compilation error
blancha...@gmail.com
DIAGNOSTIC(S) FROM PARSER:
Warning (non-fatal): assignment operator <- deprecated in the Stan language; use = instead.
In file included from /users/tblanchard/apps/R/StanHeaders/include/stan/math/prim/arr.hpp:33,
from /users/tblanchard/apps/R/StanHeaders/include/stan/math/prim/mat.hpp:232,
from /users/tblanchard/apps/R/StanHeaders/include/stan/math/rev/mat.hpp:8,
from /users/tblanchard/apps/R/StanHeaders/include/stan/math.hpp:4,
from /users/tblanchard/apps/R/StanHeaders/include/src/stan/model/model_header.hpp:4,
from file5b482c35e703.cpp:8:
/users/tblanchard/apps/R/StanHeaders/include/stan/math/prim/arr/functor/integrate_ode_rk45.hpp: In function ‘std::vector<std::vector<typename stan::return_type<T_y, T_loc, double, double, double, double>::type, std::allocator<typename stan::return_type<T_y, T_loc, double, double, double, double>::type> >, std::allocator<std::vector<typename stan::return_type<T_y, T_loc, double, double, double, double>::type, std::allocator<typename stan::return_type<T_y, T_loc, double, double, double, double>::type> > > > stan::math::integrate_ode_rk45(const F&, std::vector<S, std::allocator<_T2> >, double, const std::vector<double, std::allocator<double> >&, const std::vector<T2, std::allocator<_Tp> >&, const std::vector<double, std::allocator<double> >&, const std::vector<int, std::allocator<int> >&, std::ostream*, double, double, int)’:
/users/tblanchard/apps/R/StanHeaders/include/stan/math/prim/arr/functor/integrate_ode_rk45.hpp:81: error: ‘boost::numeric::odeint::max_step_checker’ has not been declared
/users/tblanchard/apps/R/StanHeaders/include/stan/math/prim/arr/functor/integrate_ode_rk45.hpp:136: error: there are no arguments to ‘max_step_checker’ that depend on a template parameter, so a declaration of ‘max_step_checker’ must be available
/users/tblanchard/apps/R/StanHeaders/include/stan/math/prim/arr/functor/integrate_ode_rk45.hpp:136: note: (if you use ‘-fpermissive’, G++ will accept your code, but allowing the use of an undeclared name is deprecated)
make: *** [file5b482c35e703.o] Error 1
ERROR(s) during compilation: source code errors or compiler configuration errors!
Program source:
1:
2: // includes from the plugin
3:
4:
5: // user includes
6: #define STAN__SERVICES__COMMAND_HPP// Code generated by Stan version 2.10
7:
8: #include <stan/model/model_header.hpp>
9:
10: namespace model5b4846796203_8schools_namespace {
11:
12: using std::istream;
13: using std::string;
14: using std::stringstream;
15: using std::vector;
16: using stan::io::dump;
17: using stan::math::lgamma;
18: using stan::model::prob_grad;
19: using namespace stan::math;
20:
21: typedef Eigen::Matrix<double,Eigen::Dynamic,1> vector_d;
22: typedef Eigen::Matrix<double,1,Eigen::Dynamic> row_vector_d;
23: typedef Eigen::Matrix<double,Eigen::Dynamic,Eigen::Dynamic> matrix_d;
24:
25: static int current_statement_begin__;
26:
27: class model5b4846796203_8schools : public prob_grad {
28: private:
29: int J;
30: vector<double> y;
31: vector<double> sigma;
32: public:
33: model5b4846796203_8schools(stan::io::var_context& context__,
34: std::ostream* pstream__ = 0)
35: : prob_grad(0) {
36: current_statement_begin__ = -1;
37:
38: static const char* function__ = "model5b4846796203_8schools_namespace::model5b4846796203_8schools";
39: (void) function__; // dummy call to supress warning
40: size_t pos__;
41: (void) pos__; // dummy call to supress warning
42: std::vector<int> vals_i__;
43: std::vector<double> vals_r__;
44: context__.validate_dims("data initialization", "J", "int", context__.to_vec());
45: J = int(0);
46: vals_i__ = context__.vals_i("J");
47: pos__ = 0;
48: J = vals_i__[pos__++];
49: context__.validate_dims("data initialization", "y", "double", context__.to_vec(J));
50: validate_non_negative_index("y", "J", J);
51: y = std::vector<double>(J,double(0));
52: vals_r__ = context__.vals_r("y");
53: pos__ = 0;
54: size_t y_limit_0__ = J;
55: for (size_t i_0__ = 0; i_0__ < y_limit_0__; ++i_0__) {
56: y[i_0__] = vals_r__[pos__++];
57: }
58: context__.validate_dims("data initialization", "sigma", "double", context__.to_vec(J));
59: validate_non_negative_index("sigma", "J", J);
60: sigma = std::vector<double>(J,double(0));
61: vals_r__ = context__.vals_r("sigma");
62: pos__ = 0;
63: size_t sigma_limit_0__ = J;
