PView *elasticitySolver::buildVolumeView(const std::string postFileName)
{
std::cout << "build Volume View";
std::map<int, std::vector<double> > data;
double voltot = 0;
double length = 0;
GaussQuadrature Integ_Vol(GaussQuadrature::Val);
for(std::size_t i = 0; i < elasticFields.size(); ++i) {
ScalarTermConstant<double> One(1.0);
for(groupOfElements::elementContainer::const_iterator it =
elasticFields[i].g->begin();
it != elasticFields[i].g->end(); ++it) {
MElement *e = *it;
double vol;
IntPt *GP;
int npts = Integ_Vol.getIntPoints(e, &GP);
One.get(e, npts, GP, vol);
voltot += vol;
std::vector<double> vec;
vec.push_back(vol);
data[e->getNum()] = vec;
}
}
for(std::size_t i = 0; i < LagrangeMultiplierFields.size(); ++i) {
ScalarTermConstant<double> One(1.0);
for(groupOfElements::elementContainer::const_iterator it =
LagrangeMultiplierFields[i].g->begin();
it != LagrangeMultiplierFields[i].g->end(); ++it) {
MElement *e = *it;
double l;
IntPt *GP;
int npts = Integ_Vol.getIntPoints(e, &GP);
One.get(e, npts, GP, l);
length += l;
}
std::cout << " : length " << LagrangeMultiplierFields[i]._tag << " = "
<< length;
length = 0;
}
PView *pv = new PView(postFileName, "ElementData", pModel, data, 0.0, 1);
std::cout << " / total vol = " << voltot << std::endl;
return pv;
}
void g (N::A *a, M::B *b, O::C *c)
{
One (a); // ok
One (a, b); // ok
One (b); // { dg-error "not declared" }
// { dg-message "suggested alternatives" "suggested alternative for One" { target *-*-* } 34 }
Two (c); // ok
Two (a, c); // ok
Two (a); // { dg-error "not declared" }
// { dg-message "suggested alternatives" "suggested alternative for Two" { target *-*-* } 39 }
Two (a, a); // error masked by earlier error
Two (b); // error masked by earlier error
Two (a, b); // error masked by earlier error
Three (b); // ok
Three (a, b); // ok
Three (a); // { dg-error "not declared" }
// { dg-message "suggested alternatives" "suggested alternative for Three" { target *-*-* } 47 }
}
void main(void)
{
SomeClass One(1, 999);
cout << "One: " << One.my_data << ' ' << One.count << endl ;
// Declare another instance
SomeClass Two(2);
cout << "Two: " << Two.my_data << ' ' << Two.count << endl ;
// Declare another instance
SomeClass Three(3);
cout << "Three: " << Three.my_data << ' ' << Three.count << endl ;
}
bool BigInt::isPrime(BigInt N)
{
ll start = clock();
BigInt One("1");
if (N == One)
return false;
for (BigInt i("2"); i < sqrt(N); i = i + One)
{
if (N%i == BigInt("0"))
return false;
}
ll finish = clock();
TimeOfLast = static_cast<double>(finish - start) / 1000;
return true;
}
vector<BigInt> BigInt::PollardP(BigInt N)
{
ll start = clock();
vector<BigInt> res;
BigInt One("1");
while (!isPrime(N) && N != One)
{
res.push_back(PollardP_get_factor(N));
N = N / res.back();
}
if (isPrime(N))
res.push_back(N);
ll finish = clock();
TimeOfLast = static_cast<double>(finish - start) / 1000;
return res;
}
//位移，如果非平滑SE将加上sevalue，即对应的灰度值
void G_Translation(double *src,double *dst,int width,int height,double SEvalue,Position *d,int istoFindMin){
double *temp=(double*)malloc(sizeof(double)*height*width);
if(istoFindMin)
One(temp,width,height);
else
Zero(temp,width,height);
for(int j=0;j<height;j++){
for(int i=0;i<width;i++){
int target_x=i+d->x;
int target_y=j+d->y;
if(target_x>=0&&target_y>=0&&
target_x<width&&target_y<height){
double value=src[j*width+i]+SEvalue;
value=(value>=255.0?255.0:value);
temp[target_y*width+target_x]=value;
}
}
}
matrixCopy(temp,dst,width,height);
free(&temp);
}
bool cHopperEntity::MoveItemsFromSlot(cBlockEntityWithItems & a_Entity, int a_SlotNum)
{
cItem One(a_Entity.GetSlot(a_SlotNum).CopyOne());
for (int i = 0; i < ContentsWidth * ContentsHeight; i++)
{
if (m_Contents.IsSlotEmpty(i))
{
if (cPluginManager::Get()->CallHookHopperPullingItem(*m_World, *this, i, a_Entity, a_SlotNum))
{
// Plugin disagrees with the move
continue;
}
m_Contents.SetSlot(i, One);
return true;
}
else if (m_Contents.GetSlot(i).IsEqual(One))
{
if (cPluginManager::Get()->CallHookHopperPullingItem(*m_World, *this, i, a_Entity, a_SlotNum))
{
// Plugin disagrees with the move
continue;
}
auto PreviousCount = m_Contents.GetSlot(i).m_ItemCount;
m_Contents.ChangeSlotCount(i, 1);
if (PreviousCount + 1 == m_Contents.GetSlot(i).m_ItemCount)
{
// Successfully added a new item. (Failure condition consistutes: stack full)
return true;
}
}
}
return false;
}
/* In the _vast_ majority of cases this simply checks that your chosen random
* number is >= KLastSmallPrimeSquared and return EFalse and lets the normal
* prime generation routines handle the situation. In the case where it is
* smaller, it generates a provable prime and returns ETrue. The algorithm for
* finding a provable prime < KLastPrimeSquared is not the most efficient in the
* world, but two points come to mind
* 1) The two if statements hardly _ever_ evaluate to ETrue in real life.
* 2) Even when it is, the distribution of primes < KLastPrimeSquared is pretty
* dense, so you aren't going to have check many.
* This function is essentially here for two reasons:
* 1) Ensures that it is possible to generate primes < KLastPrimeSquared (the
* test code does this)
* 2) Ensures that if you request a prime of a large bit size that there is an
* even probability distribution across all integers < 2^aBits
*/
TBool TInteger::SmallPrimeRandomizeL(void)
{
TBool foundPrime = EFalse;
//If the random number we've chosen is less than KLastSmallPrime,
//testing for primality is easy.
if(*this <= KLastSmallPrime)
{
//If Zero or One, or two, next prime number is two
if(IsZero() || *this == One() || *this == Two())
{
CopyL(TInteger::Two());
foundPrime = ETrue;
}
else
{
//Make sure any number we bother testing is at least odd
SetBit(0);
//Binary search the small primes.
while(!IsSmallPrime(ConvertToUnsignedLong()))
{
//If not prime, add two and try the next odd number.
//will never carry as the minimum size of an RInteger is 2
//words. Much bigger than KLastSmallPrime on 32bit
//architectures.
IncrementNoCarry(Ptr(), Size(), 2);
}
assert(IsSmallPrime(ConvertToUnsignedLong()));
foundPrime = ETrue;
}
}
else if(*this <= KLastSmallPrimeSquared)
{
//Make sure any number we bother testing is at least odd
SetBit(0);
while(HasSmallDivisorL(*this) && *this <= KLastSmallPrimeSquared)
{
//If not prime, add two and try the next odd number.
//will never carry as the minimum size of an RInteger is 2
//words. Much bigger than KLastSmallPrime on 32bit
//architectures.
IncrementNoCarry(Ptr(), Size(), 2);
}
//If we exited while loop because it had no small divisor then it is
//prime. Otherwise, we've exceeded the limit of what we can provably
//generate. Therefore the normal prime gen routines will be run on it
//now.
if(*this < KLastSmallPrimeSquared)
{
foundPrime = ETrue;
}
else
{
assert(foundPrime == EFalse);
}
}
//This doesn't mean there is no such prime, simply means that the number
//wasn't less than KSmallPrimeSquared and needs to be handled by the normal
//prime generation routines.
