|
@@ -1,40 +0,0 @@
|
1
|
|
-#!/usr/bin/env python3
|
2
|
|
-# -*- coding: utf-8 -*-
|
3
|
|
-"""
|
4
|
|
-Created on Sun Jan 9 11:12:30 2022
|
5
|
|
-
|
6
|
|
-@author: pfaure
|
7
|
|
-"""
|
8
|
|
-from sklearn.neighbors import NearestNeighbors
|
9
|
|
-import numpy as np
|
10
|
|
-
|
11
|
|
-from myplotlib import print_1d_data, print_2d_data
|
12
|
|
-from mydatalib import extract_data_csv, scale_data
|
13
|
|
-
|
14
|
|
-path = './new-data/'
|
15
|
|
-dataset_name = "pluie"
|
16
|
|
-save = False
|
17
|
|
-
|
18
|
|
-print("-----------------------------------------------------------")
|
19
|
|
-print(" Chargement du dataset : " + dataset_name)
|
20
|
|
-(villes, data) = extract_data_csv(path + dataset_name, 13, 13)
|
21
|
|
-print(data)
|
22
|
|
-# print_2d_data(data, dataset_name=dataset_name +
|
23
|
|
-# "_brutes", stop=False, save=save)
|
24
|
|
-
|
25
|
|
-print("-----------------------------------------------------------")
|
26
|
|
-print(" Mise à l'échelle")
|
27
|
|
-data_scaled = scale_data(data)
|
28
|
|
-# print_2d_data(data_scaled, dataset_name=dataset_name +
|
29
|
|
-# "_scaled", stop=False, save=save)
|
30
|
|
-
|
31
|
|
-print("-----------------------------------------------------------")
|
32
|
|
-print(" Calcul du voisinage")
|
33
|
|
-n = 5
|
34
|
|
-neighbors = NearestNeighbors(n_neighbors=n)
|
35
|
|
-neighbors.fit(data_scaled)
|
36
|
|
-distances, indices = neighbors.kneighbors(data_scaled)
|
37
|
|
-distances = list(map(lambda x: sum(x[1:n-1])/(len(x)-1), distances))
|
38
|
|
-distances = np.sort(distances, axis=0)
|
39
|
|
-print_1d_data(distances, range(1, len(distances)+1), x_name="distance_moyenne",
|
40
|
|
- y_name="nombre_de_points", stop=False, save=save)
|