From 6ab4cee3c0f192ab416acfc2e2b1661ba09c96f8 Mon Sep 17 00:00:00 2001
From: local_comparaison <mathieu.umec@inrae.fr>
Date: Wed, 30 Aug 2023 09:05:54 +0200
Subject: [PATCH] adding change of clusters number
---
Visualisation_des_donnes_de_mapping.py | 10 +++++-----
1 file changed, 5 insertions(+), 5 deletions(-)
diff --git a/Visualisation_des_donnes_de_mapping.py b/Visualisation_des_donnes_de_mapping.py
index d583f20..60f2e77 100644
--- a/Visualisation_des_donnes_de_mapping.py
+++ b/Visualisation_des_donnes_de_mapping.py
@@ -5,7 +5,7 @@ import matplotlib.pyplot as plt
import seaborn as sns
#### Importation des données
-def Distance_matrix_clustering (input_file,val_infini=50.2):
+def Distance_matrix_clustering (input_file,val_infini=50.2, n_clusters=5):
dataframe= pd.read_excel(input_file,index_col = 0)
print(dataframe.head())
@@ -48,7 +48,7 @@ def Distance_matrix_clustering (input_file,val_infini=50.2):
##### Traitement de la matrice de distance
- nombre_de_clusters=7
+ nombre_de_clusters=n_clusters
clustering = AgglomerativeClustering(n_clusters = nombre_de_clusters, metric = "precomputed",linkage="complete").fit(matrice_pour_traitement)
#results_clustering=pd.DataFrame ({'in': [clustering.labels_] })
results_clustering=clustering.labels_
@@ -71,7 +71,7 @@ def Distance_matrix_clustering (input_file,val_infini=50.2):
###### visualisation
- l_identifiants_de_graphes=[111,111,111,111,111,111,111,111]
+ l_identifiants_de_graphes=[111,111,111,111,111,111,111,111,111,111,111,111,111,111]
plt.figure(figsize=(15, 3))
for num_graph in range (nombre_de_clusters):
@@ -82,8 +82,8 @@ def Distance_matrix_clustering (input_file,val_infini=50.2):
print(matrice_pour_traitement[Liste_d_indice_trier_selon_cluster[num_graph][0]][Liste_d_indice_trier_selon_cluster[num_graph][sous_indice]])
plt.subplot(indentifiant_graphe)
plt.plot(Liste_de_nom_trier_selon_cluster[num_graph],donnes_graph )
-
- plt.suptitle('les differents clusters n=7 ')
+ plt.tick_params(axis='x', rotation=90, size=0.08,labelsize = 7)
+ plt.suptitle('les differents clusters n='+str(n_clusters))
plt.show()
#Distance_matrix_clustering("C:\\Users\\mumec\\Desktop\\Mini_codes\\DistanceMatrix_compose_interet.xlsx")
--
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