Develop

brainwidemap/bwm_loading.py

@@ -6,14 +6,18 @@
 
 from brainbox.behavior import training
 from brainbox.io.one import SpikeSortingLoader, SessionLoader
-from ibllib.atlas.regions import BrainRegions
-from iblutil.numerical import ismember
+from iblatlas.atlas import BrainRegions
+from iblutil.numerical import ismember, hash_uuids
 from one.alf import spec
 from one.remote import aws
 
 import brainwidemap
 
 
+MODIFIED_BEFORE = '2024-07-10'
+"""Load data last modified before this date."""
+
+
 def bwm_query(one=None, alignment_resolved=True, return_details=False, freeze='2023_12_bwm_release'):
     """
     Function to query for brainwide map sessions that pass the most important quality controls. Returns a dataframe
@@ -137,7 +141,8 @@ def load_good_units(one, pid, compute_metrics=False, qc=1., **kwargs):
     eid = kwargs.pop('eid', '')
     pname = kwargs.pop('pname', '')
     spike_loader = SpikeSortingLoader(pid=pid, one=one, eid=eid, pname=pname)
-    spikes, clusters, channels = spike_loader.load_spike_sorting()
+    download_good_units_only = qc >= 1.0
+    spikes, clusters, channels = spike_loader.load_spike_sorting(revision="2024-05-06", good_units=download_good_units_only)
     clusters_labeled = SpikeSortingLoader.merge_clusters(
         spikes, clusters, channels, compute_metrics=compute_metrics).to_df()
     iok = clusters_labeled['label'] >= qc
@@ -270,7 +275,7 @@ def load_trials_and_mask(
         ]
 
     if sess_loader is None:
-        sess_loader = SessionLoader(one=one, eid=eid)
+        sess_loader = SessionLoader(one=one, eid=eid, revision=MODIFIED_BEFORE)
 
     if sess_loader.trials.empty:
         sess_loader.load_trials()
@@ -336,7 +341,7 @@ def load_trials_and_mask(
     return sess_loader.trials, mask
 
 
-def download_aggregate_tables(one, target_path=None, type='clusters', tag='2023_Q4_IBL_et_al_BWM_2', overwrite=False):
+def download_aggregate_tables(one, target_path=None, type='clusters', tag='2024_Q2_IBL_et_al_BWM', overwrite=False):
     """
     Function to download the aggregated clusters information associated with the given data release tag from AWS.
 
@@ -525,7 +530,7 @@ def filter_sessions(eids, trials_table, bwm_include=True, min_errors=3, min_tria
 
 
 def bwm_units(one=None, freeze='2023_12_bwm_release', rt_range=(0.08, 0.2), min_errors=3,
-              min_qc=1., min_units_sessions=(10, 2)):
+              min_qc=1., min_units_sessions=(5, 2), enforce_version=True):
     """
     Creates a dataframe with units that pass the current BWM inclusion criteria.
 
@@ -546,6 +551,7 @@ def bwm_units(one=None, freeze='2023_12_bwm_release', rt_range=(0.08, 0.2), min_
         If tuple, the first entry is the minimum of units per session per region for a session to be retained, the
         second entry is the minimum number of those sessions per region for a region to be retained.
         Default is (10, 2). If None, criterion is not applied
+    enforce_version: bool (True)
 
     Returns
     -------
@@ -568,6 +574,16 @@ def bwm_units(one=None, freeze='2023_12_bwm_release', rt_range=(0.08, 0.2), min_
     clusters_table = download_aggregate_tables(one, type='clusters')
     unit_df = filter_units_region(eids, clusters_table=clusters_table, mapping='Beryl', min_qc=min_qc,
                                   min_units_sessions=min_units_sessions)
+    print(hash_uuids(unit_df['uuids']))
+    if freeze == '2023_12_bwm_release' and enforce_version:
+        if 1.0 <= min_qc:
+            assert hash_uuids(unit_df['uuids']) == 'd16d0b38d392b18c0ce8b615ec89d60d7c901df2eeb3432986b62130af28ef01'
+        elif 1 / 3 < min_qc <= 2 / 3:
+            assert hash_uuids(unit_df['uuids']) == '931802298e1a79df49226f4a7ff9d0d865b06102d7d0bedbd76f87f632da8fae'
+        elif 0 < min_qc <= 1 / 3:
+            assert hash_uuids(unit_df['uuids']) == 'aef0abbe1e3cb743f24d40e5d9dd3b739b57adca79af66b2d86dc618fc4b9908'
+        else:
+            assert hash_uuids(unit_df['uuids']) == '82a43bb2344a960b0f39a5c28fa56406dd5788b7946d0d178cb36205b1029b92'
 
     return unit_df
 

brainwidemap/decoding/functions/decoding.py

@@ -9,7 +9,7 @@
 from behavior_models.models.utils import format_data as format_data_mut
 from behavior_models.models.utils import format_input as format_input_mut
 
-from ibllib.atlas import BrainRegions
+from iblatlas.atlas import BrainRegions
 
 from brainwidemap.decoding.functions.balancedweightings import balanced_weighting
 from brainwidemap.decoding.functions.process_inputs import build_predictor_matrix

brainwidemap/encoding/pipelines/03_gather_results.py

@@ -7,7 +7,7 @@
 import pandas as pd
 
 # IBL libraries
-from ibllib.atlas import BrainRegions
+from iblatlas.atlas import BrainRegions
 
 
 if __name__ == "__main__":

brainwidemap/encoding/pipelines/04_plot_figures.py

@@ -9,8 +9,8 @@
 import seaborn as sns
 
 # IBL libraries
-from ibllib.atlas import BrainRegions
-from ibllib.atlas.plots import plot_swanson
+from iblatlas.atlas import BrainRegions
+from iblatlas.plots import plot_swanson
 
 # Brainwidemap repo imports
 from brainwidemap.encoding.params import GLM_FIT_PATH