22590555373

Committed 02 Mar 2026 06:44PM UTC coverage: 81.331% (-0.2%) from 81.508%

Build # 22590555373

Build Type

Pull #3550

github

Committed by

web-flow

Commit Message

Merge d11f2e51a into 823b4c96c

Pull Request Pull Request #3550: [Point Detector] Add distribution get_pdf functionality

Coverage Stats

17484 of 25271 branches covered (69.19%)

Branch coverage included in aggregate %.

53 of 164 new or added lines in 12 files covered. (32.32%)

33 existing lines in 3 files now uncovered.

57704 of 67176 relevant lines covered (85.9%)

44912746.91 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

65.84

/src/secondary_thermal.cpp

#include "openmc/secondary_thermal.h"

#include "openmc/hdf5_interface.h"
#include "openmc/math_functions.h"
#include "openmc/random_lcg.h"
#include "openmc/search.h"
#include "openmc/vector.h"

#include "openmc/tensor.h"

#include <cassert>
#include <cmath> // for log, exp

namespace openmc {

//==============================================================================
// CoherentElasticAE implementation
//==============================================================================

CoherentElasticAE::CoherentElasticAE(const CoherentElasticXS& xs) : xs_ {xs} {}

void CoherentElasticAE::sample(
  double E_in, double& E_out, double& mu, uint64_t* seed) const
{
  // Energy doesn't change in elastic scattering (ENDF-102, Eq. 7-1)
  E_out = E_in;

  const auto& energies {xs_.bragg_edges()};

  assert(E_in >= energies.front());

  const int i = lower_bound_index(energies.begin(), energies.end(), E_in);

  // Sample a Bragg edge between 1 and i
  // E[0] < E_in < E[i+1] -> can scatter in bragg edges 0..i
  const auto& factors = xs_.factors();
  const double prob = prn(seed) * factors[i];

  const int k = std::lower_bound(factors.begin(), factors.begin() + i, prob) -
                factors.begin();

  // Characteristic scattering cosine for this Bragg edge (ENDF-102, Eq. 7-2)
  mu = 1.0 - 2.0 * energies[k] / E_in;
}

double CoherentElasticAE::sample_energy_and_pdf(
  double E_in, double mu, double& E_out, uint64_t* seed) const
{
  // Energy doesn't change in elastic scattering (ENDF-102, Eq. 7-1)

  double pdf;
  E_out = E_in;
  const auto& energies {xs_.bragg_edges()};
  const auto& factors = xs_.factors();

  if (E_in < energies.front() || E_in > energies.back()) {
    return 0;
  }

  const int n = upper_bound_index(energies.begin(), energies.end(), E_in);

  vector<double> mu_vector;
  mu_vector.reserve(n);

  std::transform(energies.rbegin() + n - 1, energies.rend(),
    std::back_inserter(mu_vector),
    [E_in](double Ei) { return 1 - 2 * Ei / E_in; });

  vector<double> weights;
  weights.reserve(n);

  weights.emplace_back(factors[0] / factors[n]);
  for (int i = 1; i <= n; ++i) {
    weights.emplace_back((factors[i] - factors[i - 1]) / factors[n]);
  }
  return get_pdf_discrete(mu_vector, weights, mu);
}

//==============================================================================
// IncoherentElasticAE implementation
//==============================================================================

IncoherentElasticAE::IncoherentElasticAE(hid_t group)
{
  read_dataset(group, "debye_waller", debye_waller_);
}

void IncoherentElasticAE::sample(
  double E_in, double& E_out, double& mu, uint64_t* seed) const
{
  E_out = E_in;

  // Sample angle by inverting the distribution in ENDF-102, Eq. 7.4
  double c = 2 * E_in * debye_waller_;
  mu = std::log(1.0 + prn(seed) * (std::exp(2.0 * c) - 1)) / c - 1.0;
}
double IncoherentElasticAE::sample_energy_and_pdf(
  double E_in, double mu, double& E_out, uint64_t* seed) const
{
  E_out = E_in;

  // Sample angle by inverting the distribution in ENDF-102, Eq. 7.4
  double c = 2 * E_in * debye_waller_;
  double A = c / (1 - std::exp(-2.0 * c)); // normalization factor
  return A * std::exp(-c * (1 - mu));
}

//==============================================================================
// IncoherentElasticAEDiscrete implementation
//==============================================================================

IncoherentElasticAEDiscrete::IncoherentElasticAEDiscrete(
  hid_t group, const vector<double>& energy)
  : energy_ {energy}
{
  read_dataset(group, "mu_out", mu_out_);
}

void IncoherentElasticAEDiscrete::sample(
  double E_in, double& E_out, double& mu, uint64_t* seed) const
{
  // Get index and interpolation factor for elastic grid
  int i;
  double f;
  get_energy_index(energy_, E_in, i, f);

  // Interpolate between two discrete cosines corresponding to neighboring
  // incoming energies.

  // Sample outgoing cosine bin
  int n_mu = mu_out_.shape(1);
  int k = prn(seed) * n_mu;

  // Rather than use the sampled discrete mu directly, it is smeared over
  // a bin of width 0.5*min(mu[k] - mu[k-1], mu[k+1] - mu[k]) centered on the
  // discrete mu value itself.

  // Interpolate kth mu value between distributions at energies i and i+1
  mu = mu_out_(i, k) + f * (mu_out_(i + 1, k) - mu_out_(i, k));

  // Inteprolate (k-1)th mu value between distributions at energies i and i+1.
  // When k==0, pick a value that will smear the cosine out to a minimum of -1.
  double mu_left = (k == 0) ? -1.0 - (mu + 1.0)
                            : mu_out_(i, k - 1) +
                                f * (mu_out_(i + 1, k - 1) - mu_out_(i, k - 1));

  // Inteprolate (k+1)th mu value between distributions at energies i and i+1.
  // When k is the last discrete value, pick a value that will smear the cosine
  // out to a maximum of 1.
  double mu_right =
    (k == n_mu - 1)
      ? 1.0 + (1.0 - mu)
      : mu_out_(i, k + 1) + f * (mu_out_(i + 1, k + 1) - mu_out_(i, k + 1));

  // Smear cosine
  mu += std::min(mu - mu_left, mu_right - mu) * (prn(seed) - 0.5);

  // Energy doesn't change in elastic scattering
  E_out = E_in;
}

double IncoherentElasticAEDiscrete::sample_energy_and_pdf(
  double E_in, double mu, double& E_out, uint64_t* seed) const
{
  // Get index and interpolation factor for elastic grid
  int i;
  double f;
  get_energy_index(energy_, E_in, i, f);
  // Energy doesn't change in elastic scattering
  E_out = E_in;

  double pdf = 0.0;
  pdf += f * get_pdf_discrete(mu_out_.slice(i + 1, tensor::all), mu);
  pdf += (1 - f) * get_pdf_discrete(mu_out_.slice(i, tensor::all), mu);
  return pdf;
}

//==============================================================================
// IncoherentInelasticAEDiscrete implementation
//==============================================================================

IncoherentInelasticAEDiscrete::IncoherentInelasticAEDiscrete(
  hid_t group, const vector<double>& energy)
  : energy_ {energy}
{
  read_dataset(group, "energy_out", energy_out_);
  read_dataset(group, "mu_out", mu_out_);
  read_dataset(group, "skewed", skewed_);
}

void IncoherentInelasticAEDiscrete::sample_params(
  double E_in, double& E_out, int& j, uint64_t* seed) const
{
  // Get index and interpolation factor for inelastic grid
  int i;
  double f;
  get_energy_index(energy_, E_in, i, f);

  // Now that we have an incoming energy bin, we need to determine the outgoing
  // energy bin. This will depend on whether the outgoing energy distribution is
  // skewed. If it is skewed, then the first two and last two bins have lower
  // probabilities than the other bins (0.1 for the first and last bins and 0.4
  // for the second and second to last bins, relative to a normal bin
  // probability of 1). Otherwise, each bin is equally probable.

  int n = energy_out_.shape(1);
  if (!skewed_) {
    // All bins equally likely
    j = prn(seed) * n;
  } else {
    // Distribution skewed away from edge points
    double r = prn(seed) * (n - 3);
    if (r > 1.0) {
      // equally likely N-4 middle bins
      j = r + 1;
    } else if (r > 0.6) {
      // second to last bin has relative probability of 0.4
      j = n - 2;
    } else if (r > 0.5) {
      // last bin has relative probability of 0.1
      j = n - 1;
    } else if (r > 0.1) {
      // second bin has relative probability of 0.4
      j = 1;
    } else {
      // first bin has relative probability of 0.1
      j = 0;
    }
  }

  // Determine outgoing energy corresponding to E_in[i] and E_in[i+1]
  double E_ij = energy_out_(i, j);
  double E_i1j = energy_out_(i + 1, j);

  // Outgoing energy
  E_out = (1 - f) * E_ij + f * E_i1j;
}

void IncoherentInelasticAEDiscrete::sample(
  double E_in, double& E_out, double& mu, uint64_t* seed) const
{
  // Get index and interpolation factor for inelastic grid
  int i;
  double f;
  get_energy_index(energy_, E_in, i, f);

  int j;
  sample_params(E_in, E_out, j, seed);

  // Sample outgoing cosine bin
  int m = mu_out_.shape(2);
  int k = prn(seed) * m;

  // Determine outgoing cosine corresponding to E_in[i] and E_in[i+1]
  double mu_ijk = mu_out_(i, j, k);
  double mu_i1jk = mu_out_(i + 1, j, k);

  // Cosine of angle between incoming and outgoing neutron
  mu = (1 - f) * mu_ijk + f * mu_i1jk;
}

double IncoherentInelasticAEDiscrete::sample_energy_and_pdf(
  double E_in, double mu, double& E_out, uint64_t* seed) const
{
  // Get index and interpolation factor for inelastic grid
  int i;
  double f;
  get_energy_index(energy_, E_in, i, f);
  int j;
  sample_params(E_in, E_out, j, seed);

  double pdf = 0.0;
  pdf += f * get_pdf_discrete(mu_out_.slice(i + 1, j, tensor::all), mu);
  pdf += (1 - f) * get_pdf_discrete(mu_out_.slice(i, j, tensor::all), mu);
  return pdf;
}

//==============================================================================
// IncoherentInelasticAE implementation
//==============================================================================

IncoherentInelasticAE::IncoherentInelasticAE(hid_t group)
{
  // Read correlated angle-energy distribution
  CorrelatedAngleEnergy dist {group};

  // Copy incident energies
  energy_ = dist.energy();

  // Convert to S(a,b) native format
  for (const auto& edist : dist.distribution()) {
    // Create temporary distribution
    DistEnergySab d;

    // Copy outgoing energy distribution
    d.n_e_out = edist.e_out.size();
    d.e_out = edist.e_out;
    d.e_out_pdf = edist.p;
    d.e_out_cdf = edist.c;

    for (int j = 0; j < d.n_e_out; ++j) {
      auto adist = dynamic_cast<Tabular*>(edist.angle[j].get());
      if (adist) {
        // On first pass, allocate space for angles
        if (j == 0) {
          auto n_mu = adist->x().size();
          d.mu = tensor::Tensor<double>({d.n_e_out, n_mu});
        }

        // Copy outgoing angles
        tensor::View<double> mu_j = d.mu.slice(j);
        std::copy(adist->x().begin(), adist->x().end(), mu_j.begin());
      }
    }

    distribution_.emplace_back(std::move(d));
  }
}

void IncoherentInelasticAE::sample_params(
  double E_in, double& E_out, double& f, int& l, int& j, uint64_t* seed) const
{
  // Get index and interpolation factor for inelastic grid
  int i;
  double f0;
  get_energy_index(energy_, E_in, i, f0);

  // Pick closer energy based on interpolation factor
  l = f0 > 0.5 ? i + 1 : i;

  // Determine outgoing energy bin
  // (First reset n_energy_out to the right value)
  int n = distribution_[l].n_e_out;
  double r1 = prn(seed);
  double c_j = distribution_[l].e_out_cdf[0];
  double c_j1;
  for (j = 0; j < n - 1; ++j) {
    c_j1 = distribution_[l].e_out_cdf[j + 1];
    if (r1 < c_j1)
      break;
    c_j = c_j1;
  }

  // check to make sure j is <= n_energy_out - 2
  j = std::min(j, n - 2);

  // Get the data to interpolate between
  double E_l_j = distribution_[l].e_out[j];
  double p_l_j = distribution_[l].e_out_pdf[j];

  // Next part assumes linear-linear interpolation in standard
  double E_l_j1 = distribution_[l].e_out[j + 1];
  double p_l_j1 = distribution_[l].e_out_pdf[j + 1];

  // Find secondary energy (variable E)
  double frac = (p_l_j1 - p_l_j) / (E_l_j1 - E_l_j);
  if (frac == 0.0) {
    E_out = E_l_j + (r1 - c_j) / p_l_j;
  } else {
    E_out = E_l_j +
            (std::sqrt(std::max(0.0, p_l_j * p_l_j + 2.0 * frac * (r1 - c_j))) -
              p_l_j) /
              frac;
  }

  // Adjustment of outgoing energy
  double E_l = energy_[l];
  if (E_out < 0.5 * E_l) {
    E_out *= 2.0 * E_in / E_l - 1.0;
  } else {
    E_out += E_in - E_l;
  }

  f = (r1 - c_j) / (c_j1 - c_j);
}
void IncoherentInelasticAE::sample(
  double E_in, double& E_out, double& mu, uint64_t* seed) const
{
  double f;
  int l, j;
  sample_params(E_in, E_out, f, l, j, seed);

  // Sample outgoing cosine bin
  int n_mu = distribution_[l].mu.shape(1);
  std::size_t k = prn(seed) * n_mu;

  // Rather than use the sampled discrete mu directly, it is smeared over
  // a bin of width 0.5*min(mu[k] - mu[k-1], mu[k+1] - mu[k]) centered on the
  // discrete mu value itself.
  const auto& mu_l = distribution_[l].mu;

  // Interpolate kth mu value between distributions at energies j and j+1
  mu = mu_l(j, k) + f * (mu_l(j + 1, k) - mu_l(j, k));

  // Inteprolate (k-1)th mu value between distributions at energies j and j+1.
  // When k==0, pick a value that will smear the cosine out to a minimum of -1.
  double mu_left =
    (k == 0)
      ? mu_left = -1.0 - (mu + 1.0)
      : mu_left = mu_l(j, k - 1) + f * (mu_l(j + 1, k - 1) - mu_l(j, k - 1));

  // Inteprolate (k+1)th mu value between distributions at energies j and j+1.
  // When k is the last discrete value, pick a value that will smear the cosine
  // out to a maximum of 1.
  double mu_right =
    (k == n_mu - 1)
      ? mu_right = 1.0 + (1.0 - mu)
      : mu_right = mu_l(j, k + 1) + f * (mu_l(j + 1, k + 1) - mu_l(j, k + 1));