return foundPrime;
}
typename A::Field CIP(const A& a, const B& b) {
BOOST_STATIC_ASSERT((in_same_space<A, B>::value));
return CIP_impl_lin(a, One(), b);
}
// add using dual numbers
// combine diffeq and incorporation for direct RedTrace computation
void DerivativeRedTrace(float *red_out, float *ival_offset, float *da_offset, float *dk_offset,
int npts, float *deltaFrameSeconds, float *deltaFrame,
float *nuc_rise_ptr, int SUB_STEPS, int my_start,
Dual A, float SP,
Dual kr, float kmax, float d,
float sens, float gain, float tauB,
PoissonCDFApproxMemo *math_poiss)
{
int i;
Dual totocc, totgen;
// mixed_poisson_struct mix_ctrl;
MixtureMemo mix_memo;
Dual pact,pact_new;
Dual c_dntp_top, c_dntp_bot;
Dual hplus_events_sum, hplus_events_current; // mean events per molecule, cumulative and current
Dual ldt;
Dual Ival;
Dual One(1.0);
Dual Zero(0.0);
Dual Half(0.5);
Dual xSP(SP);
Dual xkmax(kmax);
Dual xd(d);
Dual xA = mix_memo.Generate(A,math_poiss);
//xA.Dump("xA");
//A = InitializeMixture(&mix_ctrl,A,MAX_HPLEN); // initialize Poisson with correct amplitude which maxes out at MAX_HPLEN
mix_memo.ScaleMixture(SP);
//ScaleMixture(&mix_ctrl,SP); // scale mixture fractions to proper number of molecules
pact = Dual(mix_memo.total_live); // active polymerases // wrong???
//pact.Dump("pact");
//Dual pact_zero = pact;
totocc = xSP*xA; // how many hydrogens we'll eventually generate
//totocc.Dump("totocc");
totgen = totocc; // number remaining to generate
//totgen.Dump("totgen");
c_dntp_bot = Zero; // concentration of dNTP in the well
c_dntp_top = Zero; // concentration at top
hplus_events_sum = hplus_events_current = Zero; // Events per molecule
memset(ival_offset,0,sizeof(float[my_start])); // zero the points we don't compute
memset(da_offset,0,sizeof(float[my_start])); // zero the points we don't compute
memset(dk_offset,0,sizeof(float[my_start])); // zero the points we don't compute
Dual scaled_kr = kr*Dual(n_to_uM_conv)/xd; // convert molecules of polymerase to active concentraction
Dual half_kr = kr *Half; // for averaging
// kr.Dump("kr");
//scaled_kr.Dump("scaled_kr");
//half_kr.Dump("half_kr");
// first non-zero index of the computed [dNTP] array for this nucleotide
int c_dntp_top_ndx = my_start*SUB_STEPS;
Dual c_dntp_bot_plus_kmax = Dual(1.0/kmax);
Dual c_dntp_old_effect = Zero;
Dual c_dntp_new_effect = Zero;
Dual cur_gen(0.0);
Dual equilibrium(0.0);
int st;
// trace variables
Dual old_val = Zero;
Dual cur_val = Zero;
Dual run_sum = Zero;
Dual half_dt = Zero;
Dual TauB(tauB);
Dual SENS(sens);
memset(red_out,0,sizeof(float[my_start]));
for (i=my_start;i < npts;i++)
{
// Do one prediction time step
if (totgen.a > 0.0)
{
// need to calculate incorporation
ldt = (deltaFrameSeconds[i]/SUB_STEPS); // multiply by half_kr out here, because I'm going to use it twice?
ldt *= half_kr; // scale time by rate out here
//ldt.Dump("ldt");
for (st=1; (st <= SUB_STEPS) && (totgen.a > 0.0);st++)
{
c_dntp_bot.a = nuc_rise_ptr[c_dntp_top_ndx];
c_dntp_top_ndx++;
// calculate denominator
equilibrium = c_dntp_bot_plus_kmax;
equilibrium *= pact;
equilibrium *= scaled_kr;
equilibrium += One;
c_dntp_bot /= equilibrium;
//c_dntp_bot.Dump("c_dntp_bot");
// the level at which new nucs are used up as fast as they diffuse in
c_dntp_bot_plus_kmax.Reciprocal(c_dntp_bot + xkmax); // scale for michaelis-menten kinetics, assuming nucs are limiting factor
//c_dntp_bot_plus_kmax.Dump("plus_kmax");
// Now compute effect of concentration on enzyme rate
c_dntp_old_effect = c_dntp_new_effect;
c_dntp_new_effect = c_dntp_bot;
c_dntp_new_effect *= c_dntp_bot_plus_kmax; // current effect of concentration on enzyme rate
//c_dntp_new_effect.Dump("c_dntp_new");
// update events per molecule
hplus_events_current = c_dntp_old_effect;
hplus_events_current += c_dntp_new_effect;
hplus_events_current *= ldt;
//hplus_events_current.Dump("current"); // events per molecule is average rate * time of rate
hplus_events_sum += hplus_events_current;
//hplus_events_sum.Dump("sum");
// how many active molecules left at end of time period given poisson process with total intensity of events
// exp(-t) * (1+t+t^2/+t^3/6+...) where we interpolate between polynomial lengths by A
// exp(-t) ( 1+... + frac*(t^k/k!)) where k = ceil(A-1) and frac = A-floor(A), for A>=1
pact_new = mix_memo.GetStep(hplus_events_sum);
//pact_new = pact_zero;
//pact_new.Dump("pact_new");
// how many hplus were generated
// reuse pact for average
// reuse hplus-events_current for total events
pact += pact_new;
pact *= Half; // average number of molecules
//hplus_events_current *= pact; // events/molecule *= molecule is total events
totgen -= pact*hplus_events_current; // active molecules * events per molecule
//totgen.Dump("totgen");
pact = pact_new; // update to current number of molecules
//pact.Dump("pact");
}
if (totgen.a < 0.0) totgen = Zero;
}
Ival = totocc;
Ival -= totgen;
ival_offset[i] = Ival.a;
Ival *= SENS; // convert from hydrogen to counts
// Now compute trace
// trace
half_dt = deltaFrame[i]*0.5;
// calculate new value
Ival *= TauB;
cur_val = Ival;
cur_val -= run_sum;
old_val *= half_dt; // update
cur_val -= old_val;
cur_val /= (TauB+half_dt);
// update run sum
run_sum += old_val; // reuse update
run_sum += cur_val*half_dt;
old_val = cur_val; // set for next value
//cur_val *= gain; // gain=1.0 always currently
red_out[i] = cur_val.a;
da_offset[i] = cur_val.da;
dk_offset[i] = cur_val.dk;
// now we have done one prediction time step
}
}
*
* Author: Adriaan,
* Company: Uppsala IT
*
* =====================================================================================
*/
#include "unit.h"
#include "module_copy.h"
int tests_run = 0;
int tests_set = 2;
TEST(getModule)
MODDATA temp = One();
CHECK("Did not fetch the One module",temp.identifier == 1);
DONE
TEST(getValue)
DATA temp = Two_value();
CHECK("Did not fetch Pair form Two.value",temp.t == PAIR);
CHECK("Pair left hand side is not INT",temp.left->t == INT);
CHECK("Pair right hand side is not BOOLEAN",temp.right->t == BOOLEAN);
CHECK("Did not obtain left value == 1",temp.left->value == 1);
CHECK("Did not obtain right value == 0",temp.right->value == 0);
DONE
LIST
RUN(getModule);
RUN(getValue);
void tree::fractalTree(int count, Vertex zero, Vertex one, float angleRight, float angleLeft)
{
count--;
if (count > 0) {
vec4 Zero(zero.coords[0], zero.coords[1],zero.coords[2],1);
vec4 One(one.coords[0], one.coords[1], one.coords[2],1);
vec4 Scale = (One - Zero);
Scale = Scale * 0.8f;
//float randValue = randomFloat(-rand, rand);
//float alpha = ((angleRight + randValue)*3.14 / 180);
////mat3x3 rotMatrix(cos(alpha), sin(alpha), -sin(alpha), cos(alpha));
//mat3x3 rotMatrixX(1, 0, 0, 0, cos(alpha), sin(alpha), 0, -sin(alpha), cos(alpha));
//float randValue2 = randomFloat(-rand, rand);
//float beta = ((angleRight + randValue2)*3.14 / 180);
//mat3x3 rotMatrixZ(cos(beta), sin(beta), 0, -sin(beta), cos(beta), 0, 0, 0, 1);
//vec3 Answer = (Scale * rotMatrixZ)*rotMatrixX;
mat4 rotMatrix = mat4(1);
rotMatrix = rotate(rotMatrix, randomFloat((-angleRight), angleRight)*3.14f/180.0f, vec3(0, 1, 0));
rotMatrix = rotate(rotMatrix, randomFloat((-angleRight), angleRight)*3.14f / 180.0f, vec3(0, 0, 1));
rotMatrix = rotate(rotMatrix, randomFloat((-angleRight), angleRight)*3.14f / 180.0f, vec3(1, 0, 0));
vec4 Answer = rotMatrix * Scale;
Answer = Answer + One;
branches[branchesIterator].zero = one;
branches[branchesIterator].zero.colors[0] = 0.3f;
branches[branchesIterator].zero.colors[1] = 0.1f;
branches[branchesIterator].one.coords[0] = Answer.x;
branches[branchesIterator].one.coords[1] = Answer.y;
branches[branchesIterator].one.coords[2] = Answer.z;
branches[branchesIterator].one.coords[3] = 1;
branches[branchesIterator].one.coords[3] = 1;
branches[branchesIterator].one.colors[0] = 0.3f;
branches[branchesIterator].one.colors[1] = 0.1f;
if (count == 1)
branches[branchesIterator].end = true;
else
branches[branchesIterator].end = false;
branchesIterator++;
depth.push_back(count);
fractalTree(count, branches[branchesIterator - 1].zero, branches[branchesIterator - 1].one, angleRight, angleLeft);
////////////////////////////////////////////////
Zero = vec4(zero.coords[0], zero.coords[1], zero.coords[2],1);
One = vec4(one.coords[0], one.coords[1], one.coords[2],1);
Scale = One - Zero;
Scale = Scale * 0.8f;
/*randValue = randomFloat(-rand, rand);
alpha = ((angleLeft +randValue)*3.14 / 180)*-1;
rotMatrixX = mat3x3(1, 0, 0, 0, cos(alpha), sin(alpha), 0, -sin(alpha), cos(alpha));
randValue2 = randomFloat(-rand, rand);
beta = ((angleLeft + randValue2)*3.14 / 180)*-1;
rotMatrixZ = mat3x3(cos(beta), sin(beta), 0, -sin(beta), cos(beta), 0, 0, 0, 1);
Answer = (Scale * rotMatrixZ)*rotMatrixX;*/
rotMatrix = mat4(1);
rotMatrix = rotate(rotMatrix, (randomFloat((-angleLeft), angleLeft)*3.14f/180.0f), vec3(0, 1, 0));
rotMatrix = rotate(rotMatrix, randomFloat((-angleLeft), angleLeft)*3.14f / 180.0f, vec3(0, 0, 1));
rotMatrix = rotate(rotMatrix, randomFloat((-angleLeft), angleLeft)*3.14f / 180.0f, vec3(1, 0, 0));
Answer = rotMatrix * Scale;
Answer = Answer + One;
branches[branchesIterator].zero = one;
branches[branchesIterator].zero.colors[0] = 0.3f;
branches[branchesIterator].zero.colors[1] = 0.1f;
branches[branchesIterator].one.coords[0] = Answer.x;
branches[branchesIterator].one.coords[1] = Answer.y;
branches[branchesIterator].one.coords[2] = Answer.z;
branches[branchesIterator].one.coords[3] = 1;
branches[branchesIterator].one.coords[3] = 1;
branches[branchesIterator].one.colors[0] = 0.3f;
branches[branchesIterator].one.colors[1] = 0.1f;
if (count == 1)
branches[branchesIterator].end = true;
else
branches[branchesIterator].end = false;
branchesIterator++;
depth.push_back(count);
fractalTree(count, branches[branchesIterator - 1].zero, branches[branchesIterator - 1].one, angleRight,angleLeft);
}
}
bool Reed_Solomon::decode(const bvec &coded_bits, const ivec &erasure_positions, bvec &decoded_message, bvec &cw_isvalid)
{
bool decoderfailure, no_dec_failure;
int j, i, kk, l, L, foundzeros, iterations = floor_i(static_cast<double>(coded_bits.length()) / (n * m));
bvec mbit(m * k);
decoded_message.set_size(iterations * k * m, false);
cw_isvalid.set_length(iterations);
GFX rx(q, n - 1), cx(q, n - 1), mx(q, k - 1), ex(q, n - 1), S(q, 2 * t), Xi(q, 2 * t), Gamma(q), Lambda(q),
Psiprime(q), OldLambda(q), T(q), Omega(q);
GFX dummy(q), One(q, (char*)"0"), Omegatemp(q);
GF delta(q), tempsum(q), rtemp(q), temp(q), Xk(q), Xkinv(q);
ivec errorpos;
if ( erasure_positions.length() ) {
it_assert(max(erasure_positions) < iterations*n, "Reed_Solomon::decode: erasure position is invalid.");
}
no_dec_failure = true;
for (i = 0; i < iterations; i++) {
decoderfailure = false;
//Fix the received polynomial r(x)
for (j = 0; j < n; j++) {
rtemp.set(q, coded_bits.mid(i * n * m + j * m, m));
rx[j] = rtemp;
}
// Fix the Erasure polynomial Gamma(x)
// and replace erased coordinates with zeros
rtemp.set(q, -1);
ivec alphapow = - ones_i(2);
Gamma = One;
for (j = 0; j < erasure_positions.length(); j++) {
rx[erasure_positions(j)] = rtemp;
alphapow(1) = erasure_positions(j);
Gamma *= (One - GFX(q, alphapow));
}
//Fix the syndrome polynomial S(x).
S.clear();
for (j = 1; j <= 2 * t; j++) {
S[j] = rx(GF(q, b + j - 1));
}
// calculate the modified syndrome polynomial Xi(x) = Gamma * (1+S) - 1
Xi = Gamma * (One + S) - One;
// Apply Berlekam-Massey algorithm
if (Xi.get_true_degree() >= 1) { //Errors in the received word
// Iterate to find Lambda(x), which hold all error locations
kk = 0;
Lambda = One;
L = 0;
T = GFX(q, (char*)"-1 0");
while (kk < 2 * t) {
kk = kk + 1;
tempsum = GF(q, -1);
for (l = 1; l <= L; l++) {
tempsum += Lambda[l] * Xi[kk - l];
}
delta = Xi[kk] - tempsum;
if (delta != GF(q, -1)) {
OldLambda = Lambda;
Lambda -= delta * T;
if (2 * L < kk) {
L = kk - L;
T = OldLambda / delta;
}
}
T = GFX(q, (char*)"-1 0") * T;
}
// Find the zeros to Lambda(x)
errorpos.set_size(Lambda.get_true_degree());
foundzeros = 0;
for (j = q - 2; j >= 0; j--) {
if (Lambda(GF(q, j)) == GF(q, -1)) {
errorpos(foundzeros) = (n - j) % n;
foundzeros += 1;
if (foundzeros >= Lambda.get_true_degree()) {
break;
}
}
}
if (foundzeros != Lambda.get_true_degree()) {
decoderfailure = true;
}
else { // Forney algorithm...
//Compute Omega(x) using the key equation for RS-decoding
Omega.set_degree(2 * t);
Omegatemp = Lambda * (One + Xi);
for (j = 0; j <= 2 * t; j++) {
Omega[j] = Omegatemp[j];
}
//Find the error/erasure magnitude polynomial by treating them the same
Psiprime = formal_derivate(Lambda*Gamma);
errorpos = concat(errorpos, erasure_positions);
ex.clear();
for (j = 0; j < errorpos.length(); j++) {
Xk = GF(q, errorpos(j));
Xkinv = GF(q, 0) / Xk;
// we calculate ex = - error polynomial, in order to avoid the
// subtraction when recunstructing the corrected codeword
ex[errorpos(j)] = (Xk * Omega(Xkinv)) / Psiprime(Xkinv);
if (b != 1) { // non-narrow-sense code needs corrected error magnitudes
int correction_exp = ( errorpos(j)*(1-b) ) % n;
ex[errorpos(j)] *= GF(q, correction_exp + ( (correction_exp < 0) ? n : 0 ));
}
}
//Reconstruct the corrected codeword.
// instead of subtracting the error/erasures, we calculated
// the negative error with 'ex' above
cx = rx + ex;
//Code word validation
S.clear();
for (j = 1; j <= 2 * t; j++) {
S[j] = cx(GF(q, b + j - 1));
}
if (S.get_true_degree() >= 1) {
decoderfailure = true;
}
}
}
else {
cx = rx;
decoderfailure = false;
}
//Find the message polynomial
mbit.clear();
if (decoderfailure == false) {
if (cx.get_true_degree() >= 1) { // A nonzero codeword was transmitted
if (systematic) {
for (j = 0; j < k; j++) {
mx[j] = cx[j];
}
}
else {
mx = divgfx(cx, g);
}
for (j = 0; j <= mx.get_true_degree(); j++) {
mbit.replace_mid(j * m, mx[j].get_vectorspace());
}
}
}
else { //Decoder failure.
// for a systematic code it is better to extract the undecoded message
// from the received code word, i.e. obtaining a bit error
// prob. p_b << 1/2, than setting all-zero (p_b = 1/2)
if (systematic) {
mbit = coded_bits.mid(i * n * m, k * m);
}
else {
mbit = zeros_b(k);
}
no_dec_failure = false;
}
decoded_message.replace_mid(i * m * k, mbit);
cw_isvalid(i) = (!decoderfailure);
}
return no_dec_failure;
}
static void
doit () throw (Two) // { dg-warning "deprecated" "" { target { c++11 } } }
{
throw One ();
}
static void
doit () throw (Two)
{
throw One ();
}
Vector SchemeRoe(const Cell& Cell1,const Cell& Cell2,const Cell& Cell3,const Cell& Cell4, int AxisNo)
{
// Local variables
Vector V1, V2, V3, V4; // Velocities
real rho1, rho2, rho3, rho4; // Densities
real p1, p2, p3, p4; // Pressures
real rhoE1, rhoE2, rhoE3, rhoE4; // Energies
Vector Result(QuantityNb);
Vector F1(QuantityNb); // Fluxes
Vector F2(QuantityNb);
Vector F3(QuantityNb);
Vector F4(QuantityNb);
Vector Q1, Q2, Q3, Q4; // Conservative quantities
Vector FL(QuantityNb),FR(QuantityNb); // Left and right fluxex
Vector QL(QuantityNb),QR(QuantityNb); // Left and right conservative quantities
real rhoL, rhoR; // Left and right densities
real pL, pR; // Left and right pressures
real rhoEL, rhoER; // Left and right energies
Vector VL(Dimension), VR(Dimension); // Left and right velocities
Vector One(QuantityNb);
real rho; // central density with Roe's average
Vector V(Dimension); // central velocity with Roe's average
real H; // central enthalpy with Roe's average
real c; // central speed of sound with Roe's average
real Roe; // Coefficient for Roe's average
Matrix L, R; // left and right eigenmatrix
Matrix Lambda(QuantityNb); // diagonal matrix containing the eigenvalues
Matrix A; // absolute value of the jacobian matrix
Vector Lim; // limiter (Van Leer)
int i; // coutner
// vector one.
for(i=1; i<=QuantityNb; i++ )
One.setValue(i,1.);
// --- Get conservative quantities ---
Q1 = Cell1.average();
Q2 = Cell2.average();
Q3 = Cell3.average();
Q4 = Cell4.average();
// --- Get primitive variables ---
// density
rho1 = Cell1.density();
rho2 = Cell2.density();
rho3 = Cell3.density();
rho4 = Cell4.density();
// velocity
V1 = Cell1.velocity();
V2 = Cell2.velocity();
V3 = Cell3.velocity();
V4 = Cell4.velocity();
// energy
rhoE1 = Cell1.energy();
rhoE2 = Cell2.energy();
rhoE3 = Cell3.energy();
rhoE4 = Cell4.energy();
// pressure
p1 = Cell1.pressure();
p2 = Cell2.pressure();
p3 = Cell3.pressure();
p4 = Cell4.pressure();
// --- Compute Euler fluxes ---
F1.setValue(1,rho1*V1.value(AxisNo));
F2.setValue(1,rho2*V2.value(AxisNo));
F3.setValue(1,rho3*V3.value(AxisNo));
F4.setValue(1,rho4*V4.value(AxisNo));
for(i=1; i<=Dimension; i++)
{
F1.setValue(i+1, rho1*V1.value(AxisNo)*V1.value(i) + ((AxisNo == i)? p1 : 0.));
F2.setValue(i+1, rho2*V2.value(AxisNo)*V2.value(i) + ((AxisNo == i)? p2 : 0.));
F3.setValue(i+1, rho3*V3.value(AxisNo)*V3.value(i) + ((AxisNo == i)? p3 : 0.));
F4.setValue(i+1, rho4*V4.value(AxisNo)*V4.value(i) + ((AxisNo == i)? p4 : 0.));
}
F1.setValue(QuantityNb,(rhoE1+p1)*V1.value(AxisNo));
F2.setValue(QuantityNb,(rhoE2+p2)*V2.value(AxisNo));
F3.setValue(QuantityNb,(rhoE3+p3)*V3.value(AxisNo));
F4.setValue(QuantityNb,(rhoE4+p4)*V4.value(AxisNo));
// --- Van Leer limiter ---
// Left
Lim = Limiter(Q3-Q2, Q2-Q1);
FL = F2 + 0.5*(Lim|(F2-F1)) + 0.5*((One-Lim)|(F3-F2));
QL = Q2 + 0.5*(Lim|(Q2-Q1)) + 0.5*((One-Lim)|(Q3-Q2));
// Right
Lim = Limiter(Q3-Q2, Q4-Q3);
FR = F3 - 0.5*(Lim|(F4-F3)) - 0.5*((One-Lim)|(F3-F2));
QR = Q3 - 0.5*(Lim|(Q4-Q3)) - 0.5*((One-Lim)|(Q3-Q2));
/*
FL = F2;
FR = F3;
QL = Q2;
QR = Q3;
*/
// --- Extract left and right primitive variables ---
rhoL = QL.value(1);
rhoR = QR.value(1);
for (i=1; i<= Dimension; i++)
{
VL.setValue(i,QL.value(i+1)/rhoL);
VR.setValue(i,QR.value(i+1)/rhoR);
}
rhoEL=QL.value(QuantityNb);
rhoER=QR.value(QuantityNb);
pL = (Gamma-1)*(rhoEL - .5*rhoL*(VL*VL));
pR = (Gamma-1)*(rhoER - .5*rhoR*(VR*VR));
// --- Compute Roe's averages ---
Roe = sqrt(rhoR/rhoL);
rho = Roe*rhoL;
V = 1./(1.+Roe)*( Roe*VR + VL );
H = 1./(1.+Roe)*( Roe*(rhoER+pR)/rhoR + (rhoEL+pL)/rhoL );
c = sqrt ( (Gamma-1)*( H - 0.5*(V*V) ) );
// --- Compute diagonal matrix containing the absolute value of the eigenvalues ---
for (i=1;i<=Dimension;i++)
Lambda.setValue(i,i, fabs(V.value(AxisNo)));
Lambda.setValue(Dimension+1, Dimension+1, fabs(V.value(AxisNo)+c));
Lambda.setValue(Dimension+2, Dimension+2, fabs(V.value(AxisNo)-c));
// --- Set left and right eigenmatrices ---
L.setEigenMatrix(true, AxisNo, V, c);
R.setEigenMatrix(false, AxisNo, V, c, H);
// --- Compute absolute Jacobian matrix ---
A = R*Lambda*L;
// --- Compute Euler Flux ---
Result = 0.5*(FL+FR) - 0.5*(A*(QR-QL));
return Result;
}