64: for (size_t i_0__ = 0; i_0__ < sigma_limit_0__; ++i_0__) {
65: sigma[i_0__] = vals_r__[pos__++];
66: }
67:
68: // validate data
69: check_greater_or_equal(function__,"J",J,0);
70: for (int k0__ = 0; k0__ < J; ++k0__) {
71: check_greater_or_equal(function__,"sigma[k0__]",sigma[k0__],0);
72: }
73:
74: double DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());
75: (void) DUMMY_VAR__; // suppress unused var warning
76:
77:
78: // initialize transformed variables to avoid seg fault on val access
79:
80: try {
81: } catch (const std::exception& e) {
82: stan::lang::rethrow_located(e,current_statement_begin__);
83: // Next line prevents compiler griping about no return
84: throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
85: }
86:
87: // validate transformed data
88:
89: // set parameter ranges
90: num_params_r__ = 0U;
91: param_ranges_i__.clear();
92: ++num_params_r__;
93: ++num_params_r__;
94: num_params_r__ += J;
95: }
96:
97: ~model5b4846796203_8schools() { }
98:
99:
100: void transform_inits(const stan::io::var_context& context__,
101: std::vector<int>& params_i__,
102: std::vector<double>& params_r__,
103: std::ostream* pstream__) const {
104: stan::io::writer<double> writer__(params_r__,params_i__);
105: size_t pos__;
106: (void) pos__; // dummy call to supress warning
107: std::vector<double> vals_r__;
108: std::vector<int> vals_i__;
109:
110: if (!(context__.contains_r("mu")))
111: throw std::runtime_error("variable mu missing");
112: vals_r__ = context__.vals_r("mu");
113: pos__ = 0U;
114: context__.validate_dims("initialization", "mu", "double", context__.to_vec());
115: double mu(0);
116: mu = vals_r__[pos__++];
117: try {
118: writer__.scalar_unconstrain(mu);
119: } catch (const std::exception& e) {
120: throw std::runtime_error(std::string("Error transforming variable mu: ") + e.what());
121: }
122:
123: if (!(context__.contains_r("tau")))
124: throw std::runtime_error("variable tau missing");
125: vals_r__ = context__.vals_r("tau");
126: pos__ = 0U;
127: context__.validate_dims("initialization", "tau", "double", context__.to_vec());
128: double tau(0);
129: tau = vals_r__[pos__++];
130: try {
131: writer__.scalar_lb_unconstrain(0,tau);
132: } catch (const std::exception& e) {
133: throw std::runtime_error(std::string("Error transforming variable tau: ") + e.what());
134: }
135:
136: if (!(context__.contains_r("eta")))
137: throw std::runtime_error("variable eta missing");
138: vals_r__ = context__.vals_r("eta");
139: pos__ = 0U;
140: context__.validate_dims("initialization", "eta", "double", context__.to_vec(J));
141: std::vector<double> eta(J,double(0));
142: for (int i0__ = 0U; i0__ < J; ++i0__)
143: eta[i0__] = vals_r__[pos__++];
144: for (int i0__ = 0U; i0__ < J; ++i0__)
145: try {
146: writer__.scalar_unconstrain(eta[i0__]);
147: } catch (const std::exception& e) {
148: throw std::runtime_error(std::string("Error transforming variable eta: ") + e.what());
149: }
150:
151: params_r__ = writer__.data_r();
152: params_i__ = writer__.data_i();
153: }
154:
155: void transform_inits(const stan::io::var_context& context,
156: Eigen::Matrix<double,Eigen::Dynamic,1>& params_r,
157: std::ostream* pstream__) const {
158: std::vector<double> params_r_vec;
159: std::vector<int> params_i_vec;
160: transform_inits(context, params_i_vec, params_r_vec, pstream__);
161: params_r.resize(params_r_vec.size());
162: for (int i = 0; i < params_r.size(); ++i)
163: params_r(i) = params_r_vec[i];
164: }
165:
166:
167: template <bool propto__, bool jacobian__, typename T__>
168: T__ log_prob(vector<T__>& params_r__,
169: vector<int>& params_i__,
170: std::ostream* pstream__ = 0) const {
171:
172: T__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());
173: (void) DUMMY_VAR__; // suppress unused var warning
174:
175: T__ lp__(0.0);
176: stan::math::accumulator<T__> lp_accum__;
177:
178: // model parameters
179: stan::io::reader<T__> in__(params_r__,params_i__);
180:
181: T__ mu;
182: (void) mu; // dummy to suppress unused var warning
183: if (jacobian__)
184: mu = in__.scalar_constrain(lp__);
185: else
186: mu = in__.scalar_constrain();
187:
188: T__ tau;
189: (void) tau; // dummy to suppress unused var warning
190: if (jacobian__)
191: tau = in__.scalar_lb_constrain(0,lp__);
192: else
