Merge pull request #21 from pauladkisson/remove_optional_notes

Remove optional notes

src/datta_lab_to_nwb/markowitz_gillis_nature_2023/fiberphotometryinterface.py

@@ -158,30 +158,28 @@ def run_conversion(self, nwbfile: NWBFile, metadata: dict):
             photodetector=0,
             fluorophores=[0],  # potentially multiple fluorophores, so list of indices
             location=metadata["FiberPhotometry"]["area"],
-            notes="None",
         )
         fibers_table.add_fiber(
             excitation_source=1,  # integers indicated rows of excitation sources table
             photodetector=0,
             fluorophores=[0],  # potentially multiple fluorophores, so list of indices
             location=metadata["FiberPhotometry"]["area"],
-            notes="None",
         )
 
         # ROI Response Series
         # Here we set up a list of fibers that our recording came from
         fibers_ref = DynamicTableRegion(name="rois", data=[0, 1], description="source fibers", table=fibers_table)
         signal_series = RoiResponseSeries(
             name="SignalDfOverF",
-            description="The ΔF/F from the blue light excitation (480nm) corresponding to the dopamine signal.",
+            description="The ΔF/F from the blue light excitation (470nm) corresponding to the dopamine signal.",
             data=H5DataIO(session_df.signal_dff.to_numpy(), compression=True),
             unit="a.u.",
             timestamps=H5DataIO(session_df.timestamp.to_numpy(), compression=True),
             rois=fibers_ref,
         )
         reference_series = RoiResponseSeries(
             name="ReferenceDfOverF",
-            description="The ∆F/F from the isosbestic UV excitation (400nm) corresponding to the reference signal.",
+            description="The ∆F/F from the isosbestic UV excitation (405nm) corresponding to the reference signal.",
             data=H5DataIO(session_df.reference_dff.to_numpy(), compression=True),
             unit="a.u.",
             timestamps=signal_series.timestamps,
@@ -190,7 +188,7 @@ def run_conversion(self, nwbfile: NWBFile, metadata: dict):
         reference_fit_series = RoiResponseSeries(
             name="ReferenceDfOverFSmoothed",
             description=(
-                "The ∆F/F from the isosbestic UV excitation (400nm) that has been smoothed "
+                "The ∆F/F from the isosbestic UV excitation (405nm) that has been smoothed "
                 "(See Methods: Photometry Active Referencing)."
             ),
             data=H5DataIO(session_df.reference_dff_fit.to_numpy(), compression=True),
@@ -201,7 +199,7 @@ def run_conversion(self, nwbfile: NWBFile, metadata: dict):
         uv_reference_fit_series = RoiResponseSeries(
             name="UVReferenceFSmoothed",
             description=(
-                "Raw fluorescence (F) from the isosbestic UV excitation (400nm) that has been smoothed "
+                "Raw fluorescence (F) from the isosbestic UV excitation (405nm) that has been smoothed "
                 "(See Methods: Photometry Active Referencing)."
             ),
             data=H5DataIO(session_df.uv_reference_fit.to_numpy(), compression=True),