From 26bebe082c451f8cde95eb11349f3572b11337ed Mon Sep 17 00:00:00 2001
From: Yannick DAYER <yannick.dayer@idiap.ch>
Date: Tue, 22 Mar 2022 15:37:21 +0100
Subject: [PATCH] [refactor] Rename k_means as kmeans
---
bob/learn/em/__init__.py | 2 +-
bob/learn/em/gmm.py | 2 +-
bob/learn/em/{k_means.py => kmeans.py} | 0
bob/learn/em/test/test_kmeans.py | 4 ++--
4 files changed, 4 insertions(+), 4 deletions(-)
rename bob/learn/em/{k_means.py => kmeans.py} (100%)
diff --git a/bob/learn/em/__init__.py b/bob/learn/em/__init__.py
index 6d67218..6c50a0a 100644
--- a/bob/learn/em/__init__.py
+++ b/bob/learn/em/__init__.py
@@ -1,7 +1,7 @@
import bob.extension
from .gmm import GMMMachine, GMMStats
-from .k_means import KMeansMachine
+from .kmeans import KMeansMachine
from .linear_scoring import linear_scoring # noqa: F401
from .wccn import WCCN
from .whitening import Whitening
diff --git a/bob/learn/em/gmm.py b/bob/learn/em/gmm.py
index 88efe81..78ab69f 100644
--- a/bob/learn/em/gmm.py
+++ b/bob/learn/em/gmm.py
@@ -18,7 +18,7 @@ import numpy as np
from h5py import File as HDF5File
from sklearn.base import BaseEstimator
-from .k_means import (
+from .kmeans import (
KMeansMachine,
array_to_delayed_list,
check_and_persist_dask_input,
diff --git a/bob/learn/em/k_means.py b/bob/learn/em/kmeans.py
similarity index 100%
rename from bob/learn/em/k_means.py
rename to bob/learn/em/kmeans.py
diff --git a/bob/learn/em/test/test_kmeans.py b/bob/learn/em/test/test_kmeans.py
index 1400b46..8edc205 100644
--- a/bob/learn/em/test/test_kmeans.py
+++ b/bob/learn/em/test/test_kmeans.py
@@ -16,7 +16,7 @@ import dask.array as da
import numpy as np
import scipy.spatial.distance
-from bob.learn.em import KMeansMachine, k_means
+from bob.learn.em import KMeansMachine, kmeans
def to_numpy(*args):
@@ -187,6 +187,6 @@ def test_get_centroids_distance():
oracle = scipy.spatial.distance.cdist(means, data, metric="sqeuclidean")
for transform in (to_numpy,):
data, means = transform(data, means)
- dist = k_means.get_centroids_distance(data, means)
+ dist = kmeans.get_centroids_distance(data, means)
np.testing.assert_allclose(dist, oracle)
assert type(data) is type(dist), (type(data), type(dist))
--
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