Changeset 25222

Timestamp:

07/06/20 20:09:46 (5 years ago)

Author:

Eric.Larour

Message:

CHG: handle partitions for histogram_bin_uncertain variables.

Location:

issm/trunk-jpl/src/m/classes/qmu

Files:

• histogram_bin_uncertain.m (modified) (3 diffs)
• normal_uncertain.m (modified) (1 diff)
• uniform_uncertain.m (modified) (1 diff)

issm/trunk-jpl/src/m/classes/qmu/histogram_bin_uncertain.m

@@ -1 +1 @@
 %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 +98 @@
             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 +137 @@
                         end
                 end % }}}
+                function distributed=isdistributed(self) % {{{
+                        if strncmp(self.descriptor,'distributed_',12),
+                                distributed=1;
+                        else
+                                distributed=0;
+                        end
+                end % }}}
         end
     methods (Static)

issm/trunk-jpl/src/m/classes/qmu/normal_uncertain.m

@@ -161 +161 @@
                 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;

issm/trunk-jpl/src/m/classes/qmu/uniform_uncertain.m

@@ -164 +164 @@
                 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;