193: tau = in__.scalar_lb_constrain(0);
194:
195: vector<T__> eta;
196: size_t dim_eta_0__ = J;
197: eta.reserve(dim_eta_0__);
198: for (size_t k_0__ = 0; k_0__ < dim_eta_0__; ++k_0__) {
199: if (jacobian__)
200: eta.push_back(in__.scalar_constrain(lp__));
201: else
202: eta.push_back(in__.scalar_constrain());
203: }
204:
205:
206: // transformed parameters
207: vector<T__> theta(J);
208:
209: // initialize transformed variables to avoid seg fault on val access
210: stan::math::fill(theta,DUMMY_VAR__);
211:
212: try {
213: current_statement_begin__ = 13;
214: for (int j = 1; j <= J; ++j) {
215: current_statement_begin__ = 14;
216: stan::math::assign(get_base1_lhs(theta,j,"theta",1), (mu + (tau * get_base1(eta,j,"eta",1))));
217: }
218: } catch (const std::exception& e) {
219: stan::lang::rethrow_located(e,current_statement_begin__);
220: // Next line prevents compiler griping about no return
221: throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
222: }
223:
224: // validate transformed parameters
225: for (int i0__ = 0; i0__ < J; ++i0__) {
226: if (stan::math::is_uninitialized(theta[i0__])) {
227: std::stringstream msg__;
228: msg__ << "Undefined transformed parameter: theta" << '[' << i0__ << ']';
229: throw std::runtime_error(msg__.str());
230: }
231: }
232:
233: const char* function__ = "validate transformed params";
234: (void) function__; // dummy to suppress unused var warning
235:
236: // model body
237: try {
238: current_statement_begin__ = 17;
239: lp_accum__.add(normal_log<propto__>(eta, 0, 1));
240: current_statement_begin__ = 18;
241: lp_accum__.add(normal_log<propto__>(y, theta, sigma));
242: } catch (const std::exception& e) {
243: stan::lang::rethrow_located(e,current_statement_begin__);
244: // Next line prevents compiler griping about no return
245: throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
246: }
247:
248: lp_accum__.add(lp__);
249: return lp_accum__.sum();
250:
251: } // log_prob()
252:
253: template <bool propto, bool jacobian, typename T_>
254: T_ log_prob(Eigen::Matrix<T_,Eigen::Dynamic,1>& params_r,
255: std::ostream* pstream = 0) const {
256: std::vector<T_> vec_params_r;
257: vec_params_r.reserve(params_r.size());
258: for (int i = 0; i < params_r.size(); ++i)
259: vec_params_r.push_back(params_r(i));
260: std::vector<int> vec_params_i;
261: return log_prob<propto,jacobian,T_>(vec_params_r, vec_params_i, pstream);
262: }
263:
264:
265: void get_param_names(std::vector<std::string>& names__) const {
266: names__.resize(0);
267: names__.push_back("mu");
268: names__.push_back("tau");
269: names__.push_back("eta");
270: names__.push_back("theta");
271: }
272:
273:
274: void get_dims(std::vector<std::vector<size_t> >& dimss__) const {
275: dimss__.resize(0);
276: std::vector<size_t> dims__;
277: dims__.resize(0);
278: dimss__.push_back(dims__);
279: dims__.resize(0);
280: dimss__.push_back(dims__);
281: dims__.resize(0);
282: dims__.push_back(J);
283: dimss__.push_back(dims__);
284: dims__.resize(0);
285: dims__.push_back(J);
286: dimss__.push_back(dims__);
287: }
288:
289: template <typename RNG>
290: void write_array(RNG& base_rng__,
291: std::vector<double>& params_r__,
292: std::vector<int>& params_i__,
293: std::vector<double>& vars__,
294: bool include_tparams__ = true,
295: bool include_gqs__ = true,
296: std::ostream* pstream__ = 0) const {
297: vars__.resize(0);
298: stan::io::reader<double> in__(params_r__,params_i__);
299: static const char* function__ = "model5b4846796203_8schools_namespace::write_array";
300: (void) function__; // dummy call to supress warning
301: // read-transform, write parameters
302: double mu = in__.scalar_constrain();
303: double tau = in__.scalar_lb_constrain(0);
304: vector<double> eta;
305: size_t dim_eta_0__ = J;
306: for (size_t k_0__ = 0; k_0__ < dim_eta_0__; ++k_0__) {
307: eta.push_back(in__.scalar_constrain());
308: }
309: vars__.push_back(mu);
310: vars__.push_back(tau);
311: for (int k_0__ = 0; k_0__ < J; ++k_0__) {
312: vars__.push_back(eta[k_0__]);
313: }
314:
315: if (!include_tparams__) return;
316: // declare and define transformed parameters
317: double lp__ = 0.0;
318: (void) lp__; // dummy call to supress warning
319: stan::math::accumulator<double> lp_accum__;
320:
321: vector<double> theta(J, 0.0);
322:
323: try {
324: current_statement_begin__ = 13;
325: for (int j = 1; j <= J; ++j) {
326: current_statement_begin__ = 14;
327: stan::math::assign(get_base1_lhs(theta,j,"theta",1), (mu + (tau * get_base1(eta,j,"eta",1))));
328: }
329: } catch (const std::exception& e) {
330: stan::lang::rethrow_located(e,current_statement_begin__);
331: // Next line prevents compiler griping about no return
332: throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
333: }
334:
335: // validate transformed parameters
336:
337: // write transformed parameters
338: for (int k_0__ = 0; k_0__ < J; ++k_0__) {
339: vars__.push_back(theta[k_0__]);
340: }
341:
342: if (!include_gqs__) return;
343: // declare and define generated quantities
344:
345: double DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());
346: (void) DUMMY_VAR__; // suppress unused var warning
347:
348:
349: // initialize transformed variables to avoid seg fault on val access
350:
351: try {
352: } catch (const std::exception& e) {
353: stan::lang::rethrow_located(e,current_statement_begin__);
354: // Next line prevents compiler griping about no return
355: throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
356: }
357:
358: // validate generated quantities
359:
360: // write generated quantities
361: }
362:
363: template <typename RNG>
364: void write_array(RNG& base_rng,
365: Eigen::Matrix<double,Eigen::Dynamic,1>& params_r,
366: Eigen::Matrix<double,Eigen::Dynamic,1>& vars,
367: bool include_tparams = true,
368: bool include_gqs = true,
369: std::ostream* pstream = 0) const {
370: std::vector<double> params_r_vec(params_r.size());
371: for (int i = 0; i < params_r.size(); ++i)
372: params_r_vec[i] = params_r(i);
373: std::vector<double> vars_vec;
374: std::vector<int> params_i_vec;
375: write_array(base_rng,params_r_vec,params_i_vec,vars_vec,include_tparams,include_gqs,pstream);
376: vars.resize(vars_vec.size());
377: for (int i = 0; i < vars.size(); ++i)
378: vars(i) = vars_vec[i];
379: }
380:
381: static std::string model_name() {
382: return "model5b4846796203_8schools";
383: }
384:
385:
386: void constrained_param_names(std::vector<std::string>& param_names__,
387: bool include_tparams__ = true,
388: bool include_gqs__ = true) const {
389: std::stringstream param_name_stream__;
390: param_name_stream__.str(std::string());
391: param_name_stream__ << "mu";
392: param_names__.push_back(param_name_stream__.str());
393: param_name_stream__.str(std::string());
394: param_name_stream__ << "tau";
395: param_names__.push_back(param_name_stream__.str());
396: for (int k_0__ = 1; k_0__ <= J; ++k_0__) {
397: param_name_stream__.str(std::string());
398: param_name_stream__ << "eta" << '.' << k_0__;
399: param_names__.push_back(param_name_stream__.str());
400: }
401:
402: if (!include_gqs__ && !include_tparams__) return;
403: for (int k_0__ = 1; k_0__ <= J; ++k_0__) {
404: param_name_stream__.str(std::string());
405: param_name_stream__ << "theta" << '.' << k_0__;
406: param_names__.push_back(param_name_stream__.str());
407: }
408:
409: if (!include_gqs__) return;
410: }
411:
412:
413: void unconstrained_param_names(std::vector<std::string>& param_names__,
414: bool include_tparams__ = true,
415: bool include_gqs__ = true) const {
416: std::stringstream param_name_stream__;
417: param_name_stream__.str(std::string());
418: param_name_stream__ << "mu";
419: param_names__.push_back(param_name_stream__.str());
420: param_name_stream__.str(std::string());
421: param_name_stream__ << "tau";
422: param_names__.push_back(param_name_stream__.str());
423: for (int k_0__ = 1; k_0__ <= J; ++k_0__) {
424: param_name_stream__.str(std::string());
425: param_name_stream__ << "eta" << '.' << k_0__;
426: param_names__.push_back(param_name_stream__.str());
427: }
428:
429: if (!include_gqs__ && !include_tparams__) return;
430: for (int k_0__ = 1; k_0__ <= J; ++k_0__) {
431: param_name_stream__.str(std::string());
432: param_name_stream__ << "theta" << '.' << k_0__;
433: param_names__.push_back(param_name_stream__.str());
434: }
435:
436: if (!include_gqs__) return;
437: }
438:
439: }; // model
440:
441: } // namespace
442:
443: typedef model5b4846796203_8schools_namespace::model5b4846796203_8schools stan_model;
444:
445: #include <rstan/rstaninc.hpp>
446: /**
447: * Define Rcpp Module to expose stan_fit's functions to R.
448: */
449: RCPP_MODULE(stan_fit4model5b4846796203_8schools_mod){
450: Rcpp::class_<rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools,
451: boost::random::ecuyer1988> >("stan_fit4model5b4846796203_8schools")
452: // .constructor<Rcpp::List>()
453: .constructor<SEXP, SEXP>()
454: // .constructor<SEXP, SEXP>()
455: .method("call_sampler",
456: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::call_sampler)
457: .method("param_names",
458: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::param_names)
459: .method("param_names_oi",
460: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::param_names_oi)
461: .method("param_fnames_oi",
462: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::param_fnames_oi)
463: .method("param_dims",
464: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::param_dims)
465: .method("param_dims_oi",
466: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::param_dims_oi)
467: .method("update_param_oi",
468: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::update_param_oi)
469: .method("param_oi_tidx",
470: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::param_oi_tidx)
471: .method("grad_log_prob",
472: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::grad_log_prob)
473: .method("log_prob",
474: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::log_prob)
475: .method("unconstrain_pars",
476: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::unconstrain_pars)
477: .method("constrain_pars",
478: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::constrain_pars)
479: .method("num_pars_unconstrained",
480: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::num_pars_unconstrained)
481: .method("unconstrained_param_names",
482: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::unconstrained_param_names)
483: .method("constrained_param_names",
484: &rstan::stan_fit<model5b4846796203_8schools_namespace::model5b4846796203_8schools, boost::random::ecuyer1988>::constrained_param_names)
485: ;
486: }
487:
488: // declarations
489: extern "C" {
490: SEXP file5b482c35e703( ) ;
491: }
492:
493: // definition
494:
495: SEXP file5b482c35e703( ){
496: return Rcpp::wrap("8schools");
497: }
498:
499:
Error in compileCode(f, code, language = language, verbose = verbose) :
Compilation ERROR, function(s)/method(s) not created! In file included from /users/tblanchard/apps/R/StanHeaders/include/stan/math/prim/arr.hpp:33,
from /users/tblanchard/apps/R/StanHeaders/include/stan/math/prim/mat.hpp:232,
from /users/tblanchard/apps/R/StanHeaders/include/stan/math/rev/mat.hpp:8,
from /users/tblanchard/apps/R/StanHeaders/include/stan/math.hpp:4,
from /users/tblanchard/apps/R/StanHeaders/include/src/stan/model/model_header.hpp:4,
from file5b482c35e703.cpp:8:
/users/tblanchard/apps/R/StanHeaders/include/stan/math/prim/arr/functor/integrate_ode_rk45.hpp: In function ‘std::vector<std::vector<typename stan::return_type<T_y, T_loc, double, double, double, double>::type, std::allocator<typename stan::return_type<T_y, T_loc, double, double, double, double>::type> >, std::allocator<std::vector<typename stan::return_type<T_y, T_loc, double, double, double, double>::type, std::allo
In addition: Warning message:
running command '/n/sw/fasrcsw/apps/Core/R_core/3.2.0-fasrc01/lib64/R/bin/R CMD SHLIB file5b482c35e703.cpp 2> file5b482c35e703.cpp.err.txt' had status 1
Daniel Lee
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Tommy Blanchard
huiying
Craig Wang
Ben Goodrich
I was installing my eggCounts package and received the same errors with BH 1.58.x-x, but it worked with BH 1.60.0-2. so a simple update should fix.
Thanks. It looks like I should increase the minimum required version of BH.
Ben