Last updated on 2024-11-22 09:49:18 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.3.0 | 8.29 | 324.91 | 333.20 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.3.0 | 5.72 | 254.67 | 260.39 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.3.0 | 505.45 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.3.0 | 308.24 | ERROR | |||
| r-devel-windows-x86_64 | 1.3.0 | 12.00 | 244.00 | 256.00 | OK | |
| r-patched-linux-x86_64 | 1.3.0 | 11.70 | 347.88 | 359.58 | OK | |
| r-release-linux-x86_64 | 1.3.0 | 9.98 | 352.05 | 362.03 | OK | |
| r-release-macos-arm64 | 1.3.0 | 53.00 | ERROR | |||
| r-release-macos-x86_64 | 1.3.0 | 94.00 | ERROR | |||
| r-release-windows-x86_64 | 1.3.0 | 14.00 | 246.00 | 260.00 | OK | |
| r-oldrel-macos-arm64 | 1.3.0 | 144.00 | OK | |||
| r-oldrel-macos-x86_64 | 1.3.0 | 448.00 | OK | |||
| r-oldrel-windows-x86_64 | 1.3.0 | 14.00 | 304.00 | 318.00 | OK |
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [177s/259s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(rbmi)
>
> test_check("rbmi")
mmrm() registered as emmeans extension
[ FAIL 4 | WARN 0 | SKIP 13 | PASS 1243 ]
══ Skipped tests (13) ══════════════════════════════════════════════════════════
• On CRAN (1): 'test-mmrm.R:337:5'
• is_full_test() is not TRUE (12): 'test-draws.R:115:5',
'test-fullusage.R:43:5', 'test-fullusage.R:117:5', 'test-fullusage.R:209:5',
'test-fullusage.R:300:5', 'test-fullusage.R:431:5', 'test-fullusage.R:520:5',
'test-fullusage.R:673:5', 'test-mcmc.R:327:5', 'test-mcmc.R:502:5',
'test-parallel.R:8:5', 'test-reproducibility.R:9:5'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-draws.R:144:9'): bayes ─────────────────────────────────────────
Error in `fit_mcmc(designmat = model_df_scaled[, -1, drop = FALSE], outcome = model_df_scaled[,
1, drop = TRUE], group = data2[[vars$group]], visit = data2[[vars$visit]],
subjid = data2[[vars$subjid]], method = method, quiet = quiet)`: unable to load shared object '/tmp/Rtmpu9A0BQ/working_dir/RtmpuXGzGB/fileeef39473f7d5e.so':
libunwind.so.1: cannot open shared object file: No such file or directory
Backtrace:
▆
1. ├─base::suppressWarnings(...) at test-draws.R:143:5
2. │ └─base::withCallingHandlers(...)
3. ├─rbmi::draws(d$dat, d$dat_ice, d$vars, meth, quiet = TRUE) at test-draws.R:144:9
4. └─rbmi:::draws.bayes(d$dat, d$dat_ice, d$vars, meth, quiet = TRUE)
5. └─rbmi:::fit_mcmc(...)
── Error ('test-mcmc.R:108:13'): Verbose suppression works ─────────────────────
Error in `fit_mcmc(designmat = model_df_scaled[, -1, drop = FALSE], outcome = model_df_scaled[,
1, drop = TRUE], group = data2[[vars$group]], visit = data2[[vars$visit]],
subjid = data2[[vars$subjid]], method = method, quiet = quiet)`: unable to load shared object '/tmp/Rtmpu9A0BQ/working_dir/RtmpuXGzGB/fileeef397b8ebfbc.so':
libunwind.so.1: cannot open shared object file: No such file or directory
Backtrace:
▆
1. ├─base::suppressWarnings(...) at test-mcmc.R:106:5
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...) at test-mcmc.R:107:9
4. │ └─base::withVisible(...elt(i))
5. ├─rbmi::draws(...) at test-mcmc.R:108:13
6. └─rbmi:::draws.bayes(...)
7. └─rbmi:::fit_mcmc(...)
── Error ('test-print.R:102:9'): print - bayesian ──────────────────────────────
Error in `fit_mcmc(designmat = model_df_scaled[, -1, drop = FALSE], outcome = model_df_scaled[,
1, drop = TRUE], group = data2[[vars$group]], visit = data2[[vars$visit]],
subjid = data2[[vars$subjid]], method = method, quiet = quiet)`: unable to load shared object '/tmp/Rtmpu9A0BQ/working_dir/RtmpuXGzGB/fileeef3926636ec7.so':
libunwind.so.1: cannot open shared object file: No such file or directory
Backtrace:
▆
1. ├─base::suppressWarnings(...) at test-print.R:101:5
2. │ └─base::withCallingHandlers(...)
3. ├─rbmi::draws(...) at test-print.R:102:9
4. └─rbmi:::draws.bayes(...)
5. └─rbmi:::fit_mcmc(...)
── Error ('test-reproducibility.R:121:9'): bayes - set.seed produces identical results ──
Error in `fit_mcmc(designmat = model_df_scaled[, -1, drop = FALSE], outcome = model_df_scaled[,
1, drop = TRUE], group = data2[[vars$group]], visit = data2[[vars$visit]],
subjid = data2[[vars$subjid]], method = method, quiet = quiet)`: unable to load shared object '/tmp/Rtmpu9A0BQ/working_dir/RtmpuXGzGB/fileeef3970e40e14.so':
libunwind.so.1: cannot open shared object file: No such file or directory
Backtrace:
▆
1. ├─base::suppressWarnings(...) at test-reproducibility.R:120:5
2. │ └─base::withCallingHandlers(...)
3. ├─rbmi::draws(dat, dat_ice, vars, meth, quiet = TRUE) at test-reproducibility.R:121:9
4. └─rbmi:::draws.bayes(dat, dat_ice, vars, meth, quiet = TRUE)
5. └─rbmi:::fit_mcmc(...)
[ FAIL 4 | WARN 0 | SKIP 13 | PASS 1243 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [7s/10s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(rbmi)
>
> test_check("rbmi")
*** caught segfault ***
address 0x0, cause 'invalid permissions'
Traceback:
1: Module(module, mustStart = TRUE)
2: .getModulePointer(x)
3: new("Module", .xData = <environment>)$stan_fit4model10310783487d8_rbmi_mmrm
4: new("Module", .xData = <environment>)$stan_fit4model10310783487d8_rbmi_mmrm
5: eval(call("$", mod, paste("stan_fit4", model_cppname, sep = "")))
6: eval(call("$", mod, paste("stan_fit4", model_cppname, sep = "")))
7: object@mk_cppmodule(object)
8: .local(object, ...)
9: (new("nonstandardGenericFunction", .Data = function (object, ...) { standardGeneric("sampling")}, generic = "sampling", package = "rstan", group = list(), valueClass = character(0), signature = "object", default = NULL, skeleton = (function (object, ...) stop(gettextf("invalid call in method dispatch to '%s' (no default method)", "sampling"), domain = NA))(object, ...)))(object = new("stanmodel", model_name = "rbmi_mmrm", model_code = "functions {\n int integer_division(int a, int b) {\n // perform a/b ensuring return value is also an int\n int i = 0;\n while(b*(i+1) <= a) {\n i = i + 1;\n }\n return(i);\n }\n array[] vector to_vector_of_arrays(vector vec, int length_array) {\n // treansform a vector into a vector of arrays. Example: vec = [1,2,3,4,5,6] and\n // length_array = 2, then output = [1,2; 3,4; 5,6]\n array[integer_division(num_elements(vec),length_array)] vector[length_array] res;\n int j = 1;\n int i = 1;\n while(j <= num_elements(vec)) {\n res[i,] = vec[j:(j+length_array-1)];\n i = i+1;\n j = j + length_array;\n }\n return(res);\n }\n}\ndata {\n int<lower=1> N; // number of observations\n int<lower=1> P; // number of covariates (number of columns of design matrix)\n int<lower=1> G; // number of Sigma Groups\n int<lower=1> n_visit; // number of visits\n int<lower=1> n_pat; // number of pat groups (# missingness patterns * groups)\n array[n_pat] int<lower=1> pat_G; // Index for which Sigma the pat group should use\n array[n_pat] int<lower=1> pat_n_pt; // number of patients in each pat group\n array[n_pat] int<lower=1> pat_n_visit; // number of non-missing visits in each pat group\n array[n_pat, n_visit] int<lower=1> pat_sigma_index; // rows/cols from sigma to subset on for the pat group\n vector[N] y; // outcome variable\n matrix[N,P] Q; // design matrix (After QR decomp)\n matrix[P,P] R; // R matrix (from QR decomp)\n array[G] matrix[n_visit, n_visit] Sigma_init; // covariance matrix estimated from MMRM\n}\ntransformed data {\n matrix[P, P] R_inverse = inverse(R);\n}\nparameters {\n vector[P] theta; // coefficients of linear model on covariates\n array[G] cov_matrix[n_visit] Sigma; // covariance matrix(s)\n}\nmodel {\n int data_start_row = 1;\n vector[N] mu = Q * theta;\n for(g in 1:G){\n Sigma[g] ~ inv_wishart(n_visit+2, Sigma_init[g]);\n }\n for(i in 1:n_pat) {\n // Index + size variables for current pat group\n int nvis = pat_n_visit[i]; // number of visits\n int npt = pat_n_pt[i]; // number of patients\n int g = pat_G[i]; // Sigma index\n // Get required/reduced Sigma for current pat group\n array[nvis] int sig_index = pat_sigma_index[i, 1:nvis];\n matrix[nvis,nvis] sig = Sigma[g][sig_index, sig_index];\n // Derive data indcies for current pat group\n int data_stop_row = data_start_row + ((nvis * npt) -1);\n // Extract required data for the current pat group\n array[npt] vector[nvis] y_obs = to_vector_of_arrays(y[data_start_row:data_stop_row], nvis);\n array[npt] vector[nvis] mu_obs = to_vector_of_arrays(mu[data_start_row:data_stop_row], nvis);\n y_obs ~ multi_normal(mu_obs, sig);\n // Update data index for next pat group\n data_start_row = data_stop_row + 1;\n }\n}\ngenerated quantities {\n vector[P] beta = R_inverse * theta;\n}", model_cpp = list(model_cppname = "model10310783487d8_rbmi_mmrm", model_cppcode = "#ifndef MODELS_HPP\n#define MODELS_HPP\n#define STAN__SERVICES__COMMAND_HPP\n#include <rstan/rstaninc.hpp>\n#ifndef USE_STANC3\n#define USE_STANC3\n#endif\n// Code generated by stanc v2.32.2\n#include <stan/model/model_header.hpp>\nnamespace model10310783487d8_rbmi_mmrm_namespace {\nusing stan::model::model_base_crtp;\nusing namespace stan::math;\nstan::math::profile_map profiles__;\nstatic constexpr std::array<const char*, 80> locations_array__ =\n {\" (found before start of program)\",\n \" (in 'rbmi_mmrm', line 43, column 4 to column 20)\",\n \" (in 'rbmi_mmrm', line 44, column 4 to column 39)\",\n \" (in 'rbmi_mmrm', line 71, column 3 to column 38)\",\n \" (in 'rbmi_mmrm', line 47, column 4 to column 27)\",\n \" (in 'rbmi_mmrm', line 48, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 48, column 4 to column 29)\",\n \" (in 'rbmi_mmrm', line 50, column 8 to column 57)\",\n \" (in 'rbmi_mmrm', line 49, column 17 to line 51, column 5)\",\n \" (in 'rbmi_mmrm', line 49, column 4 to line 51, column 5)\",\n \" (in 'rbmi_mmrm', line 54, column 8 to column 34)\",\n \" (in 'rbmi_mmrm', line 55, column 8 to column 30)\",\n \" (in 'rbmi_mmrm', line 56, column 8 to column 25)\",\n \" (in 'rbmi_mmrm', line 58, column 14 to column 18)\",\n \" (in 'rbmi_mmrm', line 58, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 59, column 15 to column 19)\",\n \" (in 'rbmi_mmrm', line 59, column 20 to column 24)\",\n \" (in 'rbmi_mmrm', line 59, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 61, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 63, column 14 to column 17)\",\n \" (in 'rbmi_mmrm', line 63, column 26 to column 30)\",\n \" (in 'rbmi_mmrm', line 63, column 8 to column 99)\",\n \" (in 'rbmi_mmrm', line 64, column 14 to column 17)\",\n \" (in 'rbmi_mmrm', line 64, column 26 to column 30)\",\n \" (in 'rbmi_mmrm', line 64, column 8 to column 101)\",\n \" (in 'rbmi_mmrm', line 65, column 8 to column 42)\",\n \" (in 'rbmi_mmrm', line 67, column 8 to column 43)\",\n \" (in 'rbmi_mmrm', line 52, column 22 to line 68, column 5)\",\n \" (in 'rbmi_mmrm', line 52, column 4 to line 68, column 5)\",\n \" (in 'rbmi_mmrm', line 25, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 26, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 27, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 28, column 4 to column 25)\",\n \" (in 'rbmi_mmrm', line 29, column 4 to column 23)\",\n \" (in 'rbmi_mmrm', line 30, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 30, column 4 to column 36)\",\n \" (in 'rbmi_mmrm', line 31, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 31, column 4 to column 39)\",\n \" (in 'rbmi_mmrm', line 32, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 32, column 4 to column 42)\",\n \" (in 'rbmi_mmrm', line 33, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 33, column 17 to column 24)\",\n \" (in 'rbmi_mmrm', line 33, column 4 to column 55)\",\n \" (in 'rbmi_mmrm', line 34, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 34, column 4 to column 16)\",\n \" (in 'rbmi_mmrm', line 35, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 35, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 35, column 4 to column 18)\",\n \" (in 'rbmi_mmrm', line 36, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 36, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 36, column 4 to column 18)\",\n \" (in 'rbmi_mmrm', line 37, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 37, column 20 to column 27)\",\n \" (in 'rbmi_mmrm', line 37, column 29 to column 36)\",\n \" (in 'rbmi_mmrm', line 37, column 4 to column 49)\",\n \" (in 'rbmi_mmrm', line 40, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 40, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 40, column 3 to column 39)\",\n \" (in 'rbmi_mmrm', line 43, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 44, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 44, column 24 to column 31)\",\n \" (in 'rbmi_mmrm', line 71, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 4, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 6, column 12 to column 22)\",\n \" (in 'rbmi_mmrm', line 5, column 28 to line 7, column 9)\",\n \" (in 'rbmi_mmrm', line 5, column 8 to line 7, column 9)\",\n \" (in 'rbmi_mmrm', line 8, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 2, column 39 to line 9, column 5)\",\n \" (in 'rbmi_mmrm', line 13, column 14 to column 62)\",\n \" (in 'rbmi_mmrm', line 13, column 71 to column 83)\",\n \" (in 'rbmi_mmrm', line 13, column 8 to column 89)\",\n \" (in 'rbmi_mmrm', line 14, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 15, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 17, column 12 to column 48)\",\n \" (in 'rbmi_mmrm', line 18, column 12 to column 20)\",\n \" (in 'rbmi_mmrm', line 19, column 12 to column 33)\",\n \" (in 'rbmi_mmrm', line 16, column 38 to line 20, column 9)\",\n \" (in 'rbmi_mmrm', line 16, column 8 to line 20, column 9)\",\n \" (in 'rbmi_mmrm', line 21, column 8 to column 20)\",\n \" (in 'rbmi_mmrm', line 10, column 69 to line 22, column 5)\"};\nint integer_division(const int& a, const int& b, std::ostream* pstream__);\ntemplate <typename T0__,\n stan::require_all_t<stan::is_col_vector<T0__>,\n stan::is_vt_not_complex<T0__>>* = nullptr>\nstd::vector<\n Eigen::Matrix<stan::promote_args_t<stan::base_type_t<T0__>>,-1,1>>\nto_vector_of_arrays(const T0__& vec_arg__, const int& length_array,\n std::ostream* pstream__);\nint integer_division(const int& a, const int& b, std::ostream* pstream__) {\n using local_scalar_t__ = double;\n int current_statement__ = 0;\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int i = std::numeric_limits<int>::min();\n current_statement__ = 62;\n i = 0;\n current_statement__ = 65;\n while (stan::math::logical_lte((b * (i + 1)), a)) {\n current_statement__ = 63;\n i = (i + 1);\n }\n current_statement__ = 66;\n return i;\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n}\ntemplate <typename T0__,\n stan::require_all_t<stan::is_col_vector<T0__>,\n stan::is_vt_not_complex<T0__>>*>\nstd::vector<\n Eigen::Matrix<stan::promote_args_t<stan::base_type_t<T0__>>,-1,1>>\nto_vector_of_arrays(const T0__& vec_arg__, const int& length_array,\n std::ostream* pstream__) {\n using local_scalar_t__ = stan::promote_args_t<stan::base_type_t<T0__>>;\n int current_statement__ = 0;\n const auto& vec = stan::math::to_ref(vec_arg__);\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n current_statement__ = 68;\n stan::math::validate_non_negative_index(\"res\",\n \"integer_division(num_elements(vec), length_array)\",\n integer_division(stan::math::num_elements(vec), length_array, pstream__));\n current_statement__ = 69;\n stan::math::validate_non_negative_index(\"res\", \"length_array\",\n length_array);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> res =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(integer_division(\n stan::math::num_elements(\n vec),\n length_array,\n pstream__),\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(length_array,\n DUMMY_VAR__));\n int j = std::numeric_limits<int>::min();\n current_statement__ = 71;\n j = 1;\n int i = std::numeric_limits<int>::min();\n current_statement__ = 72;\n i = 1;\n current_statement__ = 77;\n while (stan::math::logical_lte(j, stan::math::num_elements(vec))) {\n current_statement__ = 73;\n stan::model::assign(res,\n stan::model::rvalue(vec, \"vec\",\n stan::model::index_min_max(j, ((j + length_array) - 1))),\n \"assigning variable res\", stan::model::index_uni(i),\n stan::model::index_omni());\n current_statement__ = 74;\n i = (i + 1);\n current_statement__ = 75;\n j = (j + length_array);\n }\n current_statement__ = 78;\n return res;\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n}\nclass model10310783487d8_rbmi_mmrm final : public model_base_crtp<model10310783487d8_rbmi_mmrm> {\nprivate:\n int N;\n int P;\n int G;\n int n_visit;\n int n_pat;\n std::vector<int> pat_G;\n std::vector<int> pat_n_pt;\n std::vector<int> pat_n_visit;\n std::vector<std::vector<int>> pat_sigma_index;\n Eigen::Matrix<double,-1,1> y_data__;\n Eigen::Matrix<double,-1,-1> Q_data__;\n Eigen::Matrix<double,-1,-1> R_data__;\n std::vector<Eigen::Matrix<double,-1,-1>> Sigma_init;\n Eigen::Matrix<double,-1,-1> R_inverse_data__;\n Eigen::Map<Eigen::Matrix<double,-1,1>> y{nullptr, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> Q{nullptr, 0, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> R{nullptr, 0, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> R_inverse{nullptr, 0, 0};\npublic:\n ~model10310783487d8_rbmi_mmrm() {}\n model10310783487d8_rbmi_mmrm(stan::io::var_context& context__, unsigned int\n random_seed__ = 0, std::ostream*\n pstream__ = nullptr) : model_base_crtp(0) {\n int current_statement__ = 0;\n using local_scalar_t__ = double;\n boost::ecuyer1988 base_rng__ =\n stan::services::util::create_rng(random_seed__, 0);\n // suppress unused var warning\n (void) base_rng__;\n static constexpr const char* function__ =\n \"model10310783487d8_rbmi_mmrm_namespace::model10310783487d8_rbmi_mmrm\";\n // suppress unused var warning\n (void) function__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n current_statement__ = 29;\n context__.validate_dims(\"data initialization\", \"N\", \"int\",\n std::vector<size_t>{});\n N = std::numeric_limits<int>::min();\n current_statement__ = 29;\n N = context__.vals_i(\"N\")[(1 - 1)];\n current_statement__ = 29;\n stan::math::check_greater_or_equal(function__, \"N\", N, 1);\n current_statement__ = 30;\n context__.validate_dims(\"data initialization\", \"P\", \"int\",\n std::vector<size_t>{});\n P = std::numeric_limits<int>::min();\n current_statement__ = 30;\n P = context__.vals_i(\"P\")[(1 - 1)];\n current_statement__ = 30;\n stan::math::check_greater_or_equal(function__, \"P\", P, 1);\n current_statement__ = 31;\n context__.validate_dims(\"data initialization\", \"G\", \"int\",\n std::vector<size_t>{});\n G = std::numeric_limits<int>::min();\n current_statement__ = 31;\n G = context__.vals_i(\"G\")[(1 - 1)];\n current_statement__ = 31;\n stan::math::check_greater_or_equal(function__, \"G\", G, 1);\n current_statement__ = 32;\n context__.validate_dims(\"data initialization\", \"n_visit\", \"int\",\n std::vector<size_t>{});\n n_visit = std::numeric_limits<int>::min();\n current_statement__ = 32;\n n_visit = context__.vals_i(\"n_visit\")[(1 - 1)];\n current_statement__ = 32;\n stan::math::check_greater_or_equal(function__, \"n_visit\", n_visit, 1);\n current_statement__ = 33;\n context__.validate_dims(\"data initialization\", \"n_pat\", \"int\",\n std::vector<size_t>{});\n n_pat = std::numeric_limits<int>::min();\n current_statement__ = 33;\n n_pat = context__.vals_i(\"n_pat\")[(1 - 1)];\n current_statement__ = 33;\n stan::math::check_greater_or_equal(function__, \"n_pat\", n_pat, 1);\n current_statement__ = 34;\n stan::math::validate_non_negative_index(\"pat_G\", \"n_pat\", n_pat);\n current_statement__ = 35;\n context__.validate_dims(\"data initialization\", \"pat_G\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_G = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 35;\n pat_G = context__.vals_i(\"pat_G\");\n current_statement__ = 35;\n stan::math::check_greater_or_equal(function__, \"pat_G\", pat_G, 1);\n current_statement__ = 36;\n stan::math::validate_non_negative_index(\"pat_n_pt\", \"n_pat\", n_pat);\n current_statement__ = 37;\n context__.validate_dims(\"data initialization\", \"pat_n_pt\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_n_pt = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 37;\n pat_n_pt = context__.vals_i(\"pat_n_pt\");\n current_statement__ = 37;\n stan::math::check_greater_or_equal(function__, \"pat_n_pt\", pat_n_pt, 1);\n current_statement__ = 38;\n stan::math::validate_non_negative_index(\"pat_n_visit\", \"n_pat\", n_pat);\n current_statement__ = 39;\n context__.validate_dims(\"data initialization\", \"pat_n_visit\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_n_visit = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 39;\n pat_n_visit = context__.vals_i(\"pat_n_visit\");\n current_statement__ = 39;\n stan::math::check_greater_or_equal(function__, \"pat_n_visit\",\n pat_n_visit, 1);\n current_statement__ = 40;\n stan::math::validate_non_negative_index(\"pat_sigma_index\", \"n_pat\",\n n_pat);\n current_statement__ = 41;\n stan::math::validate_non_negative_index(\"pat_sigma_index\", \"n_visit\",\n n_visit);\n current_statement__ = 42;\n context__.validate_dims(\"data initialization\", \"pat_sigma_index\",\n \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat),\n static_cast<size_t>(n_visit)});\n pat_sigma_index = std::vector<std::vector<int>>(n_pat,\n std::vector<int>(n_visit,\n std::numeric_limits<int>::min()));\n {\n std::vector<int> pat_sigma_index_flat__;\n current_statement__ = 42;\n pat_sigma_index_flat__ = context__.vals_i(\"pat_sigma_index\");\n current_statement__ = 42;\n pos__ = 1;\n current_statement__ = 42;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 42;\n for (int sym2__ = 1; sym2__ <= n_pat; ++sym2__) {\n current_statement__ = 42;\n stan::model::assign(pat_sigma_index,\n pat_sigma_index_flat__[(pos__ - 1)],\n \"assigning variable pat_sigma_index\",\n stan::model::index_uni(sym2__), stan::model::index_uni(sym1__));\n current_statement__ = 42;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 42;\n stan::math::check_greater_or_equal(function__, \"pat_sigma_index\",\n pat_sigma_index, 1);\n current_statement__ = 43;\n stan::math::validate_non_negative_index(\"y\", \"N\", N);\n current_statement__ = 44;\n context__.validate_dims(\"data initialization\", \"y\", \"double\",\n std::vector<size_t>{static_cast<size_t>(N)});\n y_data__ = Eigen::Matrix<double,-1,1>::Constant(N,\n std::numeric_limits<double>::quiet_NaN());\n new (&y) Eigen::Map<Eigen::Matrix<double,-1,1>>(y_data__.data(), N);\n {\n std::vector<local_scalar_t__> y_flat__;\n current_statement__ = 44;\n y_flat__ = context__.vals_r(\"y\");\n current_statement__ = 44;\n pos__ = 1;\n current_statement__ = 44;\n for (int sym1__ = 1; sym1__ <= N; ++sym1__) {\n current_statement__ = 44;\n stan::model::assign(y, y_flat__[(pos__ - 1)],\n \"assigning variable y\", stan::model::index_uni(sym1__));\n current_statement__ = 44;\n pos__ = (pos__ + 1);\n }\n }\n current_statement__ = 45;\n stan::math::validate_non_negative_index(\"Q\", \"N\", N);\n current_statement__ = 46;\n stan::math::validate_non_negative_index(\"Q\", \"P\", P);\n current_statement__ = 47;\n context__.validate_dims(\"data initialization\", \"Q\", \"double\",\n std::vector<size_t>{static_cast<size_t>(N), static_cast<size_t>(P)});\n Q_data__ = Eigen::Matrix<double,-1,-1>::Constant(N, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&Q) Eigen::Map<Eigen::Matrix<double,-1,-1>>(Q_data__.data(), N, P);\n {\n std::vector<local_scalar_t__> Q_flat__;\n current_statement__ = 47;\n Q_flat__ = context__.vals_r(\"Q\");\n current_statement__ = 47;\n pos__ = 1;\n current_statement__ = 47;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 47;\n for (int sym2__ = 1; sym2__ <= N; ++sym2__) {\n current_statement__ = 47;\n stan::model::assign(Q, Q_flat__[(pos__ - 1)],\n \"assigning variable Q\", stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 47;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 48;\n stan::math::validate_non_negative_index(\"R\", \"P\", P);\n current_statement__ = 49;\n stan::math::validate_non_negative_index(\"R\", \"P\", P);\n current_statement__ = 50;\n context__.validate_dims(\"data initialization\", \"R\", \"double\",\n std::vector<size_t>{static_cast<size_t>(P), static_cast<size_t>(P)});\n R_data__ = Eigen::Matrix<double,-1,-1>::Constant(P, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&R) Eigen::Map<Eigen::Matrix<double,-1,-1>>(R_data__.data(), P, P);\n {\n std::vector<local_scalar_t__> R_flat__;\n current_statement__ = 50;\n R_flat__ = context__.vals_r(\"R\");\n current_statement__ = 50;\n pos__ = 1;\n current_statement__ = 50;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 50;\n for (int sym2__ = 1; sym2__ <= P; ++sym2__) {\n current_statement__ = 50;\n stan::model::assign(R, R_flat__[(pos__ - 1)],\n \"assigning variable R\", stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 50;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 51;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"G\", G);\n current_statement__ = 52;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"n_visit\",\n n_visit);\n current_statement__ = 53;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"n_visit\",\n n_visit);\n current_statement__ = 54;\n context__.validate_dims(\"data initialization\", \"Sigma_init\", \"double\",\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)});\n Sigma_init = std::vector<Eigen::Matrix<double,-1,-1>>(G,\n Eigen::Matrix<double,-1,-1>::Constant(n_visit, n_visit,\n std::numeric_limits<double>::quiet_NaN()));\n {\n std::vector<local_scalar_t__> Sigma_init_flat__;\n current_statement__ = 54;\n Sigma_init_flat__ = context__.vals_r(\"Sigma_init\");\n current_statement__ = 54;\n pos__ = 1;\n current_statement__ = 54;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 54;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 54;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 54;\n stan::model::assign(Sigma_init, Sigma_init_flat__[(pos__ - 1)],\n \"assigning variable Sigma_init\",\n stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 54;\n pos__ = (pos__ + 1);\n }\n }\n }\n }\n current_statement__ = 55;\n stan::math::validate_non_negative_index(\"R_inverse\", \"P\", P);\n current_statement__ = 56;\n stan::math::validate_non_negative_index(\"R_inverse\", \"P\", P);\n current_statement__ = 57;\n R_inverse_data__ = Eigen::Matrix<double,-1,-1>::Constant(P, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&R_inverse)\n Eigen::Map<Eigen::Matrix<double,-1,-1>>(R_inverse_data__.data(), P,\n P);\n current_statement__ = 57;\n stan::model::assign(R_inverse, stan::math::inverse(R),\n \"assigning variable R_inverse\");\n current_statement__ = 58;\n stan::math::validate_non_negative_index(\"theta\", \"P\", P);\n current_statement__ = 59;\n stan::math::validate_non_negative_index(\"Sigma\", \"G\", G);\n current_statement__ = 60;\n stan::math::validate_non_negative_index(\"Sigma\", \"n_visit\", n_visit);\n current_statement__ = 60;\n stan::math::validate_non_negative_index(\"Sigma\", \"n_visit\", n_visit);\n current_statement__ = 61;\n stan::math::validate_non_negative_index(\"beta\", \"P\", P);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n num_params_r__ = P + (G * (n_visit + ((n_visit * (n_visit - 1)) / 2)));\n }\n inline std::string model_name() const final {\n return \"model10310783487d8_rbmi_mmrm\";\n }\n inline std::vector<std::string> model_compile_info() const noexcept {\n return std::vector<std::string>{\"stanc_version = stanc3 v2.32.2\",\n \"stancflags = --\"};\n }\n template <bool propto__, bool jacobian__, typename VecR, typename VecI,\n stan::require_vector_like_t<VecR>* = nullptr,\n stan::require_vector_like_vt<std::is_integral, VecI>* = nullptr>\n inline stan::scalar_type_t<VecR>\n log_prob_impl(VecR& params_r__, VecI& params_i__, std::ostream*\n pstream__ = nullptr) const {\n using T__ = stan::scalar_type_t<VecR>;\n using local_scalar_t__ = T__;\n T__ lp__(0.0);\n stan::math::accumulator<T__> lp_accum__;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n static constexpr const char* function__ =\n \"model10310783487d8_rbmi_mmrm_namespace::log_prob\";\n // suppress unused var warning\n (void) function__;\n try {\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n current_statement__ = 1;\n theta = in__.template read<Eigen::Matrix<local_scalar_t__,-1,1>>(P);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n current_statement__ = 2;\n Sigma = in__.template read_constrain_cov_matrix<\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,\n jacobian__>(lp__, G, n_visit);\n {\n int data_start_row = std::numeric_limits<int>::min();\n current_statement__ = 4;\n data_start_row = 1;\n current_statement__ = 5;\n stan::math::validate_non_negative_index(\"mu\", \"N\", N);\n Eigen::Matrix<local_scalar_t__,-1,1> mu =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(N, DUMMY_VAR__);\n current_statement__ = 6;\n stan::model::assign(mu, stan::math::multiply(Q, theta),\n \"assigning variable mu\");\n current_statement__ = 9;\n for (int g = 1; g <= G; ++g) {\n current_statement__ = 7;\n lp_accum__.add(stan::math::inv_wishart_lpdf<propto__>(\n stan::model::rvalue(Sigma, \"Sigma\",\n stan::model::index_uni(g)), (n_visit + 2),\n stan::model::rvalue(Sigma_init, \"Sigma_init\",\n stan::model::index_uni(g))));\n }\n current_statement__ = 28;\n for (int i = 1; i <= n_pat; ++i) {\n int nvis = std::numeric_limits<int>::min();\n current_statement__ = 10;\n nvis = stan::model::rvalue(pat_n_visit, \"pat_n_visit\",\n stan::model::index_uni(i));\n int npt = std::numeric_limits<int>::min();\n current_statement__ = 11;\n npt = stan::model::rvalue(pat_n_pt, \"pat_n_pt\",\n stan::model::index_uni(i));\n int g = std::numeric_limits<int>::min();\n current_statement__ = 12;\n g = stan::model::rvalue(pat_G, \"pat_G\", stan::model::index_uni(i));\n current_statement__ = 13;\n stan::math::validate_non_negative_index(\"sig_index\", \"nvis\", nvis);\n std::vector<int> sig_index =\n std::vector<int>(nvis, std::numeric_limits<int>::min());\n current_statement__ = 14;\n stan::model::assign(sig_index,\n stan::model::rvalue(pat_sigma_index, \"pat_sigma_index\",\n stan::model::index_uni(i), stan::model::index_min_max(1, nvis)),\n \"assigning variable sig_index\");\n current_statement__ = 15;\n stan::math::validate_non_negative_index(\"sig\", \"nvis\", nvis);\n current_statement__ = 16;\n stan::math::validate_non_negative_index(\"sig\", \"nvis\", nvis);\n Eigen::Matrix<local_scalar_t__,-1,-1> sig =\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(nvis, nvis,\n DUMMY_VAR__);\n current_statement__ = 17;\n stan::model::assign(sig,\n stan::model::rvalue(\n stan::model::rvalue(Sigma, \"Sigma\", stan::model::index_uni(g)),\n \"Sigma[g]\", stan::model::index_multi(sig_index),\n stan::model::index_multi(sig_index)), \"assigning variable sig\");\n int data_stop_row = std::numeric_limits<int>::min();\n current_statement__ = 18;\n data_stop_row = (data_start_row + ((nvis * npt) - 1));\n current_statement__ = 19;\n stan::math::validate_non_negative_index(\"y_obs\", \"npt\", npt);\n current_statement__ = 20;\n stan::math::validate_non_negative_index(\"y_obs\", \"nvis\", nvis);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> y_obs =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(npt,\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(nvis,\n DUMMY_VAR__));\n current_statement__ = 21;\n stan::model::assign(y_obs,\n to_vector_of_arrays(\n stan::model::rvalue(y, \"y\",\n stan::model::index_min_max(data_start_row, data_stop_row)),\n nvis, pstream__), \"assigning variable y_obs\");\n current_statement__ = 22;\n stan::math::validate_non_negative_index(\"mu_obs\", \"npt\", npt);\n current_statement__ = 23;\n stan::math::validate_non_negative_index(\"mu_obs\", \"nvis\", nvis);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> mu_obs =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(npt,\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(nvis,\n DUMMY_VAR__));\n current_statement__ = 24;\n stan::model::assign(mu_obs,\n to_vector_of_arrays(\n stan::model::rvalue(mu, \"mu\",\n stan::model::index_min_max(data_start_row, data_stop_row)),\n nvis, pstream__), \"assigning variable mu_obs\");\n current_statement__ = 25;\n lp_accum__.add(stan::math::multi_normal_lpdf<propto__>(y_obs,\n mu_obs, sig));\n current_statement__ = 26;\n data_start_row = (data_stop_row + 1);\n }\n }\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n lp_accum__.add(lp__);\n return lp_accum__.sum();\n }\n template <typename RNG, typename VecR, typename VecI, typename VecVar,\n stan::require_vector_like_vt<std::is_floating_point,\n VecR>* = nullptr, stan::require_vector_like_vt<std::is_integral,\n VecI>* = nullptr, stan::require_vector_vt<std::is_floating_point,\n VecVar>* = nullptr>\n inline void\n write_array_impl(RNG& base_rng__, VecR& params_r__, VecI& params_i__,\n VecVar& vars__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true, std::ostream*\n pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n stan::io::serializer<local_scalar_t__> out__(vars__);\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n double lp__ = 0.0;\n // suppress unused var warning\n (void) lp__;\n int current_statement__ = 0;\n stan::math::accumulator<double> lp_accum__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n constexpr bool jacobian__ = false;\n static constexpr const char* function__ =\n \"model10310783487d8_rbmi_mmrm_namespace::write_array\";\n // suppress unused var warning\n (void) function__;\n try {\n Eigen::Matrix<double,-1,1> theta =\n Eigen::Matrix<double,-1,1>::Constant(P,\n std::numeric_limits<double>::quiet_NaN());\n current_statement__ = 1;\n theta = in__.template read<Eigen::Matrix<local_scalar_t__,-1,1>>(P);\n std::vector<Eigen::Matrix<double,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<double,-1,-1>>(G,\n Eigen::Matrix<double,-1,-1>::Constant(n_visit, n_visit,\n std::numeric_limits<double>::quiet_NaN()));\n current_statement__ = 2;\n Sigma = in__.template read_constrain_cov_matrix<\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,\n jacobian__>(lp__, G, n_visit);\n out__.write(theta);\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n out__.write(stan::model::rvalue(Sigma, \"Sigma\",\n stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__)));\n }\n }\n }\n if (stan::math::logical_negation(\n (stan::math::primitive_value(emit_transformed_parameters__) ||\n