Improve spike sorting docs (#11)

Author: C-Achard

neuroplatform-docs/np_utils/spikesorting.ipynb

@@ -126,7 +126,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "events_df = sorter.run_spike_sorting(\n",
+    "processed_spike_events_df = sorter.run_spike_sorting(\n",
     "    start, start + timedelta(minutes=20), fs_id=EXP_NAME, electrode_nb=ELECTRODE\n",
     ")"
    ]
@@ -234,9 +234,9 @@
     "\n",
     "You may also use some of the attributes of the SpikeSorting object to make your own plots :\n",
     "\n",
-    "- `raw_spikes_df` : DataFrame containing the raw spikes, with clustering results.\n",
-    "- `processed_spike_events_df` : DataFrame containing the spike events with clustering results.\n",
-    "- `dimred_method_spikes.fit_data_df` : DataFrame containing the dimensionality reduction, with clustering results.\n",
+    "- `sorter.raw_spikes_df` : DataFrame containing the raw spikes, with clustering results. Each time point is a row, as such the number of points per event will vary depending on the specified time window.\n",
+    "- `sorter.processed_spike_events_df` : DataFrame containing the spike events with clustering results (also returned by `sorter.run_spike_sorting()`). Each row corresponds to a spike event.\n",
+    "- `sorter.dimred_method_spikes.fit_data_df` : DataFrame containing the dimensionality reduction, with clustering results. Each column corresponds to a component, along with the cluster assignment. Each row corresponds to a (processed) spike.\n",
     "\n",
     "```{hint}\n",
     "Make sure to copy those DataFrames before modifying them, as they are directly linked to the SpikeSorting object.\n",