1212def check_project (plot = False , save_ihc_table = False ):
1313 s3 = create_s3_target ()
1414 cochleae = ['M_LR_000226_L' , 'M_LR_000226_R' , 'M_LR_000227_L' , 'M_LR_000227_R' ]
15+ synapse_table_name = "synapse_v3_ihc_v4"
16+ ihc_table_name = "IHC_v4"
1517
1618 results = {}
1719 for cochlea in cochleae :
@@ -20,14 +22,14 @@ def check_project(plot=False, save_ihc_table=False):
2022 sources = info ["sources" ]
2123
2224 # Load the synapse table.
23- syn = sources ["synapse_v3_ihc_v4" ]["spots" ]
25+ syn = sources [synapse_table_name ]["spots" ]
2426 rel_path = syn ["tableData" ]["tsv" ]["relativePath" ]
2527 table_content = s3 .open (os .path .join (BUCKET_NAME , cochlea , rel_path , "default.tsv" ), mode = "rb" )
2628 syn_table = pd .read_csv (table_content , sep = "\t " )
2729 max_dist = syn_table .distance_to_ihc .max ()
2830
2931 # Load the corresponding ihc table.
30- ihc = sources ["IHC_v4" ]["segmentation" ]
32+ ihc = sources [ihc_table_name ]["segmentation" ]
3133 rel_path = ihc ["tableData" ]["tsv" ]["relativePath" ]
3234 table_content = s3 .open (os .path .join (BUCKET_NAME , cochlea , rel_path , "default.tsv" ), mode = "rb" )
3335 ihc_table = pd .read_csv (table_content , sep = "\t " )
@@ -57,6 +59,8 @@ def check_project(plot=False, save_ihc_table=False):
5759 ihc_count_table = pd .DataFrame ({
5860 "label_id" : list (ihc_to_count .keys ()),
5961 "synapse_count" : list (ihc_to_count .values ()),
62+ "snyapse_table" : [synapse_table_name for _ in list (ihc_to_count .values ())],
63+ "ihc_table" : [ihc_table_name for _ in list (ihc_to_count .values ())],
6064 })
6165 os .makedirs (OUTPUT_FOLDER , exist_ok = True )
6266 output_path = os .path .join (OUTPUT_FOLDER , f"ihc_count_{ cochlea } .tsv" )
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