Ajout export pour les résultats

module3/exo3/exercice_python_fr.org

@@ -265,7 +265,7 @@ np.array(S_l1500).reshape(1, -1)[:9]
 #+RESULTS:
 | 1759 | 1843 | 1511 | ... | 1503 | 1515 | 1875 |
 
-#+BEGIN_SRC python :session
+#+BEGIN_SRC python :session :results replace :export both
 from sklearn.linear_model import LinearRegression
 from sklearn.metrics import mean_squared_error
 S_tt = [[value] for value in S_l1500]
@@ -282,7 +282,7 @@ f"Les coeff sont L = {lmodel.intercept_} et C =  { 1 / lmodel.coef_}"
 : Les coeff sont L = 3.257592785874401 et C =  [2761.3155395]
 
 ** Cas supérieur à la MTU
-#+BEGIN_SRC python :session
+#+BEGIN_SRC python :session :results replace :export both
 from sklearn.linear_model import LinearRegression
 from sklearn.metrics import mean_squared_error
 S_tt = [[value] for value in S_g1500]
@@ -524,7 +524,7 @@ np.array(S_l1500).reshape(1, -1)[:9]
 #+RESULTS:
 | 1759 | 1843 | 1511 | ... | 1503 | 1515 | 1875 |
 
-#+BEGIN_SRC python :session
+#+BEGIN_SRC python :session :results replace :export both
 from sklearn.linear_model import LinearRegression
 from sklearn.metrics import mean_squared_error
 S_tt = [[value] for value in S_l1500]
@@ -574,7 +574,7 @@ fig.savefig('stacko_g1500_reglineaireT-f(S).png')
 #+RESULTS:
 : None
 
-#+BEGIN_SRC python :session
+#+BEGIN_SRC python :session :results replace :export both
 from sklearn.linear_model import LinearRegression
 from sklearn.metrics import mean_squared_error
 S_tt = [[value] for value in S_g1500]