Global Index (all files) (short | long) | Local contents | Local Index (files in subdir) (short | long)

[OP1, OP2, OP3, OP4, OP5] = compdiv(WhatTask, P1, P2, P3, P4, P5, P6, P7, P8, P9, P10);

COMPute DIVerse things of GEA Toolbox This function computes diverse special results for the GEA Toolbox during computation used at different points of the toolbox. Syntax: [OP1, OP2, OP3, OP4, OP5] = compdiv(WhatTask, P1, P2, P3, P4, P5, P6, P7, P8, P9, P10) Input parameters: WhatTask - String containing the name of the needed computation P1 - P10 - Parameters needed for the specific computations Output parameter: OP1 - OP5 - Output parameters, specific for every computation Possible functions: WhatTask == 'fitness_distance_correlation' or 'fdc' Compute fitness distance correlation P1 - Vector containing Fitnesses (objective values for single objective functions), corresponds with ChromAll (P2) P2 - Matrix containing ChromAll, alle individuals for distance computation, every row in ChromAll corresponds the same value in Fitnesses(P1) P3 - Vector containing best individual or global solution OP1 - Scalar containing fitness distance correlation coefficient OP2 - Vector containing Fitnesses (same as P1) OP3 - Vector containing Distances computed from P2 and P3 WhatTask == 'distance_chrom' Compute distance between individuals (used in resplot) P1 - Matrix containing individuals, the distance between all individuals is computed OP1 - Vector containing all distances, similar to upper half of distance matrix WhatTask == 'distance_chrom_mat' Compute distance between individuals (used in resplot) P1 - Matrix containing individuals, the distance between all individuals is computed OP1 - Matrix containing all distances WhatTask == 'possubpop' Sort/order subpopulations according objective values, return position of every subpopulation P1 - Matrix/vector containing (objective) values P2 - Vector containing number of individuals per subpopulation P3 - Vector containing previous filtered order of subpopulations OP1 - (row) Vector containing position of every subpopulation subpopulation with best/minimal objective values gets 1, worst subpopulation gets length(SUBPOP) OP2 - (row) Vector containing index to best values in every subpopulation, thus, P1(OP2) = values of best individuals of every subpopulation OP3 - (row) Vector containing filtered order of subpopulations WhatTask == 'checksubpop' Check variable SUBPOP against number of objective values/individuals and set correct values P1 - Vector/scalar containing number of individuals per subpopulation P2 - Scalar containing number of (objective) values OP1 - Vector containing checked number of individuals per subpopulation WhatTask == 'cutfillstring' Check length of CFString against NewLength, if longer - cut string, if shorter, fill with white space P1 - String CFString P2 - Scalar NewLength containing number of new length of string OP1 - String containing cutted or filled string WhatTask == 'phi_convergence' Calculate the Kappa vconvergence measure P1 - Matrix with individuals of population (Chrom) P2 - Matrix with boundaries of variables (VLUB) OP1 - Scalar with Phi value WhatTask == 'kappa_convergence' Calculate the Kappa vconvergence measure P1 - Matrix with individuals of population (Chrom) P2 - Matrix with boundaries of variables (VLUB) OP1 - Scalar with Kappa value See also: geamain2, resplot, terminat

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