler_factories
 from cesnet_tszoo.utils.custom_handler.factory import PerSeriesCustomHandlerFactory, AllSeriesCustomHandlerFactory, NoFitCustomHandlerFactory
+import cesnet_tszoo.utils.css_styles.utils as css_utils
 from cesnet_tszoo.data_models.holders import FillingHolder, AnomalyHandlerHolder, TransformerHolder, PerSeriesCustomHandlerHolder, NoFitCustomHandlerHolder, AllSeriesCustomHandlerHolder
 
 
@@ -535,6 +536,104 @@ def __set_all_series_custom_handler(self, factory: AllSeriesCustomHandlerFactory
         self.test_preprocess_order.append(PreprocessNote(factory.preprocess_enum_type, True, False, factory.can_apply_to_test and self.has_test(), False, AllSeriesCustomHandlerHolder(handler)))
         self.all_preprocess_order.append(PreprocessNote(factory.preprocess_enum_type, True, False, factory.can_apply_to_all and self.has_all(), False, AllSeriesCustomHandlerHolder(handler)))
 
+    def _get_summary_steps(self) -> list[css_utils.SummaryDiagramStep]:
+        steps = []
+
+        steps.append(self._get_summary_dataset())
+        steps.append(self._get_summary_filter_time_series())
+        steps.append(self._get_summary_filter_features())
+        steps += self._get_summary_preprocessing()
+        steps += self._get_summary_loader()
+
+        return steps
+
+    def _get_summary_dataset(self) -> css_utils.SummaryDiagramStep:
+        attributes = [css_utils.StepAttribute("Database", self.database_name),
+                      css_utils.StepAttribute("Aggregation", self.aggregation),
+                      css_utils.StepAttribute("Source", self.source_type)]
+
+        return css_utils.SummaryDiagramStep("Load from dataset", attributes)
+
+    @abstractmethod
+    def _get_summary_filter_time_series(self) -> css_utils.SummaryDiagramStep:
+        ...
+
+    def _get_summary_filter_features(self) -> css_utils.SummaryDiagramStep:
+        attributes = [css_utils.StepAttribute("Taken features", self.features_to_take_without_ids),
+                      css_utils.StepAttribute("Time series ID included", self.include_ts_id),
+                      css_utils.StepAttribute("Time included", self.include_time),
+                      css_utils.StepAttribute("Time format", self.time_format)]
+
+        return css_utils.SummaryDiagramStep("Filter features", attributes)
+
+    def _get_summary_preprocessing(self) -> list[css_utils.SummaryDiagramStep]:
+        steps = []
+
+        for preprocess_type, train_pr, val_pr, test_pr, all_pr in list(zip(self.preprocess_order, self.train_preprocess_order, self.val_preprocess_order, self.test_preprocess_order, self.all_preprocess_order)):
+            preprocess_title = None
+            preprocess_type_name = None
+            is_per_time_series = train_pr.is_inner_preprocess
+            target_sets = []
+            requires_fitting = False
+            if train_pr.can_be_applied:
+                target_sets.append("train")
+                requires_fitting = train_pr.should_be_fitted
+            if val_pr.can_be_applied:
+                target_sets.append("val")
+            if test_pr.can_be_applied:
+                target_sets.append("test")
+            if all_pr.can_be_applied:
+                target_sets.append("all")
+
+            if len(target_sets) == 0:
+                continue
+
+            if train_pr.preprocess_type == PreprocessType.HANDLING_ANOMALIES:
+                preprocess_title = "Handle anomalies"
+                preprocess_type_name = self.anomaly_handler_factory.anomaly_handler_type.__name__
+
+                if self.anomaly_handler_factory.is_empty_factory:
+                    continue
+
+            elif train_pr.preprocess_type == PreprocessType.FILLING_GAPS:
+                preprocess_title = "Handle missing values"
+                preprocess_type_name = f"{self.filler_factory.filler_type.__name__}"
+
+                steps.append(css_utils.SummaryDiagramStep("Pre-fill with default values", [css_utils.StepAttribute("Default values", self.default_values)]))
+
+                if self.filler_factory.is_empty_factory:
+                    continue
+
+            elif train_pr.preprocess_type == PreprocessType.TRANSFORMING:
+                preprocess_title = "Apply transformer"
+                preprocess_type_name = self.transformer_factory.transformer_type.__name__
+
+                if self.transformer_factory.is_empty_factory:
+                    continue
+
+                is_per_time_series = self.create_transformer_per_time_series
+            elif train_pr.preprocess_type == PreprocessType.PER_SERIES_CUSTOM:
+                preprocess_title = f"Apply {preprocess_type.__name__}"
+                preprocess_type_name = preprocess_type.__name__
+            elif train_pr.preprocess_type == PreprocessType.ALL_SERIES_CUSTOM:
+                preprocess_title = f"Apply {preprocess_type.__name__}"
+                preprocess_type_name = preprocess_type.__name__
+            elif train_pr.preprocess_type == PreprocessType.NO_FIT_CUSTOM:
+                preprocess_title = f"Apply {preprocess_type.__name__}"
+                preprocess_type_name = preprocess_type.__name__
+
+            step = css_utils.SummaryDiagramStep(preprocess_title, [css_utils.StepAttribute("Type", preprocess_type_name),
+                                                                   css_utils.StepAttribute("Requires fitting", requires_fitting),
+                                                                   css_utils.StepAttribute("Is per time series", is_per_time_series),
+                                                                   css_utils.StepAttribute("Target sets", target_sets)])
+            steps.append(step)
+
+        return steps
+
+    @abstractmethod
+    def _get_summary_loader(self) -> list[css_utils.SummaryDiagramStep]:
+        ...
+
     @abstractmethod
     def _set_no_fit_custom_handler(self, factory: NoFitCustomHandlerFactory):
         ...

