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Add logic to deduplicate complementarity vector efficiently #22

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Merged
nurkanovic merged 2 commits into from
Apr 2, 2025
Merged

Add logic to deduplicate complementarity vector efficiently #22

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8f6ba2b
Add logic to deduplicate complementarity vector efficiently
apozharski Apr 2, 2025
d17127b
Also fix mathworks breaking ind2sub backwards compatibility for seemi…
apozharski Apr 2, 2025
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46 changes: 41 additions & 5 deletions src/+mpecopt/Solver.m
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Original file line number Diff line number Diff line change
Expand Up @@ -1077,10 +1077,26 @@ function create_mpec_functions(obj)
% TODO(@anton) do we actually need this here or can we calculate these "analytically"
ind_x1 = [];
ind_x2 = [];
ind_x1_fun = Function('ind_1',{x},{x.jacobian(x1)});
% HERE BE DRAGONS: This is using some casadi internals to deduplicate x1, x2, expressions.
% Get element cell arrays.
x1_elem = x1.elements();
x2_elem = x2.elements();
% Get element hashes.
x1_hashes = cellfun(@(x) x.element_hash(), x1_elem);
x2_hashes = cellfun(@(x) x.element_hash(), x2_elem);
% Get indicies of unique elements by comparing the element hashes.
% WARNING: Technically these hashes may be nonunique but looking at how they are generated this should
% never practically be the case. If it happens though the symptoms should be obvious.
[~,x1_uniq,x1_uniq_backmap] = unique(x1_hashes, 'stable');
[~,x2_uniq,x2_uniq_backmap] = unique(x2_hashes, 'stable');
% Get indicies with jacobian trick
ind_x1_fun = Function('ind_1',{x},{x.jacobian(x1(x1_uniq))});
ind_x2_fun = Function('ind_2',{x},{x.jacobian(x2(x2_uniq))});
[ind_x1,~] = find(sparse(ind_x1_fun(zeros(size(x))))==1);
ind_x2_fun = Function('ind_2',{x},{x.jacobian(x2)});
[ind_x2,~] = find(sparse(ind_x2_fun(zeros(size(x))))==1);
% Resize indices back into correct size by mapping back the nonunique elements
ind_x1 = ind_x1(x1_uniq_backmap);
ind_x2 = ind_x2(x2_uniq_backmap);
opts.nlp_is_mpec = 1; % TODO: check is this still used? (its purpose: if not an mpec, just make single nlp call without mpec machinery);
else
opts.nlp_is_mpec = 0;
Expand Down Expand Up @@ -1205,10 +1221,26 @@ function create_mpec_functions(obj)
% TODO(@anton) do we actually need this here or can we calculate these "analytically"
ind_x1 = [];
ind_x2 = [];
ind_x1_fun = Function('ind_1',{x},{x.jacobian(x1)});
% HERE BE DRAGONS: This is using some casadi internals to deduplicate x1, x2, expressions.
% Get element cell arrays.
x1_elem = x1.elements();
x2_elem = x2.elements();
% Get element hashes.
x1_hashes = cellfun(@(x) x.element_hash(), x1_elem);
x2_hashes = cellfun(@(x) x.element_hash(), x2_elem);
% Get indicies of unique elements by comparing the element hashes.
% WARNING: Technically these hashes may be nonunique but looking at how they are generated this should
% never practically be the case. If it happens though the symptoms should be obvious.
[~,x1_uniq,x1_uniq_backmap] = unique(x1_hashes, 'stable');
[~,x2_uniq,x2_uniq_backmap] = unique(x2_hashes, 'stable');
% Get indicies with jacobian trick
ind_x1_fun = Function('ind_1',{x},{x.jacobian(x1(x1_uniq))});
ind_x2_fun = Function('ind_2',{x},{x.jacobian(x2(x2_uniq))});
[ind_x1,~] = find(sparse(ind_x1_fun(zeros(size(x))))==1);
ind_x2_fun = Function('ind_2',{x},{x.jacobian(x2)});
[ind_x2,~] = find(sparse(ind_x2_fun(zeros(size(x))))==1);
% Resize indices back into correct size by mapping back the nonunique elements
ind_x1 = ind_x1(x1_uniq_backmap);
ind_x2 = ind_x2(x2_uniq_backmap);
opts.nlp_is_mpec = 1; % TODO: check is this still used? (its purpose: if not an mpec, just make single nlp call without mpec machinery);
else
opts.nlp_is_mpec = 0;
Expand Down Expand Up @@ -1869,7 +1901,11 @@ function create_lpec_functions(obj)
X = zeros(prod(sizeThisSet),numSets);
for i=1:size(X,1)
ixVect = cell(length(sizeThisSet),1);
[ixVect{:}] = ind2sub(flip(sizeThisSet),i);
sz = flip(sizeThisSet);
if length(sz) == 1
sz = [sz,1];
end
[ixVect{:}] = ind2sub(sz,i);
ixVect = flip([ixVect{:}]);
vect = zeros(1, numSets);
for jj=1:numSets
Expand Down