mirror of https://github.com/jlizier/jidt
230 lines
12 KiB
Matlab
Executable File
230 lines
12 KiB
Matlab
Executable File
%%
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%% Java Information Dynamics Toolkit (JIDT)
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%% Copyright (C) 2012, Joseph T. Lizier
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%%
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%% This program is free software: you can redistribute it and/or modify
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%% it under the terms of the GNU General Public License as published by
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%% the Free Software Foundation, either version 3 of the License, or
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%% (at your option) any later version.
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%%
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%% This program is distributed in the hope that it will be useful,
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%% but WITHOUT ANY WARRANTY; without even the implied warranty of
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%% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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%% GNU General Public License for more details.
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%%
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%% You should have received a copy of the GNU General Public License
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%% along with this program. If not, see <http://www.gnu.org/licenses/>.
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%%
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% To recreate the plots in:
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% J.T. Lizier, M. Prokopenko and A.Y. Zomaya, "A framework for the local information dynamics of distributed computation in complex systems", in Guided self-organisation: Inception, ed. M. Prokopenko, pp. 115-158, Springer, Berlin/Heidelberg, 2014; doi: 10.1007/978-3-642-53734-9_5, arXiv:0811.2690.
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clear all;
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% Set up simulation options:
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cells = 10000;
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timeSteps = 600;
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neighbourhood = 3;
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caStates = 2;
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% Set up options for information dynamics analysis, and which segment of the CA to plot
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measureParams.k=16;
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options.saveImages = true;
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options.saveImagesFormat = 'pdf';
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options.plotOptions.scaleColoursToSubsetOfPlot = true;
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scaleColoursToExtremesDefault = false;
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options.plotOptions.scaleColoursToExtremes = scaleColoursToExtremesDefault;
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% Turn up the contrast so that the small values aren't disproportionately visible: (0.15, 0.30 was good, except for separable which was better with 0.15, 0.35)
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options.plotOptions.scalingMainComponent = 0.15;
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options.plotOptions.scalingScdryComponent = 0.30;
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options.plotOptions.gammaPower = 0.5;
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%%%%%%%%%
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% Examining rule 54:
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options.plotOptions.plotRows = 35;
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options.plotOptions.plotCols = 35;
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options.plotOptions.plotStartRow = 150;
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options.plotOptions.plotStartCol = 175;
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options.seed = 2;
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if (exist('initialStates/GsoChapterDemo2013-initialState.txt', 'file'))
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% A file specifying the initial state exists -- this
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% ensures that Matlab and Octave use the same initial state
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% (otherwise only Octave recreates the same initial state used in our chapter).
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% (You can delete/move the initial state file if you want them generated from scratch.)
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options.initialState = load('initialStates/GsoChapterDemo2013-initialState.txt');
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elseif (isfield(options, 'initialState'))
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options = rmfield(options, 'initialState');
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end
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fprintf('\nStarting rule 54 ...\n');
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fprintf('\nPlotting active info storage ...\n');
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 54, cells, timeSteps, 'active', measureParams, options);
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fprintf('\nPress any key when ready for excess entropy ...\n');
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pause
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options.plotRawCa = false;
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measureParams.k=8; % just for excess entropy
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 54, cells, timeSteps, 'excess', measureParams, options);
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fprintf('\nPress any key when ready for apparent transfer entropy j = 1 ...\n');
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pause
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% Use the full red scale for transfer and separable info, since we need to see the extreme negative values properly
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options.plotOptions.scaleColoursToExtremes = true;
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options.plotOptions.scalingScdryComponent = 0.35;
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options.plotOptions.scalingMainComponent = 0.35;
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measureParams.k=16; % back to default
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measureParams.j = 1;
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 54, cells, timeSteps, 'transfer', measureParams, options);
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fprintf('\nPress any key when ready for apparent transfer entropy j = -1 ...\n');
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pause
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measureParams.j = -1;
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 54, cells, timeSteps, 'transfer', measureParams, options);
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fprintf('\nPress any key when ready for the separable information ...\n');
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pause
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options.plotOptions.scalingMainComponent = 0.15; % Return to previous value
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options.plotOptions.scalingScdryComponent = 0.35;
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 54, cells, timeSteps, 'separable', measureParams, options);
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fprintf('\nPress any key when ready to apply to the next rule\n')
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pause
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options.plotOptions.scaleColoursToExtremes = scaleColoursToExtremesDefault; % return to default value
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options.plotOptions.scalingScdryComponent = 0.30; % return to previous value
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%%%%%%%%%
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% Examining rule 110: (60, 60, 220, 230 is good but with only one collision)
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options.plotRawCa = true;
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options.plotOptions.plotRows = 50;
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options.plotOptions.plotCols = 50;
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options.plotOptions.plotStartRow = 50+20;
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options.plotOptions.plotStartCol = 800+60;
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options.seed = 2;
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if (exist('initialStates/GsoChapterDemo2013-initialState.txt', 'file'))
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% A file specifying the initial state exists -- this
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% ensures that Matlab and Octave use the same initial state
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% (otherwise only Octave recreates the same initial state used in our chapter).
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% (You can delete/move the initial state file if you want them generated from scratch.)
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options.initialState = load('initialStates/GsoChapterDemo2013-initialState.txt');
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elseif (isfield(options, 'initialState'))
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options = rmfield(options, 'initialState');
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end
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fprintf('\nStarting rule 110 ...\n');
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fprintf('\nPlotting active info storage ...\n');
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 110, cells, timeSteps, 'active', measureParams, options);
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fprintf('\nPress any key when ready for excess entropy ...\n');
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pause
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options.plotRawCa = false;
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measureParams.k=8; % just for excess entropy
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 110, cells, timeSteps, 'excess', measureParams, options);
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fprintf('\nPress any key when ready for entropy rate ...\n');
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pause
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measureParams.k=16; % back to default
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 110, cells, timeSteps, 'entropyrate', measureParams, options);
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fprintf('\nPress any key when ready for apparent transfer entropy j = -1 ...\n');
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pause
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% Use the full red scale for transfer and separable info, since we need to see the extreme negative values properly
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options.plotOptions.scaleColoursToExtremes = true;
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measureParams.j = -1;
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 110, cells, timeSteps, 'transfer', measureParams, options);
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fprintf('\nPress any key when ready for the separable information ...\n');
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pause
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options.plotOptions.scalingScdryComponent = 0.35;
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 110, cells, timeSteps, 'separable', measureParams, options);
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fprintf('\nPress any key when ready to apply to the next rule\n')
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pause
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options.plotOptions.scaleColoursToExtremes = scaleColoursToExtremesDefault; % return to default value
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options.plotOptions.scalingScdryComponent = 0.30; % return to previous value
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%%%%%%%%%
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% Examining rule phi_par:
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% (75, 75, 12, 300 - is ok, but another collision would be good)
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% (100, 100, 12, 500 - is very interesting, but perhaps slightly too complicated. Dynamics will lead to some strange colouring also)
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options.plotRawCa = true;
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options.plotOptions.plotRows = 70;
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options.plotOptions.plotCols = 70;
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options.plotOptions.plotStartRow = 17;
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options.plotOptions.plotStartCol = 585;
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options.seed = 2;
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if (exist('initialStates/GsoChapterDemo2013-initialState-phipar.txt', 'file'))
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% A file specifying the initial state exists -- this
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% ensures that Matlab and Octave use the same initial state
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% (otherwise only Octave recreates the same initial state used in our chapter).
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% (You can delete/move the initial state file if you want them generated from scratch.)