cesnet_tszoo/configs/disjoint_time_based_config.py

@@ -14,6 +14,7 @@
 from cesnet_tszoo.configs.base_config import DatasetConfig
 from cesnet_tszoo.configs.handlers.series_based_handler import SeriesBasedHandler
 from cesnet_tszoo.configs.handlers.time_based_handler import TimeBasedHandler
+import cesnet_tszoo.utils.css_styles.utils as css_utils
 from cesnet_tszoo.utils.custom_handler.factory import PerSeriesCustomHandlerFactory, NoFitCustomHandlerFactory
 from cesnet_tszoo.data_models.holders import PerSeriesCustomHandlerHolder, NoFitCustomHandlerHolder
 from cesnet_tszoo.data_models.preprocess_note import PreprocessNote
@@ -356,6 +357,38 @@ def _validate_finalization(self) -> None:
         self._validate_time_periods_overlap()
         self._validate_ts_overlap()
 
+    def _get_summary_filter_time_series(self) -> css_utils.SummaryDiagramStep:
+        attributes = [css_utils.StepAttribute("Train time series IDs", get_abbreviated_list_string(self.train_ts)),
+                      css_utils.StepAttribute("Val time series IDs", get_abbreviated_list_string(self.val_ts)),
+                      css_utils.StepAttribute("Test time series IDs", get_abbreviated_list_string(self.test_ts)),
+                      css_utils.StepAttribute("Train time periods", self.display_train_time_period),
+                      css_utils.StepAttribute("Val time periods", self.display_val_time_period),
+                      css_utils.StepAttribute("Test time periods", self.display_test_time_period),
+                      css_utils.StepAttribute("Nan threshold", self.nan_threshold)]
+
+        return css_utils.SummaryDiagramStep("Filter time series", attributes)
+
+    def _get_summary_loader(self) -> list[css_utils.SummaryDiagramStep]:
+
+        steps = []
+
+        if self.sliding_window_size is not None:
+            attributes = [
+                css_utils.StepAttribute("Window size", self.sliding_window_size),
+                css_utils.StepAttribute("Prediction size", self.sliding_window_prediction_size),
+                css_utils.StepAttribute("Step", self.sliding_window_step)
+            ]
+
+            steps.append(css_utils.SummaryDiagramStep("Apply sliding window", attributes))
+
+        attributes = [css_utils.StepAttribute("Train batch size", self.train_batch_size),
+                      css_utils.StepAttribute("Val batch size", self.val_batch_size),
+                      css_utils.StepAttribute("Test batch size", self.test_batch_size)]
+
+        steps.append(css_utils.SummaryDiagramStep("Transform into specific format", attributes))
+
+        return steps
+
     def __str__(self) -> str:
 
         if self.transformer_factory.is_empty_factory:

cesnet_tszoo/configs/series_based_config.py

@@ -14,6 +14,7 @@
 from cesnet_tszoo.configs.base_config import DatasetConfig
 from cesnet_tszoo.configs.handlers.series_based_handler import SeriesBasedHandler
 from cesnet_tszoo.configs.handlers.time_based_handler import TimeBasedHandler
+import cesnet_tszoo.utils.css_styles.utils as css_utils
 from cesnet_tszoo.utils.custom_handler.factory import PerSeriesCustomHandlerFactory, NoFitCustomHandlerFactory
 from cesnet_tszoo.data_models.holders import PerSeriesCustomHandlerHolder, NoFitCustomHandlerHolder
 from cesnet_tszoo.data_models.preprocess_note import PreprocessNote
@@ -301,6 +302,30 @@ def _get_anomaly_handlers(self) -> np.ndarray:
     def _set_per_series_custom_handler(self, factory: PerSeriesCustomHandlerFactory):
         raise ValueError(f"Cannot use {factory.name} CustomHandler, because PerSeriesCustomHandler is not supported for {self.dataset_type}. Use AllSeriesCustomHandler or NoFitCustomHandler instead. ")
 
