From 391d84c5beed4b20226ce0317d6013656e4a4375 Mon Sep 17 00:00:00 2001
From: mdavid <mdavid@student.42.fr>
Date: Wed, 9 Mar 2022 12:27:44 +0100
Subject: [PATCH 1/2] isue #162 homogenisation of examples + reduction of
 docstring + code block in new line

---
 module08/en.subject.tex | 27 ++++++++++++++++-----------
 version                 |  2 +-
 2 files changed, 17 insertions(+), 12 deletions(-)

diff --git a/module08/en.subject.tex b/module08/en.subject.tex
index 7e1b4e3a..20daa9fc 100644
--- a/module08/en.subject.tex
+++ b/module08/en.subject.tex
@@ -1251,9 +1251,10 @@ \section*{Instructions}
     """
     Compute confusion matrix to evaluate the accuracy of a classification.
     Args:
-        y_true:a numpy.ndarray for the correct labels
-        y_hat:a numpy.ndarray for the predicted labels
-        labels: optional, a list of labels to index the matrix. This may be used to reorder or select a subset of labels. (default=None)
+        y_true: numpy.ndarray for the correct labels
+        y_hat: numpy.ndarray for the predicted labels
+        labels: Optional, a list of labels to index the matrix.
+                This may be used to reorder or select a subset of labels. (default=None)
     Returns: 
         The confusion matrix as a numpy ndarray.
         None on any error.
@@ -1310,17 +1311,20 @@ \subsection{Objective(s):}
 \subsection{Instructions:}
 
 In the \texttt{confusion\_matrix.py} file, write the following function as per the instructions below:
+
 \begin{minted}[bgcolor=darcula-back,formatcom=\color{lightgrey},fontsize=\scriptsize]{python}
 def confusion_matrix_(y, y_hat, labels=None, df_option=False):
     """
     Compute confusion matrix to evaluate the accuracy of a classification.
     Args:
-        y:a numpy.ndarray for the correct labels
-        y_hat:a numpy.ndarray for the predicted labels
-        labels: optional, a list of labels to index the matrix. This may be used to reorder or select a subset of labels. (default=None)
-        df_option: optional, if set to True the function will return a pandas DataFrame instead of a numpy array. (default=False)
+        y: numpy.ndarray for the correct labels
+        y_hat: numpy.ndarray for the predicted labels
+        labels: Optional, a list of labels to index the matrix.
+                This may be used to reorder or select a subset of labels. (default=None)
+        df_option: Optional, if set to True the return is a pandas DataFrame instead of a numpy array.
+                   (default=False)
     Returns: 
-        The confusion matrix as a numpy ndarray or a pandas DataFrame according to df_option value.
+        Confusion matrix as a numpy ndarray or a pandas DataFrame according to df_option value.
         None on any error.
     Raises:
         This function should not raise any Exception.
@@ -1329,13 +1333,14 @@ \subsection{Instructions:}
 \end{minted}
 
 \section{Examples:}
+
 \begin{minted}[bgcolor=darcula-back,formatcom=\color{lightgrey},fontsize=\scriptsize]{python}
 import numpy as np
 y_hat = np.array(['norminet', 'dog', 'norminet', 'norminet', 'dog', 'bird'])
-y_true = np.array(['dog', 'dog', 'norminet', 'norminet', 'dog', 'norminet'])
+y = np.array(['dog', 'dog', 'norminet', 'norminet', 'dog', 'norminet'])
 
 # Example 1: 
-confusion_matrix_(y_true, y_hat, df_option=True)
+confusion_matrix_(y, y_hat, df_option=True)
 # Output:
            bird  dog  norminet
  bird         0    0         0
@@ -1343,7 +1348,7 @@ \section{Examples:}
  norminet     1    0         2
 
 # Example 2:
-confusion_matrix_(y_true, y_hat, labels=['bird', 'dog'], df_option=True)
+confusion_matrix_(y, y_hat, labels=['bird', 'dog'], df_option=True)
 # Output:
            bird  dog
  bird         0    0
diff --git a/version b/version
index 7cc166d3..f05f17cf 100644
--- a/version
+++ b/version
@@ -1 +1 @@
-v4.0.3
+v4.0.4

From 0cb0e8a13678294b6df23a464f9efde0a8f2a16c Mon Sep 17 00:00:00 2001
From: mdavid <mdavid@student.42.fr>
Date: Wed, 16 Mar 2022 10:13:25 +0100
Subject: [PATCH 2/2] typo in docstring

---
 module08/en.subject.tex | 12 +++++-------
 1 file changed, 5 insertions(+), 7 deletions(-)

diff --git a/module08/en.subject.tex b/module08/en.subject.tex
index a009c305..155af25d 100644
--- a/module08/en.subject.tex
+++ b/module08/en.subject.tex
@@ -1313,16 +1313,14 @@ \subsection{Instructions:}
 In the \texttt{confusion\_matrix.py} file, write the following function as per the instructions below:
 
 \begin{minted}[bgcolor=darcula-back,formatcom=\color{lightgrey},fontsize=\scriptsize]{python}
-def confusion_matrix_(y, y_hat, labels=None, df_option=False):
+def confusion_matrix_(y_true, y_hat, labels=None, df_option=False):
     """
     Compute confusion matrix to evaluate the accuracy of a classification.
     Args:
-        y: numpy.ndarray for the correct labels
-        y_hat: numpy.ndarray for the predicted labels
-        labels: Optional, a list of labels to index the matrix.
-                This may be used to reorder or select a subset of labels. (default=None)
-        df_option: Optional, if set to True the return is a pandas DataFrame instead of a numpy array.
-                   (default=False)
+        y_true: a numpy.ndarray for the correct labels
+        y_hat: a numpy.ndarray for the predicted labels
+        labels: optional, a list of labels to index the matrix. This may be used to reorder or select a subset of labels. (default=None)
+        df_option: optional, if set to True the function will return a pandas DataFrame instead of a numpy array. (default=False)
     Returns: 
         Confusion matrix as a numpy ndarray or a pandas DataFrame according to df_option value.
         None on any error.