K itemAtIndex(K a, I i) { // Return i-th item from any type as K - TODO: oom wherever this is used
I at=a->t;
if( 0< at)R ci(a);
if(-4==at)R Ks(kS(a)[i]); //could refactor all this
if(-3==at)R Kc(kC(a)[i]);
if(-2==at)R Kf(kF(a)[i]);
if(-1==at)R Ki(kI(a)[i]);
R ci(kK(a)[i]);
}
static PyObject*
_get_Kf(PyObject* self, PyObject* ko)
{
K kobj;
int ok;
ok = ko && IS_K(ko);
if (!ok) goto fail;
kobj = ((_K*)ko)->kobj;
if (kobj && kobj->t == 2) {
double f = Kf(kobj);
return Py_BuildValue("f", f);
}
fail:
PyErr_BadArgument();
return NULL;
}
static PyObject*
_set_Kf(PyObject* self, PyObject* args)
{
PyObject* ko;
double f;
if (PyArg_ParseTuple(args, "O!d", &_KType, &ko, &f)) {
K k = ((_K*)ko)->kobj;
if (k && k->t == 2) {
Kf(k) = f;
Py_INCREF(ko);
return ko;
} else {
PyErr_SetString(PyExc_TypeError, "wrong k type");
return NULL;
}
}
PyErr_BadArgument();
return NULL;
}
vector< SingleReactionData > Make_Irreversible(
vector< SingleReactionData > Reactions,
const vector< ThermodynamicData > Thermodynamics,
double Initial_Temperature, /// use initial temperature from initial data
double Range // specify +/- rang around initial temperature
)
{
/* 2002 CODATA values */
//double R = 8.314472e0; // Ea is internally given in Kelvin, therefore R is not needed
vector< SingleReactionData > Irreversible_Scheme;
int i,j,k;
int Number_Species = (int)Thermodynamics.size();
int Number_Reactions = (int)Reactions.size();
double Temperature;
vector< double > Local_Delta_N = Get_Delta_N(Reactions);
// check temperature and range provided, else use default
if(Initial_Temperature == 0)
{
Initial_Temperature = 298.15;
}
if(Range == 0)
{
Range = 25;
}
// check we don't end up below 0K
if(Initial_Temperature - Range <= 0)
{
Range = Initial_Temperature - 1;
}
vector< ReactionParameter > LocalReactionParameters;
vector< TrackSpecies > LocalReactantsForReactions;
vector< TrackSpecies > LocalProductsForReactions;
vector< TrackSpecies > LocalSpeciesLossAll;
LocalReactionParameters = Process_Reaction_Parameters(Reactions);
LocalReactantsForReactions = Reactants_ForReactionRate(Reactions);
LocalProductsForReactions = Products_ForReactionRate(Reactions,false);
LocalSpeciesLossAll = PrepareSpecies_ForSpeciesLoss(Reactions);
// Local copy of the global version. Needed to work out rate constants, but are based on data in Reactions array
vector< vector< double > > allkreverse;
vector< vector< double > > SensitivityMatrix; // called X in the paper
vector< double > OneTempSensitivityMatrix;
OneTempSensitivityMatrix.resize(3);
vector< CalculatedThermodynamics > CalculatedThermo(Number_Species);
vector< double > Kf(Number_Reactions) ;
vector< double > Kr(Number_Reactions) ;
// let us use 25 steps in either direction of the temperature
for(i=0;i<50;i++)
{
Temperature = Initial_Temperature - Range + (i*Range/25); // +/- Range, 25 Steps in either direction
Evaluate_Thermodynamic_Parameters(CalculatedThermo, Thermodynamics, Temperature);
Calculate_Rate_Constant(Kf, Kr, Temperature,LocalReactionParameters, CalculatedThermo, LocalSpeciesLossAll, Local_Delta_N);
for(j=0;j<(int)Kr.size();j++)
{
Kr[j] = log(Kr[j]);
}
allkreverse.push_back(Kr);
OneTempSensitivityMatrix[0] = 1;
OneTempSensitivityMatrix[1] = log(Temperature);
OneTempSensitivityMatrix[2] = 1/Temperature;
SensitivityMatrix.push_back(OneTempSensitivityMatrix);
}
// At this point we now have a collection of kr as well as the sensitivity matrix
vector< vector< double > > SensitivityMatrixTranspose; // called X in the paper
vector< double > RowSensitivityMatrixTranspose;
RowSensitivityMatrixTranspose.resize(SensitivityMatrix.size());
// stupid way to give the matrix 3 rows
SensitivityMatrixTranspose.push_back(RowSensitivityMatrixTranspose);
SensitivityMatrixTranspose.push_back(RowSensitivityMatrixTranspose);
SensitivityMatrixTranspose.push_back(RowSensitivityMatrixTranspose);
for(i=0;i<3;i++)
{
for(j=0;j<(int)SensitivityMatrix.size();j++)
{
SensitivityMatrixTranspose[i][j] = SensitivityMatrix[j][i];
}
}
// Now we need to calculate our betas.