+    def _get_summary_filter_time_series(self) -> css_utils.SummaryDiagramStep:
+        attributes = [css_utils.StepAttribute("Train time series IDs", get_abbreviated_list_string(self.train_ts)),
+                      css_utils.StepAttribute("Val time series IDs", get_abbreviated_list_string(self.val_ts)),
+                      css_utils.StepAttribute("Test time series IDs", get_abbreviated_list_string(self.test_ts)),
+                      css_utils.StepAttribute("All time series IDs", get_abbreviated_list_string(self.all_ts)),
+                      css_utils.StepAttribute("Time periods", self.display_time_period),
+                      css_utils.StepAttribute("Nan threshold", self.nan_threshold)]
+
+        return css_utils.SummaryDiagramStep("Filter time series", attributes)
+
+    def _get_summary_loader(self) -> list[css_utils.SummaryDiagramStep]:
+
+        steps = []
+
+        attributes = [css_utils.StepAttribute("Train batch size", self.train_batch_size),
+                      css_utils.StepAttribute("Val batch size", self.val_batch_size),
+                      css_utils.StepAttribute("Test batch size", self.test_batch_size),
+                      css_utils.StepAttribute("All batch size", self.all_batch_size),
+                      css_utils.StepAttribute("Train dataloader order", self.train_dataloader_order),]
+
+        steps.append(css_utils.SummaryDiagramStep("Transform into specific format", attributes))
+
+        return steps
+
     def _validate_finalization(self) -> None:
         """Performs final validation of the configuration. """
 

cesnet_tszoo/configs/time_based_config.py

@@ -14,6 +14,7 @@
 from cesnet_tszoo.configs.base_config import DatasetConfig
 from cesnet_tszoo.configs.handlers.series_based_handler import SeriesBasedHandler
 from cesnet_tszoo.configs.handlers.time_based_handler import TimeBasedHandler
+import cesnet_tszoo.utils.css_styles.utils as css_utils
 from cesnet_tszoo.utils.custom_handler.factory import PerSeriesCustomHandlerFactory, NoFitCustomHandlerFactory
 from cesnet_tszoo.data_models.holders import PerSeriesCustomHandlerHolder, NoFitCustomHandlerHolder
 from cesnet_tszoo.data_models.preprocess_note import PreprocessNote
@@ -389,6 +390,38 @@ def _validate_finalization(self) -> None:
 
         self._validate_time_periods_overlap()
 
+    def _get_summary_filter_time_series(self) -> css_utils.SummaryDiagramStep:
+        attributes = [css_utils.StepAttribute("Time series IDs", get_abbreviated_list_string(self.ts_ids)),
+                      css_utils.StepAttribute("Train time periods", self.display_train_time_period),
+                      css_utils.StepAttribute("Val time periods", self.display_val_time_period),
+                      css_utils.StepAttribute("Test time periods", self.display_test_time_period),
+                      css_utils.StepAttribute("All time periods", self.display_all_time_period),
+                      css_utils.StepAttribute("Nan threshold", self.nan_threshold)]
+
+        return css_utils.SummaryDiagramStep("Filter time series", attributes)
+
+    def _get_summary_loader(self) -> list[css_utils.SummaryDiagramStep]:
+
+        steps = []
+
+        if self.sliding_window_size is not None:
+            attributes = [
+                css_utils.StepAttribute("Window size", self.sliding_window_size),
+                css_utils.StepAttribute("Prediction size", self.sliding_window_prediction_size),
+                css_utils.StepAttribute("Step", self.sliding_window_step)
+            ]
+
+            steps.append(css_utils.SummaryDiagramStep("Apply sliding window", attributes))
+
+        attributes = [css_utils.StepAttribute("Train batch size", self.train_batch_size),
+                      css_utils.StepAttribute("Val batch size", self.val_batch_size),
+                      css_utils.StepAttribute("Test batch size", self.test_batch_size),
+                      css_utils.StepAttribute("All batch size", self.all_batch_size)]
+
+        steps.append(css_utils.SummaryDiagramStep("Transform into specific format", attributes))
+
+        return steps
+
     def __str__(self) -> str:
 
         if self.transformer_factory.is_empty_factory: