diff --git a/meegkit/ress.py b/meegkit/ress.py
index cdd8f022..7bc854c1 100644
--- a/meegkit/ress.py
+++ b/meegkit/ress.py
@@ -45,6 +45,7 @@ def RESS(X, sfreq: int, peak_freq: float, neig_freq: float = 1,
     --------
     To project the RESS components back into sensor space, one can proceed as
     follows:
+
     >>> # First apply RESS
     >>> from meegkit.utils import matmul3d  # handles 3D matrix multiplication
     >>> out, fromRESS, _ = ress.RESS(data, sfreq, peak_freq, return_maps=True)
@@ -53,6 +54,7 @@ def RESS(X, sfreq: int, peak_freq: float, neig_freq: float = 1,
 
     To transform a new observation into RESS component space (e.g. in the
     context of a cross-validation, with separate train/test sets):
+
     >>> # Start by applying RESS to the train set:
     >>> out, _, toRESS = ress.RESS(data, sfreq, peak_freq, return_maps=True)
     >>> # Then multiply your test data by the toRESS:
diff --git a/meegkit/utils/matrix.py b/meegkit/utils/matrix.py
index 1501eb59..2264959b 100644
--- a/meegkit/utils/matrix.py
+++ b/meegkit/utils/matrix.py
@@ -91,8 +91,8 @@ def widen_mask(mask, widen=4, axis=0):
 
     Examples
     --------
-    >> test = widen_mask(np.array([False, False, False, True, False], 1)
-    >> print(test)
+    >>> test = widen_mask(np.array([False, False, False, True, False], 1)
+    >>> print(test)
     [False False False True True]]
 
     """