Converter extractor changes

src/graphnet/data/dataconverter.py

@@ -215,16 +215,17 @@ def _assign_event_no(
                         data[k][extractor_name],
                         index=[0] if n_rows == 1 else None,
                     )
-                    if extractor_name in dataframe_dict.keys():
-                        dataframe_dict[extractor_name].append(df)
-                    else:
-                        dataframe_dict[extractor_name] = [df]
+                    if not df.empty:
+                        if extractor_name in dataframe_dict.keys():
+                            dataframe_dict[extractor_name].append(df)
+                        else:
+                            dataframe_dict[extractor_name] = [df]
 
         # Merge each list of dataframes if wanted by writer
         if self._save_method.expects_merged_dataframes:
             for key in dataframe_dict.keys():
                 dataframe_dict[key] = pd.concat(
-                    dataframe_dict[key], axis=0
+                    [df for df in dataframe_dict[key] if not df.empty], axis=0
                 ).reset_index(drop=True)
         return dataframe_dict
 
@@ -275,10 +276,11 @@ def get_map_function(
         """Identify map function to use (pure python or multiprocess)."""
         # Choose relevant map-function given the requested number of workers.
         n_workers = min(self._num_workers, nb_files)
+        self._num_workers = n_workers
         if n_workers > 1:
             self.info(
                 f"Starting pool of {n_workers} workers to process"
-                " {nb_files} {unit}"
+                f"{nb_files} {unit}"
             )
 
             manager = Manager()
@@ -321,7 +323,10 @@ def _update_shared_variables(
 
     @final
     def merge_files(
-        self, files: Optional[Union[List[str], str]] = None, **kwargs: Any
+        self,
+        files: Optional[Union[List[str], str]] = None,
+        output_dir: Optional[str] = None,
+        **kwargs: Any,
     ) -> None:
         """Merge converted files.
 
@@ -330,6 +335,9 @@ def merge_files(
 
         Args:
             files: Intermediate files to be merged.
+            output_dir: Directory to save the merged files in.
+            **kwargs: Additional keyword arguments to be passed to the
+                      `GraphNeTWriter.merge_files` method.
         """
         if (files is None) & (len(self._output_files) > 0):
             # If no input files are given, but output files from conversion
@@ -349,9 +357,10 @@ def merge_files(
                 "and you must therefore specify argument `files`."
             )
             assert files is not None
-
+        if output_dir is None:
+            output_dir = self._output_dir
         # Merge files
-        merge_path = os.path.join(self._output_dir, "merged")
+        merge_path = os.path.join(output_dir, "merged")
         self.info(f"Merging files to {merge_path}")
         self._save_method.merge_files(
             files=files_to_merge, output_dir=merge_path, **kwargs

src/graphnet/data/extractors/combine_extractors.py

@@ -1,6 +1,6 @@
 """Module for combining multiple extractors into a single extractor."""
 
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Optional
 
 from graphnet.utilities.imports import has_icecube_package
 from graphnet.data.extractors.icecube.i3extractor import I3Extractor
@@ -31,6 +31,11 @@ def __init__(self, extractors: List[I3Extractor], extractor_name: str):
         super().__init__(extractor_name=extractor_name)
         self._extractors = extractors
 
+    def set_gcd(self, i3_file: str, gcd_file: Optional[str] = None) -> None:
+        """Set the GCD file for all extractors."""
+        for extractor in self._extractors:
+            extractor.set_gcd(i3_file, gcd_file)
+
     def __call__(self, frame: "icetray.I3Frame") -> Dict[str, float]:
         """Extract data from frame using all extractors.
 

src/graphnet/data/extractors/extractor.py

@@ -1,6 +1,6 @@
 """Base I3Extractor class(es)."""
 
-from typing import Any, Union
+from typing import Any, Union, Callable
 from abc import ABC, abstractmethod
 import pandas as pd
 
@@ -23,21 +23,42 @@ class Extractor(ABC, Logger):
     An extractor is used in conjunction with a specific `FileReader`.
     """
 
-    def __init__(self, extractor_name: str):
+    def __init__(self, extractor_name: str, exclude: list = [None]):
         """Construct Extractor.
 
         Args:
             extractor_name: Name of the `Extractor` instance.
                             Used to keep track of the provenance of different
                             data, and to name tables to which this data is
                             saved. E.g. "mc_truth".
+            exclude: List of keys to exclude from the extracted data.
         """
         # Member variable(s)
         self._extractor_name: str = extractor_name
+        self._exclude = exclude
 
