Updated docstring for CVMatrix and NaiveCVMatrix. (#10)

Author: sm00thix

cvmatrix/__init__.py

@@ -1 +1 @@
-__version__ = "3.0.0"
+__version__ = "3.0.0.post1"

cvmatrix/cvmatrix.py

@@ -53,7 +53,7 @@ class CVMatrix:
     scale_Y : bool, optional, default=True
         Whether to scale `Y` before computation of
         :math:`\mathbf{X}^{\mathbf{T}}\mathbf{W}\mathbf{Y}` by dividing each row with
-        the row of `X`'s column-wise weighted standard deviations. The row of
+        the row of `Y`'s column-wise weighted standard deviations. The row of
         column-wise weighted standard deviations is computed on the training set for
         each fold to avoid data leakage. This parameter is ignored if `Y` is `None`.
 

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "cvmatrix"
-version = "3.0.0"
+version = "3.0.0.post1"
 description = "Fast computation of possibly weighted and possibly centered/scaled training set kernel matrices in a cross-validation setting."
 authors = ["Sm00thix <oleemail@icloud.com>"]
 maintainers = ["Sm00thix <oleemail@icloud.com>"]

tests/naive_cvmatrix.py

@@ -52,7 +52,7 @@ class NaiveCVMatrix(CVMatrix):
     scale_Y : bool, optional, default=True
         Whether to scale `Y` before computation of
         :math:`\mathbf{X}^{\mathbf{T}}\mathbf{W}\mathbf{Y}` by dividing each row with
-        the row of `X`'s column-wise weighted standard deviations. The row of
+        the row of `Y`'s column-wise weighted standard deviations. The row of
         column-wise weighted standard deviations is computed on the training set for
         each fold to avoid data leakage. This parameter is ignored if `Y` is `None`.