/*
* main function in order to obtain the
* correct stress using Mohr-Coulomb criteria
*/
void
mohrcoulomb (double c, double phi, double psi, double nu, double ymod,
double eps[4], double *stress, double sigma[4])
{
double elso[5];
double fnew;
for (i = 1; i <= 4; i++) {
elso[i] = 0;
}
for (i = 1; i <= 4; i++) {
cs[i] = stress[i + 3] + sigma[i];
}
invar ();
fnew = mocouf (c, phi);
if (fnew > 0) {
mocopl (phi, psi, nu, ymod);
elso[1] = pl[1][1] * eps[1] + pl[1][2] * eps[2] + pl[1][3] * eps[3];
elso[2] = pl[2][1] * eps[1] + pl[2][2] * eps[2] + pl[2][3] * eps[3];
elso[3] = pl[3][1] * eps[1] + pl[3][2] * eps[2] + pl[3][3] * eps[3];
elso[4] = pl[4][1] * eps[1] + pl[4][2] * eps[2] + pl[4][3] * eps[3];
}
for (i = 1; i <= 4; i++) {
stress[i + 3] = stress[i + 3] + sigma[i] - elso[i];
}
}
int main(const int argc, const char** argv)
{
if (argc != 2) LFATAL("USAGE: %s <image.pgm>", argv[0]);
// let's start by trying out a single model: it starts with our
// initial conditions and we give it a steady input of 255:
SurpriseModelSP m(UPDFAC, INIVAL, VARIANCE); // the model
SurpriseModelSP s(UPDFAC, 255.0f, VARIANCE); // the sample
for (int i = 0; i < NITER; i ++)
LINFO("iter = %d, mean = %f, stdev = %f, surprise = %f",
i, m.getMean(), sqrt(m.getVar()), m.surprise(s));
// get the input feature map:
Image<byte> input = Raster::ReadGray(argv[1]);
// convert to double:
Image<double> in(input);
// create sample variances:
Image<double> invar(input.getDims(), NO_INIT);
invar.clear(VARIANCE);
// create SurpriseImage from our samples and their variances:
SurpriseImage<SurpriseModelSP> sample(UPDFAC, in, invar);
// create an ImageCache to accumulate our results:
ImageCacheMinMax<float> cache;
// create a surprise map:
SurpriseMap<SurpriseModelSP> smap;
smap.init(QLEN, UPDFAC, NUPDFAC, INIVAL, VARIANCE, NEIGHSIGMA, LOCSIGMA);
// let's do it!
for (int i = 0; i < NITER; i ++)
{
// get the surprise:
Image<float> surp = smap.surprise(sample);
float mi, ma; getMinMax(surp, mi, ma);
LINFO("Done %d/%d: [%f .. %f]", i+1, NITER, mi, ma);
// cache it:
cache.push_back(surp);
}
// ok, let's save the results. First find the global max:
Image<float> imax = cache.getMax();
float mi, ma; getMinMax(imax, mi, ma);
LINFO("Global max is %f", ma);
for (int i = 0; i < NITER; i ++)
{
Image<byte> sav(cache.pop_front() * 255.0f / ma);
Raster::WriteGray(sav, sformat("SURP%03d%s", i, argv[1]));
}
return 0;
}
struct syntax_node * input_stm(){
struct syntax_node * t;
t = (struct syntax_node*)malloc(sizeof(struct syntax_node));
chushihua_t(t);
t->child[0] = rev_read();
t->child[1] = zuokuohao();
t->child[2] = invar();
t->child[3] = youkuohao();
strcpy(t->kind_name, "InputStm");
return t;
}
