[Scipy-svn] r4420 - trunk/scipy/cluster
scipy-svn at scipy.org
scipy-svn at scipy.org
Mon Jun 9 02:05:13 EDT 2008
Author: damian.eads
Date: 2008-06-09 01:05:10 -0500 (Mon, 09 Jun 2008)
New Revision: 4420
Modified:
trunk/scipy/cluster/__init__.py
trunk/scipy/cluster/hierarchy.py
Log:
Added import to cluster/__init__.py. Removed pdist import from hierarchy.
Modified: trunk/scipy/cluster/__init__.py
===================================================================
--- trunk/scipy/cluster/__init__.py 2008-06-09 06:01:51 UTC (rev 4419)
+++ trunk/scipy/cluster/__init__.py 2008-06-09 06:05:10 UTC (rev 4420)
@@ -6,6 +6,6 @@
__all__ = ['vq', 'hierarchy', 'distance']
-import vq, hierarchy
+import vq, hierarchy, distance
from scipy.testing.pkgtester import Tester
test = Tester().test
Modified: trunk/scipy/cluster/hierarchy.py
===================================================================
--- trunk/scipy/cluster/hierarchy.py 2008-06-09 06:01:51 UTC (rev 4419)
+++ trunk/scipy/cluster/hierarchy.py 2008-06-09 06:05:10 UTC (rev 4420)
@@ -149,7 +149,7 @@
import numpy as np
import _hierarchy_wrap, types
-from distance import pdist
+import distance
_cpy_non_euclid_methods = {'single': 0, 'complete': 1, 'average': 2,
'weighted': 6}
@@ -437,14 +437,14 @@
if method not in _cpy_linkage_methods:
raise ValueError('Invalid method: %s' % method)
if method in _cpy_non_euclid_methods.keys():
- dm = pdist(X, metric)
+ dm = distance.pdist(X, metric)
Z = np.zeros((n - 1, 4))
_hierarchy_wrap.linkage_wrap(dm, Z, n, \
int(_cpy_non_euclid_methods[method]))
elif method in _cpy_euclid_methods.keys():
if metric != 'euclidean':
raise ValueError('Method %s requires the distance metric to be euclidean' % s)
- dm = pdist(X, metric)
+ dm = distance.pdist(X, metric)
Z = np.zeros((n - 1, 4))
_hierarchy_wrap.linkage_euclid_wrap(dm, Z, X, m, n,
int(_cpy_euclid_methods[method]))
@@ -1341,7 +1341,7 @@
descriptions.
distance: the distance metric for calculating pairwise
- distances. See pdist for descriptions and
+ distances. See distance.pdist for descriptions and
linkage to verify compatibility with the linkage
method.
@@ -1361,7 +1361,7 @@
if type(X) != np.ndarray or len(X.shape) != 2:
raise TypeError('The observation matrix X must be an n by m numpy array.')
- Y = pdist(X, metric=distance)
+ Y = distance.pdist(X, metric=distance)
Z = linkage(Y, method=method)
if R is None:
R = inconsistent(Z, d=depth)
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