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options.initialState = load('initialStates/GsoChapterDemo2013-initialState-phipar.txt');
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elseif (isfield(options, 'initialState'))
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options = rmfield(options, 'initialState');
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end
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phi_par = 'feedffdec1aaeec0eef000a0e1a020a0';
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phi_par_neighbourhood = 7;
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phi_par_cells = 30000;
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phi_par_timeSteps = 200;
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measureParams.k=10; % Shorter for phi_par
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fprintf('\nStarting rule phi_par ...\n');
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fprintf('\nPlotting active info storage ...\n');
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plotLocalInfoMeasureForCA(phi_par_neighbourhood, caStates, phi_par, phi_par_cells, phi_par_timeSteps, 'active', measureParams, options);
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options.plotRawCa = false;
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fprintf('\nPress any key when ready for apparent transfer entropy j = -1 ...\n');
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pause
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% Use the full red scale for transfer and separable info, since we need to see the extreme negative values properly
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options.plotOptions.scaleColoursToExtremes = true;
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measureParams.j = -1;
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plotLocalInfoMeasureForCA(phi_par_neighbourhood, caStates, phi_par, phi_par_cells, phi_par_timeSteps, 'transfer', measureParams, options);
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fprintf('\nPress any key when ready for complete transfer entropy j = -1 ...\n');
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pause
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plotLocalInfoMeasureForCA(phi_par_neighbourhood, caStates, phi_par, phi_par_cells, phi_par_timeSteps, 'transfercomplete', measureParams, options);
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fprintf('\nPress any key when ready for apparent transfer entropy j = -3 ...\n');
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pause
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measureParams.j = -3;
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plotLocalInfoMeasureForCA(phi_par_neighbourhood, caStates, phi_par, phi_par_cells, phi_par_timeSteps, 'transfer', measureParams, options);
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fprintf('\nPress any key when ready for the separable information ...\n');
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pause
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options.plotOptions.scalingMainComponent = 0.35; % Make it easier to see stronger negatives
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options.plotOptions.scalingScdryComponent = 0.45;
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plotLocalInfoMeasureForCA(phi_par_neighbourhood, caStates, phi_par, phi_par_cells, phi_par_timeSteps, 'separable', measureParams, options);
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fprintf('\nPress any key when ready to apply to the next rule\n')
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pause
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options.plotOptions.scaleColoursToExtremes = scaleColoursToExtremesDefault; % return to default value
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options.plotOptions.scalingScdryComponent = 0.30; % return to previous value
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options.plotOptions.scalingMainComponent = 0.15; % Return to previous value
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measureParams.k=16; % back to default
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%%%%%%%%%
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% Examining rule 22:
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options.plotOptions.plotRows = 50;
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options.plotOptions.plotCols = 50;
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options.plotOptions.plotStartRow = 150;
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options.plotOptions.plotStartCol = 175;
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options.seed = 2;
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if (exist('initialStates/GsoChapterDemo2013-initialState.txt', 'file'))
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% A file specifying the initial state exists -- this
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% ensures that Matlab and Octave use the same initial state
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% (otherwise only Octave recreates the same initial state used in our chapter).
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% (You can delete/move the initial state file if you want them generated from scratch.)
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options.initialState = load('initialStates/GsoChapterDemo2013-initialState.txt');
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elseif (isfield(options, 'initialState'))
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options = rmfield(options, 'initialState');
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end
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fprintf('\nStarting rule 22 ...\n');
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fprintf('\nPlotting active info storage ...\n');
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options.plotRawCa = true;
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 22, cells, timeSteps, 'active', measureParams, options);
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fprintf('\nPress any key when ready for excess entropy ...\n');
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pause
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options.plotRawCa = false;
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measureParams.k=8; % just for excess entropy
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 22, cells, timeSteps, 'excess', measureParams, options);
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fprintf('\nPress any key when ready for entropy rate ...\n');
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pause
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measureParams.k=16; % back to default
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 22, cells, timeSteps, 'entropyrate', measureParams, options);
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fprintf('\nPress any key when ready for apparent transfer entropy j = 1 ...\n');
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pause
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% Use the full red scale for transfer and separable info, since we need to see the extreme negative values properly
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options.plotOptions.scaleColoursToExtremes = true;
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measureParams.j = 1;
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 22, cells, timeSteps, 'transfer', measureParams, options);
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fprintf('\nPress any key when ready for the separable information ...\n');
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pause
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options.plotOptions.scalingScdryComponent = 0.35;
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plotLocalInfoMeasureForCA(neighbourhood, caStates, 22, cells, timeSteps, 'separable', measureParams, options);
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fprintf('\nPress any key when ready to apply to the next rule\n')
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pause
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options.plotOptions.scaleColoursToExtremes = scaleColoursToExtremesDefault; % return to default value
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options.plotOptions.scalingScdryComponent = 0.30; % return to previous value
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