14840340664

Committed 05 May 2025 03:38PM UTC coverage: 85.195% (-0.009%) from 85.204%

Build # 14840340664

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Pull #3392

github

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web-flow

Commit Message

Merge 5bc1ec35f into 1e7d8324e

Pull Request Pull Request #3392: Map Compton subshell data to atomic relaxation data

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/include/openmc/scattdata.h

//! \file scattdata.h
//! A collection of multi-group scattering data classes

#ifndef OPENMC_SCATTDATA_H
#define OPENMC_SCATTDATA_H

#include "xtensor/xtensor.hpp"

#include "openmc/constants.h"
#include "openmc/vector.h"

namespace openmc {

// forward declarations so we can name our friend functions
class ScattDataLegendre;
class ScattDataTabular;

//==============================================================================
// SCATTDATA contains all the data needed to describe the scattering energy and
// angular distribution data
//==============================================================================

class ScattData {
public:
  virtual ~ScattData() = default;

protected:
  //! \brief Initializes the attributes of the base class.
  void base_init(int order, const xt::xtensor<int, 1>& in_gmin,
    const xt::xtensor<int, 1>& in_gmax, const double_2dvec& in_energy,
    const double_2dvec& in_mult);

  //! \brief Combines microscopic ScattDatas into a macroscopic one.
  void base_combine(size_t max_order, size_t order_dim,
    const vector<ScattData*>& those_scatts, const vector<double>& scalars,
    xt::xtensor<int, 1>& in_gmin, xt::xtensor<int, 1>& in_gmax,
    double_2dvec& sparse_mult, double_3dvec& sparse_scatter);

public:
  double_2dvec energy;            // Normalized p0 matrix for sampling Eout
  double_2dvec mult;              // nu-scatter multiplication (nu-scatt/scatt)
  double_3dvec dist;              // Angular distribution
  xt::xtensor<int, 1> gmin;       // minimum outgoing group
  xt::xtensor<int, 1> gmax;       // maximum outgoing group
  xt::xtensor<double, 1> scattxs; // Isotropic Sigma_{s,g_{in}}

  //! \brief Calculates the value of normalized f(mu).
  //!
  //! The value of f(mu) is normalized as in the integral of f(mu)dmu across
  //! [-1,1] is 1.
  //!
  //! @param gin Incoming energy group of interest.
  //! @param gout Outgoing energy group of interest.
  //! @param mu Cosine of the change-in-angle of interest.
  //! @return The value of f(mu).
  virtual double calc_f(int gin, int gout, double mu) = 0;

  //! \brief Samples the outgoing energy and angle from the ScattData info.
  //!
  //! @param gin Incoming energy group.
  //! @param gout Sampled outgoing energy group.
  //! @param mu Sampled cosine of the change-in-angle.
  //! @param wgt Weight of the particle to be adjusted.
  //! @param seed Pseudorandom number seed pointer
  virtual void sample(
    int gin, int& gout, double& mu, double& wgt, uint64_t* seed) = 0;

  //! \brief Initializes the ScattData object from a given scatter and
  //!   multiplicity matrix.
  //!
  //! @param in_gmin List of minimum outgoing groups for every incoming group
  //! @param in_gmax List of maximum outgoing groups for every incoming group
  //! @param in_mult Input sparse multiplicity matrix
  //! @param coeffs Input sparse scattering matrix
  virtual void init(const xt::xtensor<int, 1>& in_gmin,
    const xt::xtensor<int, 1>& in_gmax, const double_2dvec& in_mult,
    const double_3dvec& coeffs) = 0;

  //! \brief Combines the microscopic data.
  //!
  //! @param those_scatts Microscopic objects to combine.
  //! @param scalars Scalars to multiply the microscopic data by.
  virtual void combine(
    const vector<ScattData*>& those_scatts, const vector<double>& scalars) = 0;

  //! \brief Getter for the dimensionality of the scattering order.
  //!
  //! If Legendre this is the "n" in "Pn"; for Tabular, this is the number
  //! of points, and for Histogram this is the number of bins.
  //!
  //! @return The order.
  virtual size_t get_order() = 0;

  //! \brief Builds a dense scattering matrix from the constituent parts
  //!
  //! @param max_order If Legendre this is the maximum value of "n" in "Pn"
  //!   requested; ignored otherwise.
  //! @return The dense scattering matrix.
  virtual xt::xtensor<double, 3> get_matrix(size_t max_order) = 0;

  //! \brief Samples the outgoing energy from the ScattData info.
  //!
  //! @param gin Incoming energy group.
  //! @param gout Sampled outgoing energy group.
  //! @param i_gout Sampled outgoing energy group index.
  //! @param seed Pseudorandom number seed pointer
  void sample_energy(int gin, int& gout, int& i_gout, uint64_t* seed);

