Index: /issm/trunk-jpl/src/m/classes/qmu/histogram_bin_uncertain.m =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/histogram_bin_uncertain.m (revision 25221) +++ /issm/trunk-jpl/src/m/classes/qmu/histogram_bin_uncertain.m (revision 25222) @@ -1,62 +1,72 @@ %HISTOGRAM BIN UNCERTAIN class definition % -% [hbu]=histogram_bin_uncertain(varargin) +% Usage: +% hbu=histogram_bin_uncertain('descriptor',descriptor,'pairs_per_variable',pairs_per_variable,... +% 'abscissas',abscissas,'counts',counts,'partition',partition) +% +% where hbu is the histogram_bin_uncertain object returned by the constructor, pairs_per_variable the +% size of the histogram, 'abscissas' and 'counts' describe the histogram itself. +% If the variable is distributed, then a partition vector can be supplied, which can be a +% partition vector over elements or vertices. In which case counts, % -% where the required varargin are: -% descriptor (char, description, '') -% pairs_per_variable (double vector, []) -% abscissas (double vector, []) -% counts (int vector, []) -% -% NOTE: A call to the constructor with zero arguments will return a default -% instance; one argument of the class copies the instance; three or more -% arguments constructs a new instance from the arguments. -% +% Example: +% md.qmu.variables.giaid=histogram_bin_uncertain('descriptor','GiammeModelId','pairs_per_variable',3,... +% 'count',[.6 .4 0],''abscissas',[1 2 3]); +% md.qmu.variables.surfaceloadid=histogram_bin_uncertain(... +% 'descriptor','distributed_SurfaceloadModelId','pairs_per_variable',[2 3 4],... +% 'counts',{[1 0],[.6 .4 0],[.4 .4 .2 0]},... +% 'abscissas',{[1 2],[1 2 3],[1 2 3 4]},... +% 'partition',partition_vector); + classdef histogram_bin_uncertain properties descriptor=''; - pairs_per_variable=[]; - abscissas = []; + pairs_per_variable={}; + abscissas = {}; counts = []; + partition=[]; end methods - function [hbu]=histogram_bin_uncertain(varargin) % {{{ - switch nargin - case 0 % create a default object - case 1 % copy the object - if isa(varargin{1},'histogram_bin_uncertain') - hbu=varargin{1}; - else - error('Object ''%s'' is a ''%s'' class object, not ''%s''.',... - inputname(1),class(varargin{1}),'histogram_bin_uncertain'); - end - case {2,3} % not enough arguments - error('Construction of ''histogram_bin_uncertain'' class object requires at least %d inputs.',4) - case 4 % - % create the object from the input - hbu = histogram_bin_uncertain; - hbu.descriptor=varargin{1}; - hbu.pairs_per_variable=varargin{2}; - hbu.abscissas=varargin{3}; - hbu.counts=varargin{4}; + function self=histogram_bin_uncertain(varargin) % {{{ + + %recover options: + options=pairoptions(varargin{:}); - otherwise - error('Construction of histogram_bin_uncertain class object requires either (1) no arguments, (2) a histogram_bin_uncertain instance to copy from, or (3) a descriptor and pairs per variable, abscissas, and counts lists'); + %initialize fields: + self.descriptor=getfieldvalue(options,'descriptor'); + self.pairs_per_variable=getfieldvalue(options,'pairs_per_variable'); + self.abscissas=getfieldvalue(options,'abscissas'); + self.counts=getfieldvalue(options,'counts'); + + %if the variable is distributed, a partition vector should have been + %supplied, and that partition vector should have as many partitions + %as the pairs_per_variable, abscissas and counts arrays: + if self.isdistributed(), + self.partition=getfieldvalue(options,'partition'); + npart=qmupart2npart(self.partition); + if npart~=length(self.pairs_per_variable), + error(sprintf('histogram_bin_uncertain constructor: for the distributed variable %s the number of pairs_per_variable arrays (%i) should be equal to the number of partitions (%i)',self.descriptor,length(self.pairs_per_variable),npart)); + end + if