From ba39b55a16c12d90704e1d4f67dd33c631de1de6 Mon Sep 17 00:00:00 2001 From: Charlie Kemp Date: Wed, 7 Oct 2020 10:36:45 -0400 Subject: [PATCH] clarified origin of comment in code --- stretch_calibration/nodes/process_head_calibration_data | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/stretch_calibration/nodes/process_head_calibration_data b/stretch_calibration/nodes/process_head_calibration_data index c06e04e..182dea4 100755 --- a/stretch_calibration/nodes/process_head_calibration_data +++ b/stretch_calibration/nodes/process_head_calibration_data @@ -927,11 +927,10 @@ class ProcessHeadCalibrationDataNode: end_time = time.time() calibration_time_in_minutes = (end_time - start_time)/60.0 print('Minutes spent calibrating: ', calibration_time_in_minutes) - - # A results tuple from CMAEvolutionStrategy property result. + # " + # A results tuple from CMAEvolutionStrategy property result. # This tuple contains in the given position and as attribute - # 0 xbest best solution evaluated # 1 fbest objective function value of best solution # 2 evals_best evaluation count when xbest was evaluated @@ -939,6 +938,9 @@ class ProcessHeadCalibrationDataNode: # 4 iterations # 5 xfavorite distribution mean in "phenotype" space, to be considered as current best estimate of the optimum # 6 stds effective standard deviations, can be used to compute a lower bound on the expected coordinate-wise distance to the true optimum, which is (very) approximately stds[i] * dimension**0.5 / min(mueff, dimension) / 1.5 / 5 ~ std_i * dimension**0.5 / min(popsize / 2, dimension) / 5, where dimension = CMAEvolutionStrategy.N and mueff = CMAEvolutionStrategy.sp.weights.mueff ~ 0.3 * popsize. + # " + # documentation copied from + # http://cma.gforge.inria.fr/apidocs-pycma/cma.evolution_strategy.CMAEvolutionStrategyResult.html # Get best error terms best_parameters = es.result[0]