  //! \brief Provides a cross section value given certain parameters
  //!
  //! @param xstype Type of cross section requested, according to the
  //!   enumerated constants.
  //! @param gin Incoming energy group.
  //! @param gout Outgoing energy group; use nullptr if irrelevant, or if a
  //!   sum is requested.
  //! @param mu Cosine of the change-in-angle, for scattering quantities;
  //!   use nullptr if irrelevant.
  //! @return Requested cross section value.
  double get_xs(MgxsType xstype, int gin, const int* gout, const double* mu);
};

//==============================================================================
// ScattDataLegendre represents the angular distributions as Legendre kernels
//==============================================================================

class ScattDataLegendre : public ScattData {

protected:
  // Maximal value for rejection sampling from a rectangle
  double_2dvec max_val;

  // Friend convert_legendre_to_tabular so it has access to protected
  // parameters
  friend void convert_legendre_to_tabular(
    ScattDataLegendre& leg, ScattDataTabular& tab);

public:
  void init(const xt::xtensor<int, 1>& in_gmin,
    const xt::xtensor<int, 1>& in_gmax, const double_2dvec& in_mult,
    const double_3dvec& coeffs) override;

  void combine(const vector<ScattData*>& those_scatts,
    const vector<double>& scalars) override;

  //! \brief Find the maximal value of the angular distribution to use as a
  // bounding box with rejection sampling.
  void update_max_val();

  double calc_f(int gin, int gout, double mu) override;

  void sample(
    int gin, int& gout, double& mu, double& wgt, uint64_t* seed) override;

  size_t get_order() override { return dist[0][0].size() - 1; };

  xt::xtensor<double, 3> get_matrix(size_t max_order) override;
};

//==============================================================================
// ScattDataHistogram represents the angular distributions as a histogram, as it
// would be if it came from a "mu" tally in OpenMC
//==============================================================================

class ScattDataHistogram : public ScattData {

protected:
  xt::xtensor<double, 1> mu; // Angle distribution mu bin boundaries
  double dmu;                // Quick storage of the mu spacing
  double_3dvec fmu;          // The angular distribution histogram

public:
  void init(const xt::xtensor<int, 1>& in_gmin,
    const xt::xtensor<int, 1>& in_gmax, const double_2dvec& in_mult,
    const double_3dvec& coeffs) override;

  void combine(const vector<ScattData*>& those_scatts,
    const vector<double>& scalars) override;

  double calc_f(int gin, int gout, double mu) override;

  void sample(
    int gin, int& gout, double& mu, double& wgt, uint64_t* seed) override;

  size_t get_order() override { return dist[0][0].size(); };

  xt::xtensor<double, 3> get_matrix(size_t max_order) override;
};

//==============================================================================
// ScattDataTabular represents the angular distributions as a table of mu and
// f(mu)
//==============================================================================

class ScattDataTabular : public ScattData {

protected:
  xt::xtensor<double, 1> mu; // Angle distribution mu grid points
  double dmu;                // Quick storage of the mu spacing
  double_3dvec fmu;          // The angular distribution function

  // Friend convert_legendre_to_tabular so it has access to protected
  // parameters
  friend void convert_legendre_to_tabular(
    ScattDataLegendre& leg, ScattDataTabular& tab);

public:
  void init(const xt::xtensor<int, 1>& in_gmin,
    const xt::xtensor<int, 1>& in_gmax, const double_2dvec& in_mult,
    const double_3dvec& coeffs) override;

  void combine(const vector<ScattData*>& those_scatts,
    const vector<double>& scalars) override;

  double calc_f(int gin, int gout, double mu) override;

  void sample(
    int gin, int& gout, double& mu, double& wgt, uint64_t* seed) override;

  size_t get_order() override { return dist[0][0].size(); };

  xt::xtensor<double, 3> get_matrix(size_t max_order) override;
};

//==============================================================================
// Function to convert Legendre functions to tabular
//==============================================================================

//! \brief Converts a ScattDatalegendre to a ScattDataHistogram
//!
//! @param leg The initial ScattDataLegendre object.
//! @param leg The resultant ScattDataTabular object.
//! @param n_mu The number of mu points to use when building the
//!   ScattDataTabular object.
void convert_legendre_to_tabular(
  ScattDataLegendre& leg, ScattDataTabular& tab, int n_mu);

} // namespace openmc
#endif // OPENMC_SCATTDATA_H

1	//! \file scattdata.h
2	//! A collection of multi-group scattering data classes
3
4	#ifndef OPENMC_SCATTDATA_H
5	#define OPENMC_SCATTDATA_H
6
7	#include "xtensor/xtensor.hpp"
8
9	#include "openmc/constants.h"
10	#include "openmc/vector.h"
11
12	namespace openmc {
13
14	// forward declarations so we can name our friend functions
15	class ScattDataLegendre;
16	class ScattDataTabular;
17
18	//==============================================================================
19	// SCATTDATA contains all the data needed to describe the scattering energy and
20	// angular distribution data
21	//==============================================================================
22
23	class ScattData {
24	public:
UNCOV 25	virtual ~ScattData() = default;	×
26		×
UNCOV 27	protected:	×
28	//! \brief Initializes the attributes of the base class.
29	void base_init(int order, const xt::xtensor<int, 1>& in_gmin,
30	const xt::xtensor<int, 1>& in_gmax, const double_2dvec& in_energy,
31	const double_2dvec& in_mult);
32
33	//! \brief Combines microscopic ScattDatas into a macroscopic one.
34	void base_combine(size_t max_order, size_t order_dim,
35	const vector<ScattData*>& those_scatts, const vector<double>& scalars,
36	xt::xtensor<int, 1>& in_gmin, xt::xtensor<int, 1>& in_gmax,
37	double_2dvec& sparse_mult, double_3dvec& sparse_scatter);
38
39	public:
40	double_2dvec energy; // Normalized p0 matrix for sampling Eout
41	double_2dvec mult; // nu-scatter multiplication (nu-scatt/scatt)
42	double_3dvec dist; // Angular distribution
43	xt::xtensor<int, 1> gmin; // minimum outgoing group
44	xt::xtensor<int, 1> gmax; // maximum outgoing group
45	xt::xtensor<double, 1> scattxs; // Isotropic Sigma_{s,g_{in}}
46
47	//! \brief Calculates the value of normalized f(mu).
48	//!
49	//! The value of f(mu) is normalized as in the integral of f(mu)dmu across
50	//! [-1,1] is 1.
51	//!
52	//! @param gin Incoming energy group of interest.
53	//! @param gout Outgoing energy group of interest.
54	//! @param mu Cosine of the change-in-angle of interest.
55	//! @return The value of f(mu).
56	virtual double calc_f(int gin, int gout, double mu) = 0;
57
58	//! \brief Samples the outgoing energy and angle from the ScattData info.
59	//!
60	//! @param gin Incoming energy group.
61	//! @param gout Sampled outgoing energy group.
62	//! @param mu Sampled cosine of the change-in-angle.
63	//! @param wgt Weight of the particle to be adjusted.
64	//! @param seed Pseudorandom number seed pointer
65	virtual void sample(
66	int gin, int& gout, double& mu, double& wgt, uint64_t* seed) = 0;
67
68	//! \brief Initializes the ScattData object from a given scatter and
69	//! multiplicity matrix.
70	//!
71	//! @param in_gmin List of minimum outgoing groups for every incoming group
72	//! @param in_gmax List of maximum outgoing groups for every incoming group
73	//! @param in_mult Input sparse multiplicity matrix
74	//! @param coeffs Input sparse scattering matrix
75	virtual void init(const xt::xtensor<int, 1>& in_gmin,
76	const xt::xtensor<int, 1>& in_gmax, const double_2dvec& in_mult,
77	const double_3dvec& coeffs) = 0;
78
79	//! \brief Combines the microscopic data.
80	//!
81	//! @param those_scatts Microscopic objects to combine.
82	//! @param scalars Scalars to multiply the microscopic data by.
83	virtual void combine(
84	const vector<ScattData*>& those_scatts, const vector<double>& scalars) = 0;
85
86	//! \brief Getter for the dimensionality of the scattering order.
87	//!
88	//! If Legendre this is the "n" in "Pn"; for Tabular, this is the number
89	//! of points, and for Histogram this is the number of bins.
90	//!
91	//! @return The order.
92	virtual size_t get_order() = 0;
93
94	//! \brief Builds a dense scattering matrix from the constituent parts
95	//!
96	//! @param max_order If Legendre this is the maximum value of "n" in "Pn"
97	//! requested; ignored otherwise.
98	//! @return The dense scattering matrix.
99	virtual xt::xtensor<double, 3> get_matrix(size_t max_order) = 0;
100
101	//! \brief Samples the outgoing energy from the ScattData info.
102	//!
103	//! @param gin Incoming energy group.
104	//! @param gout Sampled outgoing energy group.
105	//! @param i_gout Sampled outgoing energy group index.
106	//! @param seed Pseudorandom number seed pointer
107	void sample_energy(int gin, int& gout, int& i_gout, uint64_t* seed);
108
109	//! \brief Provides a cross section value given certain parameters
110	//!
111	//! @param xstype Type of cross section requested, according to the
112	//! enumerated constants.
113	//! @param gin Incoming energy group.
114	//! @param gout Outgoing energy group; use nullptr if irrelevant, or if a
115	//! sum is requested.
116	//! @param mu Cosine of the change-in-angle, for scattering quantities;
117	//! use nullptr if irrelevant.
118	//! @return Requested cross section value.
119	double get_xs(MgxsType xstype, int gin, const int* gout, const double* mu);
120	};
121
122	//==============================================================================
123	// ScattDataLegendre represents the angular distributions as Legendre kernels
124	//==============================================================================
125
126	class ScattDataLegendre : public ScattData {
127
128	protected:
129	// Maximal value for rejection sampling from a rectangle
130	double_2dvec max_val;
131
132	// Friend convert_legendre_to_tabular so it has access to protected
133	// parameters
134	friend void convert_legendre_to_tabular(
135	ScattDataLegendre& leg, ScattDataTabular& tab);
136
137	public:
138	void init(const xt::xtensor<int, 1>& in_gmin,
139	const xt::xtensor<int, 1>& in_gmax, const double_2dvec& in_mult,
140	const double_3dvec& coeffs) override;
141
142	void combine(const vector<ScattData*>& those_scatts,
143	const vector<double>& scalars) override;
144
145	//! \brief Find the maximal value of the angular distribution to use as a
146	// bounding box with rejection sampling.
147	void update_max_val();
148
149	double calc_f(int gin, int gout, double mu) override;
150
151	void sample(
152	int gin, int& gout, double& mu, double& wgt, uint64_t* seed) override;
153
154	size_t get_order() override { return dist[0][0].size() - 1; };
155
156	xt::xtensor<double, 3> get_matrix(size_t max_order) override;
157	};
158
159	//==============================================================================
160	// ScattDataHistogram represents the angular distributions as a histogram, as it
161	// would be if it came from a "mu" tally in OpenMC
162	//==============================================================================
163
164	class ScattDataHistogram : public ScattData {
165
166	protected:
167	xt::xtensor<double, 1> mu; // Angle distribution mu bin boundaries
168	double dmu; // Quick storage of the mu spacing
169	double_3dvec fmu; // The angular distribution histogram
170
171	public:
172	void init(const xt::xtensor<int, 1>& in_gmin,
173	const xt::xtensor<int, 1>& in_gmax, const double_2dvec& in_mult,
174	const double_3dvec& coeffs) override;
175
176	void combine(const vector<ScattData*>& those_scatts,
177	const vector<double>& scalars) override;
178
179	double calc_f(int gin, int gout, double mu) override;
180
181	void sample(
182	int gin, int& gout, double& mu, double& wgt, uint64_t* seed) override;
183
184	size_t get_order() override { return dist[0][0].size(); };
185
186	xt::xtensor<double, 3> get_matrix(size_t max_order) override;
187	};
188
189	//==============================================================================
190	// ScattDataTabular represents the angular distributions as a table of mu and
191	// f(mu)
192	//==============================================================================
193
194	class ScattDataTabular : public ScattData {
195
196	protected:
197	xt::xtensor<double, 1> mu; // Angle distribution mu grid points
198	double dmu; // Quick storage of the mu spacing
199	double_3dvec fmu; // The angular distribution function
200
201	// Friend convert_legendre_to_tabular so it has access to protected
202	// parameters
203	friend void convert_legendre_to_tabular(
204	ScattDataLegendre& leg, ScattDataTabular& tab);
205
206	public:
207	void init(const xt::xtensor<int, 1>& in_gmin,
208	const xt::xtensor<int, 1>& in_gmax, const double_2dvec& in_mult,
209	const double_3dvec& coeffs) override;
210
211	void combine(const vector<ScattData*>& those_scatts,
212	const vector<double>& scalars) override;
213
214	double calc_f(int gin, int gout, double mu) override;
215
216	void sample(
217	int gin, int& gout, double& mu, double& wgt, uint64_t* seed) override;
218
219	size_t get_order() override { return dist[0][0].size(); };
220
221	xt::xtensor<double, 3> get_matrix(size_t max_order) override;
222	};
223
224	//==============================================================================
225	// Function to convert Legendre functions to tabular
226	//==============================================================================
227
228	//! \brief Converts a ScattDatalegendre to a ScattDataHistogram
229	//!
230	//! @param leg The initial ScattDataLegendre object.
231	//! @param leg The resultant ScattDataTabular object.
232	//! @param n_mu The number of mu points to use when building the
233	//! ScattDataTabular object.
234	void convert_legendre_to_tabular(
235	ScattDataLegendre& leg, ScattDataTabular& tab, int n_mu);
236
237	} // namespace openmc
238	#endif // OPENMC_SCATTDATA_H

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