stan::math::primitive_value(emit_generated_quantities__)))) {\n return ;\n }\n if (stan::math::logical_negation(emit_generated_quantities__)) {\n return ;\n }\n Eigen::Matrix<double,-1,1> beta =\n Eigen::Matrix<double,-1,1>::Constant(P,\n std::numeric_limits<double>::quiet_NaN());\n current_statement__ = 3;\n stan::model::assign(beta, stan::math::multiply(R_inverse, theta),\n \"assigning variable beta\");\n out__.write(beta);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n template <typename VecVar, typename VecI,\n stan::require_vector_t<VecVar>* = nullptr,\n stan::require_vector_like_vt<std::is_integral, VecI>* = nullptr>\n inline void\n unconstrain_array_impl(const VecVar& params_r__, const VecI& params_i__,\n VecVar& vars__, std::ostream* pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n stan::io::serializer<local_scalar_t__> out__(vars__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n current_statement__ = 1;\n stan::model::assign(theta,\n in__.read<Eigen::Matrix<local_scalar_t__,-1,1>>(P),\n \"assigning variable theta\");\n out__.write(theta);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n current_statement__ = 2;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 2;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 2;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 2;\n stan::model::assign(Sigma, in__.read<local_scalar_t__>(),\n \"assigning variable Sigma\", stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__), stan::model::index_uni(sym1__));\n }\n }\n }\n out__.write_free_cov_matrix(Sigma);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n template <typename VecVar, stan::require_vector_t<VecVar>* = nullptr>\n inline void\n transform_inits_impl(const stan::io::var_context& context__, VecVar&\n vars__, std::ostream* pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::serializer<local_scalar_t__> out__(vars__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n current_statement__ = 1;\n context__.validate_dims(\"parameter initialization\", \"theta\", \"double\",\n std::vector<size_t>{static_cast<size_t>(P)});\n current_statement__ = 2;\n context__.validate_dims(\"parameter initialization\", \"Sigma\", \"double\",\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)});\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n {\n std::vector<local_scalar_t__> theta_flat__;\n current_statement__ = 1;\n theta_flat__ = context__.vals_r(\"theta\");\n current_statement__ = 1;\n pos__ = 1;\n current_statement__ = 1;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 1;\n stan::model::assign(theta, theta_flat__[(pos__ - 1)],\n \"assigning variable theta\", stan::model::index_uni(sym1__));\n current_statement__ = 1;\n pos__ = (pos__ + 1);\n }\n }\n out__.write(theta);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n {\n std::vector<local_scalar_t__> Sigma_flat__;\n current_statement__ = 2;\n Sigma_flat__ = context__.vals_r(\"Sigma\");\n current_statement__ = 2;\n pos__ = 1;\n current_statement__ = 2;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 2;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 2;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 2;\n stan::model::assign(Sigma, Sigma_flat__[(pos__ - 1)],\n \"assigning variable Sigma\", stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 2;\n pos__ = (pos__ + 1);\n }\n }\n }\n }\n out__.write_free_cov_matrix(Sigma);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n inline void\n get_param_names(std::vector<std::string>& names__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true) const {\n names__ = std::vector<std::string>{\"theta\", \"Sigma\"};\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n std::vector<std::string> temp{\"beta\"};\n names__.reserve(names__.size() + temp.size());\n names__.insert(names__.end(), temp.begin(), temp.end());\n }\n }\n inline void\n get_dims(std::vector<std::vector<size_t>>& dimss__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true) const {\n dimss__ = std::vector<std::vector<size_t>>{std::vector<size_t>{static_cast<\n size_t>(P)},\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)}};\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n std::vector<std::vector<size_t>>\n temp{std::vector<size_t>{static_cast<size_t>(P)}};\n dimss__.reserve(dimss__.size() + temp.size());\n dimss__.insert(dimss__.end(), temp.begin(), temp.end());\n }\n }\n inline void\n constrained_param_names(std::vector<std::string>& param_names__, bool\n emit_transformed_parameters__ = true, bool\n emit_generated_quantities__ = true) const final {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"theta\" + '.' +\n std::to_string(sym1__));\n }\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n param_names__.emplace_back(std::string() + \"Sigma\" + '.' +\n std::to_string(sym3__) + '.' + std::to_string(sym2__) + '.' +\n std::to_string(sym1__));\n }\n }\n }\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"beta\" + '.' +\n std::to_string(sym1__));\n }\n }\n }\n inline void\n unconstrained_param_names(std::vector<std::string>& param_names__, bool\n emit_transformed_parameters__ = true, bool\n emit_generated_quantities__ = true) const final {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"theta\" + '.' +\n std::to_string(sym1__));\n }\n for (int sym1__ = 1; sym1__ <= (n_visit + ((n_visit * (n_visit - 1)) /\n 2)); ++sym1__) {\n for (int sym2__ = 1; sym2__ <= G; ++sym2__) {\n param_names__.emplace_back(std::string() + \"Sigma\" + '.' +\n std::to_string(sym2__) + '.' + std::to_string(sym1__));\n }\n }\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"beta\" + '.' +\n std::to_string(sym1__));\n }\n }\n }\n inline std::string get_constrained_sizedtypes() const {\n return std::string(\"[{\\\"name\\\":\\\"theta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"Sigma\\\",\\\"type\\\":{\\\"name\\\":\\\"array\\\",\\\"length\\\":\" + std::to_string(G) + \",\\\"element_type\\\":{\\\"name\\\":\\\"matrix\\\",\\\"rows\\\":\" + std::to_string(n_visit) + \",\\\"cols\\\":\" + std::to_string(n_visit) + \"}},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"beta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"generated_quantities\\\"}]\");\n }\n inline std::string get_unconstrained_sizedtypes() const {\n return std::string(\"[{\\\"name\\\":\\\"theta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"Sigma\\\",\\\"type\\\":{\\\"name\\\":\\\"array\\\",\\\"length\\\":\" + std::to_string(G) + \",\\\"element_type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string((n_visit + ((n_visit * (n_visit - 1)) /2))) + \"}},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"beta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"generated_quantities\\\"}]\");\n }\n // Begin method overload boilerplate\n template <typename RNG> inline void\n write_array(RNG& base_rng, Eigen::Matrix<double,-1,1>& params_r,\n Eigen::Matrix<double,-1,1>& vars, const bool\n emit_transformed_parameters = true, const bool\n emit_generated_quantities = true, std::ostream*\n pstream = nullptr) const {\n const size_t num_params__ = (P + ((G * n_visit) * n_visit));\n const size_t num_transformed = emit_transformed_parameters * (0);\n const size_t num_gen_quantities = emit_generated_quantities * (P);\n const size_t num_to_write = num_params__ + num_transformed +\n num_gen_quantities;\n std::vector<int> params_i;\n vars = Eigen::Matrix<double,-1,1>::Constant(num_to_write,\n std::numeric_limits<double>::quiet_NaN());\n write_array_impl(base_rng, params_r, params_i, vars,\n emit_transformed_parameters, emit_generated_quantities, pstream);\n }\n template <typename RNG> inline void\n write_array(RNG& base_rng, std::vector<double>& params_r, std::vector<int>&\n params_i, std::vector<double>& vars, bool\n emit_transformed_parameters = true, bool\n emit_generated_quantities = true, std::ostream*\n pstream = nullptr) const {\n const size_t num_params__ = (P + ((G * n_visit) * n_visit));\n const size_t num_transformed = emit_transformed_parameters * (0);\n const size_t num_gen_quantities = emit_generated_quantities * (P);\n const size_t num_to_write = num_params__ + num_transformed +\n num_gen_quantities;\n vars = std::vector<double>(num_to_write,\n std::numeric_limits<double>::quiet_NaN());\n write_array_impl(base_rng, params_r, params_i, vars,\n emit_transformed_parameters, emit_generated_quantities, pstream);\n }\n template <bool propto__, bool jacobian__, typename T_> inline T_\n log_prob(Eigen::Matrix<T_,-1,1>& params_r, std::ostream* pstream = nullptr) const {\n Eigen::Matrix<int,-1,1> params_i;\n return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);\n }\n template <bool propto__, bool jacobian__, typename T_> inline T_\n log_prob(std::vector<T_>& params_r, std::vector<int>& params_i,\n std::ostream* pstream = nullptr) const {\n return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);\n }\n inline void\n transform_inits(const stan::io::var_context& context,\n Eigen::Matrix<double,-1,1>& params_r, std::ostream*\n pstream = nullptr) const final {\n std::vector<double> params_r_vec(params_r.size());\n std::vector<int> params_i;\n transform_inits(context, params_i, params_r_vec, pstream);\n params_r = Eigen::Map<Eigen::Matrix<double,-1,1>>(params_r_vec.data(),\n params_r_vec.size());\n }\n inline void\n transform_inits(const stan::io::var_context& context, std::vector<int>&\n params_i, std::vector<double>& vars, std::ostream*\n pstream__ = nullptr) const {\n vars.resize(num_params_r__);\n transform_inits_impl(context, vars, pstream__);\n }\n inline void\n unconstrain_array(const std::vector<double>& params_constrained,\n std::vector<double>& params_unconstrained, std::ostream*\n pstream = nullptr) const {\n const std::vector<int> params_i;\n params_unconstrained = std::vector<double>(num_params_r__,\n std::numeric_limits<double>::quiet_NaN());\n unconstrain_array_impl(params_constrained, params_i,\n params_unconstrained, pstream);\n }\n inline void\n unconstrain_array(const Eigen::Matrix<double,-1,1>& params_constrained,\n Eigen::Matrix<double,-1,1>& params_unconstrained,\n std::ostream* pstream = nullptr) const {\n const std::vector<int> params_i;\n params_unconstrained = Eigen::Matrix<double,-1,1>::Constant(num_params_r__,\n std::numeric_limits<double>::quiet_NaN());\n unconstrain_array_impl(params_constrained, params_i,\n params_unconstrained, pstream);\n }\n};\n}\nusing stan_model = model10310783487d8_rbmi_mmrm_namespace::model10310783487d8_rbmi_mmrm;\n#ifndef USING_R\n// Boilerplate\nstan::model::model_base&\nnew_model(stan::io::var_context& data_context, unsigned int seed,\n std::ostream* msg_stream) {\n stan_model* m = new stan_model(data_context, seed, msg_stream);\n return *m;\n}\nstan::math::profile_map& get_stan_profile_data() {\n return model10310783487d8_rbmi_mmrm_namespace::profiles__;\n}\n#endif\n#endif"), mk_cppmodule = function (object) { prep_call_sampler(object) model_cppname <- object@model_cpp$model_cppname mod <- get("module", envir = object@dso@.CXXDSOMISC, inherits = FALSE) eval(call("$", mod, paste("stan_fit4", model_cppname, sep = ""))) }, dso = new("cxxdso", sig = list(file1031058a7199b = character(0)), dso_saved = TRUE, dso_filename = "file1031058a7199b", modulename = "stan_fit4model10310783487d8_rbmi_mmrm_mod", system = "aarch64, darwin20", cxxflags = "CXXFLAGS = -falign-functions=64 -Wall -g -O2 $(LTO)", .CXXDSOMISC = <environment>)), data = list(N = 340L, P = 8L, G = 1L, n_visit = 3L, n_pat = 2L, pat_G = c(1, 1), pat_n_pt = c(60, 80), pat_n_visit = c(3, 2), pat_sigma_index = list( c(1, 2, 3), c(1, 2, 999)), y = c(0.574036883477536, 0.139105398171835, 0.176977232131814, -1.16935503183362, -1.21591438062592, -1.08964625296442, -1.58121597188229, -1.03382417471284, -0.813329718686652, -0.659208380311965, -0.596830231476417, -0.428690642917848, 1.19340919052579, 1.19324384350827, 1.14076998750238, 0.508301722783451, 0.285101803715272, -0.080275904172036, 0.420951505580432, 0.729295857616047, 0.606493590677628, 1.36133467580718, 0.785097805390841, 0.850728879541265, 1.59518647362531, 1.99123113996823, 1.62317993728234, -1.01500989395391, -1.29590087043236, -1.09167466441661, -1.92326503149754, -1.6438232242331, -2.09494484800456, -0.916339955699448, -1.21279752527853, -0.824654473194631, 0.160587572122124, 0.533787595446638, 0.509785626882552, 0.625441265387049, 0.869595429439695, 0.606754094352448, 0.416887452319262, 0.0527870943089152, -0.290746253299322, -0.0405562348050075, 0.138363916063878, 0.199662379261492, -0.0292589587575427, 0.184625776371717, 0.596974269230419, 0.460701441061857, 0.606107749594927, 0.675147663778399, 1.66002871020651, 1.84142634216536, 1.99191103632866, 1.10904044059033, 0.414249192109747, 0.672496352831966, 0.789592735008045, 0.677931435319178, 0.543093801624015, -0.899674446856585, -0.98731077385762, -1.31298117495064, -0.790921720329644, -0.407036721173524, -0.221080281874233, 1.43428989449746, 1.46018790177788, 1.29835543116011, 1.93804574039781, 1.67293427649682, 1.58849553103043, -1.01450332611738, -0.842813717586719, -0.629379340054354, -0.267415091390975, -0.657913697591214, -0.595234267484234, 0.120679904254403, 0.178945058091685, 0.258466389498271, -0.449519107207705, -0.418311943730978, -0.607987725151117, 0.475470586549514, 0.465961733342575, 0.628255437173784, -0.269181976386959, -0.489283917847538, -0.480553495290893, 0.0126097945506518, 0.188893941324742, -0.00785768753235569, -1.64359171150621, -1.51956953580399, -1.83648421907106, -0.334174407608112, 0.173961399031304, 0.512090615451255, 0.815812442864812, 1.00796572845926, 1.08799807363422, -0.499836503819652, -0.194917201294718, -0.347531934556113, 0.0967719422298859, 0.0448422069391228, -0.0380229372755732, 0.89027308837742, 0.923859648959303, 0.693773508152388, 0.0200206385163762, 0.139715592410514, 0.355610280019225, -0.554244284647314, -0.337491541079209, -0.0476717323926218, 1.74097877156221, 1.74584951452271, 1.87453426708686, 1.53665210908614, 1.27351842521603, 0.782842422447314, 0.780226954526566, 0.533531436107968, 0.471968788026106, -1.50987360873711, -1.4213975714265, -1.32130245857978, -1.53643170343886, -1.96117485895016, -1.63868589576792, -0.0924369697453538, -0.236384532458898, -0.416943554508815, 0.524748546809872, 1.01066900867255, 1.03925121395702, -1.47575422517021, -1.84351894914451, -1.96406505049471, -0.958450708965594, -1.00073327233577, -1.15403786283949, 1.30985852929418, 0.677518704253333, 0.633123295459129, -1.00859795137567, -0.486351090482834, -0.629987247106473, -0.703803757755735, -0.423015811624416, -0.68260822611802, 1.29970709660456, 0.950166424412677, 0.700867866424596, 0.885973022497435, 0.69557127871005, 0.683167942482159, -0.448047722773281, -0.345122636504495, -0.44919578758697, -0.350389882825743, 0.218778679169879, 0.460591876155823, -1.13643984701411, -1.37594847426891, -1.38924924598483, 1.05497189150375, 1.44213159591197, 1.44244341883156, 0.989297127175544, 1.28938706033795, 0.974021459136989, 0.0997949939225535, 0.0977838256866344, 0.152771705034039, 0.0563099671794369, -0.109302500409893, -0.770343945290974, -0.840203655711169, -1.06621935574191, -0.818506844251997, 0.483309359293258, -0.077312553568267, -1.82787954030716, -1.51850241691396, 0.385765772873327, 0.318930612816827, 0.0529827480329966, -0.256048504100078, 0.755705549841678, 0.841931688341897, 0.712085742232759, 0.644772892574503, -1.14155231656161, -1.4428233579315, -1.05021841671635, -1.39451198199354, -0.267077536825949, -0.707269786974737, -1.45623361118695, -1.14058269087304, -0.768761960571674, -0.570612606157713, -0.764238909934079, -1.27539783051645, -0.845195950602966, -1.35937750037253, -0.403679174325962, -0.181315302498918, -0.138311056457262, -0.0706441028516794, 0.508084112959793, 0.620362254164868, 0.480866966820087, 0.576196611808272, -1.14455494641288, -1.35096340386058, 0.550675910279237, 0.825037960508207, 1.61286207896739, 1.67916701468662, -0.0647658829962172, -0.266749386462743, -0.282320438961451, -0.774105813761362, -0.361641848210371, -0.0216017435394257, 1.42387705128602, 1.23207105462671, 0.265776870737417, 0.515102201270055, 0.771782662506529, 0.702063509689375, 0.616876705707196, 0.789738509590256, 0.971362277748469, 0.738026162904697, 0.534226435971703, 0.045703700581884, -1.14177405496358, -0.787101784899203, -0.872756204009667, -1.09360825060612, -0.968020452649131, -0.801211978871774, 1.52141486581132, 1.40439441624722, 1.79137191952656, 1.47694519657773, -1.9360028677803, -1.12357338931634, -0.442997879839818, -0.564318885154016, 0.000626204404452472, -0.27075649131444, -2.48336093478472, -1.92707335118885, 0.366175672975573, -0.232532349854313, 0.445155531890445, 0.769878306810777, -1.60791560029354, -1.71327349294041, -0.296398526983666, -0.367067711718188, -0.838340929698702, -1.43768210681618, -0.14561552296282, -0.0941334404913737, -0.0164394933059202, 0.0218434792651633, 1.07286404251878, 1.18723665035218, -0.138595585019409, 0.0131822076110258, -0.399908316171867, -0.868639920226593, 0.7981208661895, 0.719218310535081, 0.914826810253791, 0.705606688741132, 2.27692308241729, 2.20307732877354, -1.38708681157136, -1.25624461004343, 0.0942383865047231, 0.619729596216058, -1.97029658377716, -2.12452350098981, -0.546587071142227, -0.965112515688056, -0.0103825230207238, 0.275006295304357, 1.39505387642203, 1.13837400657299, 0.653655010243044, 0.592910348706071, 2.26190956828622, 2.20569250608316, -0.979542016063513, -0.948366938019486, 0.0839816881469963, 0.496574287039973, 0.547933703350616, 0.492939941225062, -0.375076840950679, -0.483574365532446, 1.3297009420447, 1.69844054391049, -1.13265693702497, -0.849277428071457, -1.13312754672772, -0.666195857133899, 0.459008637041986, 0.59569098957591, 1.50283257817443, 1.73920182026267, -0.300363476632086, -0.00897291528474771, -1.40333016095241, -1.19317961021338, -0.600226062637804, -0.325957148423221, 0.870433641965308, 0.130170018966925, -1.77311671749508, -1.19314004127747, 1.7640917533291, 1.44334725535403, -0.871065290131151, -1.32437155254469, 0.853886175567914, 0.646816118526293, 0.294983239652497, -0.326121365030516), Q = c(-0.99852832885673, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.958225137302622, -0.958225137302671, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.825360566675442, 1.20365082640164, -0.825360566675414, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.876442111269588, -0.0244034327926963, 1.96548118704492, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.377816532241714, -0.377816532241719, -0.457024666869013, -1.12880551077197, -1.12880551077196, -1.20801364539926, -0.220331575027453, -0.220331575027453, -0.29953970965475, 0.183702853067903, 0.183702853067903, 0.104494718440605, 1.12384497625067, 1.12384497625067, 1.04463684162337, 1.24707949620404, 1.24707949620404, 1.16787136157674, -0.610672320738653, -0.610672320738653, -0.68988045536595, 0.815513912349393, 0.815513912349393, 0.736305777722095, 1.07768856337481, 1.07768856337481, 0.99848042874751, -0.116268012873417, -0.116268012873417, -0.195476147500715, -1.75570733327889, -1.75570733327889, -1.83491546790618, 0.38821352691705, 0.388213526917049, 0.309005392289752, 2.38726637449642, 2.38726637449642, 2.30805823986912, 0.0978089234405024, 0.0978089234405022, 0.0186007888132048, 0.480311137245768, 0.480311137245767, 0.40110300261847, -1.36360112479173, -1.36360112479173, -1.44280925941902, 1.93535965542202, 1.93535965542202, 1.85615152079472, 0.394010340671377, 0.394010340671377, 0.314802206044079, 1.61374775950545, 1.61374775950545, 1.53453962487815, -0.964178039762375, -0.964178039762375, -1.04338617438967, -0.798757765014893, -0.798757765014893, -0.87796589964219, -1.0944257408576, -1.0944257408576, -1.1736338754849, 0.377586753964714, 0.377586753964714, 0.298378619337417, 1.37498679426785, 1.37498679426785, 1.29577865964055, 1.68915587438649, 1.68915587438649, 1.6099477397592, 0.992596467936866, 0.992596467936866, 0.913388333309568, -0.323261319416317, -0.323261319416317, -0.402469454043614, -1.53070167383635, -1.53070167383635, -1.60990980846365, 0.985012371873182, 0.985012371873182, 0.905804237245884, -0.83124291903249, -0.83124291903249, -0.910451053659788, 0.875900958465542, 0.875900958465542, 0.796692823838244, -0.599874960211679, -0.59987496021168, -0.679083094838977, -1.21249941889568, -1.21249941889568, -1.29170755352297, 0.10152732719712, 0.10152732719712, 0.0223191925698222, 0.273641473500582, 0.273641473500581, 0.194433338873284, 0.132099054317715, 0.132099054317715, 0.0528909196904173, -0.834302902018013, -0.834302902018014, -0.913511036645311, 0.719369062657609, 0.719369062657609, 0.640160928030311, -1.14019031831383, -1.14019031831383, -1.21939845294113, -0.986131847575652, -0.986131847575652, -1.06533998220295, 1.121130179697, 1.121130179697, 1.0419220450697, 0.901558128109497, 0.901558128109497, 0.8223499934822, -0.786141113615663, -0.786141113615663, -0.86534924824296, -0.713749729008483, -0.713749729008484, -0.792957863635781, -1.21024198127622, -1.21024198127622, -1.28945011590352, -1.48456568414046, -1.48456568414046, -1.56377381876776, 1.07705092477044, 1.07705092477044, 0.99784279014314, -1.51414471003321, -1.51414471003321, -1.59335284466051, 0.197021223835606, 0.197021223835606, 0.117813089208309, -0.992651143019504, -0.992651143019504, -1.0718592776468, -0.214255998107591, -0.214255998107591, -0.293464132734889, 0.855083280875347, 0.855083280875347, 0.77587514624805, 0.424765963693628, 0.424765963693628, 0.34555782906633, 0.364243987733107, 0.364243987733107, 0.285035853105809, 0.148975237666157, 0.148975237666156, 0.069767103038859, -0.0574168068381831, -0.0574168068381833, -0.136624941465481, -0.46975623711864, -0.469756237118641, -0.548964371745938, 1.07464366058924, 1.07464366058924, 0.995435525961942, 0.220197215402141, 0.22019721540214, 0.140989080774843, 2.43308733556931, 2.43308733556931, 2.35387920094201, -0.792463299943419, -0.792463299943419, 0.398667166152911, 0.398667166152911, -0.507624730755423, -0.507624730755423, -1.14063678811883, -1.14063678811883, -0.610719518834707, -0.610719518834707, 0.0372742888124954, 0.0372742888124952, 1.60469817459311, 1.60469817459311, -0.335089450474223, -0.335089450474223, 0.398797186950103, 0.398797186950103, -1.47882967397224, -1.47882967397224, -0.667444462142149, -0.66744446214215, -0.649446871595376, -0.649446871595376, -0.279713473009783, -0.279713473009783, 0.109041394826028, 0.109041394826028, -1.47272080463623, -1.47272080463623, -0.463549540361751, -0.463549540361751, -1.00365185771742, -1.00365185771742, -0.808089317383245, -0.808089317383245, 0.145106160657612, 0.145106160657612, 0.190373516579835, 0.190373516579835, -1.11324014885282, -1.11324014885282, 0.0373498895331293, 0.0373498895331291, 0.934861192278438, 0.934861192278438, 0.526171571037055, 0.526171571037054, -0.127064672854489, -0.127064672854489, 0.107735669014991, 0.107735669014991, 1.63023634780781, 1.63023634780781, -1.01842798000048, -1.01842798000048, 0.0915540560676065, 0.0915540560676063, -0.69105660373921, -0.69105660373921, -0.510325739757003, -0.510325739757004, -0.758316424407092, -0.758316424407092, 0.66850966666813, 0.66850966666813, 0.207547505355721, 0.207547505355721, -0.957302855842871, -0.957302855842871, 0.871306376044677, 0.871306376044677, 0.854052678949774, 0.854052678949774, -1.02517751500326, -1.02517751500326, -0.14387122685017, -0.14387122685017, 0.043993557372757, 0.0439935573727568, -1.13877102137595, -1.13877102137595, 1.36106121128242, 1.36106121128242, 0.0755102782632799, 0.0755102782632797, -1.39505728407859, -1.39505728407859, -1.55223678517323, -1.55223678517323, -0.783810528384146, -0.783810528384146, -1.23550391017333, -1.23550391017333, -1.34099290537528, -1.34099290537528, 0.282522679370366, 0.282522679370366, 1.05047246454719, 1.05047246454719, 0.406048469121015, 0.406048469121015, 0.239493257040229, 0.239493257040228, 0.534396153202169, 0.534396153202169, 2.04605670576315, 2.04605670576315, -0.0259943875448687, -0.0259943875448689, 1.56185162485783, 1.56185162485783, -1.89056227250461, -1.89056227250461, -0.819059954351738, -0.819059954351738, -0.481442518835015, -0.481442518835015, -0.0511676754622087, -0.0511676754622089, 2.24057972203455, 2.24057972203455, 1.5234804097995, 1.5234804097995, -0.344361395338917, -0.344361395338917, -0.041553596863046, -0.0415535968630462, -0.025579389721469, -0.0255793897214692, -0.0639754794004533, -0.0639754794004535, 1.29091591700363, 1.29091591700363, 0.678498611351185, 0.678498611351185, 1.04860191122785, 1.04860191122785, -0.768540785317964, -0.768540785317964, 1.30809002082778, 1.30809002082778, -0.47706971830725, -0.47706971830725, -1.38225666633996, -1.38225666633996, -0.898631124236369, -0.89863112423637, 0.673024870752781, 0.673024870752781, -0.410390025474452, -0.410390025474452, 1.85569424316007, 1.85569424316007, -1.42890995686216, -1.42890995686216, 2.09388845185187, 2.09388845185187, -0.769321140423713, -0.769321140423714, 0.928218267300235, 0.928218267300184, 0.865629305624083, -0.901905120181538, -0.901905120181534, -0.964494081857647, -0.949986114091021, -0.94998611409102, -1.01257507576713, -0.971369641027934, -0.971369641027932, -1.03395860270405, 0.848742814011857, 0.848742814011858, 0.786153852335745, -1.02764886257788, -1.02764886257788, -1.09023782425399, -1.06643981685835, -1.06643981685835, -1.12902877853447, 0.865061239254727, 0.865061239254728, 0.802472277578616, -1.1557963368333, -1.1557963368333, -1.21838529850942, 1.05148830018635, 1.05148830018635, 0.988899338510239, 1.13825564581723, 1.13825564581723, 1.07566668414112, 1.02478860866219, 1.0247886086622, 0.962199646986083, 0.918988712806694, 0.918988712806695, 0.856399751130582, 0.903045784372422, 0.903045784372423, 0.84045682269631, -0.987067638013804, -0.987067638013803, -1.04965659968992, -1.02659105090308, -1.02659105090308, -1.08918001257919, -1.06407609823243, -1.06407609823243, -1.12666505990854, 0.887369320824584, 0.887369320824585, 0.824780359148473, -1.18416727619675, -1.18416727619675, -1.24675623787286, -1.0477305224531, -1.04773052245309, -1.11031948412921, -1.0564853924716, -1.0564853924716, -1.11907435414771, -0.903724669915239, -0.903724669915238, -0.96631363159135, -0.981630948800652, -0.981630948800651, -1.04421991047676, 0.835451130291063, 0.835451130291063, 0.772862168614951, 0.818823727970098, 0.818823727970099, 0.756234766293987, 0.99280163428372, 0.992801634283721, 0.930212672607609, -0.944538556138783, -0.944538556138782, -1.00712751781489, -1.01774725234731, -1.01774725234731, -1.08033621402342, 0.993203022658554, 0.993203022658555, 0.930614060982442, -1.05476611530688, -1.05476611530688, -1.11735507698299, 0.998977745517508, 0.998977745517509, 0.936388783841397, 0.939970712255066, 0.939970712255067, 0.877381750578954, 1.1095063604548, 1.10950636045481, 1.04691739877869, 0.902848987809152, 0.902848987809153, 0.84026002613304, -1.11324213498986, -1.11324213498985, -1.17583109666597, -0.96863850936219, -0.968638509362189, -1.0312274710383, 0.952377813877598, 0.952377813877599, 0.889788852201486, 0.870149706574013, 0.870149706574014, 0.807560744897902, -1.03841507050665, -1.03841507050665, -1.10100403218276, 0.960413362636251, 0.960413362636252, 0.89782440096014, -1.15809548489647, -1.15809548489647, -1.22068444657258, 0.860507348107022, 0.860507348107023, 0.79791838643091, -1.05715312889772, -1.05715312889772, -1.11974209057384, 1.0831100271553, 1.0831100271553, 1.02052106547919, 1.10938688554181, 1.10938688554181, 1.0467979238657, 0.986792979394893, 0.986792979394894, 0.924204017718781, 0.85121938974584, 0.851219389745841, 0.788630428069729, 1.12547094109423, 1.12547094109423, 1.06288197941812, 1.03490746358836, 1.03490746358836, 0.972318501912247, -1.04622358312283, -1.04622358312283, -1.10881254479895, -0.950307664072134, -0.950307664072133, -1.01289662574825, 1.00007952135283, 1.00007952135283, 0.937490559676719, 0.885741579108469, 0.88574157910847, 0.823152617432357, 0.88894470540968, 0.88894470540968, 0.826355743733568, -0.96953168156765, -0.969531681567649, -1.03212064324376, 0.911261108003043, 0.911261108003044, 0.848672146326931, 1.07019666868025, 1.07019666868025, 1.00760770700414, -1.15563518531698, -1.15563518531698, -1.21822414699309, -1.1104135969911, -1.1104135969911, -1.17300255866722, 0.916563637894152, 0.916563637894153, 0.85397467621804, 0.950163452437635, 0.950163452437636, 1.02423534968067, 1.02423534968067, -0.934781120389717, -0.934781120389716, 0.968590538461504, 0.968590538461505, 1.07765715205019, 1.0776571520502, 0.906249580633761, 0.906249580633762, 0.960406144141665, 0.960406144141666, -1.08102504356151, -1.08102504356151, 0.887115976928059, 0.88711597692806, -0.883380087159851, -0.88338008715985, 1.08065932035285, 1.08065932035285, -0.927275181890372, -0.927275181890371, 1.06013865311795, 1.06013865311795, -0.967418182457954, -0.967418182457953, -0.883703399142486, -0.883703399142485, 1.06986817918019, 1.06986817918019, 0.961340609382444, 0.961340609382446, 0.950990459597437, 0.950990459597438, 0.900542577527299, 0.9005425775273, 0.898146802173974, 0.898146802173975, -0.902728917147178, -0.902728917147177, 0.906245579464717, 0.906245579464718, -1.14823719651062, -1.14823719651062, -0.989494802020439, -0.989494802020438, -0.95492226600347, -0.954922266003468, -0.967349076903795, -0.967349076903794, 0.821942044618619, 0.82194204461862, -1.04485934371747, -1.04485934371747, 0.903376823302905, 0.903376823302906, -1.06218547771961, -1.06218547771961, -1.07175066085639, -1.07175066085638, 0.948356228641671, 0.948356228641672, 1.00995393211511, 1.00995393211511, 1.03435036001307, 1.03435036001307, -0.910981900243858, -0.910981900243857, -1.14487355710169, -1.14487355710169, -1.14396040497669, -1.14396040497669, -0.907389633096397, -0.907389633096396, -0.954032778932337, -0.954032778932336, -0.963975524883135, -0.963975524883134, 1.1056042841347, 1.1056042841347, 0.973300633337403, 0.973300633337404, -1.10275603911339, -1.10275603911339, -0.887813741896415, -0.887813741896414, 0.990374473226015, 0.990374473226016, -0.920163983748597, -0.920163983748596, 0.973611382030312, 0.973611382030313, -1.02778759118596, -1.02778759118596, -1.11371217291668, -1.11371217291668, -1.01724343307714, -1.01724343307713, 1.02384469413284, 1.02384469413285, -1.11143484022547, -1.11143484022547, 0.879939400018172, 0.879939400018173, -1.20704723234541, -1.20704723234541, 1.04671056748668, 1.04671056748668, -1.04430818124978, -1.04430818124978, 1.14539284508785, 1.14539284508785, -0.918298407457879, -0.918298407457878, 0.933702673879424, 0.933702673879425, -1.09605160689812, -1.09605160689812, -1.0802298739066, -1.0802298739066, -1.17938987563448, -1.17938987563448, 1.06356014518004, 1.06356014518004, 0.910421547425474, 0.910421547425475, 0.909576112321545, 0.909576112321546, -0.958261262321214, -0.958261262321213, -1.1670813970731, -1.1670813970731, 1.00942526709835, 1.00942526709835, 0.989837545528036, 0.989837545528038, -1.05808462648328, -1.05808462648328, -1.1679903367233, -1.1679903367233, 0.933471243359218, 0.933471243359219, -0.888491214743256, -0.888491214743254, 0.955782385807506, 0.955782385807507, -0.997267014663429, -0.997267014663428, 1.0670547112193, 1.0670547112193, 0.8100096828119, 0.810009682811901, -0.886022088784659, -0.886022088784658, -1.07246623667859, -1.07246623667859, 0.948938653368405, 0.948938653368406, 0.822922780507102, -1.1501950067864, 0.761524154870805, -0.884042163308672, 1.20514137617857, -0.945440788944957, -0.8764883205467, 1.21269521894054, -0.937886946182985, -0.873128826762482, 1.21605471272476, -0.93452745239877, 0.835408900879507, -1.137708886414, 0.774010275243219, -0.864286988110919, 1.22489655137632, -0.925685613747206, 0.79384135565294, -1.17927643164056, 0.732442730016652, 0.832845168136384, -1.14027261915712, 0.771446542500097, 0.807879857080727, -1.16523793021278, 0.74648123144444, -0.848477786323998, 1.24070575316324, -0.909876411960286, -0.862109511304625, 1.22707402818261, -0.923508136940912, -0.844283087854447, 1.24490045163279, -0.905681713490735, -0.827661223110346, 1.26152231637689, -0.889059848746634, 0.826877544385839, -1.14624024290766, 0.765478918749551, -0.870662567409932, 1.21852097207731, -0.93206119304622, 0.78758085045516, -1.18553693683834, 0.726182224818872, -0.858564027996872, 1.23061951149037, -0.919962653633159, 0.829340420692578, -1.14377736660092, 0.76794179505629, 0.812337119660705, -1.1607806676328, 0.750938494024418, 0.79090200152081, -1.18221578577269, 0.729503375884522, 0.792277449616699, -1.1808403376768, 0.730878823980411, -0.883756299987876, 1.20542723949936, -0.945154925624164, -0.87151670731268, 1.21766683217456, -0.932915332948967, 0.837497112472174, -1.13562067482133, 0.776098486835886, 0.840109387561766, -1.13300839973174, 0.778710761925479, -0.839257722211194, 1.24992581727604, -0.900656347847481, -0.87734416800038, 1.21183937148686, -0.938742793636667, 0.786191431096763, -1.18692635619674, 0.724792805460476, -0.839320782984764, 1.24986275650247, -0.900719408621052, 0.792007339780971, -1.18111044751253, 0.730608714144683, -0.840228030213318, 1.24895550927392, -0.901626655849606, 0.821076393524696, -1.15204139376881, 0.759677767888408, -0.857592808061018, 1.23159073142622, -0.918991433697306, 0.826908462430042, -1.14620932486346, 0.765509836793755, 0.801194309976777, -1.17192347731673, 0.739795684340489, -0.873557905645587, 1.21562563384165, -0.934956531281875, 0.819127155641534, -1.15399063165197, 0.757728530005247, 0.832045736200728, -1.14107205109277, 0.770647110564441, 0.789438482289227, -1.18367930500428, 0.72803985665294, 0.817864717682301, -1.1552530696112, 0.756466092046013, 0.808241068477237, -1.16487671881626, 0.74684244284095, 0.833560614613004, -1.1395571726805, 0.772161988976716, 0.792382355434139, -1.18073543185936, 0.730983729797852, -0.853445769178827, 1.23573777030841, -0.914844394815115, -0.857574037760461, 1.23160950172678, -0.918972663396749, 0.813720305079454, -1.15939748221405, 0.752321679443167, 0.835019814420149, -1.13809797287335, 0.773621188783862, -0.860100949472114, 1.22908259001512, -0.921499575108402, -0.845872827018062, 1.24331071246918, -0.90727145265435, 0.790665251365976, -1.18245253592753, 0.729266625729689, -0.876437802913846, 1.21274573657339, -0.937836428550134, -0.840401126498196, 1.24878241298904, -0.901799752134484, 0.829596149702751, -1.14352163759075, 0.768197524066464, 0.829092917334643, -1.14402486995886, 0.767694291698356, -0.873417582373317, 1.21576595711392, -0.934816208009604, 0.825586862602903, -1.1475309246906, 0.764188236966615, -0.851416994989318, 1.23776654449792, -0.912815620625605, 0.807854539109608, -1.16526324818389, 0.74645591347332, 0.800749927913273, -1.17236785938023, 0.739351302276985, -0.827280227771318, 1.26190331171592, -0.888678853407606, 0.819475046497683, -1.15364274079582, -0.844196167202163, 1.24498737228508, -0.878877125816253, 1.21030641367099, 0.816580029172382, -1.15653775812112, -0.852589086365194, 1.23659445312204, 0.826374206762554, -1.14674358053095, -0.834168176034367, 1.25501536345287, 0.79613279142007, -1.17698499587343, 0.829380222697558, -1.14373756459594, -0.886952568756393, 1.20223097073085, -0.853060746900039, 1.2361227925872, -0.880056358494176, 1.20912718099306, -0.849836814092931, 1.23934672539431, -0.873749627088995, 1.21543391239824, -0.886901774301426, 1.20228176518581, -0.851365387112054, 1.23781815237518, 0.817719041073879, -1.15539874621962, 0.819345118192542, -1.15377266910096, 0.827270814769233, -1.14584697252427, 0.827647206953348, -1.14547058034015, -0.883912739346303, 1.20527080014094, 0.826374835372726, -1.14674295192078, 0.806692266043804, -1.1664255212497, -0.870281243860378, 1.21890229562686, -0.875712818370806, 1.21347072111643, -0.873760484029496, 1.21542305545774, 0.839619479352104, -1.1334983079414, 0.790450920314975, -1.18266686697853, 0.826825535976161, -1.14629225131734, 0.793172970781972, -1.17994481651153, 0.794675724438452, -1.17844206285505, 0.819758973331977, -1.15335881396153, -0.841952461863805, 1.24723107762343, -0.845785302354621, 1.24339823713262, -0.882616141011691, 1.20656739847555, 0.8061638160028, -1.1669539712907, 0.806020353752767, -1.16709743354073, -0.883180509985469, 1.20600302950177, -0.875852562684054, 1.21333097680319, -0.874290491407491, 1.21489304807975, -0.856979766013203, 1.23220377347404, -0.836193985735054, 1.25298955375218, 0.799546874826271, -1.17357091246723, -0.886256012216736, 1.2029275272705, 0.813157628665065, -1.15996015862844, -0.881173574846094, 1.20800996464114, 0.81579122137605, -1.15732656591745, 0.787768834862726, -1.18534895243078, 0.801268156049886, -1.17184963124362, -0.865921750039247, 1.22326178944799, -0.844134792626839, 1.2450487468604, 0.800910371992874, -1.17220741530063, 0.830507710487194, -1.14261007680631, 0.815931712390488, -1.15718607490301, -0.847727172856231, 1.24145636663101, -0.861669698751095, 1.22751384073614, -0.863230812606188, 1.22595272688105, -0.881466669243999, 1.20771687024324, 0.82206114388998, -1.15105664340352, 0.798493564096925, -1.17462422319658, -0.856026162792076, 1.23315737669516, 0.811586558373925, -1.16153122891958, -0.850374353169121, 1.23880918631812, 0.825718763133163, -1.14739902416034, 0.825851586590444, -1.14726620070306, -0.875188239922729, 1.21399529956451, 0.809652814827218, -1.16346497246628, -0.841869405086362, 1.24731413440088, -0.83879204422552, 1.25039149526172, 0.792528699877594, -1.18058908741591, 0.809795615269543, -1.16332217202396, 0.822097503158327, -1.15102028413517, -0.886149576743081, 1.20303396274416, 0.818592274830236, -1.15452551246327, -0.869060177749968, 1.22012336173727, -0.850923372651362, 1.23826016683588, 0.841494132464238, -1.13162365482926, -0.886537492793357, 1.20264604669388, -0.857245881647968, 1.23193765783927, 0.819667470547847, -1.15345031674565, 0.803861462573047, -0.0211329139384137, -1.82131769404677, -0.820744084523179, 0.0527793729593485, 2.26118636758273, -0.838810415568063, 0.0347130419146579, 2.24312003653804, -0.846845230265783, 0.0266782272169289, 2.23508522184031, 0.77399873028981, -0.0509956462216396, -1.85118042633002, -0.867992027883424, 0.00553142959928828, 2.21393842422267, 0.873414756866236, 0.0484203803547871, -1.75176439975359, 0.78013034381512, -0.0448640326963297, -1.84504881280471, 0.839839234822992, 0.0148448583115432, -1.78533992179684, -0.905802488338423, -0.0322790308557104, 2.17612796376767, -0.873199843039791, 0.000323614442920782, 2.2087306090663, -0.915834840555904, -0.0423113830731917, 2.16609561155019, -0.95558892606041, -0.082065468577698, 2.12634152604568, 0.79440295573263, -0.0305914207788191, -1.8307762008872, -0.852743719195093, 0.0207797382876192, 2.229186732911, 0.888387845792512, 0.0633934692810632, -1.73679131082732, -0.881679484087365, -0.00815602660465293, 2.20025096801873, 0.788512557946793, -0.0364818185646558, -1.83666659867304, 0.829178914789803, 0.00418453827835407, -1.79600024183003, 0.88044473438655, 0.0554503578751002, -1.74473442223328, 0.87715511062575, 0.0521607341143011, -1.74802404599408, -0.82142777646, 0.0520956810227125, 2.26050267564609, -0.850700894803883, 0.022822562678829, 2.23122955730221, 0.769004408444191, -0.0559899680672583, -1.85617474817564, 0.762756697439936, -0.0622376790715133, -1.86242245917989, -0.927853878043512, -0.0543304205608001, 2.15407657406258, -0.836763507271285, 0.0367599502114275, 2.24516694483481, 0.891710884261762, 0.0667165077503131, -1.73346827235807, -0.927703057216662, -0.0541795997339494, 2.15422739488943, 0.87780112535818, 0.0528067488467312, -1.74737803126165, -0.925533217403083, -0.0520097599203712, 2.15639723470301, 0.80827741873115, -0.0167169577802996, -1.81690173788868, -0.884002325776185, -0.010478868293473, 2.19792812632991, 0.794329009843175, -0.0306653666682737, -1.83085014677665, 0.855828885521429, 0.03083450900998, -1.7693502710984, -0.845819013359934, 0.0277044441227782, 2.23611143874616, 0.812939360737585, -0.0120550157738644, -1.81223979588224, 0.782042324571453, -0.0429520519399964, -1.84313683204838, 0.883944995612685, 0.0589506191012355, -1.74123416100714, 0.815958701067215, -0.00903567544423475, -1.80922045555261, 0.838975334835647, 0.0139809583241981, -1.78620382178418, 0.778419228916563, -0.0465751475948864, -1.84675992770327, 0.876904210085971, 0.0519098335745214, -1.74827494653386, -0.893920691786934, -0.0203972343042215, 2.18800976031916, -0.884047218220251, -0.0105237607375388, 2.19788323388584, 0.825870785873342, 0.000876409361892394, -1.79930837074649, 0.774929298346527, -0.0500650781649221, -1.8502498582733, -0.878003668606899, -0.00448021112418706, 2.20392678349919, -0.91203270237146, -0.0385092448887476, 2.16989774973463, 0.88101096362998, 0.0560165871185307, -1.74416819298985, -0.838931237288528, 0.0345922201941842, 2.24299921481756, -0.925119227479841, -0.0515957699971293, 2.15681122462625, 0.787900937464198, -0.0370934390472516, -1.83727821915563, 0.789104505348933, -0.0358898711625158, -1.8360746512709, -0.846154620913599, 0.027368836569113, 2.23577583119249, 0.797489846087465, -0.027504530423984, -1.82768931053236, -0.898772858727331, -0.0252494012446189, 2.18315759337876, 0.839899787161985, 0.0149054106505357, -1.78527936945784, 0.856891702649422, 0.031897326137973, -1.76828745397041, -0.956500142793172, -0.0829766853104602, 2.12543030931292, 0.812107319143306, -0.0128870573681433, -0.916042726439721, -0.0425192689570085, -0.83309717157278, 0.0404262859099321, 0.81903125746544, -0.00596311904600869, -0.895969597992568, -0.0224461405098554, 0.795606775353457, -0.0293876011579923, -0.940026414459111, -0.066502956976399, 0.867934389000357, 0.0429400124889073, 0.788417364517319, -0.0365770119941301, -0.813783342825435, 0.059740114657277, -0.89484153964773, -0.0213180821650183, -0.830276831169969, 0.0432466263127435, -0.902552136650396, -0.0290286791676835, -0.845360478125072, 0.0281629793576403, -0.813904826614227, 0.0596186308684849, -0.898896287957265, -0.0253728304745528, 0.816307112056978, -0.00868726445447064, 0.812418065322002, -0.0125763111894468, 0.793462381092629, -0.0315319954188206, 0.792562173606831, -0.0324322029046178, -0.821053624478443, 0.0524698330042693, 0.795605271922712, -0.0293891045887375, 0.842679565697599, 0.0176851891861494, -0.85365572090051, 0.0198677365822015, -0.840665164134714, 0.0328582933479979, -0.845334511860298, 0.028188945622414, 0.763928398278326, -0.0610659782331235, 0.881523573680594, 0.0565291971691446, 0.794527342905617, -0.0304670336058324, 0.875013315735499, 0.0500189392240496, 0.871419218546546, 0.0464248420350975, 0.81142825865152, -0.0135661178599291, -0.921408938669288, -0.047885481186576, -0.912242032853194, -0.0387185753704814, -0.824154665297431, 0.0493687921852808, 0.843943446040652, 0.0189490695292026, 0.844286561006527, 0.0192921844950777, -0.822804878568622, 0.0507185789140901, -0.840330941262423, 0.0331925162202894, -0.844066906874501, 0.0294565506082111, -0.885468522641695, -0.0119450651589828, -0.935181337610223, -0.0616578801275106, 0.859769013710692, 0.0347746371992429, -0.81544927914862, 0.058074178334092, 0.827216524551485, 0.00222214804003598, -0.827604813615682, 0.0459186438670302, 0.820917828741577, -0.00407654776987265, 0.887938248329957, 0.0629438718185076, 0.855652269771647, 0.0306578932601974, -0.86408220991301, 0.00944124756970272, -0.916189514429685, -0.042666056946973, 0.856507972679448, 0.0315135961679984, 0.785720781030177, -0.0392735954812725, 0.820581820003289, -0.00441255650816064, -0.90759771122333, -0.0340742537406174, -0.874251731388556, -0.000728273905844428, -0.870518055616724, 0.00300540186598766, -0.826903827298288, 0.0466196301844242, 0.805922216662982, -0.0190721598484674, 0.862288189834543, 0.0372938133230942, -0.887749230887955, -0.0142257734052433, 0.830974012874789, 0.00597963636334002, -0.901266518296147, -0.0277430608134348, 0.797174382988783, -0.0278199935226666, 0.796856712549333, -0.0281376639621159, -0.841919784888747, 0.031603672593965, 0.835598897476072, 0.0106045209646222, -0.921607583423233, -0.0480841259405206, -0.928967628079688, -0.0554441705969753, 0.876554201852371, 0.0515598253409216, 0.835257365338632, 0.0102629888271827, 0.805835257137982, -0.0191591193734672, -0.815703838127743, 0.0578196193549694, 0.814218621388206, -0.0107757551232427, -0.856576113245609, 0.016947344237103, -0.899953442550635, -0.0264299850679227, 0.759444838746444, -0.0655495377650052, -0.814776069308258, 0.0587473881744539, -0.884832060736767, -0.0113086032540548, 0.811647103501974, -0.0133472730094755), R = c(-1.00147384015129, 0, 0, 0, 0, 0, 0, 0, -0.521355499137583, -0.500312239830598, 0, 0, 0, 0, 0, 0, -0.412371581238766, 0.00520237329552464, 0.492850855057777, 0, 0, 0, 0, 0, -0.176730677673757, -0.0104047465910492, -0.147761901765143, 0.351874380491925, 0, 0, 0, 0, -0.0148145536477168, -0.0628921007447697, -0.0117315667981618, 0.0279370916994833, 1.00236007528132, 0, 0, 0, -0.480118341013706, 0.0345264174379645, 0.00491668361530068, -0.0117083969584963, -0.0263704470162966, -0.498260577419346, 0, 0, -0.212076813208509, -0.203516843320922, 0.25564265339504, -0.00518302997367062, 0.00222305092368007, 0.00332949514226805, -0.246165884693855, 0, -0.0972018727205666, -0.0932785531887563, -0.0803448339241554, 0.191330027057476, -0.00444610184736017, -0.00665899028453589, 0.0732625048297967, -0.175220044568803), Sigma_init = list(c(0.135928026518976, 0.0348523498539457, 0.00728419213566439, 0.0348523498539457, 0.0345033646543241, 0.00223741352686603, 0.00728419213566439, 0.00223741352686603, 0.012904582693086))), pars = c("beta", "Sigma"), chains = 1, warmup = 200, thin = 2, iter = 204, init = list( list(theta = c(-5.95025313048012e-05, -0.745820423193811, -0.00612121696522474, 0.00358076868728718, 0.552831864322151, -0.281246666814181, -0.00509794025644653, -0.00632342582509862 ), sigma = list(Placebo = c(0.135928026518976, 0.0348523498539457, 0.00728419213566439, 0.0348523498539457, 0.0345033646543241, 0.00223741352686603, 0.00728419213566439, 0.00223741352686603, 0.012904582693086), TRT = c(0.135928026518976, 0.0348523498539457, 0.00728419213566439, 0.0348523498539457, 0.0345033646543241, 0.00223741352686603, 0.00728419213566439, 0.00223741352686603, 0.012904582693086)))), refresh = 0, seed = 2053082391L)
10: (new("nonstandardGenericFunction", .Data = function (object, ...) { standardGeneric("sampling")}, generic = "sampling", package = "rstan", group = list(), valueClass = character(0), signature = "object", default = NULL, skeleton = (function (object, ...) stop(gettextf("invalid call in method dispatch to '%s' (no default method)", "sampling"), domain = NA))(object, ...)))(object = new("stanmodel", model_name = "rbmi_mmrm", model_code = "functions {\n int integer_division(int a, int b) {\n // perform a/b ensuring return value is also an int\n int i = 0;\n while(b*(i+1) <= a) {\n i = i + 1;\n }\n return(i);\n }\n array[] vector to_vector_of_arrays(vector vec, int length_array) {\n // treansform a vector into a vector of arrays. Example: vec = [1,2,3,4,5,6] and\n // length_array = 2, then output = [1,2; 3,4; 5,6]\n array[integer_division(num_elements(vec),length_array)] vector[length_array] res;\n int j = 1;\n int i = 1;\n while(j <= num_elements(vec)) {\n res[i,] = vec[j:(j+length_array-1)];\n i = i+1;\n j = j + length_array;\n }\n return(res);\n }\n}\ndata {\n int<lower=1> N; // number of observations\n int<lower=1> P; // number of covariates (number of columns of design matrix)\n int<lower=1> G; // number of Sigma Groups\n int<lower=1> n_visit; // number of visits\n int<lower=1> n_pat; // number of pat groups (# missingness patterns * groups)\n array[n_pat] int<lower=1> pat_G; // Index for which Sigma the pat group should use\n array[n_pat] int<lower=1> pat_n_pt; // number of patients in each pat group\n array[n_pat] int<lower=1> pat_n_visit; // number of non-missing visits in each pat group\n array[n_pat, n_visit] int<lower=1> pat_sigma_index; // rows/cols from sigma to subset on for the pat group\n vector[N] y; // outcome variable\n matrix[N,P] Q; // design matrix (After QR decomp)\n matrix[P,P] R; // R matrix (from QR decomp)\n array[G] matrix[n_visit, n_visit] Sigma_init; // covariance matrix estimated from MMRM\n}\ntransformed data {\n matrix[P, P] R_inverse = inverse(R);\n}\nparameters {\n vector[P] theta; // coefficients of linear model on covariates\n array[G] cov_matrix[n_visit] Sigma; // covariance matrix(s)\n}\nmodel {\n int data_start_row = 1;\n vector[N] mu = Q * theta;\n for(g in 1:G){\n Sigma[g] ~ inv_wishart(n_visit+2, Sigma_init[g]);\n }\n for(i in 1:n_pat) {\n // Index + size variables for current pat group\n int nvis = pat_n_visit[i]; // number of visits\n int npt = pat_n_pt[i]; // number of patients\n int g = pat_G[i]; // Sigma index\n // Get required/reduced Sigma for current pat group\n array[nvis] int sig_index = pat_sigma_index[i, 1:nvis];\n matrix[nvis,nvis] sig = Sigma[g][sig_index, sig_index];\n // Derive data indcies for current pat group\n int data_stop_row = data_start_row + ((nvis * npt) -1);\n // Extract required data for the current pat group\n array[npt] vector[nvis] y_obs = to_vector_of_arrays(y[data_start_row:data_stop_row], nvis);\n array[npt] vector[nvis] mu_obs = to_vector_of_arrays(mu[data_start_row:data_stop_row], nvis);\n y_obs ~ multi_normal(mu_obs, sig);\n // Update data index for next pat group\n data_start_row = data_stop_row + 1;\n }\n}\ngenerated quantities {\n vector[P] beta = R_inverse * theta;\n}", model_cpp = list(model_cppname = "model10310783487d8_rbmi_mmrm", model_cppcode = "#ifndef MODELS_HPP\n#define MODELS_HPP\n#define STAN__SERVICES__COMMAND_HPP\n#include <rstan/rstaninc.hpp>\n#ifndef USE_STANC3\n#define USE_STANC3\n#endif\n// Code generated by stanc v2.32.2\n#include <stan/model/model_header.hpp>\nnamespace model10310783487d8_rbmi_mmrm_namespace {\nusing stan::model::model_base_crtp;\nusing namespace stan::math;\nstan::math::profile_map profiles__;\nstatic constexpr std::array<const char*, 80> locations_array__ =\n {\" (found before start of program)\",\n \" (in 'rbmi_mmrm', line 43, column 4 to column 20)\",\n \" (in 'rbmi_mmrm', line 44, column 4 to column 39)\",\n \" (in 'rbmi_mmrm', line 71, column 3 to column 38)\",\n \" (in 'rbmi_mmrm', line 47, column 4 to column 27)\",\n \" (in 'rbmi_mmrm', line 48, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 48, column 4 to column 29)\",\n \" (in 'rbmi_mmrm', line 50, column 8 to column 57)\",\n \" (in 'rbmi_mmrm', line 49, column 17 to line 51, column 5)\",\n \" (in 'rbmi_mmrm', line 49, column 4 to line 51, column 5)\",\n \" (in 'rbmi_mmrm', line 54, column 8 to column 34)\",\n \" (in 'rbmi_mmrm', line 55, column 8 to column 30)\",\n \" (in 'rbmi_mmrm', line 56, column 8 to column 25)\",\n \" (in 'rbmi_mmrm', line 58, column 14 to column 18)\",\n \" (in 'rbmi_mmrm', line 58, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 59, column 15 to column 19)\",\n \" (in 'rbmi_mmrm', line 59, column 20 to column 24)\",\n \" (in 'rbmi_mmrm', line 59, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 61, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 63, column 14 to column 17)\",\n \" (in 'rbmi_mmrm', line 63, column 26 to column 30)\",\n \" (in 'rbmi_mmrm', line 63, column 8 to column 99)\",\n \" (in 'rbmi_mmrm', line 64, column 14 to column 17)\",\n \" (in 'rbmi_mmrm', line 64, column 26 to column 30)\",\n \" (in 'rbmi_mmrm', line 64, column 8 to column 101)\",\n \" (in 'rbmi_mmrm', line 65, column 8 to column 42)\",\n \" (in 'rbmi_mmrm', line 67, column 8 to column 43)\",\n \" (in 'rbmi_mmrm', line 52, column 22 to line 68, column 5)\",\n \" (in 'rbmi_mmrm', line 52, column 4 to line 68, column 5)\",\n \" (in 'rbmi_mmrm', line 25, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 26, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 27, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 28, column 4 to column 25)\",\n \" (in 'rbmi_mmrm', line 29, column 4 to column 23)\",\n \" (in 'rbmi_mmrm', line 30, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 30, column 4 to column 36)\",\n \" (in 'rbmi_mmrm', line 31, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 31, column 4 to column 39)\",\n \" (in 'rbmi_mmrm', line 32, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 32, column 4 to column 42)\",\n \" (in 'rbmi_mmrm', line 33, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 33, column 17 to column 24)\",\n \" (in 'rbmi_mmrm', line 33, column 4 to column 55)\",\n \" (in 'rbmi_mmrm', line 34, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 34, column 4 to column 16)\",\n \" (in 'rbmi_mmrm', line 35, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 35, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 35, column 4 to column 18)\",\n \" (in 'rbmi_mmrm', line 36, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 36, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 36, column 4 to column 18)\",\n \" (in 'rbmi_mmrm', line 37, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 37, column 20 to column 27)\",\n \" (in 'rbmi_mmrm', line 37, column 29 to column 36)\",\n \" (in 'rbmi_mmrm', line 37, column 4 to column 49)\",\n \" (in 'rbmi_mmrm', line 40, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 40, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 40, column 3 to column 39)\",\n \" (in 'rbmi_mmrm', line 43, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 44, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 44, column 24 to column 31)\",\n \" (in 'rbmi_mmrm', line 71, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 4, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 6, column 12 to column 22)\",\n \" (in 'rbmi_mmrm', line 5, column 28 to line 7, column 9)\",\n \" (in 'rbmi_mmrm', line 5, column 8 to line 7, column 9)\",\n \" (in 'rbmi_mmrm', line 8, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 2, column 39 to line 9, column 5)\",\n \" (in 'rbmi_mmrm', line 13, column 14 to column 62)\",\n \" (in 'rbmi_mmrm', line 13, column 71 to column 83)\",\n \" (in 'rbmi_mmrm', line 13, column 8 to column 89)\",\n \" (in 'rbmi_mmrm', line 14, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 15, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 17, column 12 to column 48)\",\n \" (in 'rbmi_mmrm', line 18, column 12 to column 20)\",\n \" (in 'rbmi_mmrm', line 19, column 12 to column 33)\",\n \" (in 'rbmi_mmrm', line 16, column 38 to line 20, column 9)\",\n \" (in 'rbmi_mmrm', line 16, column 8 to line 20, column 9)\",\n \" (in 'rbmi_mmrm', line 21, column 8 to column 20)\",\n \" (in 'rbmi_mmrm', line 10, column 69 to line 22, column 5)\"};\nint integer_division(const int& a, const int& b, std::ostream* pstream__);\ntemplate <typename T0__,\n stan::require_all_t<stan::is_col_vector<T0__>,\n stan::is_vt_not_complex<T0__>>* = nullptr>\nstd::vector<\n Eigen::Matrix<stan::promote_args_t<stan::base_type_t<T0__>>,-1,1>>\nto_vector_of_arrays(const T0__& vec_arg__, const int& length_array,\n std::ostream* pstream__);\nint integer_division(const int& a, const int& b, std::ostream* pstream__) {\n using local_scalar_t__ = double;\n int current_statement__ = 0;\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int i = std::numeric_limits<int>::min();\n current_statement__ = 62;\n i = 0;\n current_statement__ = 65;\n while (stan::math::logical_lte((b * (i + 1)), a)) {\n current_statement__ = 63;\n i = (i + 1);\n }\n current_statement__ = 66;\n return i;\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n}\ntemplate <typename T0__,\n stan::require_all_t<stan::is_col_vector<T0__>,\n stan::is_vt_not_complex<T0__>>*>\nstd::vector<\n Eigen::Matrix<stan::promote_args_t<stan::base_type_t<T0__>>,-1,1>>\nto_vector_of_arrays(const T0__& vec_arg__, const int& length_array,\n std::ostream* pstream__) {\n using local_scalar_t__ = stan::promote_args_t<stan::base_type_t<T0__>>;\n int current_statement__ = 0;\n const auto& vec = stan::math::to_ref(vec_arg__);\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n current_statement__ = 68;\n stan::math::validate_non_negative_index(\"res\",\n \"integer_division(num_elements(vec), length_array)\",\n integer_division(stan::math::num_elements(vec), length_array, pstream__));\n current_statement__ = 69;\n stan::math::validate_non_negative_index(\"res\", \"length_array\",\n length_array);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> res =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(integer_division(\n stan::math::num_elements(\n vec),\n length_array,\n pstream__),\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(length_array,\n DUMMY_VAR__));\n int j = std::numeric_limits<int>::min();\n current_statement__ = 71;\n j = 1;\n int i = std::numeric_limits<int>::min();\n current_statement__ = 72;\n i = 1;\n current_statement__ = 77;\n while (stan::math::logical_lte(j, stan::math::num_elements(vec))) {\n current_statement__ = 73;\n stan::model::assign(res,\n stan::model::rvalue(vec, \"vec\",\n stan::model::index_min_max(j, ((j + length_array) - 1))),\n \"assigning variable res\", stan::model::index_uni(i),\n stan::model::index_omni());\n current_statement__ = 74;\n i = (i + 1);\n current_statement__ = 75;\n j = (j + length_array);\n }\n current_statement__ = 78;\n return res;\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n}\nclass model10310783487d8_rbmi_mmrm final : public model_base_crtp<model10310783487d8_rbmi_mmrm> {\nprivate:\n int N;\n int P;\n int G;\n int n_visit;\n int n_pat;\n std::vector<int> pat_G;\n std::vector<int> pat_n_pt;\n std::vector<int> pat_n_visit;\n std::vector<std::vector<int>> pat_sigma_index;\n Eigen::Matrix<double,-1,1> y_data__;\n Eigen::Matrix<double,-1,-1> Q_data__;\n Eigen::Matrix<double,-1,-1> R_data__;\n std::vector<Eigen::Matrix<double,-1,-1>> Sigma_init;\n Eigen::Matrix<double,-1,-1> R_inverse_data__;\n Eigen::Map<Eigen::Matrix<double,-1,1>> y{nullptr, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> Q{nullptr, 0, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> R{nullptr, 0, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> R_inverse{nullptr, 0, 0};\npublic:\n ~model10310783487d8_rbmi_mmrm() {}\n model10310783487d8_rbmi_mmrm(stan::io::var_context& context__, unsigned int\n random_seed__ = 0, std::ostream*\n pstream__ = nullptr) : model_base_crtp(0) {\n int current_statement__ = 0;\n using local_scalar_t__ = double;\n boost::ecuyer1988 base_rng__ =\n stan::services::util::create_rng(random_seed__, 0);\n // suppress unused var warning\n (void) base_rng__;\n static constexpr const char* function__ =\n \"model10310783487d8_rbmi_mmrm_namespace::model10310783487d8_rbmi_mmrm\";\n // suppress unused var warning\n (void) function__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n current_statement__ = 29;\n context__.validate_dims(\"data initialization\", \"N\", \"int\",\n std::vector<size_t>{});\n N = std::numeric_limits<int>::min();\n current_statement__ = 29;\n N = context__.vals_i(\"N\")[(1 - 1)];\n current_statement__ = 29;\n stan::math::check_greater_or_equal(function__, \"N\", N, 1);\n current_statement__ = 30;\n context__.validate_dims(\"data initialization\", \"P\", \"int\",\n std::vector<size_t>{});\n P = std::numeric_limits<int>::min();\n current_statement__ = 30;\n P = context__.vals_i(\"P\")[(1 - 1)];\n current_statement__ = 30;\n stan::math::check_greater_or_equal(function__, \"P\", P, 1);\n current_statement__ = 31;\n context__.validate_dims(\"data initialization\", \"G\", \"int\",\n std::vector<size_t>{});\n G = std::numeric_limits<int>::min();\n current_statement__ = 31;\n G = context__.vals_i(\"G\")[(1 - 1)];\n current_statement__ = 31;\n stan::math::check_greater_or_equal(function__, \"G\", G, 1);\n current_statement__ = 32;\n context__.validate_dims(\"data initialization\", \"n_visit\", \"int\",\n std::vector<size_t>{});\n n_visit = std::numeric_limits<int>::min();\n current_statement__ = 32;\n n_visit = context__.vals_i(\"n_visit\")[(1 - 1)];\n current_statement__ = 32;\n stan::math::check_greater_or_equal(function__, \"n_visit\", n_visit, 1);\n current_statement__ = 33;\n context__.validate_dims(\"data initialization\", \"n_pat\", \"int\",\n std::vector<size_t>{});\n n_pat = std::numeric_limits<int>::min();\n current_statement__ = 33;\n n_pat = context__.vals_i(\"n_pat\")[(1 - 1)];\n current_statement__ = 33;\n stan::math::check_greater_or_equal(function__, \"n_pat\", n_pat, 1);\n current_statement__ = 34;\n stan::math::validate_non_negative_index(\"pat_G\", \"n_pat\", n_pat);\n current_statement__ = 35;\n context__.validate_dims(\"data initialization\", \"pat_G\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_G = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 35;\n pat_G = context__.vals_i(\"pat_G\");\n current_statement__ = 35;\n stan::math::check_greater_or_equal(function__, \"pat_G\", pat_G, 1);\n current_statement__ = 36;\n stan::math::validate_non_negative_index(\"pat_n_pt\", \"n_pat\", n_pat);\n current_statement__ = 37;\n context__.validate_dims(\"data initialization\", \"pat_n_pt\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_n_pt = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 37;\n pat_n_pt = context__.vals_i(\"pat_n_pt\");\n current_statement__ = 37;\n stan::math::check_greater_or_equal(function__, \"pat_n_pt\", pat_n_pt, 1);\n current_statement__ = 38;\n stan::math::validate_non_negative_index(\"pat_n_visit\", \"n_pat\", n_pat);\n current_statement__ = 39;\n context__.validate_dims(\"data initialization\", \"pat_n_visit\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_n_visit = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 39;\n pat_n_visit = context__.vals_i(\"pat_n_visit\");\n current_statement__ = 39;\n stan::math::check_greater_or_equal(function__, \"pat_n_visit\",\n pat_n_visit, 1);\n current_statement__ = 40;\n stan::math::validate_non_negative_index(\"pat_sigma_index\", \"n_pat\",\n n_pat);\n current_statement__ = 41;\n stan::math::validate_non_negative_index(\"pat_sigma_index\", \"n_visit\",\n n_visit);\n current_statement__ = 42;\n context__.validate_dims(\"data initialization\", \"pat_sigma_index\",\n \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat),\n static_cast<size_t>(n_visit)});\n pat_sigma_index = std::vector<std::vector<int>>(n_pat,\n std::vector<int>(n_visit,\n std::numeric_limits<int>::min()));\n {\n std::vector<int> pat_sigma_index_flat__;\n current_statement__ = 42;\n pat_sigma_index_flat__ = context__.vals_i(\"pat_sigma_index\");\n current_statement__ = 42;\n pos__ = 1;\n current_statement__ = 42;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 42;\n for (int sym2__ = 1; sym2__ <= n_pat; ++sym2__) {\n current_statement__ = 42;\n stan::model::assign(pat_sigma_index,\n pat_sigma_index_flat__[(pos__ - 1)],\n \"assigning variable pat_sigma_index\",\n stan::model::index_uni(sym2__), stan::model::index_uni(sym1__));\n current_statement__ = 42;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 42;\n stan::math::check_greater_or_equal(function__, \"pat_sigma_index\",\n pat_sigma_index, 1);\n current_statement__ = 43;\n stan::math::validate_non_negative_index(\"y\", \"N\", N);\n current_statement__ = 44;\n context__.validate_dims(\"data initialization\", \"y\", \"double\",\n std::vector<size_t>{static_cast<size_t>(N)});\n y_data__ = Eigen::Matrix<double,-1,1>::Constant(N,\n std::numeric_limits<double>::quiet_NaN());\n new (&y) Eigen::Map<Eigen::Matrix<double,-1,1>>(y_data__.data(), N);\n {\n std::vector<local_scalar_t__> y_flat__;\n current_statement__ = 44;\n y_flat__ = context__.vals_r(\"y\");\n current_statement__ = 44;\n pos__ = 1;\n current_statement__ = 44;\n for (int sym1__ = 1; sym1__ <= N; ++sym1__) {\n current_statement__ = 44;\n stan::model::assign(y, y_flat__[(pos__ - 1)],\n \"assigning variable y\", stan::model::index_uni(sym1__));\n current_statement__ = 44;\n pos__ = (pos__ + 1);\n }\n }\n current_statement__ = 45;\n stan::math::validate_non_negative_index(\"Q\", \"N\", N);\n current_statement__ = 46;\n stan::math::validate_non_negative_index(\"Q\", \"P\", P);\n current_statement__ = 47;\n context__.validate_dims(\"data initialization\", \"Q\", \"double\",\n std::vector<size_t>{static_cast<size_t>(N), static_cast<size_t>(P)});\n Q_data__ = Eigen::Matrix<double,-1,-1>::Constant(N, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&Q) Eigen::Map<Eigen::Matrix<double,-1,-1>>(Q_data__.data(), N, P);\n {\n std::vector<local_scalar_t__> Q_flat__;\n current_statement__ = 47;\n Q_flat__ = context__.vals_r(\"Q\");\n current_statement__ = 47;\n pos__ = 1;\n current_statement__ = 47;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 47;\n for (int sym2__ = 1; sym2__ <= N; ++sym2__) {\n current_statement__ = 47;\n stan::model::assign(Q, Q_flat__[(pos__ - 1)],\n \"assigning variable Q\", stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 47;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 48;\n stan::math::validate_non_negative_index(\"R\", \"P\", P);\n current_statement__ = 49;\n stan::math::validate_non_negative_index(\"R\", \"P\", P);\n current_statement__ = 50;\n context__.validate_dims(\"data initialization\", \"R\", \"double\",\n std::vector<size_t>{static_cast<size_t>(P), static_cast<size_t>(P)});\n R_data__ = Eigen::Matrix<double,-1,-1>::Constant(P, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&R) Eigen::Map<Eigen::Matrix<double,-1,-1>>(R_data__.data(), P, P);\n {\n std::vector<local_scalar_t__> R_flat__;\n current_statement__ = 50;\n R_flat__ = context__.vals_r(\"R\");\n current_statement__ = 50;\n pos__ = 1;\n current_statement__ = 50;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 50;\n for (int sym2__ = 1; sym2__ <= P; ++sym2__) {\n current_statement__ = 50;\n stan::model::assign(R, R_flat__[(pos__ - 1)],\n \"assigning variable R\", stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 50;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 51;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"G\", G);\n current_statement__ = 52;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"n_visit\",\n n_visit);\n current_statement__ = 53;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"n_visit\",\n n_visit);\n current_statement__ = 54;\n context__.validate_dims(\"data initialization\", \"Sigma_init\", \"double\",\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)});\n Sigma_init = std::vector<Eigen::Matrix<double,-1,-1>>(G,\n Eigen::Matrix<double,-1,-1>::Constant(n_visit, n_visit,\n std::numeric_limits<double>::quiet_NaN()));\n {\n std::vector<local_scalar_t__> Sigma_init_flat__;\n current_statement__ = 54;\n Sigma_init_flat__ = context__.vals_r(\"Sigma_init\");\n current_statement__ = 54;\n pos__ = 1;\n current_statement__ = 54;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 54;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 54;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 54;\n stan::model::assign(Sigma_init, Sigma_init_flat__[(pos__ - 1)],\n \"assigning variable Sigma_init\",\n stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 54;\n pos__ = (pos__ + 1);\n }\n }\n }\n }\n current_statement__ = 55;\n stan::math::validate_non_negative_index(\"R_inverse\", \"P\", P);\n current_statement__ = 56;\n stan::math::validate_non_negative_index(\"R_inverse\", \"P\", P);\n current_statement__ = 57;\n R_inverse_data__ = Eigen::Matrix<double,-1,-1>::Constant(P, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&R_inverse)\n Eigen::Map<Eigen::Matrix<double,-1,-1>>(R_inverse_data__.data(), P,\n P);\n current_statement__ = 57;\n stan::model::assign(R_inverse, stan::math::inverse(R),\n \"assigning variable R_inverse\");\n current_statement__ = 58;\n stan::math::validate_non_negative_index(\"theta\", \"P\", P);\n current_statement__ = 59;\n stan::math::validate_non_negative_index(\"Sigma\", \"G\", G);\n current_statement__ = 60;\n stan::math::validate_non_negative_index(\"Sigma\", \"n_visit\", n_visit);\n current_statement__ = 60;\n stan::math::validate_non_negative_index(\"Sigma\", \"n_visit\", n_visit);\n current_statement__ = 61;\n stan::math::validate_non_negative_index(\"beta\", \"P\", P);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n num_params_r__ = P + (G * (n_visit + ((n_visit * (n_visit - 1)) / 2)));\n }\n inline std::string model_name() const final {\n return \"model10310783487d8_rbmi_mmrm\";\n }\n inline std::vector<std::string> model_compile_info() const noexcept {\n return std::vector<std::string>{\"stanc_version = stanc3 v2.32.2\",\n \"stancflags = --\"};\n }\n template <bool propto__, bool jacobian__, typename VecR, typename VecI,\n stan::require_vector_like_t<VecR>* = nullptr,\n stan::require_vector_like_vt<std::is_integral, VecI>* = nullptr>\n inline stan::scalar_type_t<VecR>\n log_prob_impl(VecR& params_r__, VecI& params_i__, std::ostream*\n pstream__ = nullptr) const {\n using T__ = stan::scalar_type_t<VecR>;\n using local_scalar_t__ = T__;\n T__ lp__(0.0);\n stan::math::accumulator<T__> lp_accum__;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n static constexpr const char* function__ =\n \"model10310783487d8_rbmi_mmrm_namespace::log_prob\";\n // suppress unused var warning\n (void) function__;\n try {\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n current_statement__ = 1;\n theta = in__.template read<Eigen::Matrix<local_scalar_t__,-1,1>>(P);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n current_statement__ = 2;\n Sigma = in__.template read_constrain_cov_matrix<\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,\n jacobian__>(lp__, G, n_visit);\n {\n int data_start_row = std::numeric_limits<int>::min();\n current_statement__ = 4;\n data_start_row = 1;\n current_statement__ = 5;\n stan::math::validate_non_negative_index(\"mu\", \"N\", N);\n Eigen::Matrix<local_scalar_t__,-1,1> mu =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(N, DUMMY_VAR__);\n current_statement__ = 6;\n stan::model::assign(mu, stan::math::multiply(Q, theta),\n \"assigning variable mu\");\n current_statement__ = 9;\n for (int g = 1; g <= G; ++g) {\n current_statement__ = 7;\n lp_accum__.add(stan::math::inv_wishart_lpdf<propto__>(\n stan::model::rvalue(Sigma, \"Sigma\",\n stan::model::index_uni(g)), (n_visit + 2),\n stan::model::rvalue(Sigma_init, \"Sigma_init\",\n stan::model::index_uni(g))));\n }\n current_statement__ = 28;\n for (int i = 1; i <= n_pat; ++i) {\n int nvis = std::numeric_limits<int>::min();\n current_statement__ = 10;\n nvis = stan::model::rvalue(pat_n_visit, \"pat_n_visit\",\n stan::model::index_uni(i));\n int npt = std::numeric_limits<int>::min();\n current_statement__ = 11;\n npt = stan::model::rvalue(pat_n_pt, \"pat_n_pt\",\n stan::model::index_uni(i));\n int g = std::numeric_limits<int>::min();\n current_statement__ = 12;\n g = stan::model::rvalue(pat_G, \"pat_G\", stan::model::index_uni(i));\n current_statement__ = 13;\n stan::math::validate_non_negative_index(\"sig_index\", \"nvis\", nvis);\n std::vector<int> sig_index =\n std::vector<int>(nvis, std::numeric_limits<int>::min());\n current_statement__ = 14;\n stan::model::assign(sig_index,\n stan::model::rvalue(pat_sigma_index, \"pat_sigma_index\",\n stan::model::index_uni(i), stan::model::index_min_max(1, nvis)),\n \"assigning variable sig_index\");\n current_statement__ = 15;\n stan::math::validate_non_negative_index(\"sig\", \"nvis\", nvis);\n current_statement__ = 16;\n stan::math::validate_non_negative_index(\"sig\", \"nvis\", nvis);\n Eigen::Matrix<local_scalar_t__,-1,-1> sig =\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(nvis, nvis,\n DUMMY_VAR__);\n current_statement__ = 17;\n stan::model::assign(sig,\n stan::model::rvalue(\n stan::model::rvalue(Sigma, \"Sigma\", stan::model::index_uni(g)),\n \"Sigma[g]\", stan::model::index_multi(sig_index),\n stan::model::index_multi(sig_index)), \"assigning variable sig\");\n int data_stop_row = std::numeric_limits<int>::min();\n current_statement__ = 18;\n data_stop_row = (data_start_row + ((nvis * npt) - 1));\n current_statement__ = 19;\n stan::math::validate_non_negative_index(\"y_obs\", \"npt\", npt);\n current_statement__ = 20;\n stan::math::validate_non_negative_index(\"y_obs\", \"nvis\", nvis);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> y_obs =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(npt,\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(nvis,\n DUMMY_VAR__));\n current_statement__ = 21;\n stan::model::assign(y_obs,\n to_vector_of_arrays(\n stan::model::rvalue(y, \"y\",\n stan::model::index_min_max(data_start_row, data_stop_row)),\n nvis, pstream__), \"assigning variable y_obs\");\n current_statement__ = 22;\n stan::math::validate_non_negative_index(\"mu_obs\", \"npt\", npt);\n current_statement__ = 23;\n stan::math::validate_non_negative_index(\"mu_obs\", \"nvis\", nvis);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> mu_obs =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(npt,\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(nvis,\n DUMMY_VAR__));\n current_statement__ = 24;\n stan::model::assign(mu_obs,\n to_vector_of_arrays(\n stan::model::rvalue(mu, \"mu\",\n stan::model::index_min_max(data_start_row, data_stop_row)),\n nvis, pstream__), \"assigning variable mu_obs\");\n current_statement__ = 25;\n lp_accum__.add(stan::math::multi_normal_lpdf<propto__>(y_obs,\n mu_obs, sig));\n current_statement__ = 26;\n data_start_row = (data_stop_row + 1);\n }\n }\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n lp_accum__.add(lp__);\n return lp_accum__.sum();\n }\n template <typename RNG, typename VecR, typename VecI, typename VecVar,\n stan::require_vector_like_vt<std::is_floating_point,\n VecR>* = nullptr, stan::require_vector_like_vt<std::is_integral,\n VecI>* = nullptr, stan::require_vector_vt<std::is_floating_point,\n VecVar>* = nullptr>\n inline void\n write_array_impl(RNG& base_rng__, VecR& params_r__, VecI& params_i__,\n VecVar& vars__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true, std::ostream*\n pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n stan::io::serializer<local_scalar_t__> out__(vars__);\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n double lp__ = 0.0;\n // suppress unused var warning\n (void) lp__;\n int current_statement__ = 0;\n stan::math::accumulator<double> lp_accum__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n constexpr bool jacobian__ = false;\n static constexpr const char* function__ =\n \"model10310783487d8_rbmi_mmrm_namespace::write_array\";\n // suppress unused var warning\n (void) function__;\n try {\n Eigen::Matrix<double,-1,1> theta =\n Eigen::Matrix<double,-1,1>::Constant(P,\n std::numeric_limits<double>::quiet_NaN());\n current_statement__ = 1;\n theta = in__.template read<Eigen::Matrix<local_scalar_t__,-1,1>>(P);\n std::vector<Eigen::Matrix<double,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<double,-1,-1>>(G,\n Eigen::Matrix<double,-1,-1>::Constant(n_visit, n_visit,\n std::numeric_limits<double>::quiet_NaN()));\n current_statement__ = 2;\n Sigma = in__.template read_constrain_cov_matrix<\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,\n jacobian__>(lp__, G, n_visit);\n out__.write(theta);\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n out__.write(stan::model::rvalue(Sigma, \"Sigma\",\n stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__)));\n }\n }\n }\n if (stan::math::logical_negation(\n (stan::math::primitive_value(emit_transformed_parameters__) ||\n stan::math::primitive_value(emit_generated_quantities__)))) {\n return ;\n }\n if (stan::math::logical_negation(emit_generated_quantities__)) {\n return ;\n }\n Eigen::Matrix<double,-1,1> beta =\n Eigen::Matrix<double,-1,1>::Constant(P,\n std::numeric_limits<double>::quiet_NaN());\n current_statement__ = 3;\n stan::model::assign(beta, stan::math::multiply(R_inverse, theta),\n \"assigning variable beta\");\n out__.write(beta);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n template <typename VecVar, typename VecI,\n stan::require_vector_t<VecVar>* = nullptr,\n stan::require_vector_like_vt<std::is_integral, VecI>* = nullptr>\n inline void\n unconstrain_array_impl(const VecVar& params_r__, const VecI& params_i__,\n VecVar& vars__, std::ostream* pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n stan::io::serializer<local_scalar_t__> out__(vars__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n current_statement__ = 1;\n stan::model::assign(theta,\n in__.read<Eigen::Matrix<local_scalar_t__,-1,1>>(P),\n \"assigning variable theta\");\n out__.write(theta);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n current_statement__ = 2;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 2;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 2;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 2;\n stan::model::assign(Sigma, in__.read<local_scalar_t__>(),\n \"assigning variable Sigma\", stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__), stan::model::index_uni(sym1__));\n }\n }\n }\n out__.write_free_cov_matrix(Sigma);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n template <typename VecVar, stan::require_vector_t<VecVar>* = nullptr>\n inline void\n transform_inits_impl(const stan::io::var_context& context__, VecVar&\n vars__, std::ostream* pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::serializer<local_scalar_t__> out__(vars__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n current_statement__ = 1;\n context__.validate_dims(\"parameter initialization\", \"theta\", \"double\",\n std::vector<size_t>{static_cast<size_t>(P)});\n current_statement__ = 2;\n context__.validate_dims(\"parameter initialization\", \"Sigma\", \"double\",\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)});\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n {\n std::vector<local_scalar_t__> theta_flat__;\n current_statement__ = 1;\n theta_flat__ = context__.vals_r(\"theta\");\n current_statement__ = 1;\n pos__ = 1;\n current_statement__ = 1;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 1;\n stan::model::assign(theta, theta_flat__[(pos__ - 1)],\n \"assigning variable theta\", stan::model::index_uni(sym1__));\n current_statement__ = 1;\n pos__ = (pos__ + 1);\n }\n }\n out__.write(theta);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n {\n std::vector<local_scalar_t__> Sigma_flat__;\n current_statement__ = 2;\n Sigma_flat__ = context__.vals_r(\"Sigma\");\n current_statement__ = 2;\n pos__ = 1;\n current_statement__ = 2;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 2;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 2;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 2;\n stan::model::assign(Sigma, Sigma_flat__[(pos__ - 1)],\n \"assigning variable Sigma\", stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 2;\n pos__ = (pos__ + 1);\n }\n }\n }\n }\n out__.write_free_cov_matrix(Sigma);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n inline void\n get_param_names(std::vector<std::string>& names__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true) const {\n names__ = std::vector<std::string>{\"theta\", \"Sigma\"};\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n std::vector<std::string> temp{\"beta\"};\n names__.reserve(names__.size() + temp.size());\n names__.insert(names__.end(), temp.begin(), temp.end());\n }\n }\n inline void\n get_dims(std::vector<std::vector<size_t>>& dimss__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true) const {\n dimss__ = std::vector<std::vector<size_t>>{std::vector<size_t>{static_cast<\n size_t>(P)},\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)}};\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n std::vector<std::vector<size_t>>\n temp{std::vector<size_t>{static_cast<size_t>(P)}};\n dimss__.reserve(dimss__.size() + temp.size());\n dimss__.insert(dimss__.end(), temp.begin(), temp.end());\n }\n }\n inline void\n constrained_param_names(std::vector<std::string>& param_names__, bool\n emit_transformed_parameters__ = true, bool\n emit_generated_quantities__ = true) const final {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"theta\" + '.' +\n std::to_string(sym1__));\n }\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n param_names__.emplace_back(std::string() + \"Sigma\" + '.' +\n std::to_string(sym3__) + '.' + std::to_string(sym2__) + '.' +\n std::to_string(sym1__));\n }\n }\n }\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"beta\" + '.' +\n std::to_string(sym1__));\n }\n }\n }\n inline void\n unconstrained_param_names(std::vector<std::string>& param_names__, bool\n emit_transformed_parameters__ = true, bool\n emit_generated_quantities__ = true) const final {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"theta\" + '.' +\n std::to_string(sym1__));\n }\n for (int sym1__ = 1; sym1__ <= (n_visit + ((n_visit * (n_visit - 1)) /\n 2)); ++sym1__) {\n for (int sym2__ = 1; sym2__ <= G; ++sym2__) {\n param_names__.emplace_back(std::string() + \"Sigma\" + '.' +\n std::to_string(sym2__) + '.' + std::to_string(sym1__));\n }\n }\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"beta\" + '.' +\n std::to_string(sym1__));\n }\n }\n }\n inline std::string get_constrained_sizedtypes() const {\n return std::string(\"[{\\\"name\\\":\\\"theta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"Sigma\\\",\\\"type\\\":{\\\"name\\\":\\\"array\\\",\\\"length\\\":\" + std::to_string(G) + \",\\\"element_type\\\":{\\\"name\\\":\\\"matrix\\\",\\\"rows\\\":\" + std::to_string(n_visit) + \",\\\"cols\\\":\" + std::to_string(n_visit) + \"}},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"beta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"generated_quantities\\\"}]\");\n }\n inline std::string get_unconstrained_sizedtypes() const {\n return std::string(\"[{\\\"name\\\":\\\"theta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"Sigma\\\",\\\"type\\\":{\\\"name\\\":\\\"array\\\",\\\"length\\\":\" + std::to_string(G) + \",\\\"element_type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string((n_visit + ((n_visit * (n_visit - 1)) /2))) + \"}},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"beta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"generated_quantities\\\"}]\");\n }\n // Begin method overload boilerplate\n template <typename RNG> inline void\n write_array(RNG& base_rng, Eigen::Matrix<double,-1,1>& params_r,\n Eigen::Matrix<double,-1,1>& vars, const bool\n emit_transformed_parameters = true, const bool\n emit_generated_quantities = true, std::ostream*\n pstream = nullptr) const {\n const size_t num_params__ = (P + ((G * n_visit) * n_visit));\n const size_t num_transformed = emit_transformed_parameters * (0);\n const size_t num_gen_quantities = emit_generated_quantities * (P);\n const size_t num_to_write = num_params__ + num_transformed +\n num_gen_quantities;\n std::vector<int> params_i;\n vars = Eigen::Matrix<double,-1,1>::Constant(num_to_write,\n std::numeric_limits<double>::quiet_NaN());\n write_array_impl(base_rng, params_r, params_i, vars,\n emit_transformed_parameters, emit_generated_quantities, pstream);\n }\n template <typename RNG> inline void\n write_array(RNG& base_rng, std::vector<double>& params_r, std::vector<int>&\n params_i, std::vector<double>& vars, bool\n emit_transformed_parameters = true, bool\n emit_generated_quantities = true, std::ostream*\n pstream = nullptr) const {\n const size_t num_params__ = (P + ((G * n_visit) * n_visit));\n const size_t num_transformed = emit_transformed_parameters * (0);\n const size_t num_gen_quantities = emit_generated_quantities * (P);\n const size_t num_to_write = num_params__ + num_transformed +\n num_gen_quantities;\n vars = std::vector<double>(num_to_write,\n std::numeric_limits<double>::quiet_NaN());\n write_array_impl(base_rng, params_r, params_i, vars,\n emit_transformed_parameters, emit_generated_quantities, pstream);\n }\n template <bool propto__, bool jacobian__, typename T_> inline T_\n log_prob(Eigen::Matrix<T_,-1,1>& params_r, std::ostream* pstream = nullptr) const {\n Eigen::Matrix<int,-1,1> params_i;\n return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);\n }\n template <bool propto__, bool jacobian__, typename T_> inline T_\n log_prob(std::vector<T_>& params_r, std::vector<int>& params_i,\n std::ostream* pstream = nullptr) const {\n return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);\n }\n inline void\n transform_inits(const stan::io::var_context& context,\n Eigen::Matrix<double,-1,1>& params_r, std::ostream*\n pstream = nullptr) const final {\n std::vector<double> params_r_vec(params_r.size());\n std::vector<int> params_i;\n transform_inits(context, params_i, params_r_vec, pstream);\n params_r = Eigen::Map<Eigen::Matrix<double,-1,1>>(params_r_vec.data(),\n params_r_vec.size());\n }\n inline void\n transform_inits(const stan::io::var_context& context, std::vector<int>&\n params_i, std::vector<double>& vars, std::ostream*\n pstream__ = nullptr) const {\n vars.resize(num_params_r__);\n transform_inits_impl(context, vars, pstream__);\n }\n inline void\n unconstrain_array(const std::vector<double>& params_constrained,\n std::vector<double>& params_unconstrained, std::ostream*\n pstream = nullptr) const {\n const std::vector<int> params_i;\n params_unconstrained = std::vector<double>(num_params_r__,\n std::numeric_limits<double>::quiet_NaN());\n unconstrain_array_impl(params_constrained, params_i,\n params_unconstrained, pstream);\n }\n inline void\n unconstrain_array(const Eigen::Matrix<double,-1,1>& params_constrained,\n Eigen::Matrix<double,-1,1>& params_unconstrained,\n std::ostream* pstream = nullptr) const {\n const std::vector<int> params_i;\n params_unconstrained = Eigen::Matrix<double,-1,1>::Constant(num_params_r__,\n std::numeric_limits<double>::quiet_NaN());\n unconstrain_array_impl(params_constrained, params_i,\n params_unconstrained, pstream);\n }\n};\n}\nusing stan_model = model10310783487d8_rbmi_mmrm_namespace::model10310783487d8_rbmi_mmrm;\n#ifndef USING_R\n// Boilerplate\nstan::model::model_base&\nnew_model(stan::io::var_context& data_context, unsigned int seed,\n std::ostream* msg_stream) {\n stan_model* m = new stan_model(data_context, seed, msg_stream);\n return *m;\n}\nstan::math::profile_map& get_stan_profile_data() {\n return model10310783487d8_rbmi_mmrm_namespace::profiles__;\n}\n#endif\n#endif"), mk_cppmodule = function (object) { prep_call_sampler(object) model_cppname <- object@model_cpp$model_cppname mod <- get("module", envir = object@dso@.CXXDSOMISC, inherits = FALSE) eval(call("$", mod, paste("stan_fit4", model_cppname, sep = ""))) }, dso = new("cxxdso", sig = list(file1031058a7199b = character(0)), dso_saved = TRUE, dso_filename = "file1031058a7199b", modulename = "stan_fit4model10310783487d8_rbmi_mmrm_mod", system = "aarch64, darwin20", cxxflags = "CXXFLAGS = -falign-functions=64 -Wall -g -O2 $(LTO)", .CXXDSOMISC = <environment>)), data = list(N = 340L, P = 8L, G = 1L, n_visit = 3L, n_pat = 2L, pat_G = c(1, 1), pat_n_pt = c(60, 80), pat_n_visit = c(3, 2), pat_sigma_index = list( c(1, 2, 3), c(1, 2, 999)), y = c(0.574036883477536, 0.139105398171835, 0.176977232131814, -1.16935503183362, -1.21591438062592, -1.08964625296442, -1.58121597188229, -1.03382417471284, -0.813329718686652, -0.659208380311965, -0.596830231476417, -0.428690642917848, 1.19340919052579, 1.19324384350827, 1.14076998750238, 0.508301722783451, 0.285101803715272, -0.080275904172036, 0.420951505580432, 0.729295857616047, 0.606493590677628, 1.36133467580718, 0.785097805390841, 0.850728879541265, 1.59518647362531, 1.99123113996823, 1.62317993728234, -1.01500989395391, -1.29590087043236, -1.09167466441661, -1.92326503149754, -1.6438232242331, -2.09494484800456, -0.916339955699448, -1.21279752527853, -0.824654473194631, 0.160587572122124, 0.533787595446638, 0.509785626882552, 0.625441265387049, 0.869595429439695, 0.606754094352448, 0.416887452319262, 0.0527870943089152, -0.290746253299322, -0.0405562348050075, 0.138363916063878, 0.199662379261492, -0.0292589587575427, 0.184625776371717, 0.596974269230419, 0.460701441061857, 0.606107749594927, 0.675147663778399, 1.66002871020651, 1.84142634216536, 1.99191103632866, 1.10904044059033, 0.414249192109747, 0.672496352831966, 0.789592735008045, 0.677931435319178, 0.543093801624015, -0.899674446856585, -0.98731077385762, -1.31298117495064, -0.790921720329644, -0.407036721173524, -0.221080281874233, 1.43428989449746, 1.46018790177788, 1.29835543116011, 1.93804574039781, 1.67293427649682, 1.58849553103043, -1.01450332611738, -0.842813717586719, -0.629379340054354, -0.267415091390975, -0.657913697591214, -0.595234267484234, 0.120679904254403, 0.178945058091685, 0.258466389498271, -0.449519107207705, -0.418311943730978, -0.607987725151117, 0.475470586549514, 0.465961733342575, 0.628255437173784, -0.269181976386959, -0.489283917847538, -0.480553495290893, 0.0126097945506518, 0.188893941324742, -0.00785768753235569, -1.64359171150621, -1.51956953580399, -1.83648421907106, -0.334174407608112, 0.173961399031304, 0.512090615451255, 0.815812442864812, 1.00796572845926, 1.08799807363422, -0.499836503819652, -0.194917201294718, -0.347531934556113, 0.0967719422298859, 0.0448422069391228, -0.0380229372755732, 0.89027308837742, 0.923859648959303, 0.693773508152388, 0.0200206385163762, 0.139715592410514, 0.355610280019225, -0.554244284647314, -0.337491541079209, -0.0476717323926218, 1.74097877156221, 1.74584951452271, 1.87453426708686, 1.53665210908614, 1.27351842521603, 0.782842422447314, 0.780226954526566, 0.533531436107968, 0.471968788026106, -1.50987360873711, -1.4213975714265, -1.32130245857978, -1.53643170343886, -1.96117485895016, -1.63868589576792, -0.0924369697453538, -0.236384532458898, -0.416943554508815, 0.524748546809872, 1.01066900867255, 1.03925121395702, -1.47575422517021, -1.84351894914451, -1.96406505049471, -0.958450708965594, -1.00073327233577, -1.15403786283949, 1.30985852929418, 0.677518704253333, 0.633123295459129, -1.00859795137567, -0.486351090482834, -0.629987247106473, -0.703803757755735, -0.423015811624416, -0.68260822611802, 1.29970709660456, 0.950166424412677, 0.700867866424596, 0.885973022497435, 0.69557127871005, 0.683167942482159, -0.448047722773281, -0.345122636504495, -0.44919578758697, -0.350389882825743, 0.218778679169879, 0.460591876155823, -1.13643984701411, -1.37594847426891, -1.38924924598483, 1.05497189150375, 1.44213159591197, 1.44244341883156, 0.989297127175544, 1.28938706033795, 0.974021459136989, 0.0997949939225535, 0.0977838256866344, 0.152771705034039, 0.0563099671794369, -0.109302500409893, -0.770343945290974, -0.840203655711169, -1.06621935574191, -0.818506844251997, 0.483309359293258, -0.077312553568267, -1.82787954030716, -1.51850241691396, 0.385765772873327, 0.318930612816827, 0.0529827480329966, -0.256048504100078, 0.755705549841678, 0.841931688341897, 0.712085742232759, 0.644772892574503, -1.14155231656161, -1.4428233579315, -1.05021841671635, -1.39451198199354, -0.267077536825949, -0.707269786974737, -1.45623361118695, -1.14058269087304, -0.768761960571674, -0.570612606157713, -0.764238909934079, -1.27539783051645, -0.845195950602966, -1.35937750037253, -0.403679174325962, -0.181315302498918, -0.138311056457262, -0.0706441028516794, 0.508084112959793, 0.620362254164868, 0.480866966820087, 0.576196611808272, -1.14455494641288, -1.35096340386058, 0.550675910279237, 0.825037960508207, 1.61286207896739, 1.67916701468662, -0.0647658829962172, -0.266749386462743, -0.282320438961451, -0.774105813761362, -0.361641848210371, -0.0216017435394257, 1.42387705128602, 1.23207105462671, 0.265776870737417, 0.515102201270055, 0.771782662506529, 0.702063509689375, 0.616876705707196, 0.789738509590256, 0.971362277748469, 0.738026162904697, 0.534226435971703, 0.045703700581884, -1.14177405496358, -0.787101784899203, -0.872756204009667, -1.09360825060612, -0.968020452649131, -0.801211978871774, 1.52141486581132, 1.40439441624722, 1.79137191952656, 1.47694519657773, -1.9360028677803, -1.12357338931634, -0.442997879839818, -0.564318885154016, 0.000626204404452472, -0.27075649131444, -2.48336093478472, -1.92707335118885, 0.366175672975573, -0.232532349854313, 0.445155531890445, 0.769878306810777, -1.60791560029354, -1.71327349294041, -0.296398526983666, -0.367067711718188, -0.838340929698702, -1.43768210681618, -0.14561552296282, -0.0941334404913737, -0.0164394933059202, 0.0218434792651633, 1.07286404251878, 1.18723665035218, -0.138595585019409, 0.0131822076110258, -0.399908316171867, -0.868639920226593, 0.7981208661895, 0.719218310535081, 0.914826810253791, 0.705606688741132, 2.27692308241729, 2.20307732877354, -1.38708681157136, -1.25624461004343, 0.0942383865047231, 0.619729596216058, -1.97029658377716, -2.12452350098981, -0.546587071142227, -0.965112515688056, -0.0103825230207238, 0.275006295304357, 1.39505387642203, 1.13837400657299, 0.653655010243044, 0.592910348706071, 2.26190956828622, 2.20569250608316, -0.979542016063513, -0.948366938019486, 0.0839816881469963, 0.496574287039973, 0.547933703350616, 0.492939941225062, -0.375076840950679, -0.483574365532446, 1.3297009420447, 1.69844054391049, -1.13265693702497, -0.849277428071457, -1.13312754672772, -0.666195857133899, 0.459008637041986, 0.59569098957591, 1.50283257817443, 1.73920182026267, -0.300363476632086, -0.00897291528474771, -1.40333016095241, -1.19317961021338, -0.600226062637804, -0.325957148423221, 0.870433641965308, 0.130170018966925, -1.77311671749508, -1.19314004127747, 1.7640917533291, 1.44334725535403, -0.871065290131151, -1.32437155254469, 0.853886175567914, 0.646816118526293, 0.294983239652497, -0.326121365030516), Q = c(-0.99852832885673, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.958225137302622, -0.958225137302671, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.825360566675442, 1.20365082640164, -0.825360566675414, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.876442111269588, -0.0244034327926963, 1.96548118704492, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.02583892883933, 2.015723548677, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.02583892883933, -0.826199749637549, 0.02583892883933, -0.876442111269578, -0.0244034327926988, -0.377816532241714, -0.377816532241719, -0.457024666869013, -1.12880551077197, -1.12880551077196, -1.20801364539926, -0.220331575027453, -0.220331575027453, -0.29953970965475, 0.183702853067903, 0.183702853067903, 0.104494718440605, 1.12384497625067, 1.12384497625067, 1.04463684162337, 1.24707949620404, 1.24707949620404, 1.16787136157674, -0.610672320738653, -0.610672320738653, -0.68988045536595, 0.815513912349393, 0.815513912349393, 0.736305777722095, 1.07768856337481, 1.07768856337481, 0.99848042874751, -0.116268012873417, -0.116268012873417, -0.195476147500715, -1.75570733327889, -1.75570733327889, -1.83491546790618, 0.38821352691705, 0.388213526917049, 0.309005392289752, 2.38726637449642, 2.38726637449642, 2.30805823986912, 0.0978089234405024, 0.0978089234405022, 0.0186007888132048, 0.480311137245768, 0.480311137245767, 0.40110300261847, -1.36360112479173, -1.36360112479173, -1.44280925941902, 1.93535965542202, 1.93535965542202, 1.85615152079472, 0.394010340671377, 0.394010340671377, 0.314802206044079, 1.61374775950545, 1.61374775950545, 1.53453962487815, -0.964178039762375, -0.964178039762375, -1.04338617438967, -0.798757765014893, -0.798757765014893, -0.87796589964219, -1.0944257408576, -1.0944257408576, -1.1736338754849, 0.377586753964714, 0.377586753964714, 0.298378619337417, 1.37498679426785, 1.37498679426785, 1.29577865964055, 1.68915587438649, 1.68915587438649, 1.6099477397592, 0.992596467936866, 0.992596467936866, 0.913388333309568, -0.323261319416317, -0.323261319416317, -0.402469454043614, -1.53070167383635, -1.53070167383635, -1.60990980846365, 0.985012371873182, 0.985012371873182, 0.905804237245884, -0.83124291903249, -0.83124291903249, -0.910451053659788, 0.875900958465542, 0.875900958465542, 0.796692823838244, -0.599874960211679, -0.59987496021168, -0.679083094838977, -1.21249941889568, -1.21249941889568, -1.29170755352297, 0.10152732719712, 0.10152732719712, 0.0223191925698222, 0.273641473500582, 0.273641473500581, 0.194433338873284, 0.132099054317715, 0.132099054317715, 0.0528909196904173, -0.834302902018013, -0.834302902018014, -0.913511036645311, 0.719369062657609, 0.719369062657609, 0.640160928030311, -1.14019031831383, -1.14019031831383, -1.21939845294113, -0.986131847575652, -0.986131847575652, -1.06533998220295, 1.121130179697, 1.121130179697, 1.0419220450697, 0.901558128109497, 0.901558128109497, 0.8223499934822, -0.786141113615663, -0.786141113615663, -0.86534924824296, -0.713749729008483, -0.713749729008484, -0.792957863635781, -1.21024198127622, -1.21024198127622, -1.28945011590352, -1.48456568414046, -1.48456568414046, -1.56377381876776, 1.07705092477044, 1.07705092477044, 0.99784279014314, -1.51414471003321, -1.51414471003321, -1.59335284466051, 0.197021223835606, 0.197021223835606, 0.117813089208309, -0.992651143019504, -0.992651143019504, -1.0718592776468, -0.214255998107591, -0.214255998107591, -0.293464132734889, 0.855083280875347, 0.855083280875347, 0.77587514624805, 0.424765963693628, 0.424765963693628, 0.34555782906633, 0.364243987733107, 0.364243987733107, 0.285035853105809, 0.148975237666157, 0.148975237666156, 0.069767103038859, -0.0574168068381831, -0.0574168068381833, -0.136624941465481, -0.46975623711864, -0.469756237118641, -0.548964371745938, 1.07464366058924, 1.07464366058924, 0.995435525961942, 0.220197215402141, 0.22019721540214, 0.140989080774843, 2.43308733556931, 2.43308733556931, 2.35387920094201, -0.792463299943419, -0.792463299943419, 0.398667166152911, 0.398667166152911, -0.507624730755423, -0.507624730755423, -1.14063678811883, -1.14063678811883, -0.610719518834707, -0.610719518834707, 0.0372742888124954, 0.0372742888124952, 1.60469817459311, 1.60469817459311, -0.335089450474223, -0.335089450474223, 0.398797186950103, 0.398797186950103, -1.47882967397224, -1.47882967397224, -0.667444462142149, -0.66744446214215, -0.649446871595376, -0.649446871595376, -0.279713473009783, -0.279713473009783, 0.109041394826028, 0.109041394826028, -1.47272080463623, -1.47272080463623, -0.463549540361751, -0.463549540361751, -1.00365185771742, -1.00365185771742, -0.808089317383245, -0.808089317383245, 0.145106160657612, 0.145106160657612, 0.190373516579835, 0.190373516579835, -1.11324014885282, -1.11324014885282, 0.0373498895331293, 0.0373498895331291, 0.934861192278438, 0.934861192278438, 0.526171571037055, 0.526171571037054, -0.127064672854489, -0.127064672854489, 0.107735669014991, 0.107735669014991, 1.63023634780781, 1.63023634780781, -1.01842798000048, -1.01842798000048, 0.0915540560676065, 0.0915540560676063, -0.69105660373921, -0.69105660373921, -0.510325739757003, -0.510325739757004, -0.758316424407092, -0.758316424407092, 0.66850966666813, 0.66850966666813, 0.207547505355721, 0.207547505355721, -0.957302855842871, -0.957302855842871, 0.871306376044677, 0.871306376044677, 0.854052678949774, 0.854052678949774, -1.02517751500326, -1.02517751500326, -0.14387122685017, -0.14387122685017, 0.043993557372757, 0.0439935573727568, -1.13877102137595, -1.13877102137595, 1.36106121128242, 1.36106121128242, 0.0755102782632799, 0.0755102782632797, -1.39505728407859, -1.39505728407859, -1.55223678517323, -1.55223678517323, -0.783810528384146, -0.783810528384146, -1.23550391017333, -1.23550391017333, -1.34099290537528, -1.34099290537528, 0.282522679370366, 0.282522679370366, 1.05047246454719, 1.05047246454719, 0.406048469121015, 0.406048469121015, 0.239493257040229, 0.239493257040228, 0.534396153202169, 0.534396153202169, 2.04605670576315, 2.04605670576315, -0.0259943875448687, -0.0259943875448689, 1.56185162485783, 1.56185162485783, -1.89056227250461, -1.89056227250461, -0.819059954351738, -0.819059954351738, -0.481442518835015, -0.481442518835015, -0.0511676754622087, -0.0511676754622089, 2.24057972203455, 2.24057972203455, 1.5234804097995, 1.5234804097995, -0.344361395338917, -0.344361395338917, -0.041553596863046, -0.0415535968630462, -0.025579389721469, -0.0255793897214692, -0.0639754794004533, -0.0639754794004535, 1.29091591700363, 1.29091591700363, 0.678498611351185, 0.678498611351185, 1.04860191122785, 1.04860191122785, -0.768540785317964, -0.768540785317964, 1.30809002082778, 1.30809002082778, -0.47706971830725, -0.47706971830725, -1.38225666633996, -1.38225666633996, -0.898631124236369, -0.89863112423637, 0.673024870752781, 0.673024870752781, -0.410390025474452, -0.410390025474452, 1.85569424316007, 1.85569424316007, -1.42890995686216, -1.42890995686216, 2.09388845185187, 2.09388845185187, -0.769321140423713, -0.769321140423714, 0.928218267300235, 0.928218267300184, 0.865629305624083, -0.901905120181538, -0.901905120181534, -0.964494081857647, -0.949986114091021, -0.94998611409102, -1.01257507576713, -0.971369641027934, -0.971369641027932, -1.03395860270405, 0.848742814011857, 0.848742814011858, 0.786153852335745, -1.02764886257788, -1.02764886257788, -1.09023782425399, -1.06643981685835, -1.06643981685835, -1.12902877853447, 0.865061239254727, 0.865061239254728, 0.802472277578616, -1.1557963368333, -1.1557963368333, -1.21838529850942, 1.05148830018635, 1.05148830018635, 0.988899338510239, 1.13825564581723, 1.13825564581723, 1.07566668414112, 1.02478860866219, 1.0247886086622, 0.962199646986083, 0.918988712806694, 0.918988712806695, 0.856399751130582, 0.903045784372422, 0.903045784372423, 0.84045682269631, -0.987067638013804, -0.987067638013803, -1.04965659968992, -1.02659105090308, -1.02659105090308, -1.08918001257919, -1.06407609823243, -1.06407609823243, -1.12666505990854, 0.887369320824584, 0.887369320824585, 0.824780359148473, -1.18416727619675, -1.18416727619675, -1.24675623787286, -1.0477305224531, -1.04773052245309, -1.11031948412921, -1.0564853924716, -1.0564853924716, -1.11907435414771, -0.903724669915239, -0.903724669915238, -0.96631363159135, -0.981630948800652, -0.981630948800651, -1.04421991047676, 0.835451130291063, 0.835451130291063, 0.772862168614951, 0.818823727970098, 0.818823727970099, 0.756234766293987, 0.99280163428372, 0.992801634283721, 0.930212672607609, -0.944538556138783, -0.944538556138782, -1.00712751781489, -1.01774725234731, -1.01774725234731, -1.08033621402342, 0.993203022658554, 0.993203022658555, 0.930614060982442, -1.05476611530688, -1.05476611530688, -1.11735507698299, 0.998977745517508, 0.998977745517509, 0.936388783841397, 0.939970712255066, 0.939970712255067, 0.877381750578954, 1.1095063604548, 1.10950636045481, 1.04691739877869, 0.902848987809152, 0.902848987809153, 0.84026002613304, -1.11324213498986, -1.11324213498985, -1.17583109666597, -0.96863850936219, -0.968638509362189, -1.0312274710383, 0.952377813877598, 0.952377813877599, 0.889788852201486, 0.870149706574013, 0.870149706574014, 0.807560744897902, -1.03841507050665, -1.03841507050665, -1.10100403218276, 0.960413362636251, 0.960413362636252, 0.89782440096014, -1.15809548489647, -1.15809548489647, -1.22068444657258, 0.860507348107022, 0.860507348107023, 0.79791838643091, -1.05715312889772, -1.05715312889772, -1.11974209057384, 1.0831100271553, 1.0831100271553, 1.02052106547919, 1.10938688554181, 1.10938688554181, 1.0467979238657, 0.986792979394893, 0.986792979394894, 