8000 s/euclidian_distances/euclidean_distances · scikit-learn/scikit-learn@8f745c0 · GitHub
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s/euclidian_distances/euclidean_distances
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-14
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4 files changed

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‎scikits/learn/cluster/k_means_.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -11,7 +11,7 @@
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import numpy as np
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from ..base import BaseEstimator
14-
from ..metrics.pairwise import euclidian_distances
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from ..metrics.pairwise import euclidean_distances
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###############################################################################
@@ -55,7 +55,7 @@ def k_init(X, k, n_samples_max=500, rng=None):
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X = X[rng.randint(n_samples, size=n_samples_max)]
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n_samples = n_samples_max
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58-
distances = euclidian_distances(X, X, squared=True)
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distances = euclidean_distances(X, X, squared=True)
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# choose the 1st seed randomly, and store D(x)^2 in D[]
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first_idx = rng.randint(n_samples)
@@ -263,7 +263,7 @@ def _e_step(x, centers, precompute_distances=True, x_squared_norms=None):
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k = centers.shape[0]
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if precompute_distances:
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distances = euclidian_distances(centers, x, x_squared_norms,
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distances = euclidean_distances(centers, x, x_squared_norms,
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squared=True)
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z = -np.ones(n_samples).astype(np.int)
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mindist = np.infty * np.ones(n_samples)

‎scikits/learn/cluster/mean_shift_.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -9,7 +9,7 @@
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import numpy as np
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from ..base import BaseEstimator
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from ..metrics.pairwise import euclidian_distances
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from ..metrics.pairwise import euclidean_distances
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def estimate_bandwidth(X, quantile=0.3):
@@ -23,7 +23,7 @@ def estimate_bandwidth(X, quantile=0.3):
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should be between [0, 1]
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0.5 means that the median is all pairwise distances is used
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"""
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distances = euclidian_distances(X, X)
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distances = euclidean_distances(X, X)
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distances = np.triu(distances, 1)
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distances_sorted = np.sort(distances[distances > 0])
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bandwidth = distances_sorted[floor(quantile * len(distances_sorted))]

‎scikits/learn/metrics/pairwise.py

Lines changed: 8 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -9,8 +9,8 @@
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import numpy as np
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def euclidian_distances(X, Y,
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Y_norm_squared=None,
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def euclidean_distances(X, Y,
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Y_norm_squared=None,
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squared=False):
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"""
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Considering the rows of X (and Y=X) as vectors, compute the
@@ -34,14 +34,14 @@ def euclidian_distances(X, Y,
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Examples
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--------
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>>> from scikits.learn.metrics.pairwise import euclidian_distances
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>>> from scikits.learn.metrics.pairwise import euclidean_distances
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>>> X = [[0, 1], [1, 1]]
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>>> # distrance between rows of X
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>>> euclidian_distances(X, X)
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>>> euclidean_distances(X, X)
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array([[ 0., 1.],
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[ 1., 0.]])
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>>> # get distance to origin
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>>> euclidian_distances(X, [[0, 0]])
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>>> euclidean_distances(X, [[0, 0]])
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array([[ 1. ],
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[ 1.41421356]])
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"""
@@ -64,7 +64,7 @@ def euclidian_distances(X, Y,
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YY = np.asanyarray(Y_norm_squared)
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if YY.shape != (Y.shape[0],):
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raise ValueError("Incompatible dimension for Y and Y_norm_squared")
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YY = YY[np.newaxis,:]
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YY = YY[np.newaxis, :]
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# TODO:
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# a faster cython implementation would do the dot product first,
@@ -77,3 +77,5 @@ def euclidian_distances(X, Y,
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return distances
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else:
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return np.sqrt(distances)
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euclidian_distances = euclidean_distances # both spelling for backward compat

‎scikits/learn/metrics/tests/test_pairwise.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -1,12 +1,12 @@
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from numpy.testing import assert_array_almost_equal
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3-
from ..pairwise import euclidian_distances
3+
from ..pairwise import euclidean_distances
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55

6-
def test_euclidian_distances():
6+
def test_euclidean_distances():
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"""Check that the pairwise euclidian distances computation"""
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X = [[0]]
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Y = [[1], [2]]
10-
D = euclidian_distances(X, Y)
10+
D = euclidean_distances(X, Y)
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assert_array_almost_equal(D, [[1., 2.]])
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