docs/Makefile

@@ -17,6 +17,7 @@ help:
 clean:
 	rm -rf $(BUILDDIR)/*
 	rm -rf auto_examples/
+	rm -rf api/generated/
 
 # For local build
 local: news

docs/changes/newsfragments/242.doc

@@ -0,0 +1 @@
+Update ``julearn`` example under ``examples`` by `Synchon Mandal`_

docs/conf.py

@@ -81,6 +81,7 @@ nitpick_ignore_regex = [
     ("py:class", "typing.Any"),  # python 3.11 error
     # ('py:class', 'numpy.typing.ArrayLike')
     ("py:obj", "sqlalchemy.engine.Engine"),  # ignore sqlalchemy
+    ("py:class", "pipeline.Pipeline"),  # nilearn
 ]
 
 # -- Options for HTML output -------------------------------------------------

examples/run_junifer_julearn.py

@@ -16,9 +16,9 @@ import tempfile
 
 import nilearn
 import pandas as pd
-from julearn import run_cross_validation
+from julearn import run_cross_validation, PipelineCreator
 
-import junifer.testing.registry  # noqa
+import junifer.testing.registry  # noqa: F401
 from junifer.api import collect, run
 from junifer.storage.sqlite import SQLiteFeatureStorage
 from junifer.utils import configure_logging
@@ -70,7 +70,6 @@ sex = (
 ###############################################################################
 # Create a temporary directory for junifer feature extraction:
 with tempfile.TemporaryDirectory() as tmpdir:
-
     storage = {"kind": "SQLiteFeatureStorage", "uri": f"{tmpdir}/test.sqlite"}
     # run the defined junifer feature extraction pipeline
     run(
@@ -97,15 +96,23 @@ X = list(df_vbm.columns)
 df_vbm[y] = age
 df_vbm[confound] = sex
 
+X_types = {
+    "features": X,
+    "confound": confound,
+}
+
+creator = PipelineCreator(problem_type="regression", apply_to="features")
+creator.add("zscore", apply_to=["features", "confound"])
+creator.add("confound_removal", apply_to="features", confounds="confound")
+creator.add("ridge")
+
 scores = run_cross_validation(
-    X=X,
-    confounds=confound,
+    X=X + [confound],
     y=y,
+    X_types=X_types,
     data=df_vbm,
-    problem_type="regression",
-    model="ridge",
+    model=creator,
     cv=3,
-    preprocess_X=["zscore", "remove_confound"],
 )
 print(scores)
 

pyproject.toml

@@ -68,7 +68,7 @@ docs = [
     "sphinx-gallery>=0.11.0,<0.12",
     "furo>=2022.9.29,<2023.0.0",
     "numpydoc>=1.5.0,<1.6",
-    "julearn==0.2.5",
+    "julearn==0.3.0",
     "sphinx-copybutton==0.5.1",
     "towncrier==22.12.0",
     "sphinxcontrib-mermaid==0.8.1",