enh: add 2 new convenience functions to retrieve spike features. fix doc versioning. prepare for 0.0.6 release.

Author: jnsbck

docs/conf.py

@@ -10,11 +10,17 @@
 
 sys.path.insert(0, os.path.abspath("../"))
 
+NAME = "ephyspy"
+about = {}
+here = os.path.abspath(os.path.dirname("../"))
+project_slug = NAME.lower().replace("-", "_").replace(" ", "_")
+with open(os.path.join(here, project_slug, "__version__.py")) as f:
+    exec(f.read(), about)
 
 project = "EphysPy"
 copyright = "2023, Jonas Beck"
 author = "Jonas Beck"
-release = "0.0.05"
+release = about["__version__"]
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

ephyspy/sweeps.py

@@ -22,6 +22,7 @@
 import numpy as np
 from matplotlib.pyplot import Axes
 from numpy import ndarray
+from pandas import DataFrame
 
 import ephyspy.allen_sdk.ephys_extractor as efex
 from ephyspy.allen_sdk.ephys_extractor import (
@@ -151,6 +152,21 @@ def get_features(self, recompute: bool = False) -> Dict[str, float]:
                     for k, ft in self.features.items()
                 }
 
+    def get_spike_features(self, recompute: bool = False) -> DataFrame:
+        """Compute all spike features that have been added to the `EphysSweep` instance.
+
+        Includes all features that can be found in `self.added_spike_features`.
+
+        Args:
+            recompute (bool, optional): Whether to force recomputation of the
+                features. Defaults to False.
+
+        Returns:
+            DataFrame: DataFrame of features and values."""
+        if not hasattr(self, "_spikes_df") or recompute:
+            self.process_spikes()
+        return self._spikes_df
+
     def clear_features(self):
         """Clear all features."""
         self.spikes_df = None
@@ -459,6 +475,25 @@ def get_sweep_features(self, recompute: bool = False) -> Dict[str, List[float]]:
                 LD = [sw.get_features(recompute=recompute) for sw in self.sweeps()]
                 return {k: [dic[k] for dic in LD] for k in LD[0]}
 
+    def get_spike_features(self, recompute: bool = False) -> List[DataFrame]:
+        """Collect spike features on a sweep level.
+
+        This computes / looks up all spike features that have been computed at
+        the sweep level and returns them as a list of dataframes. Each dataframe
+        contains the values for the respective feature for each spike, i.e.
+        `get_spike_features()[sweep_idx][feature_name]` returns the values of
+        `feature_name` for the `sweep_idx`-th sweep.
+
+        Args:
+            recompute (bool, optional): Whether to force recomputation of the
+                features. Defaults to False.
+
+        Returns:
+            Dict[str, List[float]]: Dictionary of features and values.
+        """
+        dfs = [sw.get_spike_features(recompute=recompute) for sw in self.sweeps()]
+        return dfs
+
     def plot(
         self, ax: Optional[Axes] = None, show_stimulus: bool = False, **kwargs
     ) -> Axes: