31 #ifndef __TASMANIAN_IOHELPERS_HPP
32 #define __TASMANIAN_IOHELPERS_HPP
117 return std::initializer_list<std::pair<std::string const, TypeOneDRule>>{
170 }
catch(std::out_of_range &){
181 return std::find_if(smap.begin(), smap.end(),
182 [&](std::pair<std::string, TypeOneDRule> r)->bool{ return (r.second == rule); })->first;
211 return ((
size_t) r < rmap.size()) ? rmap[(size_t) r] :
rule_none;
220 return (
int) std::distance(rmap.begin(), std::find_if(rmap.begin(), rmap.end(),
229 return std::initializer_list<std::pair<std::string const, TypeDepth>>{
250 }
catch(std::out_of_range &){
263 return ((
size_t) t < imap.size()) ? imap[(size_t) t] :
type_none;
271 return std::initializer_list<std::pair<std::string const, TypeRefinement>>{
285 }
catch(std::out_of_range &){
297 return ((
size_t) refinement < imap.size()) ? imap[(size_t) refinement] :
refine_none;
304 template<
bool iomode, IOPad pad>
307 os << ((flag) ?
"1" :
"0");
311 char cflag = ((flag) ?
'y' :
'n');
312 os.write(&cflag,
sizeof(
char));
320 template<
typename iomode>
322 if (std::is_same<iomode, mode_ascii_type>::value){
328 os.read(&cflag,
sizeof(
char));
329 return (cflag ==
'y');
337 template<
bool iomode, IOPad pad,
typename VecType>
338 void writeVector(
const std::vector<VecType> &x, std::ostream &os){
341 for(
auto i : x) os <<
" " << i;
343 for(
auto i : x) os << i <<
" ";
346 for(
size_t i = 1; i < x.size(); i++) os <<
" " << x[i];
347 if (pad ==
pad_line) os << std::endl;
350 os.write((
char*) x.data(), x.size() *
sizeof(VecType));
358 template<
typename iomode,
typename VecType>
360 if (std::is_same<iomode, mode_ascii_type>::value){
361 for(
auto &i : x) is >> i;
363 is.read((
char*) x.data(), x.size() *
sizeof(VecType));
371 template<
typename iomode,
typename VecType,
typename SizeType>
372 std::vector<VecType>
readVector(std::istream &is, SizeType num_entries){
373 std::vector<VecType> x((
size_t) num_entries);
374 readVector<iomode, VecType>(is, x);
382 template<
bool iomode,
IOPad pad,
typename... Vals>
384 std::vector<
typename std::tuple_element<0, std::tuple<Vals...>>::type> values = {vals...};
385 writeVector<iomode, pad>(values, os);
392 template<
typename iomode,
typename Val>
395 if (std::is_same<iomode, mode_ascii_type>::value){
398 is.read((
char*) &v,
sizeof(Val));
407 template<
bool iomode>
413 os.write((
char*) &r,
sizeof(
int));
421 template<
typename iomode>
423 if (std::is_same<iomode, mode_ascii_type>::value){
428 return getRuleInt(readNumber<mode_binary_type, int>(is));
TypeOneDRule
Used to specify the one dimensional family of rules that induces the sparse grid.
Definition: tsgEnumerates.hpp:285
TypeDepth
Used by Global Sequence and Fourier grids, indicates the selection criteria.
Definition: tsgEnumerates.hpp:203
TypeRefinement
Refinement strategy for local polynomial and wavelet grids.
Definition: tsgEnumerates.hpp:425
@ rule_minlebesgue
A greedy sequence rule with nodes added to minimize the Lebesgue constant.
Definition: tsgEnumerates.hpp:321
@ rule_gaussgegenbauer
Non-nested rule optimized for integral of the form .
Definition: tsgEnumerates.hpp:343
@ rule_gausshermite
Non-nested rule optimized for integral of the form .
Definition: tsgEnumerates.hpp:355
@ rule_gausslegendre
Non-nested rule but optimized for integration.
Definition: tsgEnumerates.hpp:329
@ rule_fejer2
Similar to rule_clenshawcurtis but with nodes strictly in the interior.
Definition: tsgEnumerates.hpp:293
@ rule_leja
Classic sequence rule, moderate Lebesgue constant growth (empirical result only).
Definition: tsgEnumerates.hpp:299
@ rule_rlejashifteddouble
Same as rule_rlejashifted but doubling the number of nodes per level, which reduced the Lebesgue cons...
Definition: tsgEnumerates.hpp:315
@ rule_gausslaguerreodd
Same as rule_gausslaguerre but using only odd levels, partially mitigates the non-nested issues.
Definition: tsgEnumerates.hpp:353
@ rule_localp
Nested rule with a hierarchy of uniformly distributed nodes and functions with compact support.
Definition: tsgEnumerates.hpp:362
@ rule_chebyshevodd
Same as rule_chebyshev but using only odd levels, partially mitigates the non-nested issues.
Definition: tsgEnumerates.hpp:297
@ rule_minlebesgueodd
Same as rule_minlebesgue but using only odd levels, quadrature is more stable.
Definition: tsgEnumerates.hpp:323
@ rule_gausslegendreodd
Same as rule_gausslegendre but using only odd levels, partially mitigates the non-nested issues.
Definition: tsgEnumerates.hpp:331
@ rule_gausschebyshev1
Non-nested rule optimized for integral of the form .
Definition: tsgEnumerates.hpp:335
@ rule_gausslaguerre
Non-nested rule optimized for integral of the form .
Definition: tsgEnumerates.hpp:351
@ rule_wavelet
Wavelet basis with uniformly distributed nodes (primarily for internal use).
Definition: tsgEnumerates.hpp:370
@ rule_mindelta
A greedy sequence rule with nodes added to minimize the norm of the surplus operator.
Definition: tsgEnumerates.hpp:325
@ rule_gaussgegenbauerodd
Same as rule_gaussgegenbauer but using only odd levels, partially mitigates the non-nested issues.
Definition: tsgEnumerates.hpp:345
@ rule_localpb
Variation of rule_localp focusing nodes on the boundary instead of the interior.
Definition: tsgEnumerates.hpp:368
@ rule_customtabulated
User provided rule, nodes and weights must be provided with a separate file.
Definition: tsgEnumerates.hpp:359
@ rule_gausshermiteodd
Same as rule_gausshermite but using only odd levels, partially mitigates the non-nested issues.
Definition: tsgEnumerates.hpp:357
@ rule_clenshawcurtis
Classic nested rule using Chebyshev nodes with very low Lebesgue constant.
Definition: tsgEnumerates.hpp:289
@ rule_gausschebyshev2odd
Same as rule_gausschebyshev2 but using only odd levels, partially mitigates the non-nested issues.
Definition: tsgEnumerates.hpp:341
@ rule_maxlebesgueodd
Same as rule_maxlebesgue but using only odd levels, quadrature is more stable.
Definition: tsgEnumerates.hpp:319
@ rule_maxlebesgue
A greedy sequence rule with nodes placed at the maximum of the Lebesgue function.
Definition: tsgEnumerates.hpp:317
@ rule_clenshawcurtis0
Same as rule_clenshawcurtis but with modified basis that assumes the model is zero at the boundary.
Definition: tsgEnumerates.hpp:291
@ rule_none
Null rule, should never be used as input (default rule for an empty grid).
Definition: tsgEnumerates.hpp:287
@ rule_chebyshev
Using Chebyshev nodes with very low Lebesgue constant and slow node growth, but non-nested.
Definition: tsgEnumerates.hpp:295
@ rule_gausschebyshev1odd
Same as rule_gausschebyshev1 but using only odd levels, partially mitigates the non-nested issues.
Definition: tsgEnumerates.hpp:337
@ rule_rlejashifted
Similar sequence to rule_rleja but with nodes strictly in the interior.
Definition: tsgEnumerates.hpp:311
@ rule_gausschebyshev2
Non-nested rule optimized for integral of the form .
Definition: tsgEnumerates.hpp:339
@ rule_localp0
Variation of rule_localp assuming the model is zero at the domain boundary.
Definition: tsgEnumerates.hpp:364
@ rule_fourier
Trigonometric basis with uniformly distributed nodes (primarily for internal use).
Definition: tsgEnumerates.hpp:372
@ rule_mindeltaodd
Same as rule_mindelta but using only odd levels, quadrature is more stable.
Definition: tsgEnumerates.hpp:327
@ rule_rlejadouble4
Using rule_rleja nodes but doubling the nodes every 4 levels, reduces the Lebesgue constant.
Definition: tsgEnumerates.hpp:307
@ rule_gaussjacobiodd
Same as rule_gaussjacobi but using only odd levels, partially mitigates the non-nested issues.
Definition: tsgEnumerates.hpp:349
@ rule_lejaodd
Same as rule_leja but using only odd levels, quadrature is more stable.
Definition: tsgEnumerates.hpp:301
@ rule_rlejaodd
Same as rule_rleja but using only odd levels, quadrature is more stable.
Definition: tsgEnumerates.hpp:309
@ rule_rlejadouble2
Using rule_rleja nodes but doubling the nodes every 2 levels, reduces the Lebesgue constant.
Definition: tsgEnumerates.hpp:305
@ rule_rlejashiftedeven
Same as rule_rlejashifted but using only even levels, quadrature is more stable.
Definition: tsgEnumerates.hpp:313
@ rule_gausspatterson
Nested rule that is optimized for integration, probably the best integration rule in more than 2 dime...
Definition: tsgEnumerates.hpp:333
@ rule_rleja
Classic sequence rule based on complex analysis, moderate Lebesgue constant growth (theoretically pro...
Definition: tsgEnumerates.hpp:303
@ rule_semilocalp
Variation of rule_localp using increased support in exchange for higher order basis (better for smoot...
Definition: tsgEnumerates.hpp:366
@ rule_gaussjacobi
Non-nested rule optimized for integral of the form .
Definition: tsgEnumerates.hpp:347
@ type_curved
Ignoring the polynomial space, use rules with index .
Definition: tsgEnumerates.hpp:213
@ type_iptensor
Make a dense tensor grid with interpolation range that includes .
Definition: tsgEnumerates.hpp:245
@ type_qptotal
Total degree polynomial space for quadrature/integration.
Definition: tsgEnumerates.hpp:224
@ type_qpcurved
Curved polynomial space for quadrature/integration.
Definition: tsgEnumerates.hpp:231
@ type_level
Ignoring the polynomial space, use rules with index .
Definition: tsgEnumerates.hpp:209
@ type_qphyperbolic
Hyperbolic cross section polynomial space for quadrature/integration.
Definition: tsgEnumerates.hpp:238
@ type_none
Null type, should never be used for input, indicates an error of some sort.
Definition: tsgEnumerates.hpp:205
@ type_iptotal
Total degree polynomial space for interpolation, i.e., the span of .
Definition: tsgEnumerates.hpp:221
@ type_qptensor
Make a dense tensor grid with quadrature/integration range that includes .
Definition: tsgEnumerates.hpp:249
@ type_hyperbolic
Ignoring the polynomial space, use rules with index .
Definition: tsgEnumerates.hpp:217
@ type_iphyperbolic
Hyperbolic cross section polynomial space for interpolation, i.e., the span of .
Definition: tsgEnumerates.hpp:235
@ type_tensor
Make a dense tensor grid with rules indexed by .
Definition: tsgEnumerates.hpp:241
@ type_ipcurved
Curved polynomial space for interpolation, i.e., the span of .
Definition: tsgEnumerates.hpp:228
@ refine_parents_first
Isotropic refinement adding children only if the parents are already included.
Definition: tsgEnumerates.hpp:429
@ refine_classic
Isotropic refinement using only the children and disregarding missing parents.
Definition: tsgEnumerates.hpp:427
@ refine_direction_selective
Anisotropic refinement using only the children and disregarding missing parents.
Definition: tsgEnumerates.hpp:431
@ refine_fds
Anisotropic refinement adding children only if the parents are already included.
Definition: tsgEnumerates.hpp:433
@ refine_none
Null method, should never be used as input.
Definition: tsgEnumerates.hpp:437
@ refine_stable
Isotropic refinement that ensures the points maintain lower-complete structures.
Definition: tsgEnumerates.hpp:435
std::map< std::string, TypeDepth > getStringToDepthMap()
Creates a map with std::string rule names (used by C/Python/CLI) mapped to TypeDepth enums.
Definition: tsgIOHelpers.hpp:228
Val readNumber(std::istream &is)
Read a single number, used to read ints (and potentially cast to size_t) or read a double.
Definition: tsgIOHelpers.hpp:393
TypeRefinement getTypeRefinementString(std::string const &name)
Map the string to the enumerate hierarchical refinement strategy, used in command line and Python.
Definition: tsgIOHelpers.hpp:282
void writeVector(const std::vector< VecType > &x, std::ostream &os)
Write the vector to the stream, the vector cannot be empty.
Definition: tsgIOHelpers.hpp:338
bool readFlag(std::istream &os)
Read a flag, ascii uses 0 and 1, binary uses characters y and n (counter intuitive,...
Definition: tsgIOHelpers.hpp:321
TypeDepth getDepthTypeString(std::string const &name)
Map the string to the enumerate multi-index selection strategy, used in command line and Python.
Definition: tsgIOHelpers.hpp:247
TypeDepth getDepthTypeInt(int t)
Map the integer to the enumerate multi-index selection strategy, used in Fortran.
Definition: tsgIOHelpers.hpp:259
std::map< std::string, TypeOneDRule > getStringRuleMap()
Creates a map with std::string rule names (used by C/Python/CLI) mapped to TypeOneDRule enums.
Definition: tsgIOHelpers.hpp:116
void writeFlag(bool flag, std::ostream &os)
Write the flag to file, ascii uses 0 and 1, binary uses characters y and n (counter intuitive,...
Definition: tsgIOHelpers.hpp:305
TypeOneDRule getRuleString(std::string const &name)
Map the string rule name to the enumerate, used in ASCII I/O, command line and Python.
Definition: tsgIOHelpers.hpp:167
void writeRule(TypeOneDRule rule, std::ostream &os)
Write a rule.
Definition: tsgIOHelpers.hpp:408
std::map< std::string, TypeRefinement > getStringToRefinementMap()
Creates a map with std::string rule names (used by C/Python/CLI) mapped to TypeRefinement enums.
Definition: tsgIOHelpers.hpp:270
void readVector(std::istream &is, std::vector< VecType > &x)
Read the vector from the stream, the size must already be set.
Definition: tsgIOHelpers.hpp:359
void writeNumbers(std::ostream &os, Vals... vals)
Write a bunch of numbers with the same type.
Definition: tsgIOHelpers.hpp:383
IOPad
Indicate the type of padding to use, none, space, new-line, etc.
Definition: tsgIOHelpers.hpp:99
TypeOneDRule readRule(std::istream &is)
Read a rule.
Definition: tsgIOHelpers.hpp:422
std::vector< TypeOneDRule > getIntRuleMap()
Creates a map with int (used by Fortran and binary I/O) mapped to TypeOneDRule enums.
Definition: tsgIOHelpers.hpp:189
TypeRefinement getTypeRefinementInt(int refinement)
Map the integer to the enumerate hierarchical refinement strategy, used by Fortran.
Definition: tsgIOHelpers.hpp:293
TypeOneDRule getRuleInt(int r)
Map the int rule index to the enumerate, used in Fortran and binary IO.
Definition: tsgIOHelpers.hpp:209
@ pad_lspace
Pad with space at the beginning.
Definition: tsgIOHelpers.hpp:105
@ pad_auto
Pad with space if the flag is true, newline if false.
Definition: tsgIOHelpers.hpp:109
@ pad_line
Pad with new line.
Definition: tsgIOHelpers.hpp:107
@ pad_rspace
Pad with space at the end.
Definition: tsgIOHelpers.hpp:103
@ pad_none
Do not add padding.
Definition: tsgIOHelpers.hpp:101
constexpr bool mode_binary
Constant allowing for more expressive selection of ascii and binary mode in IO methods.
Definition: tsgIOHelpers.hpp:68
constexpr bool mode_ascii
Constant allowing for more expressive selection of ascii and binary mode in IO methods.
Definition: tsgIOHelpers.hpp:62
Encapsulates the Tasmanian Sparse Grid module.
Definition: TasmanianSparseGrid.hpp:68
Type indicating ascii I/O mode.
Definition: tsgIOHelpers.hpp:82
Type indicating binary I/O mode.
Definition: tsgIOHelpers.hpp:88
Omnipresent enumerate types.