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[CI]: Fix examples #352

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Jul 19, 2024
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4 changes: 2 additions & 2 deletions examples/run_compute_parcel_mean.py
Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,7 @@
feature = marker.fit_transform(element_data)
# Print the output
print(feature.keys())
print(feature["VBM_GM"]["data"].shape) # Shape is (1 x parcels)
print(feature["VBM_GM"]["aggregation"]["data"].shape) # Shape is (1 x parcels)

###############################################################################
# Perform parcel aggregation on BOLD data (4D) from SPM Auditory dataset
Expand All @@ -54,4 +54,4 @@
feature = marker.fit_transform(element_data)
# Print the output
print(feature.keys())
print(feature["BOLD"]["data"].shape) # Shape is (timepoints x parcels)
print(feature["BOLD"]["aggregation"]["data"].shape) # Shape is (timepoints x parcels)
4 changes: 2 additions & 2 deletions examples/run_ets_rss_marker.py
Original file line number Diff line number Diff line change
Expand Up @@ -70,8 +70,8 @@
# List all the features
print(db.list_features())
# Read extracted features
df_vbm = db.read_df(feature_name="BOLD_Schaefer100x17_RSSETS")
df_rssets = db.read_df(feature_name="BOLD_Schaefer200x17_RSSETS_rss_ets")

###############################################################################
# Now we take a look at the dataframe
df_vbm.head()
df_rssets.head()
2 changes: 1 addition & 1 deletion examples/run_junifer_julearn.py
Original file line number Diff line number Diff line change
Expand Up @@ -84,7 +84,7 @@
collect(storage)
db = SQLiteFeatureStorage(uri=storage["uri"])

df_vbm = db.read_df(feature_name="VBM_GM_Schaefer200x17_Mean")
df_vbm = db.read_df(feature_name="VBM_GM_Schaefer200x17_Mean_aggregation")
oasis_subjects = [x[0] for x in df_vbm.index]
df_vbm.index = oasis_subjects

Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -136,8 +136,12 @@ def compute(
method=self.correlation_method,
).values,
# Columns should be named after parcellation 1
"col_names": aggregation_parcellation_one["col_names"],
"col_names": aggregation_parcellation_one["aggregation"][
"col_names"
],
# Rows should be named after parcellation 2
"row_names": aggregation_parcellation_two["col_names"],
"row_names": aggregation_parcellation_two["aggregation"][
"col_names"
],
},
}
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