// First on the list, SensitivityMatrixTranspose times SensitivityMatrix
vector< vector< double > > SMtxSM; // Sensitivity Matrix transpose times (x) Sensitivity Matrix
vector< double > SMt; // Sensitivity Matrix transpose times
SMt.resize(3);
// result is a 3x3 matrix
SMtxSM.push_back(SMt);
SMtxSM.push_back(SMt);
SMtxSM.push_back(SMt);
for(i=0;i<3;i++)
{
for(j=0;j<3;j++)
{
for(k=0;k<(int)SensitivityMatrix.size();k++)
{
SMtxSM[i][j] = SMtxSM[i][j] + SensitivityMatrixTranspose[i][k] * SensitivityMatrix[k][j];
}
}
}
/* Now we need the inverse of the matrix.
*
* a , b , c
* d , e , f
* g , h , k
*
* divisor = cdh - cge - bdk + bgf + aek - ahf
*
* So matrix is, every entry divided by divisor, rest
*
* ek - hf , -dk + gf , dh - ge
* ch - bk , -cg + ak , bg - ah
* - ce + bf , cd - af , -bd + ae
*/
double determinant =
SMtxSM[0][2]*SMtxSM[1][0]*SMtxSM[2][1] -
SMtxSM[0][2]*SMtxSM[2][0]*SMtxSM[1][1] -
SMtxSM[0][1]*SMtxSM[1][0]*SMtxSM[2][2] +
SMtxSM[0][1]*SMtxSM[2][0]*SMtxSM[1][2] +
SMtxSM[0][0]*SMtxSM[1][1]*SMtxSM[2][2] -
SMtxSM[0][0]*SMtxSM[2][1]*SMtxSM[1][2];
vector< vector< double > > SMtxSMInv; // Sensitivity Matrix transpose times (x) Sensitivity Matrix
vector< double > SMtInv; // Sensitivity Matrix transpose times
SMtInv.resize(3);
// Stupid way of creating an inverse matrix... but it is only 3*3
SMtxSMInv.push_back(SMtInv);
SMtxSMInv.push_back(SMtInv);
SMtxSMInv.push_back(SMtInv);
SMtxSMInv[0][0] = SMtxSM[1][1]*SMtxSM[2][2] - SMtxSM[2][1]*SMtxSM[1][2];
SMtxSMInv[0][1] = - SMtxSM[1][0]*SMtxSM[2][2] + SMtxSM[2][0]*SMtxSM[1][2];
SMtxSMInv[0][2] = SMtxSM[1][0]*SMtxSM[2][1] - SMtxSM[2][0]*SMtxSM[1][1];
SMtxSMInv[1][0] = SMtxSM[0][2]*SMtxSM[2][1] - SMtxSM[0][1]*SMtxSM[2][2];
SMtxSMInv[1][1] = - SMtxSM[0][2]*SMtxSM[2][0] + SMtxSM[0][0]*SMtxSM[2][2];
SMtxSMInv[1][2] = SMtxSM[0][1]*SMtxSM[2][0] - SMtxSM[0][0]*SMtxSM[2][1];
SMtxSMInv[2][0] = - SMtxSM[0][2]*SMtxSM[1][1] + SMtxSM[0][1]*SMtxSM[1][2];
SMtxSMInv[2][1] = SMtxSM[0][2]*SMtxSM[1][0] - SMtxSM[0][0]*SMtxSM[1][2];
SMtxSMInv[2][2] = - SMtxSM[0][1]*SMtxSM[1][0] + SMtxSM[0][0]*SMtxSM[1][1];
// Don't forget dividing by the determinant
for(i=0;i<3;i++)
{
for(j=0;j<3;j++)
{
SMtxSMInv[i][j] = SMtxSMInv[i][j] / determinant;
}
}
// now transpose times the logarithms of k_r to get a 3 entry vector...
vector< vector< double > > InvMxSM;
vector< double > xSM;
xSM.resize(SensitivityMatrix.size());
InvMxSM.push_back(xSM);
InvMxSM.push_back(xSM);
InvMxSM.push_back(xSM);
// matrix mult: row x column
for(i=0;i<3;i++)
{
for(j=0;j<(int)SensitivityMatrix.size();j++)
{
for(k=0;k<3;k++)
{
InvMxSM[i][j] = InvMxSM[i][j] + SMtxSMInv[i][k] * SensitivityMatrixTranspose[k][j];
}
}
}
SingleReactionData SingleReaction;
// assemble the arrays for writing a new reactions array
vector< double > ReactantData; // Reactant Information
ReactantData.resize(Number_Species);
vector< double > ProductData; // Product Information
ProductData.resize(Number_Species);
vector< double > ReactionParameters;
ReactionParameters.resize(4);
for(i=0;i<Number_Reactions;i++)
{
// 1) retain the old forward reaction
SingleReaction.Reactants = Reactions[i].Reactants;
SingleReaction.Products = Reactions[i].Products;
SingleReaction.paramA = Reactions[i].paramA;
SingleReaction.paramN = Reactions[i].paramN;
SingleReaction.paramEa = Reactions[i].paramEa;
// switch reaction to irreversible:
SingleReaction.Reversible = false;
SingleReaction.IsDuplicate = Reactions[i].IsDuplicate;
/*
printf("Reaction %u Forward: %.3e %.3e %.3e %.3e || ",i,
ReactionParamaters[0],ReactionParamaters[1],
ReactionParamaters[2],ReactionParamaters[3]); // Works :) */
Irreversible_Scheme.push_back(SingleReaction);
// Calculate the parameters
vector< double > beta;
beta.resize(3);
// check if the reaction was reversible - if yes, calculate irreversible form
if(Reactions[i].Reversible)
{
for(j=0;j<3;j++)
{
for(k=0;k<(int)SensitivityMatrix.size();k++)
{
beta[j] = beta[j] + InvMxSM[j][k] * allkreverse[k][i];
}
}
// Write out reverse reaction:
// And now the reverse Reaction - Products and Reactants reversed
for(j=0;j<Number_Species;j++)
{
ReactantData[j] = - Reactions[i].Products[j];
ProductData[j] = - Reactions[i].Reactants[j];
}
SingleReaction.Reactants = ReactantData;
SingleReaction.Products = ProductData;
SingleReaction.paramA = exp(beta[0]);
SingleReaction.paramN = beta[1];
SingleReaction.paramEa = -beta[2];
// retain reaction as irreversible:
SingleReaction.Reversible = false;
SingleReaction.IsDuplicate = Reactions[i].IsDuplicate;
/*
printf("Reverse %.3e %.3e %.3e %.3e \n",
ReactionParamaters[0],ReactionParamaters[1],
ReactionParamaters[2],ReactionParamaters[3]); // Works :) */
Irreversible_Scheme.push_back(SingleReaction);
}
}
return Irreversible_Scheme;
}
/* XXX unfortunately API function gnk of which pyk.gk
is based is a vararg function and therefore cannot
be portably exported to Python. It would be better
if libk20 supplied a function gnk_(I, K*)
