def run(): random.seed(0) flex.set_random_seed(0) test_rosenbrock_function(3) random.seed(0) flex.set_random_seed(0) test_rosenbrock_function(4)
def run_call_back(flags, space_group_info): if not space_group_info.group().is_centric(): if flags.fix_random_seeds: random.seed(1) flex.set_random_seed(1) scitbx.random.set_random_seed(1) hooft_analysis_test_case( space_group_info,use_students_t_errors=False).exercise(debug=flags.Debug) if students_t_available: hooft_analysis_test_case( space_group_info,use_students_t_errors=True).exercise(debug=flags.Debug)
def run_call_back(flags, space_group_info): if not space_group_info.group().is_centric(): if flags.fix_random_seeds: random.seed(1) flex.set_random_seed(1) scitbx.random.set_random_seed(1) hooft_analysis_test_case( space_group_info, use_students_t_errors=False).exercise(debug=flags.Debug) if students_t_available: hooft_analysis_test_case( space_group_info, use_students_t_errors=True).exercise(debug=flags.Debug)
def run(): random.seed(0) flex.set_random_seed(0) test_rosenbrock_function(1) print "OK"
max_noise = noise.norm() xyz = flex.random_double(3)*5 fixed.append( list(xyz) ) moving1.append( list(xyz + noise/10) ) moving2.append( list(xyz + noise/2) ) ne = nsd_engine(fixed) a = ne.nsd(fixed) b = ne.nsd(moving1) c = ne.nsd(moving2) assert abs(a)<1e-6 assert(b<=c) matrix = euler.zyz_matrix(0.7,1.3,2.1) fixed_r = matrix*moving1+(8,18,28) fitter = nsd_rigid_body_fitter( fixed,fixed_r) nxyz = fitter.best_shifted() dd = nxyz[0:fixed.size()]-fixed dd = dd.norms() dd = flex.max(dd) assert (dd<2.00*max_noise/10) if __name__ == "__main__": from stdlib import random random.seed(0) flex.set_random_seed(0) for ii in range(10): tst_nsd() print "OK"