68 lines
2.2 KiB
Matlab
68 lines
2.2 KiB
Matlab
function plot_ms_probabilities(computed_probabilities, options_)
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% function plot_ms_probabilities(computed_probabilities, options_)
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% Plots the regime probablities for each graph
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%
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% INPUTS
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% computed_probabilities: Txnstates
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%
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% OUTPUTS
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% none
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright © 2011-2017 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare 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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% Dynare 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 Dynare. If not, see <https://www.gnu.org/licenses/>.
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[T,num_grand_regimes] = size(computed_probabilities);
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num_chains = length(options_.ms.ms_chain);
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for i=1:num_chains
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chains(i).num_regimes = length(options_.ms.ms_chain(i).regime);
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chains(i).probabilities = zeros([T,chains(i).num_regimes]);
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end
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for t=1:T
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chains = iterate_chain(computed_probabilities(t,:), t, chains, 1, num_chains);
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end
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for i=1:num_chains
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graph_name = ['MS-Probabilities, Chain ' int2str(i)];
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figure('Name',graph_name)
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plot(chains(i).probabilities,'LineWidth', 1.2);
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ltxt = {};
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for j=1:chains(i).num_regimes
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ltxt{j} = ['Regime ' int2str(j)];
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end
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legend(ltxt{:});
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title(['Chain ' int2str(i)]);
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ylim([0 1.0]);
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dyn_save_graph([options_.ms.output_file_tag filesep 'Output' filesep 'Probabilities'], ['MS-Probabilities-Chain-' int2str(i)], ...
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options_.graph_save_formats,options_.TeX,[],[],graph_name);
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end
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end
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function [chains] = iterate_chain(probs, t, chains, chain, num_chains)
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offset_length = length(probs)/chains(chain).num_regimes;
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for i=1:chains(chain).num_regimes
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p = probs( (i-1)*offset_length+1 : i*offset_length );
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chains(chain).probabilities(t, i) = chains(chain).probabilities(t, i) + sum( p );
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if chain < num_chains
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chains = iterate_chain(p, t, chains, chain+1, num_chains);
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end
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end
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end
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