?? mesh2d.m
字號:
% the geometry in some cases, so nodes invloved in the overlap are accepted
% to get a reasonable distribution near the edges.
[p,wndx] = project2poly(p,find(~in&ok),edgexy);
% Find the closest node in P for each FIXED node and replace P(i,:) with
% FIXED(i,:)
fix = zeros(size(fixed,1),1);
for k = 1:size(ndx,1)
x = fixed(k,1);
y = fixed(k,2);
if isnan(ndx(k))
% Slow search for all p(ok,:)
[tmp,tmp] = min( (p(ok,1)-x).^2+(p(ok,2)-y).^2 );
fix(k) = tmp;
else
% Search nodes in ndx(k)
d = inf;
j = 1;
while j<=3
cn = t(ndx(k),j);
if ok(cn)
dkj = (p(cn,1)-x)^2+(p(cn,2)-y)^2;
if dkj<d
fix(k) = cn;
d = dkj;
end
end
j = j+1;
end
end
if fix(k)==0
% Slow search for all p(ok,:)
[tmp,tmp] = min( (p(ok,1)-x).^2+(p(ok,2)-y).^2 );
fix(k) = tmp;
end
end
p(fix,:) = fixed;
% Take internal nodes
p = p(ok,:);
% Re-index to keeps lists consistent
wndx = wndx(ok);
j = zeros(length(ok),1);
j(ok) = 1;
j = cumsum(j);
t = j(t(tin,:));
fix = j(fix);
tndx = zeros(size(p,1),1);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [e,bnd] = getedges(t,n)
% Get the unique edges and boundary nodes in a triangulation.
e = [t(:,[1,2]); t(:,[1,3]); t(:,[2,3])]; % Non-unique edges
swap = e(:,2)<e(:,1); % Ensure e(:,1) contains the lower value
e(swap,:) = e(swap,[2,1]);
e = sortrows(e);
idx = all(diff(e,1)==0,2); % Find shared edges
idx = [idx;false]|[false;idx]; % True for all shared edges
bnde = e(~idx,:); % Boundary edges
e = e(idx,:); % Internal edges
e = [bnde; e(1:2:end-1,:)]; % Unique edges and bnd edges for tri's
bnd = false(n,1); % True for boundary nodes
bnd(bnde) = true;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [p,ndxnew] = project2poly(p,bnd,edgexy,ndx)
% Project the points in P(BND) onto the closest edge of the polygon defined
% by the edge segments in EDGEXY. NDX is an optional argument defining
% the edge to project onto: P(BND) is projected onto EDGEXY(NDX(BND)).
% Uses (something like?) a double sweep-line approach to reduce the number
% of edges that are required to be tested in order to determine the closest
% edge for each point. On average only size(EDGEXY)/4 comparisons need to
% be made for each point.
if nargin<4 || isempty(ndx)
ndx = zeros(size(p,1),1);
end
ndxnew = zeros(size(p,1),1);
todo = true(size(bnd));
% Check NDX first
for k = 1:length(bnd)
cn = bnd(k);
if ndx(cn)>0
j = ndx(cn);
x1 = edgexy(j,1); x2mx1 = edgexy(j,3)-x1;
y1 = edgexy(j,2); y2my1 = edgexy(j,4)-y1;
r = ((p(cn,1)-x1)*x2mx1+(p(cn,2)-y1)*y2my1)/(x2mx1^2+y2my1^2);
if (r>0) && (r<1)
todo(k) = false;
p(cn,1) = x1+r*x2mx1;
p(cn,2) = y1+r*y2my1;
ndxnew(cn) = j;
end
end
end
% Do a full search for points not already projected
if any(todo)
bnd = bnd(todo);
% Choose the direction with the biggest range as the "y-coordinate" for the
% test. This should ensure that the sorting is done along the best
% direction for long and skinny problems wrt either the x or y axes.
dxy = max(p)-min(p);
if dxy(1)>dxy(2)
% Flip co-ords if x range is bigger
p = p(:,[2,1]);
edgexy = edgexy(:,[2,1,4,3]);
flip = true;
else
flip = false;
end
% Ensure edgexy(:,[1,2]) contains the lower y value
swap = edgexy(:,4)<edgexy(:,2);
edgexy(swap,:) = edgexy(swap,[3,4,1,2]);
% Sort edges
[ilower,ilower] = sort(edgexy(:,2)); % Sort edges by lower y value
edgexy_lower = edgexy(ilower,:);
[iupper,iupper] = sort(edgexy(:,4)); % Sort edges by upper y value
edgexy_upper = edgexy(iupper,:);
% Mean edge y value
ne = size(edgexy,1);
ymean = 0.5*( sum(sum(edgexy(:,[2,4]))) )/ne;
% Loop through points
for k = 1:length(bnd)
cn = bnd(k);
x = p(cn,1);
y = p(cn,2);
d = inf;
if y<ymean
% Loop through edges bottom up
for j = 1:ne
y2 = edgexy_lower(j,4);
if y2>=(y-d)
y1 = edgexy_lower(j,2);
if y1<=(y+d)
% Calculate the distance along the normal projection from [x,y] to the jth edge
x1 = edgexy_lower(j,1);
x2mx1 = edgexy_lower(j,3)-x1;
y2my1 = y2-y1;
r = ((x-x1)*x2mx1+(y-y1)*y2my1)/(x2mx1^2+y2my1^2);
if r>1 % Limit to wall endpoints
r = 1;
elseif r<0
r = 0;
end
xn = x1+r*x2mx1;
yn = y1+r*y2my1;
dj = (xn-x)^2+(yn-y)^2;
if ( dj<d^2 )
d = sqrt(dj);
p(cn,1) = xn;
p(cn,2) = yn;
ndxnew(cn) = ilower(j);
end
else
break
end
end
end
else
% Loop through edges top down
for j = ne:-1:1
y1 = edgexy_upper(j,2);
if y1<=(y+d)
y2 = edgexy_upper(j,4);
if y2>=(y-d)
% Calculate the distance along the normal projection from [x,y] to the jth edge
x1 = edgexy_upper(j,1);
x2mx1 = edgexy_upper(j,3)-x1;
y2my1 = y2-y1;
r = ((x-x1)*x2mx1+(y-y1)*y2my1)/(x2mx1^2+y2my1^2);
if r>1 % Limit to wall endpoints
r = 1;
elseif r<0
r = 0;
end
xn = x1+r*x2mx1;
yn = y1+r*y2my1;
dj = (xn-x)^2+(yn-y)^2;
if ( dj<d^2 )
d = sqrt(dj);
p(cn,1) = xn;
p(cn,2) = yn;
ndxnew(cn) = iupper(j);
end
else
break
end
end
end
end
end
if flip
p = p(:,[2,1]);
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [mlim,maxit,dhmax,output] = getoptions(options)
% Extract the user defined options
if ~isempty(options)
if ~isstruct(options)
error('OPTIONS must be a structure array');
end
if numel(options)~=1
error('Options cannot be an array of structures');
end
fields = fieldnames(options);
names = {'mlim','maxit','dhmax','output'};
for k = 1:length(fields)
if strcmp(fields{k},names)
error('Invalid field in OPTIONS');
end
end
if isfield(options,'mlim') % Movement tolerance
mlim = checkposscalar(options.mlim,'options.mlim');
else
mlim = 0.05;
end
if isfield(options,'maxit') % Maximum iterations
maxit = round(checkposscalar(options.maxit,'options.maxit'));
else
maxit = 20;
end
if isfield(options,'dhmax') % Size function gradient limit
dhmax = checkposscalar(options.dhmax,'options.dhmax');
else
dhmax = 0.3;
end
if isfield(options,'output') % Output on/off
output = checklogicalscalar(options.output,'options.output');
else
output = true;
end
else % Default values
mlim = 0.05;
maxit = 20;
dhmax = 0.3;
output = true;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function var = checkposscalar(var,name)
% Helper function to check if var is a positive scalar.
if var<0 || any(size(var)>1)
error([name,' must be a positive scalar']);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function var = checklogicalscalar(var,name)
% Helper function to check if var is a logical scalar.
if ~islogical(var) || any(size(var)>1)
error([name,' must be a logical scalar']);
end
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