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mpsy_proto_adapt.m
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mpsy_proto_adapt.m
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% Usage: mpsy_proto_adapt()
% ----------------------------------------------------------------------
% Protocols the results of the previous adaptive run:
% plots M.VAR as a function of trial number,
% writes a corresponding result line into the "psydat"
% file, in psydat format version 3.
% In case M.DEBUG > 0, all variables M.* are saved in a
% separate mat-file which can be useful for debugging
%
% input args: (none) works on set of global variables M.*
% output args: (none) processes subjects' answer and protocolls everything
%
% Copyright (C) 2003, 2004 Martin Hansen, FH OOW
% Author : Martin Hansen, <psylab AT jade-hs.de>
% Date : 23 May 2003
% Updated: <21 Feb 2017 10:33, mh>
% Change of filename from mpsy_proto (for version <= 2.7)
% to mpsy_proto_adapt (for version >= 2.8)
% Updated: <25 Okt 2016 09:36, mh>
% Changed output line of a trial in psydat file
% slightly: Instead of "####" as a marker in the first column, it
% is now "##adapt##" in order to specify the type of experiment.
% Updated: <20 Jul 2015 12:29, mh>
% added option for saving all values of M.VARS during one
% run. Original idea/commit by Stephanus Volke
% Updated: <13 Nov 2007 Sven Franz>
% added var "M.SAVEMEAN". When M.SAVEMEAN==1 the mean (not
% median) will be saved
% Updated: < 6 Jan 2006 20:07, mh>
%% This file is part of PSYLAB, a collection of scripts for
%% designing and controlling interactive psychoacoustical listening
%% experiments.
%% This file is free software; you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published
%% by the Free Software Foundation; either version 2 of the License,
%% or (at your option) any later version. See the GNU General
%% Public License for more details: http://www.gnu.org/licenses/gpl
%% This file is distributed in the hope that it will be useful,
%% but WITHOUT ANY WARRANTY; without even the implied warranty of
%% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
% determine the trial indices of the measurement phase, i.e. where the
% familiarization phase is finished, and the step size has reached its
% minimum value:
M.measurement_fidx = find(M.STEPS == M.MINSTEP);
% calculate mean, median etc. of the stimulus variable during measurement phase:
M.med_thres = median (M.VARS(M.measurement_fidx)); % THIS is defined as threshold by default
M.mean_thres = mean (M.VARS(M.measurement_fidx)); % THIS can be defined as threshold, see below
M.std_thres = std (M.VARS(M.measurement_fidx));
M.min_thres = min (M.VARS(M.measurement_fidx));
M.max_thres = max (M.VARS(M.measurement_fidx));
% for plotting in mpsy_plot_feedback we also need these indices
M.familiarization_fidx = find(M.STEPS ~= M.MINSTEP);
% Now output all relevant information to a text protocol file
% this is done in the psydat format version 3
%
% N.B. the order of the information in the following output DOES matter,
% as read_psydat.m and psydat_helper.m rely on it.
%
[fidm,message] = fopen( ['psydat_',M.SNAME], 'a' );
fprintf(fidm,'##adapt## %s %s %s__%s npar %d ####\n', ...
M.EXPNAME, M.SNAME, datestr(now,1), datestr(now,13), M.NUM_PARAMS);
for k=1:M.NUM_PARAMS,
fprintf(fidm,'%%%%----- PAR%d: %s %f %s\n', k, char(M.PARAMNAME(k)), M.PARAM(k), char(M.PARAMUNIT(k)));
end
% output the information about the adaptive method used
fprintf(fidm, '%%%%----- ADAPT:');
fprintf(fidm,' %s', M.ADAPT_METHOD);
if isfield(M, 'PC_CONVERGE'),
fprintf(fidm,' %.4f \n', M.PC_CONVERGE);
else
fprintf(fidm,' \n');
end
% if flag-variable M.SAVERUN has been set accordingly, output the
% individual values of M.VAR and the answers to the psydat file.
if (isfield(M, 'SAVERUN')) & M.SAVERUN == 1
fprintf(fidm, '%%%%----- VAL:');
for k = 1:length(M.ANSWERS)
fprintf(fidm, ' %g %d', M.VARS(k), M.ANSWERS(k));
end
fprintf(fidm, '\n');
end
if (isfield(M, 'SAVEMEAN')) & M.SAVEMEAN == 1
fprintf(fidm,' %s %f %f %f %f %s\n', ...
M.VARNAME, M.mean_thres, M.std_thres, M.min_thres, M.max_thres, M.VARUNIT);
else
fprintf(fidm,' %s %f %f %f %f %s\n', ...
M.VARNAME, M.med_thres, M.std_thres, M.min_thres, M.max_thres, M.VARUNIT);
end
fclose(fidm);
% ------------------------------------------------------------
% add new values pertaining to last run to the collection of
% parameters and thresholds: lowercase variable names are used to
% show that these do not contain user-specified values
% add this run's median threshold value (median of M_VAR during measurement phase
% of last run) to collection
if ~isfield(M, 'allthres_med'),
% hm, this seems to be the first completed run during this experiment
M.allthres_med = M.med_thres ;
else
% append a row
M.allthres_med = [ M.allthres_med; M.med_thres ];
end
% add this run's mean threshold value (mean of M_VAR during measurement phase
% of last run) to collection
if ~isfield(M, 'allthres_mean'),
% hm, this seems to be the first completed run during this experiment
M.allthres_mean = M.mean_thres ;
else
% append a row
M.allthres_mean = [ M.allthres_mean; M.mean_thres ];
end
% add this threshold's standard deviation (std.dev. of M_VAR during
% measurement phase of last run) to collection
if ~isfield(M, 'allthres_std'),
% hm, this seems to be the first completed run during this experiment
M.allthres_std = M.std_thres ;
else
% append a row
M.allthres_std = [ M.allthres_std; M.std_thres ];
end
% add the set of values of all parameters of the current run, as a
% row vector, to the collection of parameter sets (of all runs)
if ~isfield(M, 'allparam'),
% hm, this seems to be the first completed run during this experiment
M.allparam = M.PARAM(:).'; % force a ROW shape
else
% different values of the same parameter from different runs form
% a column, so there will be M.NUM_PARAMS columns in M.ALLPARAM
M.allparam = [ M.allparam; M.PARAM(:).' ]; % append a row
end
if M.DEBUG>0,
mpsy_proto_debuginfo;
end
%
if M.FEEDBACK,
fprintf(' Result: Parameter (%s): %g %s,\n', ...
char(M.PARAMNAME(1)), M.PARAM(1), char(M.PARAMUNIT(1)));
for k=2:M.NUM_PARAMS,
fprintf(' Param.%d (%s): %g %s,\n', ...
k, char(M.PARAMNAME(k)), M.PARAM(k), char(M.PARAMUNIT(k)));
end
fprintf(' Threshold (%s) Median: %g %s, STD: %g %s \n\n', ...
M.VARNAME, M.med_thres, M.VARUNIT, M.std_thres, M.VARUNIT);
end
% End of file: mpsy_proto_adapt.m
% Local Variables:
% time-stamp-pattern: "40/Updated: <%2d %3b %:y %02H:%02M, %u>"
% End: