From 14726373bac6c8d4d14e2a14c6dceabec48cac33 Mon Sep 17 00:00:00 2001
From: "ludovic.castglia" <tt982914@gmail.com>
Date: Thu, 30 Jan 2025 10:46:14 +0100
Subject: [PATCH] ajout demo1

---
 data/maison.csv | 546 ++++++++++++++++++++++++++++++++++++++++++++++++
 demo1.py        |  60 ++++++
 demo4.py        |   4 +-
 3 files changed, 608 insertions(+), 2 deletions(-)
 create mode 100644 data/maison.csv
 create mode 100644 demo1.py

diff --git a/data/maison.csv b/data/maison.csv
new file mode 100644
index 0000000..21a75e0
--- /dev/null
+++ b/data/maison.csv
@@ -0,0 +1,546 @@
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diff --git a/demo1.py b/demo1.py
new file mode 100644
index 0000000..05cf700
--- /dev/null
+++ b/demo1.py
@@ -0,0 +1,60 @@
+import os
+import sys
+parent_dir_name = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
+sys.path.append(parent_dir_name + "/3nar/code")
+
+from nnnar import *
+from knn import *
+
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+
+
+# varriable globale
+trainTestRatio = 0.8
+nnnarSubDiv = 10
+
+# lecture des données
+nnnar = Nnnar(4, 0, 100, nnnarSubDiv)
+knn = Knn()
+df = pd.read_csv('./data/maison.csv')
+df = df.iloc[:, 0:5]
+
+# Normalisation des données
+df.iloc[:, 1] = df.iloc[:, 1] - df.iloc[:, 1].min()
+df.iloc[:, 2] = df.iloc[:, 2] - df.iloc[:, 2].min()
+df.iloc[:, 3] = df.iloc[:, 3] - df.iloc[:, 3].min()
+df.iloc[:, 4] = df.iloc[:, 4] - df.iloc[:, 4].min()
+
+df.iloc[:, 1] = df.iloc[:, 1] / df.iloc[:, 1].max()
+df.iloc[:, 2] = df.iloc[:, 2] / df.iloc[:, 2].max()
+df.iloc[:, 3] = df.iloc[:, 3] / df.iloc[:, 3].max()
+df.iloc[:, 4] = df.iloc[:, 4] / df.iloc[:, 4].max()
+
+df.iloc[:, 1:5] = df.iloc[:, 1:5] * 99
+
+# Création des données d'entrainement et de test
+train = df.sample(frac=trainTestRatio)
+test = df.drop(train.index)
+
+# Entrainement du modèle
+coord = train.iloc[:, 1:].values
+value = train.iloc[:, 0].values
+
+for i in range(len(coord)):
+    knn.addPoint(np.array(coord[i]), np.array([value[i]]))
+    nnnar.addPoint(np.array(coord[i]), np.array([value[i]]))
+
+# Test du modèles
+coord = test.iloc[:, 1:].values
+value = test.iloc[:, 0].values
+
+nbErrorNnnar = 0
+
+for i in range(len(coord)):
+    v = nnnar.getValueOfPoint(np.array(coord[i]),5)[0]
+    if v != value[i]:
+        nbErrorNnnar += 100*abs(v-value[i])/value.max()
+
+print("accuracy moyenne:",str(100-nbErrorNnnar/len(coord)))
\ No newline at end of file
diff --git a/demo4.py b/demo4.py
index beb5a9e..2dcd294 100644
--- a/demo4.py
+++ b/demo4.py
@@ -59,5 +59,5 @@ for i in range(nbRepetition):
     accuracy += runOneTest(0.8)
 
 t2 = time()
-print("accuracy moyenne: ",str(accuracy/nbRepetition))
-print("delta temps: ",str(t2-t1))
\ No newline at end of file
+print("accuracy moyenne:",str(accuracy/nbRepetition))
+print("delta temps:",str(t2-t1))
\ No newline at end of file