Coverage for src/mlstatpy/ml/kppv.py : 92%
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1# -*- coding: utf-8 -*-
2"""
3@file
4@brief Implements classic k-nn.
5"""
6import numpy
7import numpy.linalg
8from scipy.spatial.distance import euclidean
11class NuagePoints:
12 """
13 Définit une classe de nuage de points.
14 On suppose qu'ils sont définis par une matrice,
15 chaque ligne est un élément.
16 """
18 def __init__(self):
19 """
20 constructeur
21 """
22 pass
24 def fit(self, X, y=None):
25 """
26 Follows sklearn API.
28 @param X training set
29 @param y labels
30 """
31 self.nuage = X
32 self.labels = y
34 def kneighbors(self, X, n_neighbors=1, return_distance=True):
35 """
36 Return the k nearest neighbors.
38 @param X test set
39 @param n_neighbors number of neighbors
40 @param return_distance return distance as well
41 @return array (dist), array (indices)
42 """
43 if n_neighbors != 1:
44 raise NotImplementedError( # pragma: no cover
45 "Not implemented when n_neighbors != 1.")
46 if not return_distance:
47 raise NotImplementedError( # pragma: no cover
48 "Not implemented when return_distance is False.")
50 dist = numpy.zeros(X.shape[0])
51 ind = numpy.zeros(X.shape[0], dtype=numpy.int64)
53 for i in range(X.shape[0]):
54 row = X[i, :]
55 row.resize((1, X.shape[1]))
56 r = self.ppv(row)
57 dist[i], ind[i] = r
58 return dist, ind
60 @property
61 def shape(self):
62 """
63 Retourne la dimension du nuage.
64 """
65 return self.nuage.shape
67 def distance(self, obj1, obj2):
68 """
69 Retourne une distance entre deux éléments.
71 @param obj1 object 1
72 @param obj2 object 2
73 @return distance
74 """
75 return euclidean(obj1, obj2)
77 def label(self, i):
78 """
79 Retourne le label de l'object d'indice ``i``.
81 @param i indice
82 @return label or None if there is no label
83 """
84 return self.label[i] if self.label is not None else None
86 def ppv(self, obj):
87 """
88 Retourne l'élément le plus proche de obj et sa distance avec obj.
90 @param obj object
91 @return ``tuple(dist, index)``
92 """
93 ones = numpy.ones((self.nuage.shape[0], 1))
94 mat = ones @ obj
95 if len(mat.shape) == 1:
96 mat.resize((mat.shape[0], 1))
97 delta = self.nuage - mat
98 norm = numpy.linalg.norm(delta, axis=1)
99 i = numpy.argmin(norm)
100 return norm[i], i