npart~=length(self.abscissas), + error(sprintf('histogram_bin_uncertain constructor: for the distributed variable %s the number of abscissas arrays (%i) should be equal to the number of partitions (%i)',self.descriptor,length(self.abscissas),npart)); + end + if npart~=length(self.counts), + error(sprintf('histogram_bin_uncertain constructor: for the distributed variable %s the size of counts (%i) should be equal to the number of partitions (%i)',self.descriptor,length(self.counts),npart)); + end end end % }}} function md=checkconsistency(self,md,solution,analyses) % {{{ end % }}} - function []=disp(hbu) % {{{ - % display the object - disp(sprintf('\n')); - for i=1:numel(hbu) - disp(sprintf('class ''%s'' object ''%s%s'' = \n',... - class(hbu),inputname(1),string_dim(hbu,i))); - disp(sprintf(' descriptor: ''%s''' ,hbu(i).descriptor)); - disp(sprintf(' pairs_per_variable: %g' ,hbu(i).pairs_per_variable)); - disp(sprintf(' abscissas: %g' ,hbu(i).abscissas)); - disp(sprintf(' counts: %g' ,hbu(i).counts)); - end - end % }}} + function disp(self) % {{{ + disp(sprintf(' histogram_bin uncertain variable: ')); + fielddisplay(self,'descriptor','name tag'); + fielddisplay(self,'pairs_per_variable','number of bins in histogram'); + fielddisplay(self,'abscissas','abscissas for histogram'); + fielddisplay(self,'counts','probabilities for histogram'); + if ~isempty(self.partition), + fielddisplay(self,'partition','partition vector defining where sampling will occur'); + end + end + %}}} %virtual functions needed by qmu processing algorithms: %implemented: @@ -88,22 +98,21 @@ upper=[]; end % }}} + function [pairs_per_variable] =prop_pairs_per_variable(hbu) % {{{ + pairs_per_variable=[]; + for i=1:numel(hbu) + pairs_per_variable=[pairs_per_variable hbu(i).pairs_per_variable]; + end + end % }}} function [abscissas]=prop_abscissas(hbu) % {{{ abscissas=[]; for i=1:numel(hbu) - abscissas=[abscissas hbu(i).abscissas]; + abscissas=[abscissas hbu(i).abscissas']; end abscissas=allequal(abscissas,-Inf); end % }}} - function [pairs_per_variable] =prop_pairs_per_variable(hbu) % {{{ - pairs_per_variable=zeros(1,numel(hbu)); - for i=1:numel(hbu) - pairs_per_variable(i)=hbu(i).pairs_per_variable; - end - pairs_per_variable=allequal(pairs_per_variable,-Inf); - end % }}} function [counts] =prop_counts(hbu) % {{{ counts=[]; for i=1:numel(hbu) - counts=[counts hbu(i).counts]; + counts=[counts hbu(i).counts']; end counts=allequal(counts,-Inf); @@ -128,4 +137,11 @@ end end % }}} + function distributed=isdistributed(self) % {{{ + if strncmp(self.descriptor,'distributed_',12), + distributed=1; + else + distributed=0; + end + end % }}} end methods (Static) Index: /issm/trunk-jpl/src/m/classes/qmu/normal_uncertain.m =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/normal_uncertain.m (revision 25221) +++ /issm/trunk-jpl/src/m/classes/qmu/normal_uncertain.m (revision 25222) @@ -161,5 +161,12 @@ end % }}} %new methods: - function scaled=isscaled(self) % {{{ + function distributed=isdistributed(self) % {{{ + if strncmp(self.descriptor,'distributed_',12), + distributed=1; + else + distributed=0; + end + end % }}} + function scaled=isscaled(self) % {{{ if strncmp(self.descriptor,'scaled_',7), scaled=1; Index: /issm/trunk-jpl/src/m/classes/qmu/uniform_uncertain.m =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu/uniform_uncertain.m (revision 25221) +++ /issm/trunk-jpl/src/m/classes/qmu/uniform_uncertain.m (revision 25222) @@ -164,5 +164,12 @@ end % }}} %new methods: - function scaled=isscaled(self) % {{{ + function distributed=isdistributed(self) % {{{ + if strncmp(self.descriptor,'distributed_',12), + distributed=1; + else + distributed=0; + end + end % }}} + function scaled=isscaled(self) % {{{ if strncmp(self.descriptor,'scaled_',7), scaled=1;