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Causal k nearest neighbors (KNN) that only looks back
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# %% | |
import numpy as np | |
from functools import partial | |
from pykdtree.kdtree import KDTree | |
class LeftKDTree(KDTree): | |
""" | |
KNN that only looks left. | |
This way it respects causality when left is the past. Usefull for local anomoly factor (LOF). | |
url: https://gist.github.com/wassname/298c5a7b4e4fb0974afbe48d9717dd14 | |
""" | |
def query(self, y, y_inds=None, *args, **kwargs): | |
x_inds = np.arange(self.n) | |
if y_inds is None: | |
y_inds = x_inds.copy() | |
# print(y.shape, y_inds.shape) | |
assert len(y) == len(y_inds), f'{y.shape}!={y_inds.shape}' | |
dists = [] | |
inds = [] | |
for i, y_ind in enumerate(y_inds): | |
d, ind = super().query(y[i:i + 1], mask=x_inds > y_ind - 1, *args, **kwargs) | |
dists.append(d) | |
inds.append(ind) | |
dists = np.concatenate(dists) | |
inds = np.concatenate(inds) | |
return dists, inds | |
# %% | |
X = np.array([np.arange(20)]*4).T | |
y = X[4:-4] | |
y_inds = np.arange(4, len(X) - 4) | |
# X, y, y_inds | |
# %% | |
tree = LeftKDTree(X) | |
d, ids = tree.query(y, y_inds) | |
id_is_left=((y_inds-ids)>0).all() | |
print(id_is_left, d, ids) | |
assert id_is_left.all() | |
# True [2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.] [ 3 4 5 6 7 8 9 10 11 12 13 14] | |
# %% | |
tree = KDTree(X) | |
d, ids = tree.query(y) | |
id_is_left=(y_inds-ids>0).all() | |
print(id_is_left, d, ids) | |
assert not id_is_left.all() | |
# False [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] [ 4 5 6 7 8 9 10 11 12 13 14 15] | |
# %% | |
# %% | |
# Note | |
# d==4294967295 and dists==1.3407807929942596e+154 are np.nan, So you may wants to go | |
# dists[dists==1.3407807929942596e+154]=np.nan | |
y_inds = np.arange(len(X)) | |
tree = LeftKDTree(X) | |
d, ids = tree.query(X, y_inds) | |
id_is_left=(y_inds-ids>0)[1:].all() | |
print(id_is_left, d, ids) | |
assert id_is_left.all() | |
# True [1.34078079e+154 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. | |
# 2. 2.] [4294967295 0 1 2 3 4 | |
# 5 6 7 8 9 10 | |
# 11 12 13 14 15 16 | |
# 17 18] | |
# %% | |
tree = KDTree(X) | |
d, ids = tree.query(X) | |
id_is_left = (y_inds - ids > 0).all() | |
print(id_is_left, d, ids) | |
assert not id_is_left.all() | |
# False [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19] | |
# %% |
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