Closed thenineteen closed 4 years ago
What's left to do before merging:
need unit test for dummy data to ensure capturing lateralising but no localising datapoints lat_not_loc
(dummy_data) ...
...and correctly combining with other lateralising+localising datapoints (lat_not_loc
and lat_and_loc
using regex _loc
)
need to double check concat vs append methods at end of Q_L and whether ignore_index=True is required (or reindex('Gif Parcellations').
enhancement: only concat join=inner (if reindexed) or Gif Parcellations that already exist in all_combined_gifs
lat_not_loc
(dummy_data) ...lat_not_loc
and lat_and_loc
using regex lat_
)all_combined_gifs = pd.concat([all_combined_gifs, lat_only_df],
join='outer', sort=False)
and
all_combined_gifs.append(lat_only_df)
are equivalent in this part of Q_L:
if (lat_only_Right != 0) | (lat_only_Left != 0):
# means both lateralising+loc and gifs_not_lat were none. occurs usually in dummy_data only.
if all_combined_gifs is None:
lat_only_df = lateralising_but_not_localising_GIF(all_combined_gifs,
lat_only_Right, lat_only_Left,
gifs_right, gifs_left,
exclusively_lateralising=True)
all_combined_gifs = lat_only_df
else:
lat_only_df = lateralising_but_not_localising_GIF(all_combined_gifs,
lat_only_Right, lat_only_Left,
gifs_right, gifs_left,
exclusively_lateralising=False)
all_combined_gifs = pd.concat([all_combined_gifs, lat_only_df],
join='outer', sort=False)
if a semiology returns a row of data from a paper that has lateralising value (CL, IL, DomH or NonDomH) but no localising value, the current SVT v 1.0.0 ignores this data which is not useful.
This branch intends to fix this by projecting all the right and/or left hemisphere GIF parcellations so that this can be used and integrated with all_combine_gifs from QUERY_LATERALISATION