Author: tlinnet Date: Mon Jun 9 00:49:18 2014 New Revision: 23752 URL: http://svn.gna.org/viewcvs/relax?rev=23752&view=rev Log: Removed unused import of numpy. Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis. Modified: branches/disp_spin_speed/lib/dispersion/cr72.py branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_cr72.py Modified: branches/disp_spin_speed/lib/dispersion/cr72.py URL: http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/lib/dispersion/cr72.py?rev=23752&r1=23751&r2=23752&view=diff ============================================================================== --- branches/disp_spin_speed/lib/dispersion/cr72.py (original) +++ branches/disp_spin_speed/lib/dispersion/cr72.py Mon Jun 9 00:49:18 2014 @@ -92,7 +92,6 @@ """ # Python module imports. -import numpy as np from numpy import allclose, arccosh, array, cos, cosh, isfinite, min, max, ndarray, ones, sqrt, sum, zeros # Repetitive calculations (to speed up calculations). Modified: branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_cr72.py URL: http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_cr72.py?rev=23752&r1=23751&r2=23752&view=diff ============================================================================== --- branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_cr72.py (original) +++ branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_cr72.py Mon Jun 9 00:49:18 2014 @@ -57,7 +57,7 @@ # Calc for single. s_filename = tempfile.NamedTemporaryFile(delete=False).name # Profile for a single spin. - cProfile.run('single(iter=1000)', s_filename) + cProfile.run('single(iter=10000)', s_filename) # Read all stats files into a single object s_stats = pstats.Stats(s_filename) @@ -75,7 +75,7 @@ # Calc for cluster. c_filename = tempfile.NamedTemporaryFile(delete=False).name # Profile for a cluster of 100 spins. - cProfile.run('cluster(iter=1000)', c_filename) + cProfile.run('cluster(iter=10000)', c_filename) # Read all stats files into a single object c_stats = pstats.Stats(c_filename)