move ref to end of examples

Author: Remi-Gau

examples/plot_2D_simulation_example.py

@@ -41,10 +41,6 @@
 significantly the spatial uncertainty compared to clustered inference
 algorithms which consider only one spatial compression.
 
-References
-----------
-.. footbibliography::
-
 """
 import matplotlib.pyplot as plt
 
@@ -356,3 +352,9 @@ def plot(maps, titles):
 # conservative. In practice, Type-1 Error guarantees seem to hold
 # for a lower spatial tolerance. This is an additional benefit of clustering
 # randomization.
+
+#############################################################################
+# References
+# ----------
+# .. footbibliography::
+# 

examples/plot_diabetes_variable_importance_example.py

@@ -36,10 +36,6 @@
 single-level case. The aim is to see if integrating the new
 statistically-controlled solution has an impact on the results.
 
-References
-----------
-.. footbibliography::
-
 """
 
 #############################################################################
@@ -255,3 +251,10 @@ def compute_pval(vim):
 ax.set_xticks(range(len(diabetes.feature_names)))
 ax.set_xticklabels(diabetes.feature_names)
 plt.show()
+
+
+#############################################################################
+# References
+# ----------
+# .. footbibliography::
+#