in addition to gnk(I,...) which would take an array
of K objects as the second argument */
static PyObject*
_gk(PyObject* self, PyObject* args)
{
int n = PyTuple_Size(args);
if (!n) {
return _mk_K(gtn(0,0));
}
int i, type = INT_MAX;
K* ks = (K*)malloc(n*sizeof(K));
K kobj;
for(i = 0; i < n; i++) {
K ki;
int t;
PyObject* argi = PyTuple_GET_ITEM(args, i);
if (!IS_K(argi)) {
goto fail;
}
ks[i] = ki = ((_K*)argi)->kobj;
t = ki->t;
if (INT_MAX == type) {
type = t;
} else if (t > 4 || t < 1 || t != type) {
type = 0;
}
}
kobj = gtn((type>0 && type<5)?-type:0, n);
if (!kobj) {
free(ks);
return PyErr_Format(PyExc_TypeError, "gtn(%d,%d) returned null", -type, n);
}
switch (type) {
case 1:
for (i = 0; i < n; i++) {
KI(kobj)[i] = Ki(ks[i]);
}
break;
case 2:
for (i = 0; i < n; i++) {
KF(kobj)[i] = Kf(ks[i]);
}
break;
case 3:
for (i = 0; i < n; i++) {
KC(kobj)[i] = Kc(ks[i]);
}
break;
case 4:
for (i = 0; i < n; i++) {
KS(kobj)[i] = Ks(ks[i]);
}
break;
default:
memcpy(KK(kobj), ks, n*sizeof(K));
for (i = 0; i < n; i++) {
ci(ks[i]);
}
break;
}
free(ks);
return _mk_K(kobj);
fail:
free(ks);
PyErr_BadArgument();
return NULL;
}
K gf(F x) {K z=newK(2,1); Kf(z)=x; R z;}
int
main(int argc, char** argv)
{
F pi = atan(1.0)*4;
K a = gi(2);
K b = gi(3);
K c = gi(4);
K* v;
cd(ksk("",0));
tst(Ki(a)==2);
tst(Ki(b) + 1 == Ki(c));
cd(a); cd(b); cd(c);
b = gf(1.0); c = gf(2);
tst(Kf(b) + 1 == Kf(c));
cd(b); cd(c);
a = gs(sp("foo"));
b = ksk("`foo", 0);
tst(Ks(a) == Ks(b));
cd(a); cd(b);
a = ksk("2 + 3", 0);
tst(Ki(a) == 5);
cd(a);
a = ksk("_ci 65", 0);
tst(Kc(a) == 'A');
// XXX this should return type 1 uniform vector
a=gnk(3,gi(11),gi(22),gi(33));
tst(a->t == 0);
v = (K*)a->k;
tst(Ki(v[0])+Ki(v[1])==Ki(v[2]));
cd(a);
{
b = gsk("pi",gf(pi));
kap(&KTREE, &b);
a = X(".pi");
tst(Kf(a) == pi);
cd(a);
}
{
K dir = gtn(5,0);
K t;
t = gsk("x",gi(1)); kap(&dir, &t);
t = gsk("y",gi(2)); kap(&dir, &t);
t = gsk("z",dir); kap(&KTREE, &t);
a = X(".z.x");
tst(Ki(a) == 1);
cd(a);
a = X(".z.y");
tst(Ki(a) == 2);
cd(a);
}
{
I i;
K d = gtn(5,0);
K c0 = gtn(0,0);
K c1 = gtn(-1,0);
K t0, t1, e;
t0 = gsk("a", c0); kap(&d,&t0);
t1 = gsk("b", c1); kap(&d,&t1);
e = gp("hello1"); kap(&c0,&e);
e = gp("hello2"); kap(&c0,&e);
KK(KK(d)[0])[1] = c0;
i = 1; kap(&KK(KK(d)[1])[1], &i);
i = 2; kap(&KK(KK(d)[1])[1], &i);
//i = 1; kap(&c1, &i);
//i = 2; kap(&c1, &i);
//KK(KK(d)[1])[1] = c1;
show(d);
}
//b = ksk("+/", a);
//tst(Ki(b) == 66);
//argc--;argv++;
//DO(i, argc, {a=ksk(argv[i], 0);
//ksk("`0:,/$!10;`0:,\"\n\"", 0);
fprintf(stderr, "Pass:%4d, fail:%4d\n", pass, fail);
if (argc > 1 && strcmp(argv[1], "-i") == 0) {
boilerplate();
attend();
}
}