  // Smear cosine
  mu += std::min(mu - mu_left, mu_right - mu) * (prn(seed) - 0.5);
}

double IncoherentInelasticAE::sample_energy_and_pdf(
  double E_in, double mu, double& E_out, uint64_t* seed) const
{
  double f;
  int l, j;
  sample_params(E_in, E_out, f, l, j, seed);

  int n_mu = distribution_[l].mu.shape()[1];
  const auto& mu_l = distribution_[l].mu;

  double pdf = 0.0;
  pdf += f * get_pdf_discrete(mu_l.slice(j + 1, tensor::all), mu);
  pdf += (1 - f) * get_pdf_discrete(mu_l.slice(j, tensor::all), mu);
  return pdf;
}

//==============================================================================
// MixedElasticAE implementation
//==============================================================================

MixedElasticAE::MixedElasticAE(
  hid_t group, const CoherentElasticXS& coh_xs, const Function1D& incoh_xs)
  : coherent_dist_(coh_xs), coherent_xs_(coh_xs), incoherent_xs_(incoh_xs)
{
  // Read incoherent elastic distribution
  hid_t incoherent_group = open_group(group, "incoherent");
  std::string temp;
  read_attribute(incoherent_group, "type", temp);
  if (temp == "incoherent_elastic") {
    incoherent_dist_ = make_unique<IncoherentElasticAE>(incoherent_group);
  } else if (temp == "incoherent_elastic_discrete") {
    auto xs = dynamic_cast<const Tabulated1D*>(&incoh_xs);
    incoherent_dist_ =
      make_unique<IncoherentElasticAEDiscrete>(incoherent_group, xs->x());
  }
  close_group(incoherent_group);
}

const AngleEnergy& MixedElasticAE::sample_dist(
  double E_in, uint64_t* seed) const
{
  // Evaluate coherent and incoherent elastic cross sections
  double xs_coh = coherent_xs_(E_in);
  double xs_incoh = incoherent_xs_(E_in);

  if (prn(seed) * (xs_coh + xs_incoh) < xs_coh) {
    return coherent_dist_;
  } else {
    return *incoherent_dist_;
  }
}

void MixedElasticAE::sample(
  double E_in, double& E_out, double& mu, uint64_t* seed) const
{
  sample_dist(E_in, seed).sample(E_in, E_out, mu, seed);
}

double MixedElasticAE::sample_energy_and_pdf(
  double E_in, double mu, double& E_out, uint64_t* seed) const
{
  return sample_dist(E_in, seed).sample_energy_and_pdf(E_in, mu, E_out, seed);
}

} // namespace openmc

1	#include "openmc/secondary_thermal.h"
2
3	#include "openmc/hdf5_interface.h"
4	#include "openmc/math_functions.h"
5	#include "openmc/random_lcg.h"
6	#include "openmc/search.h"
7	#include "openmc/vector.h"
8
9	#include "openmc/tensor.h"
10
11	#include <cassert>
12	#include <cmath> // for log, exp
13
14	namespace openmc {
15
16	//==============================================================================
17	// CoherentElasticAE implementation
18	//==============================================================================
19
20	CoherentElasticAE::CoherentElasticAE(const CoherentElasticXS& xs) : xs_ {xs} {}	134✔
21
22	void CoherentElasticAE::sample(	178,013✔
23	double E_in, double& E_out, double& mu, uint64_t* seed) const
24	{
25	// Energy doesn't change in elastic scattering (ENDF-102, Eq. 7-1)
26	E_out = E_in;	178,013✔
27
28	const auto& energies {xs_.bragg_edges()};	178,013!
29
30	assert(E_in >= energies.front());	178,013!
31
32	const int i = lower_bound_index(energies.begin(), energies.end(), E_in);	178,013✔
33
34	// Sample a Bragg edge between 1 and i
35	// E[0] < E_in < E[i+1] -> can scatter in bragg edges 0..i
36	const auto& factors = xs_.factors();	178,013✔
37	const double prob = prn(seed) * factors[i];	178,013✔
38
39	const int k = std::lower_bound(factors.begin(), factors.begin() + i, prob) -	178,013✔
40	factors.begin();	178,013✔
41
42	// Characteristic scattering cosine for this Bragg edge (ENDF-102, Eq. 7-2)
43	mu = 1.0 - 2.0 * energies[k] / E_in;	178,013✔
44	}	178,013✔
45
UNCOV 46	double CoherentElasticAE::sample_energy_and_pdf(	×
47	double E_in, double mu, double& E_out, uint64_t* seed) const
48	{
49	// Energy doesn't change in elastic scattering (ENDF-102, Eq. 7-1)
50
UNCOV 51	double pdf;	×
UNCOV 52	E_out = E_in;	×
UNCOV 53	const auto& energies {xs_.bragg_edges()};	×
UNCOV 54	const auto& factors = xs_.factors();	×
55
NEW 56	if (E_in < energies.front() \|\| E_in > energies.back()) {	×
57	return 0;
58	}
59
NEW 60	const int n = upper_bound_index(energies.begin(), energies.end(), E_in);	×
61
NEW 62	vector<double> mu_vector;	×
NEW 63	mu_vector.reserve(n);	×
64
NEW 65	std::transform(energies.rbegin() + n - 1, energies.rend(),	×
66	std::back_inserter(mu_vector),
NEW 67	[E_in](double Ei) { return 1 - 2 * Ei / E_in; });	×
68
NEW 69	vector<double> weights;	×
NEW 70	weights.reserve(n);	×
71
NEW 72	weights.emplace_back(factors[0] / factors[n]);	×
NEW 73	for (int i = 1; i <= n; ++i) {	×
NEW 74	weights.emplace_back((factors[i] - factors[i - 1]) / factors[n]);	×
75	}
NEW 76	return get_pdf_discrete(mu_vector, weights, mu);	×
NEW 77	}	×
78
79	//==============================================================================
80	// IncoherentElasticAE implementation
81	//==============================================================================
82
UNCOV 83	IncoherentElasticAE::IncoherentElasticAE(hid_t group)	×
84	{
UNCOV 85	read_dataset(group, "debye_waller", debye_waller_);	×
86	}	×
87
88	void IncoherentElasticAE::sample(	×
89	double E_in, double& E_out, double& mu, uint64_t* seed) const
90	{
91	E_out = E_in;	×
92
93	// Sample angle by inverting the distribution in ENDF-102, Eq. 7.4
NEW 94	double c = 2 * E_in * debye_waller_;	×
NEW 95	mu = std::log(1.0 + prn(seed) * (std::exp(2.0 * c) - 1)) / c - 1.0;	×
96	}	×
97	double IncoherentElasticAE::sample_energy_and_pdf(	×
98	double E_in, double mu, double& E_out, uint64_t* seed) const
99	{
NEW 100	E_out = E_in;	×
101
102	// Sample angle by inverting the distribution in ENDF-102, Eq. 7.4
103	double c = 2 * E_in * debye_waller_;	×
NEW 104	double A = c / (1 - std::exp(-2.0 * c)); // normalization factor	×
NEW 105	return A * std::exp(-c * (1 - mu));	×
106	}
107
108	//==============================================================================
109	// IncoherentElasticAEDiscrete implementation
110	//==============================================================================
111
112	IncoherentElasticAEDiscrete::IncoherentElasticAEDiscrete(	44✔
113	hid_t group, const vector<double>& energy)	44✔
114	: energy_ {energy}	44✔
115	{
116	read_dataset(group, "mu_out", mu_out_);	44✔
117	}	44✔
118
119	void IncoherentElasticAEDiscrete::sample(	1,342✔
120	double E_in, double& E_out, double& mu, uint64_t* seed) const
121	{
122	// Get index and interpolation factor for elastic grid
123	int i;	1,342✔
124	double f;	1,342✔
125	get_energy_index(energy_, E_in, i, f);	1,342✔
126
127	// Interpolate between two discrete cosines corresponding to neighboring
128	// incoming energies.
129
130	// Sample outgoing cosine bin
131	int n_mu = mu_out_.shape(1);	1,342!
132	int k = prn(seed) * n_mu;	1,342✔
133
134	// Rather than use the sampled discrete mu directly, it is smeared over
135	// a bin of width 0.5*min(mu[k] - mu[k-1], mu[k+1] - mu[k]) centered on the
136	// discrete mu value itself.
137
138	// Interpolate kth mu value between distributions at energies i and i+1
139	mu = mu_out_(i, k) + f * (mu_out_(i + 1, k) - mu_out_(i, k));	1,342✔
140
141	// Inteprolate (k-1)th mu value between distributions at energies i and i+1.
142	// When k==0, pick a value that will smear the cosine out to a minimum of -1.
143	double mu_left = (k == 0) ? -1.0 - (mu + 1.0)	1,342✔
144	: mu_out_(i, k - 1) +	990✔
145	f * (mu_out_(i + 1, k - 1) - mu_out_(i, k - 1));	990✔
146
147	// Inteprolate (k+1)th mu value between distributions at energies i and i+1.
148	// When k is the last discrete value, pick a value that will smear the cosine
149	// out to a maximum of 1.
150	double mu_right =	1,342✔
151	(k == n_mu - 1)	1,342✔
152	? 1.0 + (1.0 - mu)	1,342✔
153	: mu_out_(i, k + 1) + f * (mu_out_(i + 1, k + 1) - mu_out_(i, k + 1));	990✔
154
155	// Smear cosine
156	mu += std::min(mu - mu_left, mu_right - mu) * (prn(seed) - 0.5);	1,947✔
157
158	// Energy doesn't change in elastic scattering
159	E_out = E_in;	1,342✔
160	}	1,342✔
161
UNCOV 162	double IncoherentElasticAEDiscrete::sample_energy_and_pdf(	×
163	double E_in, double mu, double& E_out, uint64_t* seed) const
164	{
165	// Get index and interpolation factor for elastic grid
NEW 166	int i;	×
NEW 167	double f;	×
NEW 168	get_energy_index(energy_, E_in, i, f);	×
169	// Energy doesn't change in elastic scattering
NEW 170	E_out = E_in;	×
171
NEW 172	double pdf = 0.0;	×
NEW 173	pdf += f * get_pdf_discrete(mu_out_.slice(i + 1, tensor::all), mu);	×
NEW 174	pdf += (1 - f) * get_pdf_discrete(mu_out_.slice(i, tensor::all), mu);	×
NEW 175	return pdf;	×
176	}
177
178	//==============================================================================
179	// IncoherentInelasticAEDiscrete implementation
180	//==============================================================================
181
182	IncoherentInelasticAEDiscrete::IncoherentInelasticAEDiscrete(	1,240✔
183	hid_t group, const vector<double>& energy)	1,240✔
184	: energy_ {energy}	1,240✔
185	{
186	read_dataset(group, "energy_out", energy_out_);	1,240✔
187	read_dataset(group, "mu_out", mu_out_);	1,240✔
188	read_dataset(group, "skewed", skewed_);	1,240✔
189	}	1,240✔
190
191	void IncoherentInelasticAEDiscrete::sample_params(	123,683,823✔
192	double E_in, double& E_out, int& j, uint64_t* seed) const
193	{
194	// Get index and interpolation factor for inelastic grid
195	int i;	123,683,823✔
196	double f;	123,683,823✔
197	get_energy_index(energy_, E_in, i, f);	123,683,823✔
198
199	// Now that we have an incoming energy bin, we need to determine the outgoing
200	// energy bin. This will depend on whether the outgoing energy distribution is
201	// skewed. If it is skewed, then the first two and last two bins have lower
202	// probabilities than the other bins (0.1 for the first and last bins and 0.4
203	// for the second and second to last bins, relative to a normal bin
204	// probability of 1). Otherwise, each bin is equally probable.
205
206	int n = energy_out_.shape(1);	123,683,823!
207	if (!skewed_) {	123,683,823!
208	// All bins equally likely
UNCOV 209	j = prn(seed) * n;	×
210	} else {
211	// Distribution skewed away from edge points
212	double r = prn(seed) * (n - 3);	123,683,823✔
213	if (r > 1.0) {	123,683,823✔
214	// equally likely N-4 middle bins
215	j = r + 1;	121,650,936✔
216	} else if (r > 0.6) {	2,032,887✔
217	// second to last bin has relative probability of 0.4
218	j = n - 2;	806,605✔
219	} else if (r > 0.5) {	1,226,282✔
220	// last bin has relative probability of 0.1
221	j = n - 1;	203,402✔
222	} else if (r > 0.1) {	1,022,880✔
223	// second bin has relative probability of 0.4
224	j = 1;	819,261✔
225	} else {
226	// first bin has relative probability of 0.1
227	j = 0;	203,619✔
228	}
229	}
230
231	// Determine outgoing energy corresponding to E_in[i] and E_in[i+1]
232	double E_ij = energy_out_(i, j);	123,683,823✔
233	double E_i1j = energy_out_(i + 1, j);	123,683,823✔
234
235	// Outgoing energy
236	E_out = (1 - f) * E_ij + f * E_i1j;	123,683,823✔
237	}	123,683,823✔
238
239	void IncoherentInelasticAEDiscrete::sample(	123,683,823✔
240	double E_in, double& E_out, double& mu, uint64_t* seed) const
241	{
242	// Get index and interpolation factor for inelastic grid
243	int i;	123,683,823✔
244	double f;	123,683,823✔
245	get_energy_index(energy_, E_in, i, f);	123,683,823✔
246
247	int j;	123,683,823✔
248	sample_params(E_in, E_out, j, seed);	123,683,823✔
249
250	// Sample outgoing cosine bin
251	int m = mu_out_.shape(2);	123,683,823!
252	int k = prn(seed) * m;	123,683,823✔
253
254	// Determine outgoing cosine corresponding to E_in[i] and E_in[i+1]
255	double mu_ijk = mu_out_(i, j, k);	123,683,823✔
256	double mu_i1jk = mu_out_(i + 1, j, k);	123,683,823✔
257
258	// Cosine of angle between incoming and outgoing neutron
259	mu = (1 - f) * mu_ijk + f * mu_i1jk;	123,683,823✔
260	}	123,683,823✔
261
UNCOV 262	double IncoherentInelasticAEDiscrete::sample_energy_and_pdf(	×
263	double E_in, double mu, double& E_out, uint64_t* seed) const
264	{
265	// Get index and interpolation factor for inelastic grid
NEW 266	int i;	×
NEW 267	double f;	×
NEW 268	get_energy_index(energy_, E_in, i, f);	×
NEW 269	int j;	×
NEW 270	sample_params(E_in, E_out, j, seed);	×
271
NEW 272	double pdf = 0.0;	×
NEW 273	pdf += f * get_pdf_discrete(mu_out_.slice(i + 1, j, tensor::all), mu);	×
NEW 274	pdf += (1 - f) * get_pdf_discrete(mu_out_.slice(i, j, tensor::all), mu);	×
NEW 275	return pdf;	×
276	}
277
278	//==============================================================================
279	// IncoherentInelasticAE implementation
280	//==============================================================================
281
282	IncoherentInelasticAE::IncoherentInelasticAE(hid_t group)	44✔
283	{
284	// Read correlated angle-energy distribution
285	CorrelatedAngleEnergy dist {group};	44✔
286
287	// Copy incident energies
288	energy_ = dist.energy();	44✔
289
290	// Convert to S(a,b) native format
291	for (const auto& edist : dist.distribution()) {	176✔
292	// Create temporary distribution
293	DistEnergySab d;	132✔
294
295	// Copy outgoing energy distribution
296	d.n_e_out = edist.e_out.size();	132✔
297	d.e_out = edist.e_out;	132✔
298	d.e_out_pdf = edist.p;	132✔
299	d.e_out_cdf = edist.c;	132✔
300
301	for (int j = 0; j < d.n_e_out; ++j) {	660✔
302	auto adist = dynamic_cast<Tabular*>(edist.angle[j].get());	528!
303	if (adist) {	528!
304	// On first pass, allocate space for angles
305	if (j == 0) {	528✔
306	auto n_mu = adist->x().size();	132✔
307	d.mu = tensor::Tensor<double>({d.n_e_out, n_mu});	264✔
308	}
309
310	// Copy outgoing angles
311	tensor::View<double> mu_j = d.mu.slice(j);	528✔
312	std::copy(adist->x().begin(), adist->x().end(), mu_j.begin());	528✔
313	}	528✔
314	}
315
316	distribution_.emplace_back(std::move(d));	132✔
317	}	132✔
318	}	44✔
319
320	void IncoherentInelasticAE::sample_params(	3,614,897✔
321	double E_in, double& E_out, double& f, int& l, int& j, uint64_t* seed) const
322	{
323	// Get index and interpolation factor for inelastic grid
324	int i;	3,614,897✔
325	double f0;	3,614,897✔
326	get_energy_index(energy_, E_in, i, f0);	3,614,897✔
327
328	// Pick closer energy based on interpolation factor
329	l = f0 > 0.5 ? i + 1 : i;	3,614,897✔
330
331	// Determine outgoing energy bin
332	// (First reset n_energy_out to the right value)
333	int n = distribution_[l].n_e_out;	3,614,897✔
334	double r1 = prn(seed);	3,614,897✔
335	double c_j = distribution_[l].e_out_cdf[0];	3,614,897✔
336	double c_j1;	3,614,897✔
337	for (j = 0; j < n - 1; ++j) {	8,721,537!
338	c_j1 = distribution_[l].e_out_cdf[j + 1];	8,721,537✔
339	if (r1 < c_j1)	8,721,537✔
340	break;
341	c_j = c_j1;	5,106,640✔
342	}
343
344	// check to make sure j is <= n_energy_out - 2
345	j = std::min(j, n - 2);	3,614,897!
346
347	// Get the data to interpolate between
348	double E_l_j = distribution_[l].e_out[j];	3,614,897!
349	double p_l_j = distribution_[l].e_out_pdf[j];	3,614,897✔
350
351	// Next part assumes linear-linear interpolation in standard
352	double E_l_j1 = distribution_[l].e_out[j + 1];	3,614,897✔
353	double p_l_j1 = distribution_[l].e_out_pdf[j + 1];	3,614,897✔
354
355	// Find secondary energy (variable E)
356	double frac = (p_l_j1 - p_l_j) / (E_l_j1 - E_l_j);	3,614,897✔
357	if (frac == 0.0) {	3,614,897!
358	E_out = E_l_j + (r1 - c_j) / p_l_j;	3,614,897✔
359	} else {
UNCOV 360	E_out = E_l_j +	×
UNCOV 361	(std::sqrt(std::max(0.0, p_l_j * p_l_j + 2.0 * frac * (r1 - c_j))) -	×
UNCOV 362	p_l_j) /	×
363	frac;
364	}
365
366	// Adjustment of outgoing energy
367	double E_l = energy_[l];	3,614,897✔
368	if (E_out < 0.5 * E_l) {	3,614,897✔
369	E_out = 2.0 E_in / E_l - 1.0;	344,476✔
370	} else {
371	E_out += E_in - E_l;	3,270,421✔
372	}
373
374	f = (r1 - c_j) / (c_j1 - c_j);	3,614,897✔
375	}	3,614,897✔
376	void IncoherentInelasticAE::sample(	3,614,897✔
377	double E_in, double& E_out, double& mu, uint64_t* seed) const
378	{
379	double f;	3,614,897✔
380	int l, j;	3,614,897✔
381	sample_params(E_in, E_out, f, l, j, seed);	3,614,897✔
382
383	// Sample outgoing cosine bin
384	int n_mu = distribution_[l].mu.shape(1);	3,614,897!
385	std::size_t k = prn(seed) * n_mu;	3,614,897✔
386
387	// Rather than use the sampled discrete mu directly, it is smeared over
388	// a bin of width 0.5*min(mu[k] - mu[k-1], mu[k+1] - mu[k]) centered on the
389	// discrete mu value itself.
390	const auto& mu_l = distribution_[l].mu;	3,614,897✔
391
392	// Interpolate kth mu value between distributions at energies j and j+1
393	mu = mu_l(j, k) + f * (mu_l(j + 1, k) - mu_l(j, k));	3,614,897✔
394
395	// Inteprolate (k-1)th mu value between distributions at energies j and j+1.
396	// When k==0, pick a value that will smear the cosine out to a minimum of -1.
397	double mu_left =	3,614,897✔
398	(k == 0)
399	? mu_left = -1.0 - (mu + 1.0)	3,614,897✔
400	: mu_left = mu_l(j, k - 1) + f * (mu_l(j + 1, k - 1) - mu_l(j, k - 1));	3,159,464✔
401
402	// Inteprolate (k+1)th mu value between distributions at energies j and j+1.
403	// When k is the last discrete value, pick a value that will smear the cosine
404	// out to a maximum of 1.
405	double mu_right =	3,614,897✔
406	(k == n_mu - 1)	3,614,897✔
407	? mu_right = 1.0 + (1.0 - mu)	3,614,897✔
408	: mu_right = mu_l(j, k + 1) + f * (mu_l(j + 1, k + 1) - mu_l(j, k + 1));	3,160,762✔
409
410	// Smear cosine
411	mu += std::min(mu - mu_left, mu_right - mu) * (prn(seed) - 0.5);	5,427,510✔
412	}	3,614,897✔
413
UNCOV 414	double IncoherentInelasticAE::sample_energy_and_pdf(	×
415	double E_in, double mu, double& E_out, uint64_t* seed) const
416	{
NEW 417	double f;	×
NEW 418	int l, j;	×
NEW 419	sample_params(E_in, E_out, f, l, j, seed);	×
420
NEW 421	int n_mu = distribution_[l].mu.shape()[1];	×
NEW 422	const auto& mu_l = distribution_[l].mu;	×
423
NEW 424	double pdf = 0.0;	×
NEW 425	pdf += f * get_pdf_discrete(mu_l.slice(j + 1, tensor::all), mu);	×
NEW 426	pdf += (1 - f) * get_pdf_discrete(mu_l.slice(j, tensor::all), mu);	×
NEW 427	return pdf;	×
428	}
429
430	//==============================================================================
431	// MixedElasticAE implementation
432	//==============================================================================
433
434	MixedElasticAE::MixedElasticAE(	44✔
435	hid_t group, const CoherentElasticXS& coh_xs, const Function1D& incoh_xs)	44✔
436	: coherent_dist_(coh_xs), coherent_xs_(coh_xs), incoherent_xs_(incoh_xs)	44✔
437	{
438	// Read incoherent elastic distribution
439	hid_t incoherent_group = open_group(group, "incoherent");	44✔
440	std::string temp;	44✔
441	read_attribute(incoherent_group, "type", temp);	44✔
442	if (temp == "incoherent_elastic") {	44!
UNCOV 443	incoherent_dist_ = make_unique<IncoherentElasticAE>(incoherent_group);	×
444	} else if (temp == "incoherent_elastic_discrete") {	44!
445	auto xs = dynamic_cast<const Tabulated1D*>(&incoh_xs);	44✔
446	incoherent_dist_ =	44✔
447	make_unique<IncoherentElasticAEDiscrete>(incoherent_group, xs->x());	44✔
448	}
449	close_group(incoherent_group);	44✔
450	}	44✔
451
452	const AngleEnergy& MixedElasticAE::sample_dist(	46,486✔
453	double E_in, uint64_t* seed) const
454	{
455	// Evaluate coherent and incoherent elastic cross sections
456	double xs_coh = coherent_xs_(E_in);	46,486✔
457	double xs_incoh = incoherent_xs_(E_in);	46,486✔
458
459	if (prn(seed) * (xs_coh + xs_incoh) < xs_coh) {	46,486✔
460	return coherent_dist_;	45,144✔
461	} else {
462	return *incoherent_dist_;	1,342✔
463	}
464	}
465
466	void MixedElasticAE::sample(	46,486✔
467	double E_in, double& E_out, double& mu, uint64_t* seed) const
468	{
469	sample_dist(E_in, seed).sample(E_in, E_out, mu, seed);	46,486✔
470	}	46,486✔
471
NEW 472	double MixedElasticAE::sample_energy_and_pdf(	×
473	double E_in, double mu, double& E_out, uint64_t* seed) const
474	{
NEW 475	return sample_dist(E_in, seed).sample_energy_and_pdf(E_in, mu, E_out, seed);	×
476	}
477
478	} // namespace openmc

openmc-dev / openmc / 22590555373

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous