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Removes tabs, use algorithm section
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@sjoelund @OpenModelica-Hudson
sjoelund authored and OpenModelica-Hudson committed Dec 13, 2016
1 parent fdb6f8f commit d60d7e6
Showing 1 changed file with 43 additions and 42 deletions.
85 changes: 43 additions & 42 deletions Compiler/BackEnd/SymbolicJacobian.mo
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Expand Up @@ -1114,25 +1114,25 @@ algorithm
// is an empty pattern for the dependent variables
case (_,_,{}) then (({},{},({},{}),-1),{});
case(BackendDAE.DAE(eqs = (syst as BackendDAE.EQSYSTEM(matching=bdaeMatching as BackendDAE.MATCHING(comps=comps, ass1=ass1)))::{}),independentVars,dependentVars)
equation
algorithm
if Flags.isSet(Flags.DUMP_SPARSE_VERBOSE) then
print(" start getting sparsity pattern for variables : " + intString(listLength(dependentVars)) + " and the independent vars: " + intString(listLength(independentVars)) +"\n");
end if;
if debug then execStat("generateSparsePattern -> do start "); end if;
// prepare crefs
depCompRefsLst = List.map(dependentVars, BackendVariable.varCref);
inDepCompRefsLst = List.map(independentVars, BackendVariable.varCref);
depCompRefs = listArray(depCompRefsLst);
inDepCompRefs = listArray(inDepCompRefsLst);
depCompRefsLst := List.map(dependentVars, BackendVariable.varCref);
inDepCompRefsLst := List.map(independentVars, BackendVariable.varCref);
depCompRefs := listArray(depCompRefsLst);
inDepCompRefs := listArray(inDepCompRefsLst);
// create jacobian vars
jacDiffVars = list(BackendVariable.createpDerVar(v) for v in independentVars);
sizeN = arrayLength(inDepCompRefs);
jacDiffVars := list(BackendVariable.createpDerVar(v) for v in independentVars);
sizeN := arrayLength(inDepCompRefs);

// generate adjacency matrix including diff vars
(syst1 as BackendDAE.EQSYSTEM(orderedVars=varswithDiffs,orderedEqs=orderedEqns)) = BackendDAEUtil.addVarsToEqSystem(syst,jacDiffVars);
(adjMatrix, adjMatrixT) = BackendDAEUtil.incidenceMatrix(syst1,BackendDAE.SPARSE(),NONE());
adjSize = arrayLength(adjMatrix) "number of equations";
adjSizeT = arrayLength(adjMatrixT) "number of variables";
(syst1 as BackendDAE.EQSYSTEM(orderedVars=varswithDiffs,orderedEqs=orderedEqns)) := BackendDAEUtil.addVarsToEqSystem(syst,jacDiffVars);
(adjMatrix, adjMatrixT) := BackendDAEUtil.incidenceMatrix(syst1,BackendDAE.SPARSE(),NONE());
adjSize := arrayLength(adjMatrix) "number of equations";
adjSizeT := arrayLength(adjMatrixT) "number of variables";

// Debug dumping
if Flags.isSet(Flags.DUMP_SPARSE_VERBOSE) then
Expand All @@ -1144,8 +1144,8 @@ algorithm
end if;

// get indexes of diffed vars (rows)
nodesEqnsIndex = BackendVariable.getVarIndexFromVars(dependentVars,varswithDiffs);
nodesEqnsIndex = List.map1(nodesEqnsIndex, Array.getIndexFirst, ass1);
nodesEqnsIndex := BackendVariable.getVarIndexFromVars(dependentVars,varswithDiffs);
nodesEqnsIndex := List.map1(nodesEqnsIndex, Array.getIndexFirst, ass1);

// debug dump
if Flags.isSet(Flags.DUMP_SPARSE_VERBOSE) then
Expand All @@ -1156,19 +1156,19 @@ algorithm
end if;

// prepare data for getSparsePattern
eqnSparse = arrayCreate(adjSize, {});
varSparse = arrayCreate(adjSizeT, {});
mark = arrayCreate(adjSizeT, 0);
usedvar = arrayCreate(adjSizeT, 0);
eqnSparse := arrayCreate(adjSize, {});
varSparse := arrayCreate(adjSizeT, {});
mark := arrayCreate(adjSizeT, 0);
usedvar := arrayCreate(adjSizeT, 0);

// make dependent variables as used if there are some
// otherwise Array.setRange fails start is greater than end
if (sizeN>0) then
usedvar = Array.setRange(adjSizeT-(sizeN-1), adjSizeT, usedvar, 1);
usedvar := Array.setRange(adjSizeT-(sizeN-1), adjSizeT, usedvar, 1);
end if;

if debug then execStat("generateSparsePattern -> start "); end if;
eqnSparse = getSparsePattern(comps, eqnSparse, varSparse, mark, usedvar, 1, adjMatrix, adjMatrixT);
eqnSparse := getSparsePattern(comps, eqnSparse, varSparse, mark, usedvar, 1, adjMatrix, adjMatrixT);
if debug then execStat("generateSparsePattern -> end "); end if;
// debug dump
if Flags.isSet(Flags.DUMP_SPARSE_VERBOSE) then
Expand All @@ -1177,18 +1177,19 @@ algorithm
end if;

