make_summary_impls_stats_table.m

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function make_summary_impls_stats_table(s, stat_to_get, stat_to_get2, fileout, flag, ratio_metrics, round_kind, round_digits)
% % make_summary_impls_stats_table: Makes a summary table of the output of the Impulsive_Noise_Meter; Impulse, Impulsive, Noise, Sound, Meter
% %
% % Syntax:  
% % 
% % make_summary_impls_stats_table(s, stat_to_get, stat_to_get2, fileout, flag, ratio_metrics, round_kind, round_digits);
% % 
% % *****************************************************************
% %
% % Description:
% %
% % This program takes the output from the Impulsive_Noise_Meter and 
% % calc_channel_diff prorgams and prints a summary of the descriptive 
% % statistics of the metrics to a table.  Also a summary of the statistics
% % across channels and overall statistic across files is printed.
% % 
% % The Table has a format described by the summary pattern below 
% % 
% % Label stat_to_get(1) (Arithmetic Mean, Robust Mean , etc)
% % 
% %                         Metric 1                Metric 1              ...
% %                         var 1 var 2 ...var n    var 1 var 2 ...var n  ...
% % File 1          
% %        channel 1        d1    d2       dn       d1    d2       dn
% %        channel ...      ...
% %        channel m
% %    
% % ...
% %    
% % File x          
% %        channel 1        d1    d2       dn       d1    d2       dn
% %        channel ...      ...
% %        channel m
% %  
% %  
% %  Summary Across Channels  var 1 var 2 ...var n    var 1 var 2 ...var n
% %  stat_to_get2(1)   
% %  File 1                   d1    d2       dn       d1    d2       dn
% %  ...                      ...
% %  File x  
% %  
% %  ...
% %  
% %  stat_to_get2(xx)    
% %  File 1                   d1    d2       dn       d1    d2       dn
% %  ...                      ...
% %  File x  
% %  
% %  
% %  Summary Across Files    var 1 var 2 ...var n
% %  stat_to_get2(1)   
% %  File 1                   d1    d2       dn       d1    d2       dn
% %  ...                      ...
% %  File x  
% %  
% %  ...
% %  
% %  stat_to_get2(xx)    
% %  File 1                   d1    d2       dn       d1    d2       dn
% %  ...                      ...
% %  File x                          
% %  
% %  
% % ...
% %  
% %  
% % Label stat_to_get(2) (Arithmetic Mean, Robust MEan , etc)
% % 
% %                         Metric 1                Metric 1              ...
% %                         var 1 var 2 ...var n    var 1 var 2 ...var n  ...
% % File 1          
% %        channel 1        d1    d2       dn       d1    d2       dn
% %        channel ...      ...
% %        channel m
% %    
% % ...
% %    
% % File x          
% %        channel 1        d1    d2       dn       d1    d2       dn
% %        channel ...      ...
% %        channel m
% %  
% %  
% %  Summary Across Channels  var 1 var 2 ...var n    var 1 var 2 ...var n
% %  stat_to_get2(1)   
% %  File 1                   d1    d2       dn       d1    d2       dn
% %  ...                      ...
% %  File x  
% %  
% %  ...
% %  
% %  stat_to_get2(xx)    
% %  File 1                   d1    d2       dn       d1    d2       dn
% %  ...                      ...
% %  File x  
% %  
% %  
% %  Summary Across Files    var 1 var 2 ...var n
% %  stat_to_get2(1)   
% %  File 1                   d1    d2       dn       d1    d2       dn
% %  ...                      ...
% %  File x  
% %  
% %  ...
% %  
% %  stat_to_get2(xx)    
% %  File 1                   d1    d2       dn       d1    d2       dn
% %  ...                      ...
% %  File x        
% %  
% %  
% %  
% %  
% % The input and output variables are described below.
% %
% % *****************************************************************
% %
% % Input Variables
% %
% % s={}; load shock_tube;  % is the data structure created using the
% %                         % Impulsive_Noise_Meter.  
% %                         % default is load shock_tube. Runs a demo table.
% %
% % stat_to_get=1:8;        % is a vector or constant stipulating which 
% %                         % descriptive statistics to display in the
% %                         % table summarizing the metrics across the 
% %                         % impulses in a single file.   
% %                         % default is stat_to_get2=1:8; all statistics
% %
% % Any combination of the following stats can be displayed by placing the
% % index of the stat in the array stat_to_get in any desired order.
% %
% %                         % stat_to_get=1;  % Arithmetic Mean
% %                         % stat_to_get=2;  % Robust Mean
% %                         % stat_to_get=3;  % Standard Deviation
% %                         % stat_to_get=4;  % 95% Confidence Interval
% %                         % stat_to_get=5;  % Median
% %                         % stat_to_get=6;  % Median Index
% %                         % stat_to_get=7;  % Minimum
% %                         % stat_to_get=8;  % Maximum
% %
% % stat_to_get2=1:8;       % is a vector or constant stipulating which 
% %                         % descriptive statistics to display in the
% %                         % table summarizing the metrics across the files.
% %                         % These are called the overall values.
% %                         % default is stat_to_get2=1:8; all statistics
% %
% % fileout='Output_file_name.txt';
% %                         % fileout is the filenmae of the output file.
% %                         % The extension '.txt' is automatically added.
% %
% % flag=1; print absolute stats only
% % flag=2; print difference stats only
% % flag=3; print both absolute and difference stats
% % 
% %                         % if flag does not equal 1, 2, or 3 then print
% %                         % both absolute and difference stats.
% % 
% % ratio_metrics=[3, 4, 5, 20];    % is an array of indices of metrics for
% %                                 % the diff_chans array that are
% %                                 % calculated as ratios instead of
% %                                 % differences
% % 
% % round_kind=1;           % Array of values one element for the rta array
% %                         % and one element for each varargin array
% %                         % (see example)
% %                         % 1 round to specified number of significant
% %                         % digits
% %                         %
% %                         % 0 round to specified digits place
% %                         %
% %                         % default is round_kind=1;
% %
% % round_digits=3;         % Array of values one element for the rta array
% %                         % and one element for each varargin array
% %                         % (see example)% Type of rounding depends on round_kind
% %                         %
% %                         % if round_kind==1 number of significant digits
% %                         % if round_kind==0 specified digits place
% %                         %
% %                         % default is round_digits=3;
% % 
% % *****************************************************************
% 
%
% Example='1';
%
% % This is an example using shock tube data! The data compares two
% % data acquisition rates.
%
% % An example which outputs the mean of the metrics.
% 
% load shock_tube;
% stat_to_get=1;
% stat_to_get2=1;
% fileout='Compare_data_acquisition_sytems';
% flag=1;
% make_summary_impls_stats_table(s, stat_to_get, stat_to_get2, fileout, flag);
%
%
% % Example='2';
%
% % An example which outputs all of the metrics.
%
% load shock_tube;
% stat_to_get=[1:8];    % return all of the stats, from Arithmetic mean 
%                       % to maximum!
% stat_to_get2=[1:8];   % return all of the stats, from Arithmetic mean 
%                       % to maximum!
% 
% fileout='Compare_data_acquisition_sytems2';
% flag=3;
% make_summary_impls_stats_table(s, stat_to_get, stat_to_get2, fileout, flag);
%
%
% % *****************************************************************
% %
% % 
% % Subprograms
% % 
% % 
% % 
% % List of Dependent Subprograms for 
% % make_summary_impls_stats_table
% % 
% % 
% % Program Name   Author   FEX ID#
% %  1) file_extension		
% %  2) genHyper		Ben Barrowes		6218	
% %  3) LMSloc		Alexandros Leontitsis		801	
% %  4) m_round		
% %  5) num_impulsive_samples		
% %  6) pow10_round		
% %  7) print_channel_stats		
% %  8) print_overall_stats		
% %  9) sd_round		
% % 10) splat_cell		
% % 11) t_alpha		
% % 12) t_confidence_interval		
% % 13) t_icpbf		
% % 
% % 
% % 
% % *****************************************************************
% % 
% % Written by Edward L. Zechmann
% %  
% %     date  6 August      2008
% %  
% % modified  9 August      2008    Vectrorized stat_to_get. 
% %                                 Updated comments.
% %  
% % modified 10 August      2008    Updated comments.
% %  
% % modified  1 September   2008    Added print_channel_stats and
% %                                 print_overall_stats to the program 
% %                                 which greatly improved its
% %                                 usefulness.
% %  
% % modified 10 September   2008    Updated comments.
% % 
% % modified 10 December    2008    Updated comments.
% % 
% % modified  7 January     2009    Updated comments.
% % 
% % modified 19 January     2009    Updated to include rounding. 
% %
% % 
% % *****************************************************************
% % 
% % Please feel free to modify this code.
% %
% % See Also:  Main_Sound, Impulsive_Noise_Meter, Main_sound_and_vibs, Continuous_Sound_and_Vibrations_Analysis
% %


if (nargin < 1 || isempty(s)) || ~iscell(s)
    s={}; 
    load shock_tube;
end

if (nargin < 2 || isempty(stat_to_get)) || ~isnumeric(stat_to_get)
    stat_to_get=[1:8];
end

if (nargin < 3 || isempty(stat_to_get2)) || ~isnumeric(stat_to_get2)
    stat_to_get2=[1:8];
end

if (nargin < 4 || isempty(fileout)) || ~ischar(fileout)
    fileout='Output_file_name.txt';
end

if (nargin < 5 || isempty(flag)) || ~isnumeric(flag)
    flag=3; 
end

if (nargin < 6 || isempty(ratio_metrics)) || ~isnumeric(ratio_metrics)
    ratio_metrics=[3, 4, 5]; 
end

if (nargin < 7 || isempty(round_kind)) || ~isnumeric(round_kind)
    round_kind=1; 
end

if (nargin < 8 || isempty(round_digits)) || ~isnumeric(round_digits)
    round_digits=3; 
end




[num_files, num_vars]=size(s);
num_channels_array=zeros(num_files,1);
num_stats=length(stat_to_get);
sum_num_channels_a=zeros(num_files, num_vars);
num_channels_a=zeros(num_files, num_vars);
num_diff_channels_a=zeros(num_files, num_vars);

[num_samples_ca]=num_impulsive_samples(s);



% Determine the size of the concatenated metrics table
for e1=1:num_files;    % Data files

    num_channels=[];

    % Number of Variables (Number of Data Acquisition Systems)
    for e3=1:num_vars; 

        if ~isempty(s{e1,e3})

            num_channels=0;
            num_stats2=0;

            if isfield(s{e1,e3}, 'stats_of_metrics')
                [num_metrics, num_channels, num_stats2]=size(s{e1,e3}.stats_of_metrics);
            end

            num_diff_channels=0;
            num_diff_stats2=0;

            if isfield(s{e1,e3}, 'diff_stats_of_metrics')
                [num_metrics, num_diff_channels, num_diff_stats2]=size(s{e1,e3}.diff_stats_of_metrics);
            end

            if num_channels >= 1 || logical(num_diff_channels >= 1)

                switch flag
                    case 1
                        num_channels_a(e1, e3)=num_channels;
                        num_diff_channels_a(e1, e3)=0;
                        sum_num_channels_a(e1, e3)=num_channels;
                        num_channels_array(e1)=max([num_channels, num_channels_array(e1)]);
                    case 2
                        num_channels_a(e1, e3)=0;
                        num_diff_channels_a(e1, e3)=num_diff_channels;