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jobs_processfile_hyperbdistribution.m
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jobs_processfile_hyperbdistribution.m
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function jobs_processfile_hyperbdistribution( paramstr, ...
attributions, paramstrext, targetdir )
%JOBS_PROCESSFILE_HYPERBDISTRIBUTION loads a combined job file and stores
% data tables for proper time separation distribution in csv files (to be
% plotted with LaTeX-TikZ).
% Columns in the output files are ( radial unit hyperboloid coordinate,
% probability ).
%
% Arguments:
% PARAMSTR name of the file (without extension) to be processed.
%
% Optional arguments:
% ATTRIBUTIONS Nx4 cell array where each element is either a single
% index or a vector of indexes, which give the
% combination of location attributes.
% First cell array column: preferred future criteria
% (see CAUSET_FIND_PREFTIMES to process preferred
% future)
% 0 to process all links, not only preferred future
% (default)
% Second cell array column: criteria minima
% (see CAUSET_FIND_PREFTIMES to process preferred
% future)
% 0 to process all links, not only preferred future
% (default)
% Third cell array column: subvolumes
% 1 entire causet
% 2 one top volume layer removed
% 3 two top volume layers removed (default)
% ...
% Forth cell array column: diamond link arrangement
% (This column is ignored for preferred future
% analysis, and hence could be set to zero.)
% 1 links anywhere in the causet (default)
% 2 links along the chain from bottom to top
% 3 links along further chains to the top
% PARAMSTREXT extra name parameters for the file to be processed.
% TARGETDIR directory for processed csv file output.
% Default: data/UnitHyperboloid
%
% Copyright 2021, C. Minz. BSD 3-Clause License.
%% set default values:
if nargin < 2 || isempty( attributions )
attributions = { 0, 0, 3, 1 };
end
paramstr_load = paramstr;
if nargin >= 3 && ~isempty( paramstrext )
paramstr_load = [ paramstr_load, paramstrext ];
end
if nargin < 4 || isempty( targetdir )
targetdir = 'data/UnitHyperboloid';
end
%% load data:
results = load( jobs_getfilename( paramstr_load, 'mat' ), ...
'maxhyperbcoord', 'maxhyperbspeed' );
%% process all selected indexes:
for i = 1 : size( attributions, 1 )
for cri = attributions{ i, 1 }
for cmi = attributions{ i, 2 }
for vol = attributions{ i, 3 }
for arr = attributions{ i, 4 }
%% select data:
if cri == 0
if ~isfield( results, 'hyperbdistribution' )
temp = load( jobs_getfilename( paramstr_load, 'mat' ), ...
'hyperbdistribution' );
results.hyperbdistribution = temp.hyperbdistribution;
clear temp;
end
Y = results.hyperbdistribution( :, vol, arr );
thisparamstr = sprintf( '%sArr%dVol%d', ...
paramstr, arr, vol );
else
if ~isfield( results, 'hyperbdistribution' )
temp = load( jobs_getfilename( paramstr_load, 'mat' ), ...
'preffutures' );
results.preffutures.hyperbdistribution = ...
temp.preffutures.hyperbdistribution;
clear temp;
end
Y = results.preffutures.hyperbdistribution( :, cri, cmi, vol );
thisparamstr = sprintf( '%sCri%dMin%dVol%d', ...
paramstr, cri, cmi, vol );
end
l = length( Y ) - 2;
Xbinsize = results.maxhyperbcoord / l;
Y = transpose( double( Y( 2 : ( l + 1 ) ) ) );
X = ( 1 : l ) - 0.5;
Ysum = sum( Y );
%% save unit hyperboloid distributions to csv files:
saveas_csv( sprintf( '%s/%s', targetdir, thisparamstr ), ...
100 * Y / Ysum, Xbinsize * X );
fileID = fopen( sprintf( '%s/%sev.tex', ...
targetdir, thisparamstr ), 'w' );
fprintf( fileID, '\\def\\expectationvalue{%0.6f}\n', ...
Xbinsize * sum( Y .* X ) / Ysum );
fprintf( fileID, '\\def\\xbinwidth{%0.6f}\n', Xbinsize );
fclose( fileID );
end
end
end
end
end
end