// select nodesEqnsIndex and map index to incoming vars
sparseArray = Array.select(eqnSparse, nodesEqnsIndex);
sparsepattern = arrayList(sparseArray);
sparsepattern = List.map1List(sparsepattern, intSub, adjSizeT-sizeN);
sparseArray = listArray(sparsepattern);
sparseArray := Array.select(eqnSparse, nodesEqnsIndex);
sparsepattern := arrayList(sparseArray);

sparsepattern := List.map1List(sparsepattern, intSub, adjSizeT-sizeN);
sparseArray := listArray(sparsepattern);

if debug then execStat("generateSparsePattern -> postProcess "); end if;

// transpose the column-based pattern to row-based pattern
sparseArrayT = arrayCreate(sizeN,{});
sparseArrayT = transposeSparsePattern(sparsepattern, sparseArrayT, 1);
sparsepatternT = arrayList(sparseArrayT);
nonZeroElements = List.lengthListElements(sparsepattern);
sparseArrayT := arrayCreate(sizeN,{});
sparseArrayT := transposeSparsePattern(sparsepattern, sparseArrayT, 1);
sparsepatternT := arrayList(sparseArrayT);
nonZeroElements := List.lengthListElements(sparsepattern);
if debug then execStat("generateSparsePattern -> transpose done "); end if;

if Flags.isSet(Flags.DUMP_SPARSE_VERBOSE) then
Expand All @@ -1200,27 +1201,27 @@ algorithm
end if;

// translated to DAE.ComRefs
translated = list(list(arrayGet(inDepCompRefs, i) for i in lst) for lst in sparsepattern);
sparsetuple = list((cr,t) threaded for cr in depCompRefs, t in translated);
translated = list(list(arrayGet(depCompRefs, i) for i in lst) for lst in sparsepatternT);
sparsetupleT = list((cr,t) threaded for cr in inDepCompRefs, t in translated);
translated := list(list(arrayGet(inDepCompRefs, i) for i in lst) for lst in sparsepattern);
sparsetuple := list((cr,t) threaded for cr in depCompRefs, t in translated);
translated := list(list(arrayGet(depCompRefs, i) for i in lst) for lst in sparsepatternT);
sparsetupleT := list((cr,t) threaded for cr in inDepCompRefs, t in translated);

if debug then execStat("generateSparsePattern -> coloring start "); end if;
if not Flags.isSet(Flags.DISABLE_COLORING) then
// get coloring based on sparse pattern
coloredArray = createColoring(sparseArray, sparseArrayT, sizeN, adjSize);
coloring = list(list(arrayGet(inDepCompRefs, i) for i in lst) for lst in coloredArray);
coloredArray := createColoring(sparseArray, sparseArrayT, sizeN, adjSize);
coloring := list(list(arrayGet(inDepCompRefs, i) for i in lst) for lst in coloredArray);
else
//without coloring
coloring = list({arrayGet(inDepCompRefs, i)} for i in 1:sizeN);
coloring := list({arrayGet(inDepCompRefs, i)} for i in 1:sizeN);
end if;
if debug then execStat("generateSparsePattern -> coloring done "); end if;

if Flags.isSet(Flags.DUMP_SPARSE_VERBOSE) then
print("analytical Jacobians[SPARSE] -> ready! " + realString(clock()) + "\n");
end if;

outSparsePattern = (sparsetupleT, sparsetuple, (inDepCompRefsLst, depCompRefsLst), nonZeroElements);
outSparsePattern := (sparsetupleT, sparsetuple, (inDepCompRefsLst, depCompRefsLst), nonZeroElements);
if Flags.isSet(Flags.DUMP_SPARSE) then
BackendDump.dumpSparsityPattern(outSparsePattern, " --- SparsityPattern ---");
BackendDump.dumpSparseColoring(coloring, " --- Sparsity Coloring ---");
Expand Down Expand Up @@ -2538,13 +2539,13 @@ algorithm
end if;

if (not onlySparsePattern) then
eqns = BackendEquation.listEquation(reqns);
// create residual equations
reqns = BackendEquation.traverseEquationArray(eqns, BackendEquation.traverseEquationToScalarResidualForm, {});
reqns = listReverse(reqns);
(reqns, resVarsLst) = BackendEquation.convertResidualsIntoSolvedEquations(reqns, "$res", BackendVariable.makeVar(DAE.emptyCref), 1);
resVars = BackendVariable.listVar1(resVarsLst);
resEqns = BackendEquation.listEquation(reqns);
eqns = BackendEquation.listEquation(reqns);
// create residual equations
reqns = BackendEquation.traverseEquationArray(eqns, BackendEquation.traverseEquationToScalarResidualForm, {});
reqns = listReverse(reqns);
(reqns, resVarsLst) = BackendEquation.convertResidualsIntoSolvedEquations(reqns, "$res", BackendVariable.makeVar(DAE.emptyCref), 1);
resVars = BackendVariable.listVar1(resVarsLst);
resEqns = BackendEquation.listEquation(reqns);
else
resVars = diffVars;
resEqns = BackendEquation.listEquation(reqns);
Expand Down

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