Mercurial > hg > emotion-detection-top-level
view Code/Collation/basicMetricSet.m @ 3:e1cfa7765647
initial commit - this file calculates the basic set of metrics (mean, variance, min and max, from an array of supplied data.
author | Dawn Black <dawn.black@eecs.qmul.ac.uk> |
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date | Mon, 10 Sep 2012 09:20:12 +0100 |
parents | |
children | 92ca03a8fa99 |
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function [metrics] = basicMetricSet( frameByFrameMetric, statsFileID ) % from ShahHewlitt2008 metrics = []; meanValue = mean( frameByFrameMetric ); metrics = [metrics meanValue]; fprintf( statsFileID, '\t %f ', meanValue ); % % median F0 % medianValue = median( frameByFrameMetric ); % metrics = [metrics medianValue]; % fprintf( statsFileID, '\t %f ', medianValue ); % % Standard deviation % stdValue = std( frameByFrameMetric ); % metrics = [metrics stdValue]; % fprintf( statsFileID, '\t %f ', stdValue ); % the varience seemed to make the pitch calculations worse, but I'm not % sure I am using it correctly - Dawn % Variance varValue = var(frameByFrameMetric); metrics = [metrics varValue]; fprintf( statsFileID, '\t %f ', varValue ); % Minimum minValue = min( frameByFrameMetric ); metrics = [metrics minValue]; fprintf( statsFileID, '\t %f ', minValue ); % Maximum maxValue = max( frameByFrameMetric ); metrics = [metrics maxValue]; fprintf( statsFileID, '\t %f ', maxValue ); % range % rangeValue = max( frameByFrameMetric ) - min( frameByFrameMetric ); % metrics = [metrics rangeValue]; % fprintf( statsFileID, '\t %f ', rangeValue ); end