         # Base class constructor
         super().__init__(name=__name__, class_name=self.__class__.__name__)
 
+    def exclude(func: Callable) -> Callable:
+        """Exclude specified keys from the extracted data."""
+
+        def wrapper(
+            self: "Extractor", *args: Any
+        ) -> Union[dict, pd.DataFrame]:
+            result = func(self, *args)
+            if isinstance(result, dict):
+                for key in self._exclude:
+                    if key in result:
+                        del result[key]
+            elif isinstance(result, pd.DataFrame):
+                for key in self._exclude:
+                    if key in result.columns:
+                        result = result.drop(columns=[key])
+            return result
+
+        return wrapper
+
     @abstractmethod
     def __call__(self, data: Any) -> Union[dict, pd.DataFrame]:
         """Extract information from data."""
@@ -47,3 +68,8 @@ def __call__(self, data: Any) -> Union[dict, pd.DataFrame]:
     def name(self) -> str:
         """Get the name of the `Extractor` instance."""
         return self._extractor_name
+
+    def __init_subclass__(cls) -> None:
+        """Initialize subclass and apply the exclude decorator to __call__."""
+        super().__init_subclass__()
+        cls.__call__ = cls.exclude(cls.__call__)  # type: ignore

src/graphnet/data/extractors/icecube/i3extractor.py

@@ -20,13 +20,14 @@ class I3Extractor(Extractor):
     method.
     """
 
-    def __init__(self, extractor_name: str):
+    def __init__(self, extractor_name: str, exclude: list = [None]):
         """Construct I3Extractor.
 
         Args:
             extractor_name: Name of the `I3Extractor` instance. Used to keep
                 track of the provenance of different data, and to name tables
                 to which this data is saved.
+            exclude: List of features to exclude from the extractor.
         """
         # Member variable(s)
         self._i3_file: str = ""
@@ -35,7 +36,7 @@ def __init__(self, extractor_name: str):
         self._calibration: Optional["icetray.I3Frame.Calibration"] = None
 
         # Base class constructor
-        super().__init__(extractor_name=extractor_name)
+        super().__init__(extractor_name=extractor_name, exclude=exclude)
 
     def set_gcd(self, i3_file: str, gcd_file: Optional[str] = None) -> None:
         """Extract GFrame and CFrame from i3/gcd-file pair.

src/graphnet/data/extractors/icecube/i3featureextractor.py

@@ -14,18 +14,19 @@
 class I3FeatureExtractor(I3Extractor):
     """Base class for extracting specific, reconstructed features."""
 
-    def __init__(self, pulsemap: str):
+    def __init__(self, pulsemap: str, exclude: list = [None]):
         """Construct I3FeatureExtractor.
 
         Args:
             pulsemap: Name of the pulse (series) map for which to extract
                 reconstructed features.
+            exclude: List of keys to exclude from the extracted data.
         """
         # Member variable(s)
         self._pulsemap = pulsemap
 
         # Base class constructor
-        super().__init__(pulsemap)
+        super().__init__(pulsemap, exclude=exclude)
 
 
 class I3FeatureExtractorIceCube86(I3FeatureExtractor):

src/graphnet/data/extractors/icecube/i3genericextractor.py

@@ -46,6 +46,7 @@ def __init__(
         keys: Optional[Union[str, List[str]]] = None,
         exclude_keys: Optional[Union[str, List[str]]] = None,
         extractor_name: str = GENERIC_EXTRACTOR_NAME,
+        exclude: list = [None],
     ):
         """Construct I3GenericExtractor.
 
@@ -73,7 +74,7 @@ def __init__(
         self._exclude_keys: Optional[List[str]] = exclude_keys
 
         # Base class constructor
-        super().__init__(extractor_name)
+        super().__init__(extractor_name, exclude=exclude)
 
     def _get_keys(self, frame: "icetray.I3Frame") -> List[str]:
         """Get the list of keys to be queried from `frame`.

src/graphnet/data/extractors/icecube/i3hybridrecoextractor.py

@@ -11,10 +11,10 @@
 class I3GalacticPlaneHybridRecoExtractor(I3Extractor):
     """Class for extracting galatictic plane hybrid reconstruction."""
 
-    def __init__(self, name: str = "dnn_hybrid"):
+    def __init__(self, name: str = "dnn_hybrid", exclude: list = [None]):
         """Construct I3GalacticPlaneHybridRecoExtractor."""
         # Base class constructor
-        super().__init__(name)
+        super().__init__(name, exclude=exclude)
 
     def __call__(self, frame: "icetray.I3Frame") -> Dict[str, Any]:
         """Extract TUMs DNN reconcstructions and associated variables."""

src/graphnet/data/extractors/icecube/i3ntmuonlabelsextractor.py

@@ -15,10 +15,11 @@ def __init__(
         self,
         name: str = "northeren_tracks_muon_labels",
         padding_value: int = -1,
+        exclude: list = [None],
     ):
         """Construct I3NTMuonLabelExtractor."""
         # Base class constructor
-        super().__init__(name)
+        super().__init__(name, exclude=exclude)
         self._padding_value = padding_value
 
     def __call__(self, frame: "icetray.I3Frame") -> Dict[str, float]:

src/graphnet/data/extractors/icecube/i3particleextractor.py

@@ -15,10 +15,10 @@ class I3ParticleExtractor(I3Extractor):
     with GraphNeT.
     """
 
-    def __init__(self, extractor_name: str):
+    def __init__(self, extractor_name: str, exclude: list = [None]):
         """Construct I3ParticleExtractor."""
         # Base class constructor
-        super().__init__(extractor_name=extractor_name)
+        super().__init__(extractor_name=extractor_name, exclude=exclude)
 
     def __call__(self, frame: "icetray.I3Frame") -> Dict[str, float]:
         """Extract I3Particle properties from I3Particle in frame."""

src/graphnet/data/extractors/icecube/i3pisaextractor.py

@@ -11,10 +11,12 @@
 class I3PISAExtractor(I3Extractor):
     """Class for extracting quantities required by PISA."""
 
-    def __init__(self, name: str = "pisa_dependencies"):
+    def __init__(
+        self, name: str = "pisa_dependencies", exclude: list = [None]
+    ):
         """Construct `I3PISAExtractor`."""
         # Base class constructor
-        super().__init__(name)
+        super().__init__(name, exclude=exclude)
 
     def __call__(
         self, frame: "icetray.I3Frame", padding_value: float = -1.0

src/graphnet/data/extractors/icecube/i3quesoextractor.py

@@ -15,10 +15,11 @@ def __init__(
         self,
         name: str = "queso",
         padding_value: int = -1,
+        exclude: list = [None],
     ):
         """Construct I3QUESOExtractor."""
         # Base class constructor
-        super().__init__(name)
+        super().__init__(name, exclude=exclude)
         self._padding_value = padding_value
 
     def __call__(self, frame: "icetray.I3Frame") -> Dict[str, float]:
@@ -42,5 +43,4 @@ def __call__(self, frame: "icetray.I3Frame") -> Dict[str, float]:
                     key: value,
                 }
             )
-
         return output

src/graphnet/data/extractors/icecube/i3retroextractor.py

@@ -15,10 +15,10 @@
 class I3RetroExtractor(I3Extractor):
     """Class for extracting RETRO reconstruction."""
 
-    def __init__(self, name: str = "retro"):
+    def __init__(self, name: str = "retro", exclude: list = [None]):
         """Construct `I3RetroExtractor`."""
         # Base class constructor
-        super().__init__(name)
+        super().__init__(name, exclude=exclude)
 
     def __call__(self, frame: "icetray.I3Frame") -> Dict[str, Any]:
         """Extract RETRO reconstruction and associated quantities."""
@@ -100,6 +100,7 @@ def __call__(self, frame: "icetray.I3Frame") -> Dict[str, Any]:
                     frame["I3MCWeightDict"], "weight", default_value=-1
                 )
 
+        output = {k: v for k, v in output.items() if k not in self._exclude}
         return output
 
     def _frame_contains_retro(self, frame: "icetray.I3Frame") -> bool:

src/graphnet/data/extractors/icecube/i3splinempeextractor.py

@@ -11,10 +11,10 @@
 class I3SplineMPEICExtractor(I3Extractor):
     """Class for extracting SplineMPE pointing predictions."""
 
-    def __init__(self, name: str = "spline_mpe_ic"):
+    def __init__(self, name: str = "spline_mpe_ic", exclude: list = [None]):
         """Construct I3SplineMPEICExtractor."""
         # Base class constructor
-        super().__init__(name)
+        super().__init__(name, exclude=exclude)
 
     def __call__(self, frame: "icetray.I3Frame") -> Dict[str, float]:
         """Extract SplineMPE pointing predictions."""
@@ -26,5 +26,4 @@ def __call__(self, frame: "icetray.I3Frame") -> Dict[str, float]:
                     "azimuth_spline_mpe_ic": frame["SplineMPEIC"].dir.azimuth,
                 }
             )
-
         return output

src/graphnet/data/extractors/icecube/i3truthextractor.py

@@ -31,6 +31,7 @@ def __init__(
         borders: Optional[List[np.ndarray]] = None,
         mctree: Optional[str] = "I3MCTree",
         extend_boundary: Optional[float] = 0.0,
+        exclude: list = [None],
     ):
         """Construct I3TruthExtractor.
 
@@ -43,9 +44,10 @@ def __init__(
             mctree: Str of which MCTree to use for truth values.
             extend_boundary: Distance to extend the convex hull of the detector
                 for defining starting events.
+            exclude: List of keys to exclude from the extracted data.
         """
         # Base class constructor
-        super().__init__(name)
+        super().__init__(name, exclude=exclude)
 
         if borders is None:
             border_xy = np.array(

src/graphnet/data/extractors/icecube/i3tumextractor.py

@@ -11,10 +11,10 @@
 class I3TUMExtractor(I3Extractor):
     """Class for extracting TUM DNN predictions."""
 
-    def __init__(self, name: str = "tum_dnn"):
+    def __init__(self, name: str = "tum_dnn", exclude: list = [None]):
         """Construct I3TUMExtractor."""
         # Base class constructor
-        super().__init__(name)
+        super().__init__(name, exclude=exclude)
 
     def __call__(self, frame: "icetray.I3Frame") -> Dict[str, float]:
         """Extract TUM DNN recoconstruction and associated variables."""
@@ -29,5 +29,4 @@ def __call__(self, frame: "icetray.I3Frame") -> Dict[str, float]:
                     "tum_bdt_sigma": frame["TUM_bdt_sigma"].value,
                 }
             )
-
         return output