This commit is contained in:
P.M. Sutter 2014-07-04 07:17:21 -04:00
commit 1ae7022f6d
3 changed files with 10 additions and 21 deletions

4
README
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@ -26,7 +26,7 @@ This software is put under the GNU Public License.
Please see LICENSE for further information.
Mainline VIDE contributions from Ben Wandelt, Nico Hamaus, Alice Pisani,
Paul Zibick, and Qingqing Mao.
Paul Zivick, and Qingqing Mao.
This toolkit includes ZOBOV, originally developed by Mark Neyrinck.
See zobov/zobov_readme.txt for copyright/license information.
SDF library provided by Michael S. Warren and John Salmon.
@ -48,4 +48,4 @@ cd pipeline/
Version Summary
-----------------
v1.0 - Initial Release
v1.0 - Initial Release

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@ -45,7 +45,7 @@ IF(INTERNAL_SCIPY)
ENDIF(INTERNAL_SCIPY)
IF(INTERNAL_KDTREE_SCIPY)
SET(KDTREE_SCIPY_URL "https://github.com/patvarilly/periodic_kdtree/archive/master.zip" CACHE STRING "URL to download kdtree from")
SET(KDTREE_SCIPY_URL "https://github.com/patvarilly/periodic_kdtree/archive/ea2d9e8c9d.zip" CACHE STRING "URL to download kdtree from")
mark_as_advanced(KDTREE_SCIPY_URL)
ENDIF(INTERNAL_KDTREE_SCIPY)
@ -200,15 +200,13 @@ IF(INTERNAL_KDTREE_SCIPY)
BUILD_COMMAND ${BUILD_ENVIRONMENT} ${CMAKE_SOURCE_DIR}/external/python_build.cmake
INSTALL_COMMAND ${BUILD_ENVIRONMENT} ${CMAKE_SOURCE_DIR}/external/python_install.cmake
PATCH_COMMAND ${CMAKE_COMMAND}
-DBUILD_PREFIX=${BUILD_PREFIX}/kdtree-scipy-prefix
-DPATCH_FILE=${CMAKE_SOURCE_DIR}/external/patch_kdtree
-DBUILD_PREFIX=${BUILD_PREFIX}/kdtree-scipy-prefix
-DSOURCE_PREFIX=${BUILD_PREFIX}/kdtree-scipy-prefix/src/kdtree-scipy
-P ${CMAKE_SOURCE_DIR}/external/check_and_apply_patch.cmake
)
SET(AUXILIARY_PYTHON_DEPEND ${AUXILIARY_PYTHON_DEPEND} kdtree-scipy)
ENDIF(INTERNAL_KDTREE_SCIPY)

19
external/patch_kdtree vendored
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@ -1,12 +1,12 @@
--- periodic_kdtree.py.old 2014-04-18 17:30:39.000000000 +0200
+++ periodic_kdtree.py 2014-04-18 17:31:59.000000000 +0200
--- periodic_kdtree.py.old 2014-05-31 17:08:00.000000000 +0200
+++ periodic_kdtree.py 2014-06-24 13:42:13.769770000 +0200
@@ -102,7 +102,7 @@
# all neighbors within the given distance_upper_bound".
# Cap distance_upper_bound
- distance_upper_bound = np.min(distance_upper_bound,
+ distance_upper_bound = min(distance_upper_bound,
self.max_distance_upper_bound)
- distance_upper_bound = np.min([distance_upper_bound,
+ distance_upper_bound = min([distance_upper_bound,
self.max_distance_upper_bound])
# Run queries over all relevant images of x
@@ -128,7 +128,7 @@
@ -18,12 +18,3 @@
# Run queries over all relevant images of x
results = []
@@ -213,7 +213,7 @@
# all neighbors within the given distance_upper_bound".
# Cap distance_upper_bound
- distance_upper_bound = np.min(distance_upper_bound,
+ distance_upper_bound = min(distance_upper_bound,
self.max_distance_upper_bound)
# Run queries over all relevant images of x