0.924204017718781, 0.85121938974584, 0.851219389745841, 0.788630428069729, 1.12547094109423, 1.12547094109423, 1.06288197941812, 1.03490746358836, 1.03490746358836, 0.972318501912247, -1.04622358312283, -1.04622358312283, -1.10881254479895, -0.950307664072134, -0.950307664072133, -1.01289662574825, 1.00007952135283, 1.00007952135283, 0.937490559676719, 0.885741579108469, 0.88574157910847, 0.823152617432357, 0.88894470540968, 0.88894470540968, 0.826355743733568, -0.96953168156765, -0.969531681567649, -1.03212064324376, 0.911261108003043, 0.911261108003044, 0.848672146326931, 1.07019666868025, 1.07019666868025, 1.00760770700414, -1.15563518531698, -1.15563518531698, -1.21822414699309, -1.1104135969911, -1.1104135969911, -1.17300255866722, 0.916563637894152, 0.916563637894153, 0.85397467621804, 0.950163452437635, 0.950163452437636, 1.02423534968067, 1.02423534968067, -0.934781120389717, -0.934781120389716, 0.968590538461504, 0.968590538461505, 1.07765715205019, 1.0776571520502, 0.906249580633761, 0.906249580633762, 0.960406144141665, 0.960406144141666, -1.08102504356151, -1.08102504356151, 0.887115976928059, 0.88711597692806, -0.883380087159851, -0.88338008715985, 1.08065932035285, 1.08065932035285, -0.927275181890372, -0.927275181890371, 1.06013865311795, 1.06013865311795, -0.967418182457954, -0.967418182457953, -0.883703399142486, -0.883703399142485, 1.06986817918019, 1.06986817918019, 0.961340609382444, 0.961340609382446, 0.950990459597437, 0.950990459597438, 0.900542577527299, 0.9005425775273, 0.898146802173974, 0.898146802173975, -0.902728917147178, -0.902728917147177, 0.906245579464717, 0.906245579464718, -1.14823719651062, -1.14823719651062, -0.989494802020439, -0.989494802020438, -0.95492226600347, -0.954922266003468, -0.967349076903795, -0.967349076903794, 0.821942044618619, 0.82194204461862, -1.04485934371747, -1.04485934371747, 0.903376823302905, 0.903376823302906, -1.06218547771961, -1.06218547771961, -1.07175066085639, -1.07175066085638, 0.948356228641671, 0.948356228641672, 1.00995393211511, 1.00995393211511, 1.03435036001307, 1.03435036001307, -0.910981900243858, -0.910981900243857, -1.14487355710169, -1.14487355710169, -1.14396040497669, -1.14396040497669, -0.907389633096397, -0.907389633096396, -0.954032778932337, -0.954032778932336, -0.963975524883135, -0.963975524883134, 1.1056042841347, 1.1056042841347, 0.973300633337403, 0.973300633337404, -1.10275603911339, -1.10275603911339, -0.887813741896415, -0.887813741896414, 0.990374473226015, 0.990374473226016, -0.920163983748597, -0.920163983748596, 0.973611382030312, 0.973611382030313, -1.02778759118596, -1.02778759118596, -1.11371217291668, -1.11371217291668, -1.01724343307714, -1.01724343307713, 1.02384469413284, 1.02384469413285, -1.11143484022547, -1.11143484022547, 0.879939400018172, 0.879939400018173, -1.20704723234541, -1.20704723234541, 1.04671056748668, 1.04671056748668, -1.04430818124978, -1.04430818124978, 1.14539284508785, 1.14539284508785, -0.918298407457879, -0.918298407457878, 0.933702673879424, 0.933702673879425, -1.09605160689812, -1.09605160689812, -1.0802298739066, -1.0802298739066, -1.17938987563448, -1.17938987563448, 1.06356014518004, 1.06356014518004, 0.910421547425474, 0.910421547425475, 0.909576112321545, 0.909576112321546, -0.958261262321214, -0.958261262321213, -1.1670813970731, -1.1670813970731, 1.00942526709835, 1.00942526709835, 0.989837545528036, 0.989837545528038, -1.05808462648328, -1.05808462648328, -1.1679903367233, -1.1679903367233, 0.933471243359218, 0.933471243359219, -0.888491214743256, -0.888491214743254, 0.955782385807506, 0.955782385807507, -0.997267014663429, -0.997267014663428, 1.0670547112193, 1.0670547112193, 0.8100096828119, 0.810009682811901, -0.886022088784659, -0.886022088784658, -1.07246623667859, -1.07246623667859, 0.948938653368405, 0.948938653368406, 0.822922780507102, -1.1501950067864, 0.761524154870805, -0.884042163308672, 1.20514137617857, -0.945440788944957, -0.8764883205467, 1.21269521894054, -0.937886946182985, -0.873128826762482, 1.21605471272476, -0.93452745239877, 0.835408900879507, -1.137708886414, 0.774010275243219, -0.864286988110919, 1.22489655137632, -0.925685613747206, 0.79384135565294, -1.17927643164056, 0.732442730016652, 0.832845168136384, -1.14027261915712, 0.771446542500097, 0.807879857080727, -1.16523793021278, 0.74648123144444, -0.848477786323998, 1.24070575316324, -0.909876411960286, -0.862109511304625, 1.22707402818261, -0.923508136940912, -0.844283087854447, 1.24490045163279, -0.905681713490735, -0.827661223110346, 1.26152231637689, -0.889059848746634, 0.826877544385839, -1.14624024290766, 0.765478918749551, -0.870662567409932, 1.21852097207731, -0.93206119304622, 0.78758085045516, -1.18553693683834, 0.726182224818872, -0.858564027996872, 1.23061951149037, -0.919962653633159, 0.829340420692578, -1.14377736660092, 0.76794179505629, 0.812337119660705, -1.1607806676328, 0.750938494024418, 0.79090200152081, -1.18221578577269, 0.729503375884522, 0.792277449616699, -1.1808403376768, 0.730878823980411, -0.883756299987876, 1.20542723949936, -0.945154925624164, -0.87151670731268, 1.21766683217456, -0.932915332948967, 0.837497112472174, -1.13562067482133, 0.776098486835886, 0.840109387561766, -1.13300839973174, 0.778710761925479, -0.839257722211194, 1.24992581727604, -0.900656347847481, -0.87734416800038, 1.21183937148686, -0.938742793636667, 0.786191431096763, -1.18692635619674, 0.724792805460476, -0.839320782984764, 1.24986275650247, -0.900719408621052, 0.792007339780971, -1.18111044751253, 0.730608714144683, -0.840228030213318, 1.24895550927392, -0.901626655849606, 0.821076393524696, -1.15204139376881, 0.759677767888408, -0.857592808061018, 1.23159073142622, -0.918991433697306, 0.826908462430042, -1.14620932486346, 0.765509836793755, 0.801194309976777, -1.17192347731673, 0.739795684340489, -0.873557905645587, 1.21562563384165, -0.934956531281875, 0.819127155641534, -1.15399063165197, 0.757728530005247, 0.832045736200728, -1.14107205109277, 0.770647110564441, 0.789438482289227, -1.18367930500428, 0.72803985665294, 0.817864717682301, -1.1552530696112, 0.756466092046013, 0.808241068477237, -1.16487671881626, 0.74684244284095, 0.833560614613004, -1.1395571726805, 0.772161988976716, 0.792382355434139, -1.18073543185936, 0.730983729797852, -0.853445769178827, 1.23573777030841, -0.914844394815115, -0.857574037760461, 1.23160950172678, -0.918972663396749, 0.813720305079454, -1.15939748221405, 0.752321679443167, 0.835019814420149, -1.13809797287335, 0.773621188783862, -0.860100949472114, 1.22908259001512, -0.921499575108402, -0.845872827018062, 1.24331071246918, -0.90727145265435, 0.790665251365976, -1.18245253592753, 0.729266625729689, -0.876437802913846, 1.21274573657339, -0.937836428550134, -0.840401126498196, 1.24878241298904, -0.901799752134484, 0.829596149702751, -1.14352163759075, 0.768197524066464, 0.829092917334643, -1.14402486995886, 0.767694291698356, -0.873417582373317, 1.21576595711392, -0.934816208009604, 0.825586862602903, -1.1475309246906, 0.764188236966615, -0.851416994989318, 1.23776654449792, -0.912815620625605, 0.807854539109608, -1.16526324818389, 0.74645591347332, 0.800749927913273, -1.17236785938023, 0.739351302276985, -0.827280227771318, 1.26190331171592, -0.888678853407606, 0.819475046497683, -1.15364274079582, -0.844196167202163, 1.24498737228508, -0.878877125816253, 1.21030641367099, 0.816580029172382, -1.15653775812112, -0.852589086365194, 1.23659445312204, 0.826374206762554, -1.14674358053095, -0.834168176034367, 1.25501536345287, 0.79613279142007, -1.17698499587343, 0.829380222697558, -1.14373756459594, -0.886952568756393, 1.20223097073085, -0.853060746900039, 1.2361227925872, -0.880056358494176, 1.20912718099306, -0.849836814092931, 1.23934672539431, -0.873749627088995, 1.21543391239824, -0.886901774301426, 1.20228176518581, -0.851365387112054, 1.23781815237518, 0.817719041073879, -1.15539874621962, 0.819345118192542, -1.15377266910096, 0.827270814769233, -1.14584697252427, 0.827647206953348, -1.14547058034015, -0.883912739346303, 1.20527080014094, 0.826374835372726, -1.14674295192078, 0.806692266043804, -1.1664255212497, -0.870281243860378, 1.21890229562686, -0.875712818370806, 1.21347072111643, -0.873760484029496, 1.21542305545774, 0.839619479352104, -1.1334983079414, 0.790450920314975, -1.18266686697853, 0.826825535976161, -1.14629225131734, 0.793172970781972, -1.17994481651153, 0.794675724438452, -1.17844206285505, 0.819758973331977, -1.15335881396153, -0.841952461863805, 1.24723107762343, -0.845785302354621, 1.24339823713262, -0.882616141011691, 1.20656739847555, 0.8061638160028, -1.1669539712907, 0.806020353752767, -1.16709743354073, -0.883180509985469, 1.20600302950177, -0.875852562684054, 1.21333097680319, -0.874290491407491, 1.21489304807975, -0.856979766013203, 1.23220377347404, -0.836193985735054, 1.25298955375218, 0.799546874826271, -1.17357091246723, -0.886256012216736, 1.2029275272705, 0.813157628665065, -1.15996015862844, -0.881173574846094, 1.20800996464114, 0.81579122137605, -1.15732656591745, 0.787768834862726, -1.18534895243078, 0.801268156049886, -1.17184963124362, -0.865921750039247, 1.22326178944799, -0.844134792626839, 1.2450487468604, 0.800910371992874, -1.17220741530063, 0.830507710487194, -1.14261007680631, 0.815931712390488, -1.15718607490301, -0.847727172856231, 1.24145636663101, -0.861669698751095, 1.22751384073614, -0.863230812606188, 1.22595272688105, -0.881466669243999, 1.20771687024324, 0.82206114388998, -1.15105664340352, 0.798493564096925, -1.17462422319658, -0.856026162792076, 1.23315737669516, 0.811586558373925, -1.16153122891958, -0.850374353169121, 1.23880918631812, 0.825718763133163, -1.14739902416034, 0.825851586590444, -1.14726620070306, -0.875188239922729, 1.21399529956451, 0.809652814827218, -1.16346497246628, -0.841869405086362, 1.24731413440088, -0.83879204422552, 1.25039149526172, 0.792528699877594, -1.18058908741591, 0.809795615269543, -1.16332217202396, 0.822097503158327, -1.15102028413517, -0.886149576743081, 1.20303396274416, 0.818592274830236, -1.15452551246327, -0.869060177749968, 1.22012336173727, -0.850923372651362, 1.23826016683588, 0.841494132464238, -1.13162365482926, -0.886537492793357, 1.20264604669388, -0.857245881647968, 1.23193765783927, 0.819667470547847, -1.15345031674565, 0.803861462573047, -0.0211329139384137, -1.82131769404677, -0.820744084523179, 0.0527793729593485, 2.26118636758273, -0.838810415568063, 0.0347130419146579, 2.24312003653804, -0.846845230265783, 0.0266782272169289, 2.23508522184031, 0.77399873028981, -0.0509956462216396, -1.85118042633002, -0.867992027883424, 0.00553142959928828, 2.21393842422267, 0.873414756866236, 0.0484203803547871, -1.75176439975359, 0.78013034381512, -0.0448640326963297, -1.84504881280471, 0.839839234822992, 0.0148448583115432, -1.78533992179684, -0.905802488338423, -0.0322790308557104, 2.17612796376767, -0.873199843039791, 0.000323614442920782, 2.2087306090663, -0.915834840555904, -0.0423113830731917, 2.16609561155019, -0.95558892606041, -0.082065468577698, 2.12634152604568, 0.79440295573263, -0.0305914207788191, -1.8307762008872, -0.852743719195093, 0.0207797382876192, 2.229186732911, 0.888387845792512, 0.0633934692810632, -1.73679131082732, -0.881679484087365, -0.00815602660465293, 2.20025096801873, 0.788512557946793, -0.0364818185646558, -1.83666659867304, 0.829178914789803, 0.00418453827835407, -1.79600024183003, 0.88044473438655, 0.0554503578751002, -1.74473442223328, 0.87715511062575, 0.0521607341143011, -1.74802404599408, -0.82142777646, 0.0520956810227125, 2.26050267564609, -0.850700894803883, 0.022822562678829, 2.23122955730221, 0.769004408444191, -0.0559899680672583, -1.85617474817564, 0.762756697439936, -0.0622376790715133, -1.86242245917989, -0.927853878043512, -0.0543304205608001, 2.15407657406258, -0.836763507271285, 0.0367599502114275, 2.24516694483481, 0.891710884261762, 0.0667165077503131, -1.73346827235807, -0.927703057216662, -0.0541795997339494, 2.15422739488943, 0.87780112535818, 0.0528067488467312, -1.74737803126165, -0.925533217403083, -0.0520097599203712, 2.15639723470301, 0.80827741873115, -0.0167169577802996, -1.81690173788868, -0.884002325776185, -0.010478868293473, 2.19792812632991, 0.794329009843175, -0.0306653666682737, -1.83085014677665, 0.855828885521429, 0.03083450900998, -1.7693502710984, -0.845819013359934, 0.0277044441227782, 2.23611143874616, 0.812939360737585, -0.0120550157738644, -1.81223979588224, 0.782042324571453, -0.0429520519399964, -1.84313683204838, 0.883944995612685, 0.0589506191012355, -1.74123416100714, 0.815958701067215, -0.00903567544423475, -1.80922045555261, 0.838975334835647, 0.0139809583241981, -1.78620382178418, 0.778419228916563, -0.0465751475948864, -1.84675992770327, 0.876904210085971, 0.0519098335745214, -1.74827494653386, -0.893920691786934, -0.0203972343042215, 2.18800976031916, -0.884047218220251, -0.0105237607375388, 2.19788323388584, 0.825870785873342, 0.000876409361892394, -1.79930837074649, 0.774929298346527, -0.0500650781649221, -1.8502498582733, -0.878003668606899, -0.00448021112418706, 2.20392678349919, -0.91203270237146, -0.0385092448887476, 2.16989774973463, 0.88101096362998, 0.0560165871185307, -1.74416819298985, -0.838931237288528, 0.0345922201941842, 2.24299921481756, -0.925119227479841, -0.0515957699971293, 2.15681122462625, 0.787900937464198, -0.0370934390472516, -1.83727821915563, 0.789104505348933, -0.0358898711625158, -1.8360746512709, -0.846154620913599, 0.027368836569113, 2.23577583119249, 0.797489846087465, -0.027504530423984, -1.82768931053236, -0.898772858727331, -0.0252494012446189, 2.18315759337876, 0.839899787161985, 0.0149054106505357, -1.78527936945784, 0.856891702649422, 0.031897326137973, -1.76828745397041, -0.956500142793172, -0.0829766853104602, 2.12543030931292, 0.812107319143306, -0.0128870573681433, -0.916042726439721, -0.0425192689570085, -0.83309717157278, 0.0404262859099321, 0.81903125746544, -0.00596311904600869, -0.895969597992568, -0.0224461405098554, 0.795606775353457, -0.0293876011579923, -0.940026414459111, -0.066502956976399, 0.867934389000357, 0.0429400124889073, 0.788417364517319, -0.0365770119941301, -0.813783342825435, 0.059740114657277, -0.89484153964773, -0.0213180821650183, -0.830276831169969, 0.0432466263127435, -0.902552136650396, -0.0290286791676835, -0.845360478125072, 0.0281629793576403, -0.813904826614227, 0.0596186308684849, -0.898896287957265, -0.0253728304745528, 0.816307112056978, -0.00868726445447064, 0.812418065322002, -0.0125763111894468, 0.793462381092629, -0.0315319954188206, 0.792562173606831, -0.0324322029046178, -0.821053624478443, 0.0524698330042693, 0.795605271922712, -0.0293891045887375, 0.842679565697599, 0.0176851891861494, -0.85365572090051, 0.0198677365822015, -0.840665164134714, 0.0328582933479979, -0.845334511860298, 0.028188945622414, 0.763928398278326, -0.0610659782331235, 0.881523573680594, 0.0565291971691446, 0.794527342905617, -0.0304670336058324, 0.875013315735499, 0.0500189392240496, 0.871419218546546, 0.0464248420350975, 0.81142825865152, -0.0135661178599291, -0.921408938669288, -0.047885481186576, -0.912242032853194, -0.0387185753704814, -0.824154665297431, 0.0493687921852808, 0.843943446040652, 0.0189490695292026, 0.844286561006527, 0.0192921844950777, -0.822804878568622, 0.0507185789140901, -0.840330941262423, 0.0331925162202894, -0.844066906874501, 0.0294565506082111, -0.885468522641695, -0.0119450651589828, -0.935181337610223, -0.0616578801275106, 0.859769013710692, 0.0347746371992429, -0.81544927914862, 0.058074178334092, 0.827216524551485, 0.00222214804003598, -0.827604813615682, 0.0459186438670302, 0.820917828741577, -0.00407654776987265, 0.887938248329957, 0.0629438718185076, 0.855652269771647, 0.0306578932601974, -0.86408220991301, 0.00944124756970272, -0.916189514429685, -0.042666056946973, 0.856507972679448, 0.0315135961679984, 0.785720781030177, -0.0392735954812725, 0.820581820003289, -0.00441255650816064, -0.90759771122333, -0.0340742537406174, -0.874251731388556, -0.000728273905844428, -0.870518055616724, 0.00300540186598766, -0.826903827298288, 0.0466196301844242, 0.805922216662982, -0.0190721598484674, 0.862288189834543, 0.0372938133230942, -0.887749230887955, -0.0142257734052433, 0.830974012874789, 0.00597963636334002, -0.901266518296147, -0.0277430608134348, 0.797174382988783, -0.0278199935226666, 0.796856712549333, -0.0281376639621159, -0.841919784888747, 0.031603672593965, 0.835598897476072, 0.0106045209646222, -0.921607583423233, -0.0480841259405206, -0.928967628079688, -0.0554441705969753, 0.876554201852371, 0.0515598253409216, 0.835257365338632, 0.0102629888271827, 0.805835257137982, -0.0191591193734672, -0.815703838127743, 0.0578196193549694, 0.814218621388206, -0.0107757551232427, -0.856576113245609, 0.016947344237103, -0.899953442550635, -0.0264299850679227, 0.759444838746444, -0.0655495377650052, -0.814776069308258, 0.0587473881744539, -0.884832060736767, -0.0113086032540548, 0.811647103501974, -0.0133472730094755), R = c(-1.00147384015129, 0, 0, 0, 0, 0, 0, 0, -0.521355499137583, -0.500312239830598, 0, 0, 0, 0, 0, 0, -0.412371581238766, 0.00520237329552464, 0.492850855057777, 0, 0, 0, 0, 0, -0.176730677673757, -0.0104047465910492, -0.147761901765143, 0.351874380491925, 0, 0, 0, 0, -0.0148145536477168, -0.0628921007447697, -0.0117315667981618, 0.0279370916994833, 1.00236007528132, 0, 0, 0, -0.480118341013706, 0.0345264174379645, 0.00491668361530068, -0.0117083969584963, -0.0263704470162966, -0.498260577419346, 0, 0, -0.212076813208509, -0.203516843320922, 0.25564265339504, -0.00518302997367062, 0.00222305092368007, 0.00332949514226805, -0.246165884693855, 0, -0.0972018727205666, -0.0932785531887563, -0.0803448339241554, 0.191330027057476, -0.00444610184736017, -0.00665899028453589, 0.0732625048297967, -0.175220044568803), Sigma_init = list(c(0.135928026518976, 0.0348523498539457, 0.00728419213566439, 0.0348523498539457, 0.0345033646543241, 0.00223741352686603, 0.00728419213566439, 0.00223741352686603, 0.012904582693086))), pars = c("beta", "Sigma"), chains = 1, warmup = 200, thin = 2, iter = 204, init = list( list(theta = c(-5.95025313048012e-05, -0.745820423193811, -0.00612121696522474, 0.00358076868728718, 0.552831864322151, -0.281246666814181, -0.00509794025644653, -0.00632342582509862 ), sigma = list(Placebo = c(0.135928026518976, 0.0348523498539457, 0.00728419213566439, 0.0348523498539457, 0.0345033646543241, 0.00223741352686603, 0.00728419213566439, 0.00223741352686603, 0.012904582693086), TRT = c(0.135928026518976, 0.0348523498539457, 0.00728419213566439, 0.0348523498539457, 0.0345033646543241, 0.00223741352686603, 0.00728419213566439, 0.00223741352686603, 0.012904582693086)))), refresh = 0, seed = 2053082391L)
11: do.call(rstan::sampling, sampling_args)
12: doWithOneRestart(return(expr), restart)
13: withOneRestart(expr, restarts[[1L]])
14: withRestarts(expr, muffleStop = function() list())
15: withCallingHandlers(withRestarts(expr, muffleStop = function() list()), message = function(m) { env$message <- c(env$message, m$message) invokeRestart("muffleMessage") }, warning = function(w) { env$warning <- c(env$warning, w$message) invokeRestart("muffleWarning") }, error = function(e) { env$error <- c(env$error, e$message) invokeRestart("muffleStop") })
16: record({ do.call(rstan::sampling, sampling_args)})
17: fit_mcmc(designmat = model_df_scaled[, -1, drop = FALSE], outcome = model_df_scaled[, 1, drop = TRUE], group = data2[[vars$group]], visit = data2[[vars$visit]], subjid = data2[[vars$subjid]], method = method, quiet = quiet)
18: draws.bayes(d$dat, d$dat_ice, d$vars, meth, quiet = TRUE)
19: draws(d$dat, d$dat_ice, d$vars, meth, quiet = TRUE)
20: withCallingHandlers(expr, warning = function(w) if (inherits(w, classes)) tryInvokeRestart("muffleWarning"))
21: suppressWarnings({ draws(d$dat, d$dat_ice, d$vars, meth, quiet = TRUE)})
22: eval(code, test_env)
23: eval(code, test_env)
24: withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error)
25: doTryCatch(return(expr), name, parentenv, handler)
26: tryCatchOne(expr, names, parentenv, handlers[[1L]])
27: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
28: doTryCatch(return(expr), name, parentenv, handler)
29: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]])
30: tryCatchList(expr, classes, parentenv, handlers)
31: tryCatch(withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error), error = handle_fatal, skip = function(e) { })
32: test_code(desc, code, env = parent.frame(), default_reporter = local_interactive_reporter())
33: test_that("bayes", { set.seed(40123) d <- get_data(140) meth <- method_bayes(n_samples = 2, burn_in = 200, burn_between = 2) dobj <- suppressWarnings({ draws(d$dat, d$dat_ice, d$vars, meth, quiet = TRUE) }) standard_checks(dobj, d, meth) expect_length(dobj$samples, 2) expect_true(all(vapply(dobj$samples, function(x) all(x$ids == levels(d$dat$id)), logical(1))))})
34: eval(code, test_env)
35: eval(code, test_env)
36: withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error)
37: doTryCatch(return(expr), name, parentenv, handler)
38: tryCatchOne(expr, names, parentenv, handlers[[1L]])
39: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
40: doTryCatch(return(expr), name, parentenv, handler)
41: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]])
42: tryCatchList(expr, classes, parentenv, handlers)
43: tryCatch(withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error), error = handle_fatal, skip = function(e) { })
44: test_code(test = NULL, code = exprs, env = env, default_reporter = StopReporter$new())
45: source_file(path, env = env(env), desc = desc, error_call = error_call)
46: FUN(X[[i]], ...)
47: lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call)
48: doTryCatch(return(expr), name, parentenv, handler)
49: tryCatchOne(expr, names, parentenv, handlers[[1L]])
50: tryCatchList(expr, classes, parentenv, handlers)
51: tryCatch(code, testthat_abort_reporter = function(cnd) { cat(conditionMessage(cnd), "\n") NULL})
52: with_reporter(reporters$multi, lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call))
53: test_files_serial(test_dir = test_dir, test_package = test_package, test_paths = test_paths, load_helpers = load_helpers, reporter = reporter, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, desc = desc, load_package = load_package, error_call = error_call)
54: test_files(test_dir = path, test_paths = test_paths, test_package = package, reporter = reporter, load_helpers = load_helpers, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, load_package = load_package, parallel = parallel)
55: test_dir("testthat", package = package, reporter = reporter, ..., load_package = "installed")
56: test_check("rbmi")
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-release-macos-arm64
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [10s/17s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(rbmi)
>
> test_check("rbmi")
*** caught segfault ***
address 0x0, cause 'memory not mapped'
Traceback:
1: Module(module, mustStart = TRUE)
2: .getModulePointer(x)
3: new("Module", .xData = <environment>)$stan_fit4modelaa9c6a27673f_rbmi_mmrm
4: new("Module", .xData = <environment>)$stan_fit4modelaa9c6a27673f_rbmi_mmrm
5: eval(call("$", mod, paste("stan_fit4", model_cppname, sep = "")))
6: eval(call("$", mod, paste("stan_fit4", model_cppname, sep = "")))
7: object@mk_cppmodule(object)
8: .local(object, ...)
9: (new("nonstandardGenericFunction", .Data = function (object, ...) { standardGeneric("sampling")}, generic = "sampling", package = "rstan", group = list(), valueClass = character(0), signature = "object", default = NULL, skeleton = (function (object, ...) stop(gettextf("invalid call in method dispatch to '%s' (no default method)", "sampling"), domain = NA))(object, ...)))(object = new("stanmodel", model_name = "rbmi_mmrm", model_code = "functions {\n int integer_division(int a, int b) {\n // perform a/b ensuring return value is also an int\n int i = 0;\n while(b*(i+1) <= a) {\n i = i + 1;\n }\n return(i);\n }\n array[] vector to_vector_of_arrays(vector vec, int length_array) {\n // treansform a vector into a vector of arrays. Example: vec = [1,2,3,4,5,6] and\n // length_array = 2, then output = [1,2; 3,4; 5,6]\n array[integer_division(num_elements(vec),length_array)] vector[length_array] res;\n int j = 1;\n int i = 1;\n while(j <= num_elements(vec)) {\n res[i,] = vec[j:(j+length_array-1)];\n i = i+1;\n j = j + length_array;\n }\n return(res);\n }\n}\ndata {\n int<lower=1> N; // number of observations\n int<lower=1> P; // number of covariates (number of columns of design matrix)\n int<lower=1> G; // number of Sigma Groups\n int<lower=1> n_visit; // number of visits\n int<lower=1> n_pat; // number of pat groups (# missingness patterns * groups)\n array[n_pat] int<lower=1> pat_G; // Index for which Sigma the pat group should use\n array[n_pat] int<lower=1> pat_n_pt; // number of patients in each pat group\n array[n_pat] int<lower=1> pat_n_visit; // number of non-missing visits in each pat group\n array[n_pat, n_visit] int<lower=1> pat_sigma_index; // rows/cols from sigma to subset on for the pat group\n vector[N] y; // outcome variable\n matrix[N,P] Q; // design matrix (After QR decomp)\n matrix[P,P] R; // R matrix (from QR decomp)\n array[G] matrix[n_visit, n_visit] Sigma_init; // covariance matrix estimated from MMRM\n}\ntransformed data {\n matrix[P, P] R_inverse = inverse(R);\n}\nparameters {\n vector[P] theta; // coefficients of linear model on covariates\n array[G] cov_matrix[n_visit] Sigma; // covariance matrix(s)\n}\nmodel {\n int data_start_row = 1;\n vector[N] mu = Q * theta;\n for(g in 1:G){\n Sigma[g] ~ inv_wishart(n_visit+2, Sigma_init[g]);\n }\n for(i in 1:n_pat) {\n // Index + size variables for current pat group\n int nvis = pat_n_visit[i]; // number of visits\n int npt = pat_n_pt[i]; // number of patients\n int g = pat_G[i]; // Sigma index\n // Get required/reduced Sigma for current pat group\n array[nvis] int sig_index = pat_sigma_index[i, 1:nvis];\n matrix[nvis,nvis] sig = Sigma[g][sig_index, sig_index];\n // Derive data indcies for current pat group\n int data_stop_row = data_start_row + ((nvis * npt) -1);\n // Extract required data for the current pat group\n array[npt] vector[nvis] y_obs = to_vector_of_arrays(y[data_start_row:data_stop_row], nvis);\n array[npt] vector[nvis] mu_obs = to_vector_of_arrays(mu[data_start_row:data_stop_row], nvis);\n y_obs ~ multi_normal(mu_obs, sig);\n // Update data index for next pat group\n data_start_row = data_stop_row + 1;\n }\n}\ngenerated quantities {\n vector[P] beta = R_inverse * theta;\n}", model_cpp = list(model_cppname = "modelaa9c6a27673f_rbmi_mmrm", model_cppcode = "#ifndef MODELS_HPP\n#define MODELS_HPP\n#define STAN__SERVICES__COMMAND_HPP\n#include <rstan/rstaninc.hpp>\n#ifndef USE_STANC3\n#define USE_STANC3\n#endif\n// Code generated by stanc v2.32.2\n#include <stan/model/model_header.hpp>\nnamespace modelaa9c6a27673f_rbmi_mmrm_namespace {\nusing stan::model::model_base_crtp;\nusing namespace stan::math;\nstan::math::profile_map profiles__;\nstatic constexpr std::array<const char*, 80> locations_array__ =\n {\" (found before start of program)\",\n \" (in 'rbmi_mmrm', line 43, column 4 to column 20)\",\n \" (in 'rbmi_mmrm', line 44, column 4 to column 39)\",\n \" (in 'rbmi_mmrm', line 71, column 3 to column 38)\",\n \" (in 'rbmi_mmrm', line 47, column 4 to column 27)\",\n \" (in 'rbmi_mmrm', line 48, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 48, column 4 to column 29)\",\n \" (in 'rbmi_mmrm', line 50, column 8 to column 57)\",\n \" (in 'rbmi_mmrm', line 49, column 17 to line 51, column 5)\",\n \" (in 'rbmi_mmrm', line 49, column 4 to line 51, column 5)\",\n \" (in 'rbmi_mmrm', line 54, column 8 to column 34)\",\n \" (in 'rbmi_mmrm', line 55, column 8 to column 30)\",\n \" (in 'rbmi_mmrm', line 56, column 8 to column 25)\",\n \" (in 'rbmi_mmrm', line 58, column 14 to column 18)\",\n \" (in 'rbmi_mmrm', line 58, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 59, column 15 to column 19)\",\n \" (in 'rbmi_mmrm', line 59, column 20 to column 24)\",\n \" (in 'rbmi_mmrm', line 59, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 61, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 63, column 14 to column 17)\",\n \" (in 'rbmi_mmrm', line 63, column 26 to column 30)\",\n \" (in 'rbmi_mmrm', line 63, column 8 to column 99)\",\n \" (in 'rbmi_mmrm', line 64, column 14 to column 17)\",\n \" (in 'rbmi_mmrm', line 64, column 26 to column 30)\",\n \" (in 'rbmi_mmrm', line 64, column 8 to column 101)\",\n \" (in 'rbmi_mmrm', line 65, column 8 to column 42)\",\n \" (in 'rbmi_mmrm', line 67, column 8 to column 43)\",\n \" (in 'rbmi_mmrm', line 52, column 22 to line 68, column 5)\",\n \" (in 'rbmi_mmrm', line 52, column 4 to line 68, column 5)\",\n \" (in 'rbmi_mmrm', line 25, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 26, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 27, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 28, column 4 to column 25)\",\n \" (in 'rbmi_mmrm', line 29, column 4 to column 23)\",\n \" (in 'rbmi_mmrm', line 30, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 30, column 4 to column 36)\",\n \" (in 'rbmi_mmrm', line 31, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 31, column 4 to column 39)\",\n \" (in 'rbmi_mmrm', line 32, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 32, column 4 to column 42)\",\n \" (in 'rbmi_mmrm', line 33, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 33, column 17 to column 24)\",\n \" (in 'rbmi_mmrm', line 33, column 4 to column 55)\",\n \" (in 'rbmi_mmrm', line 34, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 34, column 4 to column 16)\",\n \" (in 'rbmi_mmrm', line 35, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 35, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 35, column 4 to column 18)\",\n \" (in 'rbmi_mmrm', line 36, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 36, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 36, column 4 to column 18)\",\n \" (in 'rbmi_mmrm', line 37, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 37, column 20 to column 27)\",\n \" (in 'rbmi_mmrm', line 37, column 29 to column 36)\",\n \" (in 'rbmi_mmrm', line 37, column 4 to column 49)\",\n \" (in 'rbmi_mmrm', line 40, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 40, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 40, column 3 to column 39)\",\n \" (in 'rbmi_mmrm', line 43, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 44, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 44, column 24 to column 31)\",\n \" (in 'rbmi_mmrm', line 71, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 4, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 6, column 12 to column 22)\",\n \" (in 'rbmi_mmrm', line 5, column 28 to line 7, column 9)\",\n \" (in 'rbmi_mmrm', line 5, column 8 to line 7, column 9)\",\n \" (in 'rbmi_mmrm', line 8, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 2, column 39 to line 9, column 5)\",\n \" (in 'rbmi_mmrm', line 13, column 14 to column 62)\",\n \" (in 'rbmi_mmrm', line 13, column 71 to column 83)\",\n \" (in 'rbmi_mmrm', line 13, column 8 to column 89)\",\n \" (in 'rbmi_mmrm', line 14, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 15, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 17, column 12 to column 48)\",\n \" (in 'rbmi_mmrm', line 18, column 12 to column 20)\",\n \" (in 'rbmi_mmrm', line 19, column 12 to column 33)\",\n \" (in 'rbmi_mmrm', line 16, column 38 to line 20, column 9)\",\n \" (in 'rbmi_mmrm', line 16, column 8 to line 20, column 9)\",\n \" (in 'rbmi_mmrm', line 21, column 8 to column 20)\",\n \" (in 'rbmi_mmrm', line 10, column 69 to line 22, column 5)\"};\nint integer_division(const int& a, const int& b, std::ostream* pstream__);\ntemplate <typename T0__,\n stan::require_all_t<stan::is_col_vector<T0__>,\n stan::is_vt_not_complex<T0__>>* = nullptr>\nstd::vector<\n Eigen::Matrix<stan::promote_args_t<stan::base_type_t<T0__>>,-1,1>>\nto_vector_of_arrays(const T0__& vec_arg__, const int& length_array,\n std::ostream* pstream__);\nint integer_division(const int& a, const int& b, std::ostream* pstream__) {\n using local_scalar_t__ = double;\n int current_statement__ = 0;\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int i = std::numeric_limits<int>::min();\n current_statement__ = 62;\n i = 0;\n current_statement__ = 65;\n while (stan::math::logical_lte((b * (i + 1)), a)) {\n current_statement__ = 63;\n i = (i + 1);\n }\n current_statement__ = 66;\n return i;\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n}\ntemplate <typename T0__,\n stan::require_all_t<stan::is_col_vector<T0__>,\n stan::is_vt_not_complex<T0__>>*>\nstd::vector<\n Eigen::Matrix<stan::promote_args_t<stan::base_type_t<T0__>>,-1,1>>\nto_vector_of_arrays(const T0__& vec_arg__, const int& length_array,\n std::ostream* pstream__) {\n using local_scalar_t__ = stan::promote_args_t<stan::base_type_t<T0__>>;\n int current_statement__ = 0;\n const auto& vec = stan::math::to_ref(vec_arg__);\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n current_statement__ = 68;\n stan::math::validate_non_negative_index(\"res\",\n \"integer_division(num_elements(vec), length_array)\",\n integer_division(stan::math::num_elements(vec), length_array, pstream__));\n current_statement__ = 69;\n stan::math::validate_non_negative_index(\"res\", \"length_array\",\n length_array);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> res =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(integer_division(\n stan::math::num_elements(\n vec),\n length_array,\n pstream__),\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(length_array,\n DUMMY_VAR__));\n int j = std::numeric_limits<int>::min();\n current_statement__ = 71;\n j = 1;\n int i = std::numeric_limits<int>::min();\n current_statement__ = 72;\n i = 1;\n current_statement__ = 77;\n while (stan::math::logical_lte(j, stan::math::num_elements(vec))) {\n current_statement__ = 73;\n stan::model::assign(res,\n stan::model::rvalue(vec, \"vec\",\n stan::model::index_min_max(j, ((j + length_array) - 1))),\n \"assigning variable res\", stan::model::index_uni(i),\n stan::model::index_omni());\n current_statement__ = 74;\n i = (i + 1);\n current_statement__ = 75;\n j = (j + length_array);\n }\n current_statement__ = 78;\n return res;\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n}\nclass modelaa9c6a27673f_rbmi_mmrm final : public model_base_crtp<modelaa9c6a27673f_rbmi_mmrm> {\nprivate:\n int N;\n int P;\n int G;\n int n_visit;\n int n_pat;\n std::vector<int> pat_G;\n std::vector<int> pat_n_pt;\n std::vector<int> pat_n_visit;\n std::vector<std::vector<int>> pat_sigma_index;\n Eigen::Matrix<double,-1,1> y_data__;\n Eigen::Matrix<double,-1,-1> Q_data__;\n Eigen::Matrix<double,-1,-1> R_data__;\n std::vector<Eigen::Matrix<double,-1,-1>> Sigma_init;\n Eigen::Matrix<double,-1,-1> R_inverse_data__;\n Eigen::Map<Eigen::Matrix<double,-1,1>> y{nullptr, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> Q{nullptr, 0, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> R{nullptr, 0, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> R_inverse{nullptr, 0, 0};\npublic:\n ~modelaa9c6a27673f_rbmi_mmrm() {}\n modelaa9c6a27673f_rbmi_mmrm(stan::io::var_context& context__, unsigned int\n random_seed__ = 0, std::ostream*\n pstream__ = nullptr) : model_base_crtp(0) {\n int current_statement__ = 0;\n using local_scalar_t__ = double;\n boost::ecuyer1988 base_rng__ =\n stan::services::util::create_rng(random_seed__, 0);\n // suppress unused var warning\n (void) base_rng__;\n static constexpr const char* function__ =\n \"modelaa9c6a27673f_rbmi_mmrm_namespace::modelaa9c6a27673f_rbmi_mmrm\";\n // suppress unused var warning\n (void) function__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n current_statement__ = 29;\n context__.validate_dims(\"data initialization\", \"N\", \"int\",\n std::vector<size_t>{});\n N = std::numeric_limits<int>::min();\n current_statement__ = 29;\n N = context__.vals_i(\"N\")[(1 - 1)];\n current_statement__ = 29;\n stan::math::check_greater_or_equal(function__, \"N\", N, 1);\n current_statement__ = 30;\n context__.validate_dims(\"data initialization\", \"P\", \"int\",\n std::vector<size_t>{});\n P = std::numeric_limits<int>::min();\n current_statement__ = 30;\n P = context__.vals_i(\"P\")[(1 - 1)];\n current_statement__ = 30;\n stan::math::check_greater_or_equal(function__, \"P\", P, 1);\n current_statement__ = 31;\n context__.validate_dims(\"data initialization\", \"G\", \"int\",\n std::vector<size_t>{});\n G = std::numeric_limits<int>::min();\n current_statement__ = 31;\n G = context__.vals_i(\"G\")[(1 - 1)];\n current_statement__ = 31;\n stan::math::check_greater_or_equal(function__, \"G\", G, 1);\n current_statement__ = 32;\n context__.validate_dims(\"data initialization\", \"n_visit\", \"int\",\n std::vector<size_t>{});\n n_visit = std::numeric_limits<int>::min();\n current_statement__ = 32;\n n_visit = context__.vals_i(\"n_visit\")[(1 - 1)];\n current_statement__ = 32;\n stan::math::check_greater_or_equal(function__, \"n_visit\", n_visit, 1);\n current_statement__ = 33;\n context__.validate_dims(\"data initialization\", \"n_pat\", \"int\",\n std::vector<size_t>{});\n n_pat = std::numeric_limits<int>::min();\n current_statement__ = 33;\n n_pat = context__.vals_i(\"n_pat\")[(1 - 1)];\n current_statement__ = 33;\n stan::math::check_greater_or_equal(function__, \"n_pat\", n_pat, 1);\n current_statement__ = 34;\n stan::math::validate_non_negative_index(\"pat_G\", \"n_pat\", n_pat);\n current_statement__ = 35;\n context__.validate_dims(\"data initialization\", \"pat_G\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_G = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 35;\n pat_G = context__.vals_i(\"pat_G\");\n current_statement__ = 35;\n stan::math::check_greater_or_equal(function__, \"pat_G\", pat_G, 1);\n current_statement__ = 36;\n stan::math::validate_non_negative_index(\"pat_n_pt\", \"n_pat\", n_pat);\n current_statement__ = 37;\n context__.validate_dims(\"data initialization\", \"pat_n_pt\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_n_pt = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 37;\n pat_n_pt = context__.vals_i(\"pat_n_pt\");\n current_statement__ = 37;\n stan::math::check_greater_or_equal(function__, \"pat_n_pt\", pat_n_pt, 1);\n current_statement__ = 38;\n stan::math::validate_non_negative_index(\"pat_n_visit\", \"n_pat\", n_pat);\n current_statement__ = 39;\n context__.validate_dims(\"data initialization\", \"pat_n_visit\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_n_visit = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 39;\n pat_n_visit = context__.vals_i(\"pat_n_visit\");\n current_statement__ = 39;\n stan::math::check_greater_or_equal(function__, \"pat_n_visit\",\n pat_n_visit, 1);\n current_statement__ = 40;\n stan::math::validate_non_negative_index(\"pat_sigma_index\", \"n_pat\",\n n_pat);\n current_statement__ = 41;\n stan::math::validate_non_negative_index(\"pat_sigma_index\", \"n_visit\",\n n_visit);\n current_statement__ = 42;\n context__.validate_dims(\"data initialization\", \"pat_sigma_index\",\n \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat),\n static_cast<size_t>(n_visit)});\n pat_sigma_index = std::vector<std::vector<int>>(n_pat,\n std::vector<int>(n_visit,\n std::numeric_limits<int>::min()));\n {\n std::vector<int> pat_sigma_index_flat__;\n current_statement__ = 42;\n pat_sigma_index_flat__ = context__.vals_i(\"pat_sigma_index\");\n current_statement__ = 42;\n pos__ = 1;\n current_statement__ = 42;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 42;\n for (int sym2__ = 1; sym2__ <= n_pat; ++sym2__) {\n current_statement__ = 42;\n stan::model::assign(pat_sigma_index,\n pat_sigma_index_flat__[(pos__ - 1)],\n \"assigning variable pat_sigma_index\",\n stan::model::index_uni(sym2__), stan::model::index_uni(sym1__));\n current_statement__ = 42;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 42;\n stan::math::check_greater_or_equal(function__, \"pat_sigma_index\",\n pat_sigma_index, 1);\n current_statement__ = 43;\n stan::math::validate_non_negative_index(\"y\", \"N\", N);\n current_statement__ = 44;\n context__.validate_dims(\"data initialization\", \"y\", \"double\",\n std::vector<size_t>{static_cast<size_t>(N)});\n y_data__ = Eigen::Matrix<double,-1,1>::Constant(N,\n std::numeric_limits<double>::quiet_NaN());\n new (&y) Eigen::Map<Eigen::Matrix<double,-1,1>>(y_data__.data(), N);\n {\n std::vector<local_scalar_t__> y_flat__;\n current_statement__ = 44;\n y_flat__ = context__.vals_r(\"y\");\n current_statement__ = 44;\n pos__ = 1;\n current_statement__ = 44;\n for (int sym1__ = 1; sym1__ <= N; ++sym1__) {\n current_statement__ = 44;\n stan::model::assign(y, y_flat__[(pos__ - 1)],\n \"assigning variable y\", stan::model::index_uni(sym1__));\n current_statement__ = 44;\n pos__ = (pos__ + 1);\n }\n }\n current_statement__ = 45;\n stan::math::validate_non_negative_index(\"Q\", \"N\", N);\n current_statement__ = 46;\n stan::math::validate_non_negative_index(\"Q\", \"P\", P);\n current_statement__ = 47;\n context__.validate_dims(\"data initialization\", \"Q\", \"double\",\n std::vector<size_t>{static_cast<size_t>(N), static_cast<size_t>(P)});\n Q_data__ = Eigen::Matrix<double,-1,-1>::Constant(N, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&Q) Eigen::Map<Eigen::Matrix<double,-1,-1>>(Q_data__.data(), N, P);\n {\n std::vector<local_scalar_t__> Q_flat__;\n current_statement__ = 47;\n Q_flat__ = context__.vals_r(\"Q\");\n current_statement__ = 47;\n pos__ = 1;\n current_statement__ = 47;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 47;\n for (int sym2__ = 1; sym2__ <= N; ++sym2__) {\n current_statement__ = 47;\n stan::model::assign(Q, Q_flat__[(pos__ - 1)],\n \"assigning variable Q\", stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 47;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 48;\n stan::math::validate_non_negative_index(\"R\", \"P\", P);\n current_statement__ = 49;\n stan::math::validate_non_negative_index(\"R\", \"P\", P);\n current_statement__ = 50;\n context__.validate_dims(\"data initialization\", \"R\", \"double\",\n std::vector<size_t>{static_cast<size_t>(P), static_cast<size_t>(P)});\n R_data__ = Eigen::Matrix<double,-1,-1>::Constant(P, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&R) Eigen::Map<Eigen::Matrix<double,-1,-1>>(R_data__.data(), P, P);\n {\n std::vector<local_scalar_t__> R_flat__;\n current_statement__ = 50;\n R_flat__ = context__.vals_r(\"R\");\n current_statement__ = 50;\n pos__ = 1;\n current_statement__ = 50;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 50;\n for (int sym2__ = 1; sym2__ <= P; ++sym2__) {\n current_statement__ = 50;\n stan::model::assign(R, R_flat__[(pos__ - 1)],\n \"assigning variable R\", stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 50;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 51;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"G\", G);\n current_statement__ = 52;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"n_visit\",\n n_visit);\n current_statement__ = 53;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"n_visit\",\n n_visit);\n current_statement__ = 54;\n context__.validate_dims(\"data initialization\", \"Sigma_init\", \"double\",\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)});\n Sigma_init = std::vector<Eigen::Matrix<double,-1,-1>>(G,\n Eigen::Matrix<double,-1,-1>::Constant(n_visit, n_visit,\n std::numeric_limits<double>::quiet_NaN()));\n {\n std::vector<local_scalar_t__> Sigma_init_flat__;\n current_statement__ = 54;\n Sigma_init_flat__ = context__.vals_r(\"Sigma_init\");\n current_statement__ = 54;\n pos__ = 1;\n current_statement__ = 54;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 54;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 54;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 54;\n stan::model::assign(Sigma_init, Sigma_init_flat__[(pos__ - 1)],\n \"assigning variable Sigma_init\",\n stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 54;\n pos__ = (pos__ + 1);\n }\n }\n }\n }\n current_statement__ = 55;\n stan::math::validate_non_negative_index(\"R_inverse\", \"P\", P);\n current_statement__ = 56;\n stan::math::validate_non_negative_index(\"R_inverse\", \"P\", P);\n current_statement__ = 57;\n R_inverse_data__ = Eigen::Matrix<double,-1,-1>::Constant(P, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&R_inverse)\n Eigen::Map<Eigen::Matrix<double,-1,-1>>(R_inverse_data__.data(), P,\n P);\n current_statement__ = 57;\n stan::model::assign(R_inverse, stan::math::inverse(R),\n \"assigning variable R_inverse\");\n current_statement__ = 58;\n stan::math::validate_non_negative_index(\"theta\", \"P\", P);\n current_statement__ = 59;\n stan::math::validate_non_negative_index(\"Sigma\", \"G\", G);\n current_statement__ = 60;\n stan::math::validate_non_negative_index(\"Sigma\", \"n_visit\", n_visit);\n current_statement__ = 60;\n stan::math::validate_non_negative_index(\"Sigma\", \"n_visit\", n_visit);\n current_statement__ = 61;\n stan::math::validate_non_negative_index(\"beta\", \"P\", P);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n num_params_r__ = P + (G * (n_visit + ((n_visit * (n_visit - 1)) / 2)));\n }\n inline std::string model_name() const final {\n return \"modelaa9c6a27673f_rbmi_mmrm\";\n }\n inline std::vector<std::string> model_compile_info() const noexcept {\n return std::vector<std::string>{\"stanc_version = stanc3 v2.32.2\",\n \"stancflags = --\"};\n }\n template <bool propto__, bool jacobian__, typename VecR, typename VecI,\n stan::require_vector_like_t<VecR>* = nullptr,\n stan::require_vector_like_vt<std::is_integral, VecI>* = nullptr>\n inline stan::scalar_type_t<VecR>\n log_prob_impl(VecR& params_r__, VecI& params_i__, std::ostream*\n pstream__ = nullptr) const {\n using T__ = stan::scalar_type_t<VecR>;\n using local_scalar_t__ = T__;\n T__ lp__(0.0);\n stan::math::accumulator<T__> lp_accum__;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n static constexpr const char* function__ =\n \"modelaa9c6a27673f_rbmi_mmrm_namespace::log_prob\";\n // suppress unused var warning\n (void) function__;\n try {\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n current_statement__ = 1;\n theta = in__.template read<Eigen::Matrix<local_scalar_t__,-1,1>>(P);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n current_statement__ = 2;\n Sigma = in__.template read_constrain_cov_matrix<\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,\n jacobian__>(lp__, G, n_visit);\n {\n int data_start_row = std::numeric_limits<int>::min();\n current_statement__ = 4;\n data_start_row = 1;\n current_statement__ = 5;\n stan::math::validate_non_negative_index(\"mu\", \"N\", N);\n Eigen::Matrix<local_scalar_t__,-1,1> mu =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(N, DUMMY_VAR__);\n current_statement__ = 6;\n stan::model::assign(mu, stan::math::multiply(Q, theta),\n \"assigning variable mu\");\n current_statement__ = 9;\n for (int g = 1; g <= G; ++g) {\n current_statement__ = 7;\n lp_accum__.add(stan::math::inv_wishart_lpdf<propto__>(\n stan::model::rvalue(Sigma, \"Sigma\",\n stan::model::index_uni(g)), (n_visit + 2),\n stan::model::rvalue(Sigma_init, \"Sigma_init\",\n stan::model::index_uni(g))));\n }\n current_statement__ = 28;\n for (int i = 1; i <= n_pat; ++i) {\n int nvis = std::numeric_limits<int>::min();\n current_statement__ = 10;\n nvis = stan::model::rvalue(pat_n_visit, \"pat_n_visit\",\n stan::model::index_uni(i));\n int npt = std::numeric_limits<int>::min();\n current_statement__ = 11;\n npt = stan::model::rvalue(pat_n_pt, \"pat_n_pt\",\n stan::model::index_uni(i));\n int g = std::numeric_limits<int>::min();\n current_statement__ = 12;\n g = stan::model::rvalue(pat_G, \"pat_G\", stan::model::index_uni(i));\n current_statement__ = 13;\n stan::math::validate_non_negative_index(\"sig_index\", \"nvis\", nvis);\n std::vector<int> sig_index =\n std::vector<int>(nvis, std::numeric_limits<int>::min());\n current_statement__ = 14;\n stan::model::assign(sig_index,\n stan::model::rvalue(pat_sigma_index, \"pat_sigma_index\",\n stan::model::index_uni(i), stan::model::index_min_max(1, nvis)),\n \"assigning variable sig_index\");\n current_statement__ = 15;\n stan::math::validate_non_negative_index(\"sig\", \"nvis\", nvis);\n current_statement__ = 16;\n stan::math::validate_non_negative_index(\"sig\", \"nvis\", nvis);\n Eigen::Matrix<local_scalar_t__,-1,-1> sig =\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(nvis, nvis,\n DUMMY_VAR__);\n current_statement__ = 17;\n stan::model::assign(sig,\n stan::model::rvalue(\n stan::model::rvalue(Sigma, \"Sigma\", stan::model::index_uni(g)),\n \"Sigma[g]\", stan::model::index_multi(sig_index),\n stan::model::index_multi(sig_index)), \"assigning variable sig\");\n int data_stop_row = std::numeric_limits<int>::min();\n current_statement__ = 18;\n data_stop_row = (data_start_row + ((nvis * npt) - 1));\n current_statement__ = 19;\n stan::math::validate_non_negative_index(\"y_obs\", \"npt\", npt);\n current_statement__ = 20;\n stan::math::validate_non_negative_index(\"y_obs\", \"nvis\", nvis);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> y_obs =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(npt,\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(nvis,\n DUMMY_VAR__));\n current_statement__ = 21;\n stan::model::assign(y_obs,\n to_vector_of_arrays(\n stan::model::rvalue(y, \"y\",\n stan::model::index_min_max(data_start_row, data_stop_row)),\n nvis, pstream__), \"assigning variable y_obs\");\n current_statement__ = 22;\n stan::math::validate_non_negative_index(\"mu_obs\", \"npt\", npt);\n current_statement__ = 23;\n stan::math::validate_non_negative_index(\"mu_obs\", \"nvis\", nvis);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> mu_obs =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(npt,\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(nvis,\n DUMMY_VAR__));\n current_statement__ = 24;\n stan::model::assign(mu_obs,\n to_vector_of_arrays(\n stan::model::rvalue(mu, \"mu\",\n stan::model::index_min_max(data_start_row, data_stop_row)),\n nvis, pstream__), \"assigning variable mu_obs\");\n current_statement__ = 25;\n lp_accum__.add(stan::math::multi_normal_lpdf<propto__>(y_obs,\n mu_obs, sig));\n current_statement__ = 26;\n data_start_row = (data_stop_row + 1);\n }\n }\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n lp_accum__.add(lp__);\n return lp_accum__.sum();\n }\n template <typename RNG, typename VecR, typename VecI, typename VecVar,\n stan::require_vector_like_vt<std::is_floating_point,\n VecR>* = nullptr, stan::require_vector_like_vt<std::is_integral,\n VecI>* = nullptr, stan::require_vector_vt<std::is_floating_point,\n VecVar>* = nullptr>\n inline void\n write_array_impl(RNG& base_rng__, VecR& params_r__, VecI& params_i__,\n VecVar& vars__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true, std::ostream*\n pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n stan::io::serializer<local_scalar_t__> out__(vars__);\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n double lp__ = 0.0;\n // suppress unused var warning\n (void) lp__;\n int current_statement__ = 0;\n stan::math::accumulator<double> lp_accum__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n constexpr bool jacobian__ = false;\n static constexpr const char* function__ =\n \"modelaa9c6a27673f_rbmi_mmrm_namespace::write_array\";\n // suppress unused var warning\n (void) function__;\n try {\n Eigen::Matrix<double,-1,1> theta =\n Eigen::Matrix<double,-1,1>::Constant(P,\n std::numeric_limits<double>::quiet_NaN());\n current_statement__ = 1;\n theta = in__.template read<Eigen::Matrix<local_scalar_t__,-1,1>>(P);\n std::vector<Eigen::Matrix<double,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<double,-1,-1>>(G,\n Eigen::Matrix<double,-1,-1>::Constant(n_visit, n_visit,\n std::numeric_limits<double>::quiet_NaN()));\n current_statement__ = 2;\n Sigma = in__.template read_constrain_cov_matrix<\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,\n jacobian__>(lp__, G, n_visit);\n out__.write(theta);\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n out__.write(stan::model::rvalue(Sigma, \"Sigma\",\n stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__)));\n }\n }\n }\n if (stan::math::logical_negation(\n (stan::math::primitive_value(emit_transformed_parameters__) ||\n stan::math::primitive_value(emit_generated_quantities__)))) {\n return ;\n }\n if (stan::math::logical_negation(emit_generated_quantities__)) {\n return ;\n }\n Eigen::Matrix<double,-1,1> beta =\n Eigen::Matrix<double,-1,1>::Constant(P,\n std::numeric_limits<double>::quiet_NaN());\n current_statement__ = 3;\n stan::model::assign(beta, stan::math::multiply(R_inverse, theta),\n \"assigning variable beta\");\n out__.write(beta);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n template <typename VecVar, typename VecI,\n stan::require_vector_t<VecVar>* = nullptr,\n stan::require_vector_like_vt<std::is_integral, VecI>* = nullptr>\n inline void\n unconstrain_array_impl(const VecVar& params_r__, const VecI& params_i__,\n VecVar& vars__, std::ostream* pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n stan::io::serializer<local_scalar_t__> out__(vars__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n current_statement__ = 1;\n stan::model::assign(theta,\n in__.read<Eigen::Matrix<local_scalar_t__,-1,1>>(P),\n \"assigning variable theta\");\n out__.write(theta);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n current_statement__ = 2;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 2;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 2;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 2;\n stan::model::assign(Sigma, in__.read<local_scalar_t__>(),\n \"assigning variable Sigma\", stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__), stan::model::index_uni(sym1__));\n }\n }\n }\n out__.write_free_cov_matrix(Sigma);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n template <typename VecVar, stan::require_vector_t<VecVar>* = nullptr>\n inline void\n transform_inits_impl(const stan::io::var_context& context__, VecVar&\n vars__, std::ostream* pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::serializer<local_scalar_t__> out__(vars__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n current_statement__ = 1;\n context__.validate_dims(\"parameter initialization\", \"theta\", \"double\",\n std::vector<size_t>{static_cast<size_t>(P)});\n current_statement__ = 2;\n context__.validate_dims(\"parameter initialization\", \"Sigma\", \"double\",\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)});\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n {\n std::vector<local_scalar_t__> theta_flat__;\n current_statement__ = 1;\n theta_flat__ = context__.vals_r(\"theta\");\n current_statement__ = 1;\n pos__ = 1;\n current_statement__ = 1;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 1;\n stan::model::assign(theta, theta_flat__[(pos__ - 1)],\n \"assigning variable theta\", stan::model::index_uni(sym1__));\n current_statement__ = 1;\n pos__ = (pos__ + 1);\n }\n }\n out__.write(theta);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n {\n std::vector<local_scalar_t__> Sigma_flat__;\n current_statement__ = 2;\n Sigma_flat__ = context__.vals_r(\"Sigma\");\n current_statement__ = 2;\n pos__ = 1;\n current_statement__ = 2;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 2;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 2;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 2;\n stan::model::assign(Sigma, Sigma_flat__[(pos__ - 1)],\n \"assigning variable Sigma\", stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 2;\n pos__ = (pos__ + 1);\n }\n }\n }\n }\n out__.write_free_cov_matrix(Sigma);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n inline void\n get_param_names(std::vector<std::string>& names__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true) const {\n names__ = std::vector<std::string>{\"theta\", \"Sigma\"};\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n std::vector<std::string> temp{\"beta\"};\n names__.reserve(names__.size() + temp.size());\n names__.insert(names__.end(), temp.begin(), temp.end());\n }\n }\n inline void\n get_dims(std::vector<std::vector<size_t>>& dimss__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true) const {\n dimss__ = std::vector<std::vector<size_t>>{std::vector<size_t>{static_cast<\n size_t>(P)},\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)}};\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n std::vector<std::vector<size_t>>\n temp{std::vector<size_t>{static_cast<size_t>(P)}};\n dimss__.reserve(dimss__.size() + temp.size());\n dimss__.insert(dimss__.end(), temp.begin(), temp.end());\n }\n }\n inline void\n constrained_param_names(std::vector<std::string>& param_names__, bool\n emit_transformed_parameters__ = true, bool\n emit_generated_quantities__ = true) const final {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"theta\" + '.' +\n std::to_string(sym1__));\n }\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n param_names__.emplace_back(std::string() + \"Sigma\" + '.' +\n std::to_string(sym3__) + '.' + std::to_string(sym2__) + '.' +\n std::to_string(sym1__));\n }\n }\n }\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"beta\" + '.' +\n std::to_string(sym1__));\n }\n }\n }\n inline void\n unconstrained_param_names(std::vector<std::string>& param_names__, bool\n emit_transformed_parameters__ = true, bool\n emit_generated_quantities__ = true) const final {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"theta\" + '.' +\n std::to_string(sym1__));\n }\n for (int sym1__ = 1; sym1__ <= (n_visit + ((n_visit * (n_visit - 1)) /\n 2)); ++sym1__) {\n for (int sym2__ = 1; sym2__ <= G; ++sym2__) {\n param_names__.emplace_back(std::string() + \"Sigma\" + '.' +\n std::to_string(sym2__) + '.' + std::to_string(sym1__));\n }\n }\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"beta\" + '.' +\n std::to_string(sym1__));\n }\n }\n }\n inline std::string get_constrained_sizedtypes() const {\n return std::string(\"[{\\\"name\\\":\\\"theta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"Sigma\\\",\\\"type\\\":{\\\"name\\\":\\\"array\\\",\\\"length\\\":\" + std::to_string(G) + \",\\\"element_type\\\":{\\\"name\\\":\\\"matrix\\\",\\\"rows\\\":\" + std::to_string(n_visit) + \",\\\"cols\\\":\" + std::to_string(n_visit) + \"}},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"beta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"generated_quantities\\\"}]\");\n }\n inline std::string get_unconstrained_sizedtypes() const {\n return std::string(\"[{\\\"name\\\":\\\"theta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"Sigma\\\",\\\"type\\\":{\\\"name\\\":\\\"array\\\",\\\"length\\\":\" + std::to_string(G) + \",\\\"element_type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string((n_visit + ((n_visit * (n_visit - 1)) /2))) + \"}},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"beta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"generated_quantities\\\"}]\");\n }\n // Begin method overload boilerplate\n template <typename RNG> inline void\n write_array(RNG& base_rng, Eigen::Matrix<double,-1,1>& params_r,\n Eigen::Matrix<double,-1,1>& vars, const bool\n emit_transformed_parameters = true, const bool\n emit_generated_quantities = true, std::ostream*\n pstream = nullptr) const {\n const size_t num_params__ = (P + ((G * n_visit) * n_visit));\n const size_t num_transformed = emit_transformed_parameters * (0);\n const size_t num_gen_quantities = emit_generated_quantities * (P);\n const size_t num_to_write = num_params__ + num_transformed +\n num_gen_quantities;\n std::vector<int> params_i;\n vars = Eigen::Matrix<double,-1,1>::Constant(num_to_write,\n std::numeric_limits<double>::quiet_NaN());\n write_array_impl(base_rng, params_r, params_i, vars,\n emit_transformed_parameters, emit_generated_quantities, pstream);\n }\n template <typename RNG> inline void\n write_array(RNG& base_rng, std::vector<double>& params_r, std::vector<int>&\n params_i, std::vector<double>& vars, bool\n emit_transformed_parameters = true, bool\n emit_generated_quantities = true, std::ostream*\n pstream = nullptr) const {\n const size_t num_params__ = (P + ((G * n_visit) * n_visit));\n const size_t num_transformed = emit_transformed_parameters * (0);\n const size_t num_gen_quantities = emit_generated_quantities * (P);\n const size_t num_to_write = num_params__ + num_transformed +\n num_gen_quantities;\n vars = std::vector<double>(num_to_write,\n std::numeric_limits<double>::quiet_NaN());\n write_array_impl(base_rng, params_r, params_i, vars,\n emit_transformed_parameters, emit_generated_quantities, pstream);\n }\n template <bool propto__, bool jacobian__, typename T_> inline T_\n log_prob(Eigen::Matrix<T_,-1,1>& params_r, std::ostream* pstream = nullptr) const {\n Eigen::Matrix<int,-1,1> params_i;\n return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);\n }\n template <bool propto__, bool jacobian__, typename T_> inline T_\n log_prob(std::vector<T_>& params_r, std::vector<int>& params_i,\n std::ostream* pstream = nullptr) const {\n return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);\n }\n inline void\n transform_inits(const stan::io::var_context& context,\n Eigen::Matrix<double,-1,1>& params_r, std::ostream*\n pstream = nullptr) const final {\n std::vector<double> params_r_vec(params_r.size());\n std::vector<int> params_i;\n transform_inits(context, params_i, params_r_vec, pstream);\n params_r = Eigen::Map<Eigen::Matrix<double,-1,1>>(params_r_vec.data(),\n params_r_vec.size());\n }\n inline void\n transform_inits(const stan::io::var_context& context, std::vector<int>&\n params_i, std::vector<double>& vars, std::ostream*\n pstream__ = nullptr) const {\n vars.resize(num_params_r__);\n transform_inits_impl(context, vars, pstream__);\n }\n inline void\n unconstrain_array(const std::vector<double>& params_constrained,\n std::vector<double>& params_unconstrained, std::ostream*\n pstream = nullptr) const {\n const std::vector<int> params_i;\n params_unconstrained = std::vector<double>(num_params_r__,\n std::numeric_limits<double>::quiet_NaN());\n unconstrain_array_impl(params_constrained, params_i,\n params_unconstrained, pstream);\n }\n inline void\n unconstrain_array(const Eigen::Matrix<double,-1,1>& params_constrained,\n Eigen::Matrix<double,-1,1>& params_unconstrained,\n std::ostream* pstream = nullptr) const {\n const std::vector<int> params_i;\n params_unconstrained = Eigen::Matrix<double,-1,1>::Constant(num_params_r__,\n std::numeric_limits<double>::quiet_NaN());\n unconstrain_array_impl(params_constrained, params_i,\n params_unconstrained, pstream);\n }\n};\n}\nusing stan_model = modelaa9c6a27673f_rbmi_mmrm_namespace::modelaa9c6a27673f_rbmi_mmrm;\n#ifndef USING_R\n// Boilerplate\nstan::model::model_base&\nnew_model(stan::io::var_context& data_context, unsigned int seed,\n std::ostream* msg_stream) {\n stan_model* m = new stan_model(data_context, seed, msg_stream);\n return *m;\n}\nstan::math::profile_map& get_stan_profile_data() {\n return modelaa9c6a27673f_rbmi_mmrm_namespace::profiles__;\n}\n#endif\n#endif"), mk_cppmodule = function (object) { prep_call_sampler(object) model_cppname <- object@model_cpp$model_cppname mod <- get("module", envir = object@dso@.CXXDSOMISC, inherits = FALSE) eval(call("$", mod, paste("stan_fit4", model_cppname, sep = ""))) }, dso = new("cxxdso", sig = list(fileaa9c5c0bb1fd = character(0)), dso_saved = TRUE, dso_filename = "fileaa9c5c0bb1fd", modulename = "stan_fit4modelaa9c6a27673f_rbmi_mmrm_mod", system = "x86_64, darwin20", cxxflags = "CXXFLAGS = -falign-functions=64 -Wall -g -O2 $(LTO)", .CXXDSOMISC = <environment>)), data = list(N = 340L, P = 8L, G = 1L, n_visit = 3L, n_pat = 2L, pat_G = c(1, 1), pat_n_pt = c(60, 80), pat_n_visit = c(3, 2), pat_sigma_index = list( c(1, 2, 3), c(1, 2, 999)), y = c(0.574036883477536, 0.139105398171835, 0.176977232131814, -1.16935503183362, -1.21591438062592, -1.08964625296442, -1.58121597188229, -1.03382417471284, -0.813329718686652, -0.659208380311965, -0.596830231476417, -0.428690642917848, 1.19340919052579, 1.19324384350827, 1.14076998750238, 0.508301722783451, 0.285101803715272, -0.080275904172036, 0.420951505580432, 0.729295857616047, 0.606493590677628, 1.36133467580718, 0.785097805390841, 0.850728879541265, 1.59518647362531, 1.99123113996823, 1.62317993728234, -1.01500989395391, -1.29590087043236, -1.09167466441661, -1.92326503149754, -1.6438232242331, -2.09494484800456, -0.916339955699448, -1.21279752527853, -0.824654473194631, 0.160587572122124, 0.533787595446638, 0.509785626882552, 0.625441265387049, 0.869595429439695, 0.606754094352448, 0.416887452319262, 0.0527870943089152, -0.290746253299322, -0.0405562348050075, 0.138363916063878, 0.199662379261492, -0.0292589587575427, 0.184625776371717, 0.596974269230419, 0.460701441061857, 0.606107749594927, 0.675147663778399, 1.66002871020651, 1.84142634216536, 1.99191103632866, 1.10904044059033, 0.414249192109747, 0.672496352831966, 0.789592735008045, 0.677931435319177, 0.543093801624015, -0.899674446856585, -0.98731077385762, -1.31298117495064, -0.790921720329644, -0.407036721173524, -0.221080281874233, 1.43428989449746, 1.46018790177788, 1.29835543116011, 1.93804574039781, 1.67293427649682, 1.58849553103043, -1.01450332611738, -0.842813717586719, -0.629379340054354, -0.267415091390975, -0.657913697591214, -0.595234267484234, 0.120679904254403, 0.178945058091685, 0.258466389498271, -0.449519107207705, -0.418311943730978, -0.607987725151117, 0.475470586549514, 0.465961733342575, 0.628255437173784, -0.269181976386959, -0.489283917847538, -0.480553495290893, 0.0126097945506521, 0.188893941324742, -0.00785768753235569, -1.64359171150621, -1.51956953580399, -1.83648421907106, -0.334174407608112, 0.173961399031304, 0.512090615451255, 0.815812442864812, 1.00796572845926, 1.08799807363422, -0.499836503819652, -0.194917201294718, -0.347531934556113, 0.0967719422298859, 0.0448422069391228, -0.0380229372755732, 0.89027308837742, 0.923859648959303, 0.693773508152388, 0.0200206385163762, 0.139715592410514, 0.355610280019225, -0.554244284647314, -0.337491541079209, -0.0476717323926215, 1.74097877156221, 1.74584951452271, 1.87453426708686, 1.53665210908614, 1.27351842521603, 0.782842422447314, 0.780226954526566, 0.533531436107968, 0.471968788026106, -1.50987360873711, -1.4213975714265, -1.32130245857978, -1.53643170343886, -1.96117485895016, -1.63868589576792, -0.0924369697453538, -0.236384532458898, -0.416943554508815, 0.524748546809872, 1.01066900867255, 1.03925121395702, -1.47575422517021, -1.84351894914451, -1.96406505049471, -0.958450708965594, -1.00073327233577, -1.15403786283949, 1.30985852929418, 0.677518704253333, 0.633123295459129, -1.00859795137567, -0.486351090482834, -0.629987247106474, -0.703803757755735, -0.423015811624416, -0.68260822611802, 1.29970709660456, 0.950166424412677, 0.700867866424596, 0.885973022497435, 0.69557127871005, 0.683167942482159, -0.448047722773281, -0.345122636504496, -0.44919578758697, -0.350389882825743, 0.218778679169879, 0.460591876155823, -1.13643984701411, -1.37594847426891, -1.38924924598483, 1.05497189150375, 1.44213159591197, 1.44244341883156, 0.989297127175544, 1.28938706033795, 0.974021459136989, 0.0997949939225535, 0.0977838256866348, 0.152771705034039, 0.0563099671794369, -0.109302500409893, -0.770343945290974, -0.840203655711169, -1.06621935574191, -0.818506844251997, 0.483309359293258, -0.077312553568267, -1.82787954030716, -1.51850241691396, 0.385765772873327, 0.318930612816827, 0.0529827480329966, -0.256048504100078, 0.755705549841678, 0.841931688341897, 0.712085742232759, 0.644772892574503, -1.14155231656161, -1.4428233579315, -1.05021841671635, -1.39451198199354, -0.267077536825949, -0.707269786974737, -1.45623361118695, -1.14058269087304, -0.768761960571674, -0.570612606157713, -0.764238909934079, -1.27539783051645, -0.845195950602966, -1.35937750037253, -0.403679174325962, -0.181315302498918, -0.138311056457262, -0.0706441028516794, 0.508084112959793, 0.620362254164868, 0.480866966820087, 0.576196611808272, -1.14455494641288, -1.35096340386058, 0.550675910279237, 0.825037960508207, 1.61286207896739, 1.67916701468662, -0.0647658829962172, -0.266749386462743, -0.282320438961451, -0.774105813761362, -0.361641848210371, -0.0216017435394257, 1.42387705128602, 1.23207105462671, 0.265776870737417, 0.515102201270055, 0.771782662506529, 0.702063509689375, 0.616876705707196, 0.789738509590256, 0.971362277748469, 0.738026162904697, 0.534226435971703, 0.045703700581884, -1.14177405496358, -0.787101784899203, -0.872756204009667, -1.09360825060612, -0.968020452649131, -0.801211978871774, 1.52141486581132, 1.40439441624722, 1.79137191952656, 1.47694519657773, -1.9360028677803, -1.12357338931634, -0.442997879839818, -0.564318885154016, 0.000626204404452472, -0.27075649131444, -2.48336093478472, -1.92707335118885, 0.366175672975573, -0.232532349854313, 0.445155531890445, 0.769878306810777, -1.60791560029354, -1.71327349294041, -0.296398526983666, -0.367067711718188, -0.838340929698702, -1.43768210681618, -0.14561552296282, -0.0941334404913737, -0.0164394933059202, 0.0218434792651633, 1.07286404251878, 1.18723665035218, -0.138595585019409, 0.0131822076110258, -0.399908316171867, -0.868639920226593, 0.7981208661895, 0.719218310535082, 0.914826810253791, 0.705606688741132, 2.27692308241729, 2.20307732877354, -1.38708681157136, -1.25624461004343, 0.0942383865047231, 0.619729596216058, -1.97029658377716, -2.12452350098981, -0.546587071142227, -0.965112515688056, -0.0103825230207238, 0.275006295304356, 1.39505387642203, 1.13837400657299, 0.653655010243044, 0.592910348706071, 2.26190956828622, 2.20569250608316, -0.979542016063513, -0.948366938019486, 0.0839816881469963, 0.496574287039973, 0.547933703350616, 0.492939941225062, -0.375076840950679, -0.483574365532446, 1.3297009420447, 1.69844054391049, -1.13265693702497, -0.849277428071457, -1.13312754672772, -0.666195857133899, 0.459008637041986, 0.595690989575909, 1.50283257817443, 1.73920182026267, -0.300363476632086, -0.00897291528474771, -1.40333016095241, -1.19317961021338, -0.600226062637804, -0.325957148423221, 0.870433641965308, 0.130170018966925, -1.77311671749508, -1.19314004127747, 1.7640917533291, 1.44334725535403, -0.871065290131151, -1.32437155254469, 0.853886175567914, 0.646816118526293, 0.294983239652497, -0.326121365030516), Q = c(-0.99852832885673, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.958225137302622, -0.958225137302671, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.825360566675442, 1.20365082640164, -0.825360566675414, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.876442111269587, -0.024403432792697, 1.96548118704492, -0.826199749637548, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.377816532241714, -0.377816532241718, -0.457024666869012, -1.12880551077197, -1.12880551077196, -1.20801364539926, -0.220331575027453, -0.220331575027453, -0.29953970965475, 0.183702853067903, 0.183702853067903, 0.104494718440605, 1.12384497625067, 1.12384497625067, 1.04463684162337, 1.24707949620404, 1.24707949620404, 1.16787136157674, -0.610672320738653, -0.610672320738653, -0.689880455365951, 0.815513912349393, 0.815513912349393, 0.736305777722095, 1.07768856337481, 1.07768856337481, 0.99848042874751, -0.116268012873417, -0.116268012873417, -0.195476147500715, -1.75570733327889, -1.75570733327889, -1.83491546790618, 0.38821352691705, 0.388213526917049, 0.309005392289752, 2.38726637449642, 2.38726637449642, 2.30805823986912, 0.0978089234405026, 0.0978089234405023, 0.0186007888132049, 0.480311137245768, 0.480311137245767, 0.40110300261847, -1.36360112479173, -1.36360112479173, -1.44280925941902, 1.93535965542202, 1.93535965542202, 1.85615152079472, 0.394010340671377, 0.394010340671377, 0.314802206044079, 1.61374775950545, 1.61374775950545, 1.53453962487815, -0.964178039762375, -0.964178039762375, -1.04338617438967, -0.798757765014893, -0.798757765014893, -0.87796589964219, -1.0944257408576, -1.0944257408576, -1.1736338754849, 0.377586753964714, 0.377586753964714, 0.298378619337416, 1.37498679426785, 1.37498679426785, 1.29577865964055, 1.68915587438649, 1.68915587438649, 1.6099477397592, 0.992596467936866, 0.992596467936865, 0.913388333309568, -0.323261319416317, -0.323261319416317, -0.402469454043615, -1.53070167383635, -1.53070167383635, -1.60990980846365, 0.985012371873182, 0.985012371873181, 0.905804237245884, -0.83124291903249, -0.83124291903249, -0.910451053659788, 0.875900958465542, 0.875900958465542, 0.796692823838244, -0.599874960211679, -0.59987496021168, -0.679083094838977, -1.21249941889568, -1.21249941889568, -1.29170755352297, 0.10152732719712, 0.10152732719712, 0.0223191925698222, 0.273641473500582, 0.273641473500581, 0.194433338873284, 0.132099054317715, 0.132099054317715, 0.0528909196904172, -0.834302902018013, -0.834302902018014, -0.913511036645311, 0.719369062657609, 0.719369062657609, 0.640160928030311, -1.14019031831383, -1.14019031831383, -1.21939845294113, -0.986131847575652, -0.986131847575652, -1.06533998220295, 1.121130179697, 1.121130179697, 1.0419220450697, 0.901558128109497, 0.901558128109497, 0.822349993482199, -0.786141113615663, -0.786141113615663, -0.865349248242961, -0.713749729008484, -0.713749729008484, -0.792957863635781, -1.21024198127622, -1.21024198127622, -1.28945011590352, -1.48456568414046, -1.48456568414046, -1.56377381876776, 1.07705092477044, 1.07705092477044, 0.99784279014314, -1.51414471003321, -1.51414471003321, -1.59335284466051, 0.197021223835606, 0.197021223835606, 0.117813089208309, -0.992651143019504, -0.992651143019504, -1.0718592776468, -0.214255998107591, -0.214255998107591, -0.293464132734889, 0.855083280875347, 0.855083280875347, 0.77587514624805, 0.424765963693628, 0.424765963693628, 0.34555782906633, 0.364243987733107, 0.364243987733107, 0.285035853105809, 0.148975237666157, 0.148975237666156, 0.0697671030388588, -0.057416806838183, -0.0574168068381832, -0.136624941465481, -0.469756237118641, -0.469756237118641, -0.548964371745938, 1.07464366058924, 1.07464366058924, 0.995435525961942, 0.220197215402141, 0.22019721540214, 0.140989080774843, 2.43308733556931, 2.43308733556931, 2.35387920094201, -0.792463299943419, -0.792463299943419, 0.398667166152911, 0.398667166152911, -0.507624730755423, -0.507624730755423, -1.14063678811883, -1.14063678811883, -0.610719518834707, -0.610719518834707, 0.0372742888124956, 0.0372742888124953, 1.60469817459311, 1.60469817459311, -0.335089450474223, -0.335089450474223, 0.398797186950103, 0.398797186950103, -1.47882967397224, -1.47882967397224, -0.667444462142149, -0.66744446214215, -0.649446871595376, -0.649446871595376, -0.279713473009783, -0.279713473009783, 0.109041394826028, 0.109041394826028, -1.47272080463623, -1.47272080463623, -0.463549540361751, -0.463549540361752, -1.00365185771742, -1.00365185771742, -0.808089317383245, -0.808089317383245, 0.145106160657612, 0.145106160657612, 0.190373516579835, 0.190373516579835, -1.11324014885282, -1.11324014885282, 0.0373498895331294, 0.0373498895331292, 0.934861192278438, 0.934861192278438, 0.526171571037054, 0.526171571037054, -0.127064672854489, -0.127064672854489, 0.107735669014991, 0.107735669014991, 1.63023634780781, 1.63023634780781, -1.01842798000048, -1.01842798000048, 0.0915540560676067, 0.0915540560676064, -0.69105660373921, -0.69105660373921, -0.510325739757003, -0.510325739757004, -0.758316424407092, -0.758316424407092, 0.66850966666813, 0.66850966666813, 0.207547505355721, 0.207547505355721, -0.957302855842871, -0.957302855842871, 0.871306376044677, 0.871306376044677, 0.854052678949774, 0.854052678949774, -1.02517751500326, -1.02517751500326, -0.14387122685017, -0.14387122685017, 0.0439935573727569, 0.0439935573727567, -1.13877102137595, -1.13877102137595, 1.36106121128242, 1.36106121128242, 0.07551027826328, 0.0755102782632798, -1.39505728407859, -1.39505728407859, -1.55223678517323, -1.55223678517323, -0.783810528384146, -0.783810528384147, -1.23550391017333, -1.23550391017333, -1.34099290537528, -1.34099290537528, 0.282522679370366, 0.282522679370366, 1.05047246454719, 1.05047246454719, 0.406048469121015, 0.406048469121015, 0.239493257040229, 0.239493257040228, 0.534396153202169, 0.534396153202169, 2.04605670576315, 2.04605670576315, -0.0259943875448687, -0.0259943875448689, 1.56185162485783, 1.56185162485783, -1.89056227250461, -1.89056227250461, -0.819059954351738, -0.819059954351738, -0.481442518835015, -0.481442518835015, -0.0511676754622085, -0.0511676754622088, 2.24057972203455, 2.24057972203455, 1.5234804097995, 1.5234804097995, -0.344361395338917, -0.344361395338917, -0.0415535968630459, -0.0415535968630462, -0.0255793897214689, -0.0255793897214691, -0.0639754794004533, -0.0639754794004536, 1.29091591700363, 1.29091591700363, 0.678498611351185, 0.678498611351185, 1.04860191122785, 1.04860191122785, -0.768540785317964, -0.768540785317964, 1.30809002082778, 1.30809002082778, -0.47706971830725, -0.47706971830725, -1.38225666633996, -1.38225666633996, -0.898631124236369, -0.898631124236369, 0.673024870752781, 0.673024870752781, -0.410390025474452, -0.410390025474452, 1.85569424316007, 1.85569424316007, -1.42890995686216, -1.42890995686216, 2.09388845185187, 2.09388845185187, -0.769321140423713, -0.769321140423714, 0.928218267300235, 0.928218267300184, 0.865629305624082, -0.901905120181537, -0.901905120181534, -0.964494081857647, -0.949986114091021, -0.94998611409102, -1.01257507576713, -0.971369641027934, -0.971369641027932, -1.03395860270405, 0.848742814011857, 0.848742814011858, 0.786153852335745, -1.02764886257788, -1.02764886257788, -1.09023782425399, -1.06643981685835, -1.06643981685835, -1.12902877853447, 0.865061239254727, 0.865061239254728, 0.802472277578616, -1.1557963368333, -1.1557963368333, -1.21838529850942, 1.05148830018635, 1.05148830018635, 0.988899338510239, 1.13825564581723, 1.13825564581723, 1.07566668414112, 1.02478860866219, 1.0247886086622, 0.962199646986083, 0.918988712806694, 0.918988712806695, 0.856399751130582, 0.903045784372422, 0.903045784372423, 0.84045682269631, -0.987067638013804, -0.987067638013803, -1.04965659968992, -1.02659105090308, -1.02659105090308, -1.08918001257919, -1.06407609823243, -1.06407609823243, -1.12666505990854, 0.887369320824584, 0.887369320824586, 0.824780359148473, -1.18416727619675, -1.18416727619675, -1.24675623787286, -1.0477305224531, -1.04773052245309, -1.11031948412921, -1.0564853924716, -1.0564853924716, -1.11907435414771, -0.903724669915239, -0.903724669915238, -0.96631363159135, -0.981630948800652, -0.981630948800651, -1.04421991047676, 0.835451130291062, 0.835451130291064, 0.772862168614951, 0.818823727970098, 0.818823727970099, 0.756234766293987, 0.99280163428372, 0.992801634283721, 0.930212672607609, -0.944538556138783, -0.944538556138781, -1.00712751781489, -1.01774725234731, -1.01774725234731, -1.08033621402342, 0.993203022658554, 0.993203022658555, 0.930614060982442, -1.05476611530688, -1.05476611530688, -1.11735507698299, 0.998977745517508, 0.998977745517509, 0.936388783841396, 0.939970712255066, 0.939970712255067, 0.877381750578954, 1.1095063604548, 1.10950636045481, 1.04691739877869, 0.902848987809151, 0.902848987809153, 0.84026002613304, -1.11324213498986, -1.11324213498985, -1.17583109666597, -0.96863850936219, -0.968638509362189, -1.0312274710383, 0.952377813877598, 0.952377813877599, 0.889788852201486, 0.870149706574013, 0.870149706574014, 0.807560744897902, -1.03841507050665, -1.03841507050665, -1.10100403218276, 0.960413362636251, 0.960413362636252, 0.897824400960139, -1.15809548489647, -1.15809548489647, -1.22068444657258, 0.860507348107022, 0.860507348107023, 0.79791838643091, -1.05715312889772, -1.05715312889772, -1.11974209057384, 1.0831100271553, 1.0831100271553, 1.02052106547919, 1.10938688554181, 1.10938688554181, 1.0467979238657, 0.986792979394893, 0.986792979394894, 0.924204017718781, 0.85121938974584, 0.851219389745841, 0.788630428069729, 1.12547094109423, 1.12547094109423, 1.06288197941812, 1.03490746358836, 1.03490746358836, 0.972318501912247, -1.04622358312283, -1.04622358312283, -1.10881254479895, -0.950307664072134, -0.950307664072133, -1.01289662574825, 1.00007952135283, 1.00007952135283, 0.937490559676719, 0.885741579108468, 0.88574157910847, 0.823152617432357, 0.888944705409679, 0.888944705409681, 0.826355743733568, -0.96953168156765, -0.969531681567649, -1.03212064324376, 0.911261108003043, 0.911261108003044, 0.848672146326931, 1.07019666868025, 1.07019666868025, 1.00760770700414, -1.15563518531698, -1.15563518531698, -1.21822414699309, -1.1104135969911, -1.1104135969911, -1.17300255866722, 0.916563637894152, 0.916563637894153, 0.85397467621804, 0.950163452437635, 0.950163452437636, 1.02423534968067, 1.02423534968067, -0.934781120389717, -0.934781120389716, 0.968590538461504, 0.968590538461505, 1.07765715205019, 1.0776571520502, 0.906249580633761, 0.906249580633762, 0.960406144141665, 0.960406144141666, -1.08102504356151, -1.08102504356151, 0.887115976928059, 0.88711597692806, -0.883380087159851, -0.883380087159849, 1.08065932035285, 1.08065932035285, -0.927275181890372, -0.927275181890371, 1.06013865311795, 1.06013865311795, -0.967418182457954, -0.967418182457952, -0.883703399142486, -0.883703399142485, 1.06986817918019, 1.06986817918019, 0.961340609382444, 0.961340609382446, 0.950990459597437, 0.950990459597438, 0.900542577527299, 0.9005425775273, 0.898146802173973, 0.898146802173975, -0.902728917147178, -0.902728917147177, 0.906245579464717, 0.906245579464718, -1.14823719651062, -1.14823719651062, -0.98949480202044, -0.989494802020438, -0.95492226600347, -0.954922266003468, -0.967349076903795, -0.967349076903794, 0.821942044618619, 0.82194204461862, -1.04485934371747, -1.04485934371747, 0.903376823302905, 0.903376823302906, -1.06218547771961, -1.06218547771961, -1.07175066085639, -1.07175066085638, 0.948356228641671, 0.948356228641673, 1.00995393211511, 1.00995393211511, 1.03435036001307, 1.03435036001307, -0.910981900243858, -0.910981900243856, -1.14487355710169, -1.14487355710169, -1.14396040497669, -1.14396040497669, -0.907389633096397, -0.907389633096396, -0.954032778932337, -0.954032778932336, -0.963975524883135, -0.963975524883134, 1.1056042841347, 1.1056042841347, 0.973300633337403, 0.973300633337404, -1.10275603911339, -1.10275603911339, -0.887813741896416, -0.887813741896414, 0.990374473226015, 0.990374473226016, -0.920163983748597, -0.920163983748596, 0.973611382030312, 0.973611382030313, -1.02778759118596, -1.02778759118596, -1.11371217291668, -1.11371217291668, -1.01724343307714, -1.01724343307713, 1.02384469413284, 1.02384469413285, -1.11143484022547, -1.11143484022547, 0.879939400018172, 0.879939400018173, -1.20704723234541, -1.20704723234541, 1.04671056748668, 1.04671056748668, -1.04430818124978, -1.04430818124978, 1.14539284508785, 1.14539284508785, -0.918298407457879, -0.918298407457877, 0.933702673879424, 0.933702673879425, -1.09605160689812, -1.09605160689812, -1.0802298739066, -1.0802298739066, -1.17938987563448, -1.17938987563448, 1.06356014518004, 1.06356014518004, 0.910421547425474, 0.910421547425475, 0.909576112321545, 0.909576112321546, -0.958261262321214, -0.958261262321213, -1.1670813970731, -1.1670813970731, 1.00942526709835, 1.00942526709835, 0.989837545528036, 0.989837545528038, -1.05808462648328, -1.05808462648328, -1.1679903367233, -1.1679903367233, 0.933471243359218, 0.933471243359219, -0.888491214743256, -0.888491214743254, 0.955782385807506, 0.955782385807507, -0.997267014663429, -0.997267014663428, 1.0670547112193, 1.0670547112193, 0.8100096828119, 0.810009682811901, -0.886022088784659, -0.886022088784658, -1.07246623667859, -1.07246623667859, 0.948938653368405, 0.948938653368406, 0.822922780507105, -1.1501950067864, 0.761524154870805, -0.884042163308671, 1.20514137617857, -0.945440788944958, -0.8764883205467, 1.21269521894054, -0.937886946182985, -0.873128826762482, 1.21605471272476, -0.93452745239877, 0.835408900879507, -1.137708886414, 0.774010275243219, -0.864286988110919, 1.22489655137632, -0.925685613747207, 0.79384135565294, -1.17927643164056, 0.732442730016652, 0.832845168136384, -1.14027261915712, 0.771446542500097, 0.807879857080727, -1.16523793021277, 0.746481231444439, -0.848477786323998, 1.24070575316324, -0.909876411960286, -0.862109511304625, 1.22707402818261, -0.923508136940912, -0.844283087854447, 1.24490045163279, -0.905681713490735, -0.827661223110346, 1.26152231637689, -0.889059848746634, 0.826877544385839, -1.14624024290766, 0.765478918749551, -0.870662567409932, 1.21852097207731, -0.93206119304622, 0.78758085045516, -1.18553693683834, 0.726182224818872, -0.858564027996871, 1.23061951149037, -0.919962653633159, 0.829340420692578, -1.14377736660092, 0.76794179505629, 0.812337119660705, -1.1607806676328, 0.750938494024418, 0.79090200152081, -1.18221578577269, 0.729503375884522, 0.792277449616699, -1.1808403376768, 0.730878823980412, -0.883756299987876, 1.20542723949936, -0.945154925624164, -0.87151670731268, 1.21766683217456, -0.932915332948968, 0.837497112472174, -1.13562067482133, 0.776098486835886, 0.840109387561767, -1.13300839973174, 0.778710761925479, -0.839257722211194, 1.24992581727604, -0.900656347847481, -0.87734416800038, 1.21183937148686, -0.938742793636667, 0.786191431096763, -1.18692635619674, 0.724792805460476, -0.839320782984764, 1.24986275650247, -0.900719408621052, 0.792007339780971, -1.18111044751253, 0.730608714144683, -0.840228030213318, 1.24895550927392, -0.901626655849606, 0.821076393524696, -1.15204139376881, 0.759677767888408, -0.857592808061018, 1.23159073142622, -0.918991433697306, 0.826908462430042, -1.14620932486346, 0.765509836793755, 0.801194309976777, -1.17192347731673, 0.739795684340489, -0.873557905645587, 1.21562563384165, -0.934956531281875, 0.819127155641534, -1.15399063165197, 0.757728530005247, 0.832045736200728, -1.14107205109277, 0.770647110564441, 0.789438482289227, -1.18367930500428, 0.728039856652939, 0.817864717682301, -1.1552530696112, 0.756466092046013, 0.808241068477237, -1.16487671881626, 0.74684244284095, 0.833560614613004, -1.1395571726805, 0.772161988976716, 0.792382355434139, -1.18073543185936, 0.730983729797852, -0.853445769178827, 1.23573777030841, -0.914844394815115, -0.857574037760461, 1.23160950172678, -0.918972663396749, 0.813720305079455, -1.15939748221405, 0.752321679443167, 0.835019814420149, -1.13809797287335, 0.773621188783862, -0.860100949472114, 1.22908259001512, -0.921499575108402, -0.845872827018062, 1.24331071246918, -0.90727145265435, 0.790665251365976, -1.18245253592753, 0.729266625729689, -0.876437802913846, 1.21274573657339, -0.937836428550134, -0.840401126498196, 1.24878241298904, -0.901799752134484, 0.829596149702751, -1.14352163759075, 0.768197524066464, 0.829092917334643, -1.14402486995886, 0.767694291698356, -0.873417582373317, 1.21576595711392, -0.934816208009604, 0.825586862602903, -1.1475309246906, 0.764188236966615, -0.851416994989318, 1.23776654449792, -0.912815620625605, 0.807854539109608, -1.16526324818389, 0.74645591347332, 0.800749927913273, -1.17236785938023, 0.739351302276985, -0.827280227771318, 1.26190331171592, -0.888678853407606, 0.819475046497683, -1.15364274079582, -0.844196167202163, 1.24498737228508, -0.878877125816253, 1.21030641367099, 0.816580029172383, -1.15653775812112, -0.852589086365194, 1.23659445312204, 0.826374206762554, -1.14674358053095, -0.834168176034367, 1.25501536345287, 0.79613279142007, -1.17698499587343, 0.829380222697559, -1.14373756459594, -0.886952568756393, 1.20223097073085, -0.853060746900039, 1.2361227925872, -0.880056358494176, 1.20912718099306, -0.849836814092931, 1.23934672539431, -0.873749627088995, 1.21543391239824, -0.886901774301426, 1.20228176518581, -0.851365387112054, 1.23781815237518, 0.817719041073879, -1.15539874621962, 0.819345118192542, -1.15377266910096, 0.827270814769233, -1.14584697252427, 0.827647206953348, -1.14547058034015, -0.883912739346304, 1.20527080014094, 0.826374835372726, -1.14674295192078, 0.806692266043805, -1.1664255212497, -0.870281243860378, 1.21890229562686, -0.875712818370806, 1.21347072111643, -0.873760484029496, 1.21542305545774, 0.839619479352104, -1.1334983079414, 0.790450920314975, -1.18266686697853, 0.826825535976161, -1.14629225131734, 0.793172970781972, -1.17994481651153, 0.794675724438452, -1.17844206285505, 0.819758973331977, -1.15335881396153, -0.841952461863805, 1.24723107762343, -0.845785302354621, 1.24339823713262, -0.882616141011691, 1.20656739847555, 0.8061638160028, -1.1669539712907, 0.806020353752768, -1.16709743354073, -0.883180509985469, 1.20600302950177, -0.875852562684054, 1.21333097680318, -0.874290491407491, 1.21489304807975, -0.856979766013203, 1.23220377347404, -0.836193985735054, 1.25298955375218, 0.799546874826271, -1.17357091246723, -0.886256012216735, 1.2029275272705, 0.813157628665065, -1.15996015862844, -0.881173574846094, 1.20800996464114, 0.81579122137605, -1.15732656591745, 0.787768834862726, -1.18534895243078, 0.801268156049886, -1.17184963124362, -0.865921750039247, 1.22326178944799, -0.844134792626839, 1.2450487468604, 0.800910371992874, -1.17220741530063, 0.830507710487194, -1.14261007680631, 0.815931712390488, -1.15718607490301, -0.847727172856231, 1.24145636663101, -0.861669698751094, 1.22751384073614, -0.863230812606188, 1.22595272688105, -0.881466669243999, 1.20771687024324, 0.82206114388998, -1.15105664340352, 0.798493564096925, -1.17462422319658, -0.856026162792076, 1.23315737669516, 0.811586558373925, -1.16153122891958, -0.850374353169121, 1.23880918631812, 0.825718763133163, -1.14739902416034, 0.825851586590444, -1.14726620070306, -0.875188239922729, 1.21399529956451, 0.809652814827218, -1.16346497246628, -0.841869405086362, 1.24731413440088, -0.83879204422552, 1.25039149526172, 0.792528699877594, -1.18058908741591, 0.809795615269543, -1.16332217202396, 0.822097503158327, -1.15102028413518, -0.886149576743081, 1.20303396274416, 0.818592274830236, -1.15452551246327, -0.869060177749967, 1.22012336173727, -0.850923372651362, 1.23826016683588, 0.841494132464238, -1.13162365482926, -0.886537492793357, 1.20264604669388, -0.857245881647968, 1.23193765783927, 0.819667470547847, -1.15345031674566, 0.803861462573047, -0.0211329139384156, -1.82131769404675, -0.820744084523179, 0.0527793729593497, 2.26118636758273, -0.838810415568061, 0.0347130419146569, 2.24312003653804, -0.846845230265783, 0.026678227216929, 2.23508522184031, 0.77399873028981, -0.0509956462216396, -1.85118042633002, -0.867992027883424, 0.00553142959928859, 2.21393842422267, 0.873414756866236, 0.0484203803547872, -1.75176439975359, 0.780130343815119, -0.0448640326963297, -1.84504881280471, 0.839839234822993, 0.0148448583115435, -1.78533992179684, -0.905802488338423, -0.0322790308557106, 2.17612796376767, -0.873199843039792, 0.000323614442920459, 2.2087306090663, -0.915834840555904, -0.0423113830731918, 2.16609561155019, -0.95558892606041, -0.0820654685776981, 2.12634152604568, 0.79440295573263, -0.0305914207788192, -1.8307762008872, -0.852743719195093, 0.0207797382876193, 2.229186732911, 0.888387845792513, 0.0633934692810632, -1.73679131082732, -0.881679484087365, -0.00815602660465274, 2.20025096801873, 0.788512557946793, -0.0364818185646559, -1.83666659867304, 0.829178914789803, 0.0041845382783543, -1.79600024183003, 0.88044473438655, 0.0554503578751003, -1.74473442223328, 0.87715511062575, 0.0521607341143012, -1.74802404599408, -0.82142777646, 0.0520956810227126, 2.26050267564609, -0.850700894803883, 0.0228225626788291, 2.23122955730221, 0.769004408444191, -0.0559899680672583, -1.85617474817564, 0.762756697439936, -0.0622376790715132, -1.86242245917989, -0.927853878043513, -0.0543304205608001, 2.15407657406258, -0.836763507271285, 0.0367599502114277, 2.24516694483481, 0.891710884261762, 0.0667165077503133, -1.73346827235807, -0.927703057216662, -0.0541795997339494, 2.15422739488943, 0.877801125358181, 0.0528067488467312, -1.74737803126165, -0.925533217403083, -0.0520097599203713, 2.15639723470301, 0.808277418731149, -0.0167169577802998, -1.81690173788868, -0.884002325776186, -0.0104788682934731, 2.19792812632991, 0.794329009843176, -0.0306653666682737, -1.83085014677665, 0.855828885521429, 0.0308345090099801, -1.7693502710984, -0.845819013359934, 0.0277044441227784, 2.23611143874616, 0.812939360737585, -0.0120550157738646, -1.81223979588224, 0.782042324571453, -0.0429520519399964, -1.84313683204838, 0.883944995612685, 0.0589506191012357, -1.74123416100714, 0.815958701067214, -0.00903567544423477, -1.80922045555261, 0.838975334835647, 0.0139809583241984, -1.78620382178418, 0.778419228916563, -0.0465751475948864, -1.84675992770327, 0.876904210085971, 0.0519098335745217, -1.74827494653386, -0.893920691786934, -0.0203972343042217, 2.18800976031916, -0.884047218220252, -0.010523760737539, 2.19788323388584, 0.825870785873341, 0.000876409361892246, -1.79930837074649, 0.774929298346527, -0.0500650781649221, -1.8502498582733, -0.878003668606899, -0.00448021112418726, 2.20392678349919, -0.91203270237146, -0.0385092448887477, 2.16989774973463, 0.88101096362998, 0.0560165871185309, -1.74416819298985, -0.838931237288528, 0.0345922201941843, 2.24299921481756, -0.925119227479842, -0.0515957699971294, 2.15681122462625, 0.787900937464197, -0.0370934390472518, -1.83727821915563, 0.789104505348933, -0.0358898711625159, -1.8360746512709, -0.846154620913599, 0.0273688365691129, 2.23577583119249, 0.797489846087465, -0.0275045304239841, -1.82768931053236, -0.898772858727331, -0.025249401244619, 2.18315759337876, 0.839899787161985, 0.0149054106505359, -1.78527936945784, 0.856891702649422, 0.0318973261379731, -1.76828745397041, -0.956500142793173, -0.0829766853104602, 2.12543030931292, 0.812107319143305, -0.0128870573681433, -0.916042726439721, -0.0425192689570086, -0.83309717157278, 0.0404262859099321, 0.81903125746544, -0.00596311904600874, -0.895969597992568, -0.0224461405098556, 0.795606775353457, -0.0293876011579923, -0.940026414459111, -0.0665029569763992, 0.867934389000357, 0.0429400124889075, 0.788417364517319, -0.0365770119941302, -0.813783342825435, 0.0597401146572771, -0.894841539647731, -0.0213180821650186, -0.830276831169969, 0.0432466263127437, -0.902552136650396, -0.0290286791676837, -0.845360478125072, 0.0281629793576404, -0.813904826614228, 0.059618630868485, -0.898896287957265, -0.025372830474553, 0.816307112056978, -0.00868726445447075, 0.812418065322002, -0.0125763111894468, 0.793462381092629, -0.0315319954188206, 0.792562173606831, -0.0324322029046178, -0.821053624478443, 0.0524698330042695, 0.795605271922712, -0.0293891045887376, 0.842679565697599, 0.0176851891861495, -0.853655720900511, 0.0198677365822016, -0.840665164134714, 0.0328582933479981, -0.845334511860298, 0.0281889456224142, 0.763928398278325, -0.0610659782331235, 0.881523573680594, 0.0565291971691448, 0.794527342905617, -0.0304670336058325, 0.875013315735499, 0.0500189392240497, 0.871419218546547, 0.0464248420350977, 0.81142825865152, -0.0135661178599293, -0.921408938669288, -0.047885481186576, -0.912242032853194, -0.0387185753704815, -0.824154665297431, 0.0493687921852809, 0.843943446040652, 0.0189490695292029, 0.844286561006527, 0.0192921844950779, -0.822804878568622, 0.0507185789140902, -0.840330941262423, 0.0331925162202896, -0.844066906874501, 0.0294565506082113, -0.885468522641695, -0.011945065158983, -0.935181337610223, -0.0616578801275106, 0.859769013710692, 0.0347746371992431, -0.81544927914862, 0.0580741783340921, 0.827216524551485, 0.00222214804003571, -0.827604813615682, 0.0459186438670304, 0.820917828741576, -0.0040765477698727, 0.887938248329957, 0.0629438718185078, 0.855652269771647, 0.0306578932601976, -0.86408220991301, 0.00944124756970293, -0.916189514429685, -0.0426660569469729, 0.856507972679448, 0.0315135961679986, 0.785720781030177, -0.0392735954812725, 0.820581820003289, -0.00441255650816027, -0.90759771122333, -0.0340742537406174, -0.874251731388556, -0.00072827390584424, -0.870518055616725, 0.0030054018659874, -0.826903827298288, 0.0466196301844241, 0.805922216662982, -0.0190721598484675, 0.862288189834544, 0.0372938133230945, -0.887749230887956, -0.014225773405243, 0.830974012874789, 0.00597963636334023, -0.901266518296148, -0.0277430608134351, 0.797174382988782, -0.0278199935226667, 0.796856712549333, -0.028137663962116, -0.841919784888747, 0.0316036725939652, 0.835598897476072, 0.0106045209646224, -0.921607583423233, -0.0480841259405207, -0.928967628079688, -0.0554441705969753, 0.876554201852371, 0.0515598253409218, 0.835257365338632, 0.0102629888271829, 0.805835257137982, -0.0191591193734673, -0.815703838127743, 0.0578196193549695, 0.814218621388206, -0.0107757551232429, -0.856576113245609, 0.0169473442371033, -0.899953442550635, -0.0264299850679229, 0.759444838746444, -0.0655495377650052, -0.814776069308258, 0.058747388174454, -0.884832060736767, -0.0113086032540545, 0.811647103501974, -0.0133472730094756 ), R = c(-1.00147384015129, 0, 0, 0, 0, 0, 0, 0, -0.521355499137583, -0.500312239830598, 0, 0, 0, 0, 0, 0, -0.412371581238766, 0.00520237329552464, 0.492850855057777, 0, 0, 0, 0, 0, -0.176730677673757, -0.0104047465910492, -0.147761901765143, 0.351874380491925, 0, 0, 0, 0, -0.0148145536477168, -0.0628921007447697, -0.0117315667981618, 0.0279370916994833, 1.00236007528132, 0, 0, 0, -0.480118341013706, 0.0345264174379645, 0.00491668361530068, -0.0117083969584963, -0.0263704470162966, -0.498260577419346, 0, 0, -0.212076813208509, -0.203516843320922, 0.25564265339504, -0.00518302997367062, 0.00222305092368008, 0.00332949514226805, -0.246165884693855, 0, -0.0972018727205666, -0.0932785531887564, -0.0803448339241552, 0.191330027057476, -0.00444610184736015, -0.00665899028453591, 0.0732625048297967, -0.175220044568803), Sigma_init = list( c(0.135928026518976, 0.0348523498539469, 0.00728419213566572, 0.0348523498539469, 0.0345033646543252, 0.00223741352686764, 0.00728419213566572, 0.00223741352686764, 0.0129045826930864 ))), pars = c("beta", "Sigma"), chains = 1, warmup = 200, thin = 2, iter = 204, init = list(list(theta = c(-5.9502531301265e-05, -0.745820423193819, -0.00612121696522099, 0.00358076868728952, 0.552831864322152, -0.281246666814181, -0.00509794025644147, -0.00632342582509301), sigma = list(Placebo = c(0.135928026518976, 0.0348523498539469, 0.00728419213566572, 0.0348523498539469, 0.0345033646543252, 0.00223741352686764, 0.00728419213566572, 0.00223741352686764, 0.0129045826930864), TRT = c(0.135928026518976, 0.0348523498539469, 0.00728419213566572, 0.0348523498539469, 0.0345033646543252, 0.00223741352686764, 0.00728419213566572, 0.00223741352686764, 0.0129045826930864)))), refresh = 0, seed = 2053082391L)
10: (new("nonstandardGenericFunction", .Data = function (object, ...) { standardGeneric("sampling")}, generic = "sampling", package = "rstan", group = list(), valueClass = character(0), signature = "object", default = NULL, skeleton = (function (object, ...) stop(gettextf("invalid call in method dispatch to '%s' (no default method)", "sampling"), domain = NA))(object, ...)))(object = new("stanmodel", model_name = "rbmi_mmrm", model_code = "functions {\n int integer_division(int a, int b) {\n // perform a/b ensuring return value is also an int\n int i = 0;\n while(b*(i+1) <= a) {\n i = i + 1;\n }\n return(i);\n }\n array[] vector to_vector_of_arrays(vector vec, int length_array) {\n // treansform a vector into a vector of arrays. Example: vec = [1,2,3,4,5,6] and\n // length_array = 2, then output = [1,2; 3,4; 5,6]\n array[integer_division(num_elements(vec),length_array)] vector[length_array] res;\n int j = 1;\n int i = 1;\n while(j <= num_elements(vec)) {\n res[i,] = vec[j:(j+length_array-1)];\n i = i+1;\n j = j + length_array;\n }\n return(res);\n }\n}\ndata {\n int<lower=1> N; // number of observations\n int<lower=1> P; // number of covariates (number of columns of design matrix)\n int<lower=1> G; // number of Sigma Groups\n int<lower=1> n_visit; // number of visits\n int<lower=1> n_pat; // number of pat groups (# missingness patterns * groups)\n array[n_pat] int<lower=1> pat_G; // Index for which Sigma the pat group should use\n array[n_pat] int<lower=1> pat_n_pt; // number of patients in each pat group\n array[n_pat] int<lower=1> pat_n_visit; // number of non-missing visits in each pat group\n array[n_pat, n_visit] int<lower=1> pat_sigma_index; // rows/cols from sigma to subset on for the pat group\n vector[N] y; // outcome variable\n matrix[N,P] Q; // design matrix (After QR decomp)\n matrix[P,P] R; // R matrix (from QR decomp)\n array[G] matrix[n_visit, n_visit] Sigma_init; // covariance matrix estimated from MMRM\n}\ntransformed data {\n matrix[P, P] R_inverse = inverse(R);\n}\nparameters {\n vector[P] theta; // coefficients of linear model on covariates\n array[G] cov_matrix[n_visit] Sigma; // covariance matrix(s)\n}\nmodel {\n int data_start_row = 1;\n vector[N] mu = Q * theta;\n for(g in 1:G){\n Sigma[g] ~ inv_wishart(n_visit+2, Sigma_init[g]);\n }\n for(i in 1:n_pat) {\n // Index + size variables for current pat group\n int nvis = pat_n_visit[i]; // number of visits\n int npt = pat_n_pt[i]; // number of patients\n int g = pat_G[i]; // Sigma index\n // Get required/reduced Sigma for current pat group\n array[nvis] int sig_index = pat_sigma_index[i, 1:nvis];\n matrix[nvis,nvis] sig = Sigma[g][sig_index, sig_index];\n // Derive data indcies for current pat group\n int data_stop_row = data_start_row + ((nvis * npt) -1);\n // Extract required data for the current pat group\n array[npt] vector[nvis] y_obs = to_vector_of_arrays(y[data_start_row:data_stop_row], nvis);\n array[npt] vector[nvis] mu_obs = to_vector_of_arrays(mu[data_start_row:data_stop_row], nvis);\n y_obs ~ multi_normal(mu_obs, sig);\n // Update data index for next pat group\n data_start_row = data_stop_row + 1;\n }\n}\ngenerated quantities {\n vector[P] beta = R_inverse * theta;\n}", model_cpp = list(model_cppname = "modelaa9c6a27673f_rbmi_mmrm", model_cppcode = "#ifndef MODELS_HPP\n#define MODELS_HPP\n#define STAN__SERVICES__COMMAND_HPP\n#include <rstan/rstaninc.hpp>\n#ifndef USE_STANC3\n#define USE_STANC3\n#endif\n// Code generated by stanc v2.32.2\n#include <stan/model/model_header.hpp>\nnamespace modelaa9c6a27673f_rbmi_mmrm_namespace {\nusing stan::model::model_base_crtp;\nusing namespace stan::math;\nstan::math::profile_map profiles__;\nstatic constexpr std::array<const char*, 80> locations_array__ =\n {\" (found before start of program)\",\n \" (in 'rbmi_mmrm', line 43, column 4 to column 20)\",\n \" (in 'rbmi_mmrm', line 44, column 4 to column 39)\",\n \" (in 'rbmi_mmrm', line 71, column 3 to column 38)\",\n \" (in 'rbmi_mmrm', line 47, column 4 to column 27)\",\n \" (in 'rbmi_mmrm', line 48, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 48, column 4 to column 29)\",\n \" (in 'rbmi_mmrm', line 50, column 8 to column 57)\",\n \" (in 'rbmi_mmrm', line 49, column 17 to line 51, column 5)\",\n \" (in 'rbmi_mmrm', line 49, column 4 to line 51, column 5)\",\n \" (in 'rbmi_mmrm', line 54, column 8 to column 34)\",\n \" (in 'rbmi_mmrm', line 55, column 8 to column 30)\",\n \" (in 'rbmi_mmrm', line 56, column 8 to column 25)\",\n \" (in 'rbmi_mmrm', line 58, column 14 to column 18)\",\n \" (in 'rbmi_mmrm', line 58, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 59, column 15 to column 19)\",\n \" (in 'rbmi_mmrm', line 59, column 20 to column 24)\",\n \" (in 'rbmi_mmrm', line 59, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 61, column 8 to column 63)\",\n \" (in 'rbmi_mmrm', line 63, column 14 to column 17)\",\n \" (in 'rbmi_mmrm', line 63, column 26 to column 30)\",\n \" (in 'rbmi_mmrm', line 63, column 8 to column 99)\",\n \" (in 'rbmi_mmrm', line 64, column 14 to column 17)\",\n \" (in 'rbmi_mmrm', line 64, column 26 to column 30)\",\n \" (in 'rbmi_mmrm', line 64, column 8 to column 101)\",\n \" (in 'rbmi_mmrm', line 65, column 8 to column 42)\",\n \" (in 'rbmi_mmrm', line 67, column 8 to column 43)\",\n \" (in 'rbmi_mmrm', line 52, column 22 to line 68, column 5)\",\n \" (in 'rbmi_mmrm', line 52, column 4 to line 68, column 5)\",\n \" (in 'rbmi_mmrm', line 25, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 26, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 27, column 4 to column 19)\",\n \" (in 'rbmi_mmrm', line 28, column 4 to column 25)\",\n \" (in 'rbmi_mmrm', line 29, column 4 to column 23)\",\n \" (in 'rbmi_mmrm', line 30, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 30, column 4 to column 36)\",\n \" (in 'rbmi_mmrm', line 31, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 31, column 4 to column 39)\",\n \" (in 'rbmi_mmrm', line 32, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 32, column 4 to column 42)\",\n \" (in 'rbmi_mmrm', line 33, column 10 to column 15)\",\n \" (in 'rbmi_mmrm', line 33, column 17 to column 24)\",\n \" (in 'rbmi_mmrm', line 33, column 4 to column 55)\",\n \" (in 'rbmi_mmrm', line 34, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 34, column 4 to column 16)\",\n \" (in 'rbmi_mmrm', line 35, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 35, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 35, column 4 to column 18)\",\n \" (in 'rbmi_mmrm', line 36, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 36, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 36, column 4 to column 18)\",\n \" (in 'rbmi_mmrm', line 37, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 37, column 20 to column 27)\",\n \" (in 'rbmi_mmrm', line 37, column 29 to column 36)\",\n \" (in 'rbmi_mmrm', line 37, column 4 to column 49)\",\n \" (in 'rbmi_mmrm', line 40, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 40, column 13 to column 14)\",\n \" (in 'rbmi_mmrm', line 40, column 3 to column 39)\",\n \" (in 'rbmi_mmrm', line 43, column 11 to column 12)\",\n \" (in 'rbmi_mmrm', line 44, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 44, column 24 to column 31)\",\n \" (in 'rbmi_mmrm', line 71, column 10 to column 11)\",\n \" (in 'rbmi_mmrm', line 4, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 6, column 12 to column 22)\",\n \" (in 'rbmi_mmrm', line 5, column 28 to line 7, column 9)\",\n \" (in 'rbmi_mmrm', line 5, column 8 to line 7, column 9)\",\n \" (in 'rbmi_mmrm', line 8, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 2, column 39 to line 9, column 5)\",\n \" (in 'rbmi_mmrm', line 13, column 14 to column 62)\",\n \" (in 'rbmi_mmrm', line 13, column 71 to column 83)\",\n \" (in 'rbmi_mmrm', line 13, column 8 to column 89)\",\n \" (in 'rbmi_mmrm', line 14, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 15, column 8 to column 18)\",\n \" (in 'rbmi_mmrm', line 17, column 12 to column 48)\",\n \" (in 'rbmi_mmrm', line 18, column 12 to column 20)\",\n \" (in 'rbmi_mmrm', line 19, column 12 to column 33)\",\n \" (in 'rbmi_mmrm', line 16, column 38 to line 20, column 9)\",\n \" (in 'rbmi_mmrm', line 16, column 8 to line 20, column 9)\",\n \" (in 'rbmi_mmrm', line 21, column 8 to column 20)\",\n \" (in 'rbmi_mmrm', line 10, column 69 to line 22, column 5)\"};\nint integer_division(const int& a, const int& b, std::ostream* pstream__);\ntemplate <typename T0__,\n stan::require_all_t<stan::is_col_vector<T0__>,\n stan::is_vt_not_complex<T0__>>* = nullptr>\nstd::vector<\n Eigen::Matrix<stan::promote_args_t<stan::base_type_t<T0__>>,-1,1>>\nto_vector_of_arrays(const T0__& vec_arg__, const int& length_array,\n std::ostream* pstream__);\nint integer_division(const int& a, const int& b, std::ostream* pstream__) {\n using local_scalar_t__ = double;\n int current_statement__ = 0;\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int i = std::numeric_limits<int>::min();\n current_statement__ = 62;\n i = 0;\n current_statement__ = 65;\n while (stan::math::logical_lte((b * (i + 1)), a)) {\n current_statement__ = 63;\n i = (i + 1);\n }\n current_statement__ = 66;\n return i;\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n}\ntemplate <typename T0__,\n stan::require_all_t<stan::is_col_vector<T0__>,\n stan::is_vt_not_complex<T0__>>*>\nstd::vector<\n Eigen::Matrix<stan::promote_args_t<stan::base_type_t<T0__>>,-1,1>>\nto_vector_of_arrays(const T0__& vec_arg__, const int& length_array,\n std::ostream* pstream__) {\n using local_scalar_t__ = stan::promote_args_t<stan::base_type_t<T0__>>;\n int current_statement__ = 0;\n const auto& vec = stan::math::to_ref(vec_arg__);\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n current_statement__ = 68;\n stan::math::validate_non_negative_index(\"res\",\n \"integer_division(num_elements(vec), length_array)\",\n integer_division(stan::math::num_elements(vec), length_array, pstream__));\n current_statement__ = 69;\n stan::math::validate_non_negative_index(\"res\", \"length_array\",\n length_array);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> res =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(integer_division(\n stan::math::num_elements(\n vec),\n length_array,\n pstream__),\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(length_array,\n DUMMY_VAR__));\n int j = std::numeric_limits<int>::min();\n current_statement__ = 71;\n j = 1;\n int i = std::numeric_limits<int>::min();\n current_statement__ = 72;\n i = 1;\n current_statement__ = 77;\n while (stan::math::logical_lte(j, stan::math::num_elements(vec))) {\n current_statement__ = 73;\n stan::model::assign(res,\n stan::model::rvalue(vec, \"vec\",\n stan::model::index_min_max(j, ((j + length_array) - 1))),\n \"assigning variable res\", stan::model::index_uni(i),\n stan::model::index_omni());\n current_statement__ = 74;\n i = (i + 1);\n current_statement__ = 75;\n j = (j + length_array);\n }\n current_statement__ = 78;\n return res;\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n}\nclass modelaa9c6a27673f_rbmi_mmrm final : public model_base_crtp<modelaa9c6a27673f_rbmi_mmrm> {\nprivate:\n int N;\n int P;\n int G;\n int n_visit;\n int n_pat;\n std::vector<int> pat_G;\n std::vector<int> pat_n_pt;\n std::vector<int> pat_n_visit;\n std::vector<std::vector<int>> pat_sigma_index;\n Eigen::Matrix<double,-1,1> y_data__;\n Eigen::Matrix<double,-1,-1> Q_data__;\n Eigen::Matrix<double,-1,-1> R_data__;\n std::vector<Eigen::Matrix<double,-1,-1>> Sigma_init;\n Eigen::Matrix<double,-1,-1> R_inverse_data__;\n Eigen::Map<Eigen::Matrix<double,-1,1>> y{nullptr, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> Q{nullptr, 0, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> R{nullptr, 0, 0};\n Eigen::Map<Eigen::Matrix<double,-1,-1>> R_inverse{nullptr, 0, 0};\npublic:\n ~modelaa9c6a27673f_rbmi_mmrm() {}\n modelaa9c6a27673f_rbmi_mmrm(stan::io::var_context& context__, unsigned int\n random_seed__ = 0, std::ostream*\n pstream__ = nullptr) : model_base_crtp(0) {\n int current_statement__ = 0;\n using local_scalar_t__ = double;\n boost::ecuyer1988 base_rng__ =\n stan::services::util::create_rng(random_seed__, 0);\n // suppress unused var warning\n (void) base_rng__;\n static constexpr const char* function__ =\n \"modelaa9c6a27673f_rbmi_mmrm_namespace::modelaa9c6a27673f_rbmi_mmrm\";\n // suppress unused var warning\n (void) function__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n current_statement__ = 29;\n context__.validate_dims(\"data initialization\", \"N\", \"int\",\n std::vector<size_t>{});\n N = std::numeric_limits<int>::min();\n current_statement__ = 29;\n N = context__.vals_i(\"N\")[(1 - 1)];\n current_statement__ = 29;\n stan::math::check_greater_or_equal(function__, \"N\", N, 1);\n current_statement__ = 30;\n context__.validate_dims(\"data initialization\", \"P\", \"int\",\n std::vector<size_t>{});\n P = std::numeric_limits<int>::min();\n current_statement__ = 30;\n P = context__.vals_i(\"P\")[(1 - 1)];\n current_statement__ = 30;\n stan::math::check_greater_or_equal(function__, \"P\", P, 1);\n current_statement__ = 31;\n context__.validate_dims(\"data initialization\", \"G\", \"int\",\n std::vector<size_t>{});\n G = std::numeric_limits<int>::min();\n current_statement__ = 31;\n G = context__.vals_i(\"G\")[(1 - 1)];\n current_statement__ = 31;\n stan::math::check_greater_or_equal(function__, \"G\", G, 1);\n current_statement__ = 32;\n context__.validate_dims(\"data initialization\", \"n_visit\", \"int\",\n std::vector<size_t>{});\n n_visit = std::numeric_limits<int>::min();\n current_statement__ = 32;\n n_visit = context__.vals_i(\"n_visit\")[(1 - 1)];\n current_statement__ = 32;\n stan::math::check_greater_or_equal(function__, \"n_visit\", n_visit, 1);\n current_statement__ = 33;\n context__.validate_dims(\"data initialization\", \"n_pat\", \"int\",\n std::vector<size_t>{});\n n_pat = std::numeric_limits<int>::min();\n current_statement__ = 33;\n n_pat = context__.vals_i(\"n_pat\")[(1 - 1)];\n current_statement__ = 33;\n stan::math::check_greater_or_equal(function__, \"n_pat\", n_pat, 1);\n current_statement__ = 34;\n stan::math::validate_non_negative_index(\"pat_G\", \"n_pat\", n_pat);\n current_statement__ = 35;\n context__.validate_dims(\"data initialization\", \"pat_G\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_G = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 35;\n pat_G = context__.vals_i(\"pat_G\");\n current_statement__ = 35;\n stan::math::check_greater_or_equal(function__, \"pat_G\", pat_G, 1);\n current_statement__ = 36;\n stan::math::validate_non_negative_index(\"pat_n_pt\", \"n_pat\", n_pat);\n current_statement__ = 37;\n context__.validate_dims(\"data initialization\", \"pat_n_pt\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_n_pt = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 37;\n pat_n_pt = context__.vals_i(\"pat_n_pt\");\n current_statement__ = 37;\n stan::math::check_greater_or_equal(function__, \"pat_n_pt\", pat_n_pt, 1);\n current_statement__ = 38;\n stan::math::validate_non_negative_index(\"pat_n_visit\", \"n_pat\", n_pat);\n current_statement__ = 39;\n context__.validate_dims(\"data initialization\", \"pat_n_visit\", \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat)});\n pat_n_visit = std::vector<int>(n_pat, std::numeric_limits<int>::min());\n current_statement__ = 39;\n pat_n_visit = context__.vals_i(\"pat_n_visit\");\n current_statement__ = 39;\n stan::math::check_greater_or_equal(function__, \"pat_n_visit\",\n pat_n_visit, 1);\n current_statement__ = 40;\n stan::math::validate_non_negative_index(\"pat_sigma_index\", \"n_pat\",\n n_pat);\n current_statement__ = 41;\n stan::math::validate_non_negative_index(\"pat_sigma_index\", \"n_visit\",\n n_visit);\n current_statement__ = 42;\n context__.validate_dims(\"data initialization\", \"pat_sigma_index\",\n \"int\",\n std::vector<size_t>{static_cast<size_t>(n_pat),\n static_cast<size_t>(n_visit)});\n pat_sigma_index = std::vector<std::vector<int>>(n_pat,\n std::vector<int>(n_visit,\n std::numeric_limits<int>::min()));\n {\n std::vector<int> pat_sigma_index_flat__;\n current_statement__ = 42;\n pat_sigma_index_flat__ = context__.vals_i(\"pat_sigma_index\");\n current_statement__ = 42;\n pos__ = 1;\n current_statement__ = 42;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 42;\n for (int sym2__ = 1; sym2__ <= n_pat; ++sym2__) {\n current_statement__ = 42;\n stan::model::assign(pat_sigma_index,\n pat_sigma_index_flat__[(pos__ - 1)],\n \"assigning variable pat_sigma_index\",\n stan::model::index_uni(sym2__), stan::model::index_uni(sym1__));\n current_statement__ = 42;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 42;\n stan::math::check_greater_or_equal(function__, \"pat_sigma_index\",\n pat_sigma_index, 1);\n current_statement__ = 43;\n stan::math::validate_non_negative_index(\"y\", \"N\", N);\n current_statement__ = 44;\n context__.validate_dims(\"data initialization\", \"y\", \"double\",\n std::vector<size_t>{static_cast<size_t>(N)});\n y_data__ = Eigen::Matrix<double,-1,1>::Constant(N,\n std::numeric_limits<double>::quiet_NaN());\n new (&y) Eigen::Map<Eigen::Matrix<double,-1,1>>(y_data__.data(), N);\n {\n std::vector<local_scalar_t__> y_flat__;\n current_statement__ = 44;\n y_flat__ = context__.vals_r(\"y\");\n current_statement__ = 44;\n pos__ = 1;\n current_statement__ = 44;\n for (int sym1__ = 1; sym1__ <= N; ++sym1__) {\n current_statement__ = 44;\n stan::model::assign(y, y_flat__[(pos__ - 1)],\n \"assigning variable y\", stan::model::index_uni(sym1__));\n current_statement__ = 44;\n pos__ = (pos__ + 1);\n }\n }\n current_statement__ = 45;\n stan::math::validate_non_negative_index(\"Q\", \"N\", N);\n current_statement__ = 46;\n stan::math::validate_non_negative_index(\"Q\", \"P\", P);\n current_statement__ = 47;\n context__.validate_dims(\"data initialization\", \"Q\", \"double\",\n std::vector<size_t>{static_cast<size_t>(N), static_cast<size_t>(P)});\n Q_data__ = Eigen::Matrix<double,-1,-1>::Constant(N, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&Q) Eigen::Map<Eigen::Matrix<double,-1,-1>>(Q_data__.data(), N, P);\n {\n std::vector<local_scalar_t__> Q_flat__;\n current_statement__ = 47;\n Q_flat__ = context__.vals_r(\"Q\");\n current_statement__ = 47;\n pos__ = 1;\n current_statement__ = 47;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 47;\n for (int sym2__ = 1; sym2__ <= N; ++sym2__) {\n current_statement__ = 47;\n stan::model::assign(Q, Q_flat__[(pos__ - 1)],\n \"assigning variable Q\", stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 47;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 48;\n stan::math::validate_non_negative_index(\"R\", \"P\", P);\n current_statement__ = 49;\n stan::math::validate_non_negative_index(\"R\", \"P\", P);\n current_statement__ = 50;\n context__.validate_dims(\"data initialization\", \"R\", \"double\",\n std::vector<size_t>{static_cast<size_t>(P), static_cast<size_t>(P)});\n R_data__ = Eigen::Matrix<double,-1,-1>::Constant(P, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&R) Eigen::Map<Eigen::Matrix<double,-1,-1>>(R_data__.data(), P, P);\n {\n std::vector<local_scalar_t__> R_flat__;\n current_statement__ = 50;\n R_flat__ = context__.vals_r(\"R\");\n current_statement__ = 50;\n pos__ = 1;\n current_statement__ = 50;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 50;\n for (int sym2__ = 1; sym2__ <= P; ++sym2__) {\n current_statement__ = 50;\n stan::model::assign(R, R_flat__[(pos__ - 1)],\n \"assigning variable R\", stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 50;\n pos__ = (pos__ + 1);\n }\n }\n }\n current_statement__ = 51;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"G\", G);\n current_statement__ = 52;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"n_visit\",\n n_visit);\n current_statement__ = 53;\n stan::math::validate_non_negative_index(\"Sigma_init\", \"n_visit\",\n n_visit);\n current_statement__ = 54;\n context__.validate_dims(\"data initialization\", \"Sigma_init\", \"double\",\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)});\n Sigma_init = std::vector<Eigen::Matrix<double,-1,-1>>(G,\n Eigen::Matrix<double,-1,-1>::Constant(n_visit, n_visit,\n std::numeric_limits<double>::quiet_NaN()));\n {\n std::vector<local_scalar_t__> Sigma_init_flat__;\n current_statement__ = 54;\n Sigma_init_flat__ = context__.vals_r(\"Sigma_init\");\n current_statement__ = 54;\n pos__ = 1;\n current_statement__ = 54;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 54;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 54;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 54;\n stan::model::assign(Sigma_init, Sigma_init_flat__[(pos__ - 1)],\n \"assigning variable Sigma_init\",\n stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 54;\n pos__ = (pos__ + 1);\n }\n }\n }\n }\n current_statement__ = 55;\n stan::math::validate_non_negative_index(\"R_inverse\", \"P\", P);\n current_statement__ = 56;\n stan::math::validate_non_negative_index(\"R_inverse\", \"P\", P);\n current_statement__ = 57;\n R_inverse_data__ = Eigen::Matrix<double,-1,-1>::Constant(P, P,\n std::numeric_limits<double>::quiet_NaN());\n new (&R_inverse)\n Eigen::Map<Eigen::Matrix<double,-1,-1>>(R_inverse_data__.data(), P,\n P);\n current_statement__ = 57;\n stan::model::assign(R_inverse, stan::math::inverse(R),\n \"assigning variable R_inverse\");\n current_statement__ = 58;\n stan::math::validate_non_negative_index(\"theta\", \"P\", P);\n current_statement__ = 59;\n stan::math::validate_non_negative_index(\"Sigma\", \"G\", G);\n current_statement__ = 60;\n stan::math::validate_non_negative_index(\"Sigma\", \"n_visit\", n_visit);\n current_statement__ = 60;\n stan::math::validate_non_negative_index(\"Sigma\", \"n_visit\", n_visit);\n current_statement__ = 61;\n stan::math::validate_non_negative_index(\"beta\", \"P\", P);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n num_params_r__ = P + (G * (n_visit + ((n_visit * (n_visit - 1)) / 2)));\n }\n inline std::string model_name() const final {\n return \"modelaa9c6a27673f_rbmi_mmrm\";\n }\n inline std::vector<std::string> model_compile_info() const noexcept {\n return std::vector<std::string>{\"stanc_version = stanc3 v2.32.2\",\n \"stancflags = --\"};\n }\n template <bool propto__, bool jacobian__, typename VecR, typename VecI,\n stan::require_vector_like_t<VecR>* = nullptr,\n stan::require_vector_like_vt<std::is_integral, VecI>* = nullptr>\n inline stan::scalar_type_t<VecR>\n log_prob_impl(VecR& params_r__, VecI& params_i__, std::ostream*\n pstream__ = nullptr) const {\n using T__ = stan::scalar_type_t<VecR>;\n using local_scalar_t__ = T__;\n T__ lp__(0.0);\n stan::math::accumulator<T__> lp_accum__;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n static constexpr const char* function__ =\n \"modelaa9c6a27673f_rbmi_mmrm_namespace::log_prob\";\n // suppress unused var warning\n (void) function__;\n try {\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n current_statement__ = 1;\n theta = in__.template read<Eigen::Matrix<local_scalar_t__,-1,1>>(P);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n current_statement__ = 2;\n Sigma = in__.template read_constrain_cov_matrix<\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,\n jacobian__>(lp__, G, n_visit);\n {\n int data_start_row = std::numeric_limits<int>::min();\n current_statement__ = 4;\n data_start_row = 1;\n current_statement__ = 5;\n stan::math::validate_non_negative_index(\"mu\", \"N\", N);\n Eigen::Matrix<local_scalar_t__,-1,1> mu =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(N, DUMMY_VAR__);\n current_statement__ = 6;\n stan::model::assign(mu, stan::math::multiply(Q, theta),\n \"assigning variable mu\");\n current_statement__ = 9;\n for (int g = 1; g <= G; ++g) {\n current_statement__ = 7;\n lp_accum__.add(stan::math::inv_wishart_lpdf<propto__>(\n stan::model::rvalue(Sigma, \"Sigma\",\n stan::model::index_uni(g)), (n_visit + 2),\n stan::model::rvalue(Sigma_init, \"Sigma_init\",\n stan::model::index_uni(g))));\n }\n current_statement__ = 28;\n for (int i = 1; i <= n_pat; ++i) {\n int nvis = std::numeric_limits<int>::min();\n current_statement__ = 10;\n nvis = stan::model::rvalue(pat_n_visit, \"pat_n_visit\",\n stan::model::index_uni(i));\n int npt = std::numeric_limits<int>::min();\n current_statement__ = 11;\n npt = stan::model::rvalue(pat_n_pt, \"pat_n_pt\",\n stan::model::index_uni(i));\n int g = std::numeric_limits<int>::min();\n current_statement__ = 12;\n g = stan::model::rvalue(pat_G, \"pat_G\", stan::model::index_uni(i));\n current_statement__ = 13;\n stan::math::validate_non_negative_index(\"sig_index\", \"nvis\", nvis);\n std::vector<int> sig_index =\n std::vector<int>(nvis, std::numeric_limits<int>::min());\n current_statement__ = 14;\n stan::model::assign(sig_index,\n stan::model::rvalue(pat_sigma_index, \"pat_sigma_index\",\n stan::model::index_uni(i), stan::model::index_min_max(1, nvis)),\n \"assigning variable sig_index\");\n current_statement__ = 15;\n stan::math::validate_non_negative_index(\"sig\", \"nvis\", nvis);\n current_statement__ = 16;\n stan::math::validate_non_negative_index(\"sig\", \"nvis\", nvis);\n Eigen::Matrix<local_scalar_t__,-1,-1> sig =\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(nvis, nvis,\n DUMMY_VAR__);\n current_statement__ = 17;\n stan::model::assign(sig,\n stan::model::rvalue(\n stan::model::rvalue(Sigma, \"Sigma\", stan::model::index_uni(g)),\n \"Sigma[g]\", stan::model::index_multi(sig_index),\n stan::model::index_multi(sig_index)), \"assigning variable sig\");\n int data_stop_row = std::numeric_limits<int>::min();\n current_statement__ = 18;\n data_stop_row = (data_start_row + ((nvis * npt) - 1));\n current_statement__ = 19;\n stan::math::validate_non_negative_index(\"y_obs\", \"npt\", npt);\n current_statement__ = 20;\n stan::math::validate_non_negative_index(\"y_obs\", \"nvis\", nvis);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> y_obs =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(npt,\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(nvis,\n DUMMY_VAR__));\n current_statement__ = 21;\n stan::model::assign(y_obs,\n to_vector_of_arrays(\n stan::model::rvalue(y, \"y\",\n stan::model::index_min_max(data_start_row, data_stop_row)),\n nvis, pstream__), \"assigning variable y_obs\");\n current_statement__ = 22;\n stan::math::validate_non_negative_index(\"mu_obs\", \"npt\", npt);\n current_statement__ = 23;\n stan::math::validate_non_negative_index(\"mu_obs\", \"nvis\", nvis);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>> mu_obs =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,1>>(npt,\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(nvis,\n DUMMY_VAR__));\n current_statement__ = 24;\n stan::model::assign(mu_obs,\n to_vector_of_arrays(\n stan::model::rvalue(mu, \"mu\",\n stan::model::index_min_max(data_start_row, data_stop_row)),\n nvis, pstream__), \"assigning variable mu_obs\");\n current_statement__ = 25;\n lp_accum__.add(stan::math::multi_normal_lpdf<propto__>(y_obs,\n mu_obs, sig));\n current_statement__ = 26;\n data_start_row = (data_stop_row + 1);\n }\n }\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n lp_accum__.add(lp__);\n return lp_accum__.sum();\n }\n template <typename RNG, typename VecR, typename VecI, typename VecVar,\n stan::require_vector_like_vt<std::is_floating_point,\n VecR>* = nullptr, stan::require_vector_like_vt<std::is_integral,\n VecI>* = nullptr, stan::require_vector_vt<std::is_floating_point,\n VecVar>* = nullptr>\n inline void\n write_array_impl(RNG& base_rng__, VecR& params_r__, VecI& params_i__,\n VecVar& vars__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true, std::ostream*\n pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n stan::io::serializer<local_scalar_t__> out__(vars__);\n static constexpr bool propto__ = true;\n // suppress unused var warning\n (void) propto__;\n double lp__ = 0.0;\n // suppress unused var warning\n (void) lp__;\n int current_statement__ = 0;\n stan::math::accumulator<double> lp_accum__;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n constexpr bool jacobian__ = false;\n static constexpr const char* function__ =\n \"modelaa9c6a27673f_rbmi_mmrm_namespace::write_array\";\n // suppress unused var warning\n (void) function__;\n try {\n Eigen::Matrix<double,-1,1> theta =\n Eigen::Matrix<double,-1,1>::Constant(P,\n std::numeric_limits<double>::quiet_NaN());\n current_statement__ = 1;\n theta = in__.template read<Eigen::Matrix<local_scalar_t__,-1,1>>(P);\n std::vector<Eigen::Matrix<double,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<double,-1,-1>>(G,\n Eigen::Matrix<double,-1,-1>::Constant(n_visit, n_visit,\n std::numeric_limits<double>::quiet_NaN()));\n current_statement__ = 2;\n Sigma = in__.template read_constrain_cov_matrix<\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,\n jacobian__>(lp__, G, n_visit);\n out__.write(theta);\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n out__.write(stan::model::rvalue(Sigma, \"Sigma\",\n stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__)));\n }\n }\n }\n if (stan::math::logical_negation(\n (stan::math::primitive_value(emit_transformed_parameters__) ||\n stan::math::primitive_value(emit_generated_quantities__)))) {\n return ;\n }\n if (stan::math::logical_negation(emit_generated_quantities__)) {\n return ;\n }\n Eigen::Matrix<double,-1,1> beta =\n Eigen::Matrix<double,-1,1>::Constant(P,\n std::numeric_limits<double>::quiet_NaN());\n current_statement__ = 3;\n stan::model::assign(beta, stan::math::multiply(R_inverse, theta),\n \"assigning variable beta\");\n out__.write(beta);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n template <typename VecVar, typename VecI,\n stan::require_vector_t<VecVar>* = nullptr,\n stan::require_vector_like_vt<std::is_integral, VecI>* = nullptr>\n inline void\n unconstrain_array_impl(const VecVar& params_r__, const VecI& params_i__,\n VecVar& vars__, std::ostream* pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::deserializer<local_scalar_t__> in__(params_r__, params_i__);\n stan::io::serializer<local_scalar_t__> out__(vars__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n current_statement__ = 1;\n stan::model::assign(theta,\n in__.read<Eigen::Matrix<local_scalar_t__,-1,1>>(P),\n \"assigning variable theta\");\n out__.write(theta);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n current_statement__ = 2;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 2;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 2;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 2;\n stan::model::assign(Sigma, in__.read<local_scalar_t__>(),\n \"assigning variable Sigma\", stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__), stan::model::index_uni(sym1__));\n }\n }\n }\n out__.write_free_cov_matrix(Sigma);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n template <typename VecVar, stan::require_vector_t<VecVar>* = nullptr>\n inline void\n transform_inits_impl(const stan::io::var_context& context__, VecVar&\n vars__, std::ostream* pstream__ = nullptr) const {\n using local_scalar_t__ = double;\n stan::io::serializer<local_scalar_t__> out__(vars__);\n int current_statement__ = 0;\n local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());\n // suppress unused var warning\n (void) DUMMY_VAR__;\n try {\n current_statement__ = 1;\n context__.validate_dims(\"parameter initialization\", \"theta\", \"double\",\n std::vector<size_t>{static_cast<size_t>(P)});\n current_statement__ = 2;\n context__.validate_dims(\"parameter initialization\", \"Sigma\", \"double\",\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)});\n int pos__ = std::numeric_limits<int>::min();\n pos__ = 1;\n Eigen::Matrix<local_scalar_t__,-1,1> theta =\n Eigen::Matrix<local_scalar_t__,-1,1>::Constant(P, DUMMY_VAR__);\n {\n std::vector<local_scalar_t__> theta_flat__;\n current_statement__ = 1;\n theta_flat__ = context__.vals_r(\"theta\");\n current_statement__ = 1;\n pos__ = 1;\n current_statement__ = 1;\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n current_statement__ = 1;\n stan::model::assign(theta, theta_flat__[(pos__ - 1)],\n \"assigning variable theta\", stan::model::index_uni(sym1__));\n current_statement__ = 1;\n pos__ = (pos__ + 1);\n }\n }\n out__.write(theta);\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>> Sigma =\n std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>(G,\n Eigen::Matrix<local_scalar_t__,-1,-1>::Constant(n_visit, n_visit,\n DUMMY_VAR__));\n {\n std::vector<local_scalar_t__> Sigma_flat__;\n current_statement__ = 2;\n Sigma_flat__ = context__.vals_r(\"Sigma\");\n current_statement__ = 2;\n pos__ = 1;\n current_statement__ = 2;\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n current_statement__ = 2;\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n current_statement__ = 2;\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n current_statement__ = 2;\n stan::model::assign(Sigma, Sigma_flat__[(pos__ - 1)],\n \"assigning variable Sigma\", stan::model::index_uni(sym3__),\n stan::model::index_uni(sym2__),\n stan::model::index_uni(sym1__));\n current_statement__ = 2;\n pos__ = (pos__ + 1);\n }\n }\n }\n }\n out__.write_free_cov_matrix(Sigma);\n } catch (const std::exception& e) {\n stan::lang::rethrow_located(e, locations_array__[current_statement__]);\n }\n }\n inline void\n get_param_names(std::vector<std::string>& names__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true) const {\n names__ = std::vector<std::string>{\"theta\", \"Sigma\"};\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n std::vector<std::string> temp{\"beta\"};\n names__.reserve(names__.size() + temp.size());\n names__.insert(names__.end(), temp.begin(), temp.end());\n }\n }\n inline void\n get_dims(std::vector<std::vector<size_t>>& dimss__, const bool\n emit_transformed_parameters__ = true, const bool\n emit_generated_quantities__ = true) const {\n dimss__ = std::vector<std::vector<size_t>>{std::vector<size_t>{static_cast<\n size_t>(P)},\n std::vector<size_t>{static_cast<size_t>(G),\n static_cast<size_t>(n_visit), static_cast<size_t>(n_visit)}};\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n std::vector<std::vector<size_t>>\n temp{std::vector<size_t>{static_cast<size_t>(P)}};\n dimss__.reserve(dimss__.size() + temp.size());\n dimss__.insert(dimss__.end(), temp.begin(), temp.end());\n }\n }\n inline void\n constrained_param_names(std::vector<std::string>& param_names__, bool\n emit_transformed_parameters__ = true, bool\n emit_generated_quantities__ = true) const final {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"theta\" + '.' +\n std::to_string(sym1__));\n }\n for (int sym1__ = 1; sym1__ <= n_visit; ++sym1__) {\n for (int sym2__ = 1; sym2__ <= n_visit; ++sym2__) {\n for (int sym3__ = 1; sym3__ <= G; ++sym3__) {\n param_names__.emplace_back(std::string() + \"Sigma\" + '.' +\n std::to_string(sym3__) + '.' + std::to_string(sym2__) + '.' +\n std::to_string(sym1__));\n }\n }\n }\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"beta\" + '.' +\n std::to_string(sym1__));\n }\n }\n }\n inline void\n unconstrained_param_names(std::vector<std::string>& param_names__, bool\n emit_transformed_parameters__ = true, bool\n emit_generated_quantities__ = true) const final {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"theta\" + '.' +\n std::to_string(sym1__));\n }\n for (int sym1__ = 1; sym1__ <= (n_visit + ((n_visit * (n_visit - 1)) /\n 2)); ++sym1__) {\n for (int sym2__ = 1; sym2__ <= G; ++sym2__) {\n param_names__.emplace_back(std::string() + \"Sigma\" + '.' +\n std::to_string(sym2__) + '.' + std::to_string(sym1__));\n }\n }\n if (emit_transformed_parameters__) {}\n if (emit_generated_quantities__) {\n for (int sym1__ = 1; sym1__ <= P; ++sym1__) {\n param_names__.emplace_back(std::string() + \"beta\" + '.' +\n std::to_string(sym1__));\n }\n }\n }\n inline std::string get_constrained_sizedtypes() const {\n return std::string(\"[{\\\"name\\\":\\\"theta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"Sigma\\\",\\\"type\\\":{\\\"name\\\":\\\"array\\\",\\\"length\\\":\" + std::to_string(G) + \",\\\"element_type\\\":{\\\"name\\\":\\\"matrix\\\",\\\"rows\\\":\" + std::to_string(n_visit) + \",\\\"cols\\\":\" + std::to_string(n_visit) + \"}},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"beta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"generated_quantities\\\"}]\");\n }\n inline std::string get_unconstrained_sizedtypes() const {\n return std::string(\"[{\\\"name\\\":\\\"theta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"Sigma\\\",\\\"type\\\":{\\\"name\\\":\\\"array\\\",\\\"length\\\":\" + std::to_string(G) + \",\\\"element_type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string((n_visit + ((n_visit * (n_visit - 1)) /2))) + \"}},\\\"block\\\":\\\"parameters\\\"},{\\\"name\\\":\\\"beta\\\",\\\"type\\\":{\\\"name\\\":\\\"vector\\\",\\\"length\\\":\" + std::to_string(P) + \"},\\\"block\\\":\\\"generated_quantities\\\"}]\");\n }\n // Begin method overload boilerplate\n template <typename RNG> inline void\n write_array(RNG& base_rng, Eigen::Matrix<double,-1,1>& params_r,\n Eigen::Matrix<double,-1,1>& vars, const bool\n emit_transformed_parameters = true, const bool\n emit_generated_quantities = true, std::ostream*\n pstream = nullptr) const {\n const size_t num_params__ = (P + ((G * n_visit) * n_visit));\n const size_t num_transformed = emit_transformed_parameters * (0);\n const size_t num_gen_quantities = emit_generated_quantities * (P);\n const size_t num_to_write = num_params__ + num_transformed +\n num_gen_quantities;\n std::vector<int> params_i;\n vars = Eigen::Matrix<double,-1,1>::Constant(num_to_write,\n std::numeric_limits<double>::quiet_NaN());\n write_array_impl(base_rng, params_r, params_i, vars,\n emit_transformed_parameters, emit_generated_quantities, pstream);\n }\n template <typename RNG> inline void\n write_array(RNG& base_rng, std::vector<double>& params_r, std::vector<int>&\n params_i, std::vector<double>& vars, bool\n emit_transformed_parameters = true, bool\n emit_generated_quantities = true, std::ostream*\n pstream = nullptr) const {\n const size_t num_params__ = (P + ((G * n_visit) * n_visit));\n const size_t num_transformed = emit_transformed_parameters * (0);\n const size_t num_gen_quantities = emit_generated_quantities * (P);\n const size_t num_to_write = num_params__ + num_transformed +\n num_gen_quantities;\n vars = std::vector<double>(num_to_write,\n std::numeric_limits<double>::quiet_NaN());\n write_array_impl(base_rng, params_r, params_i, vars,\n emit_transformed_parameters, emit_generated_quantities, pstream);\n }\n template <bool propto__, bool jacobian__, typename T_> inline T_\n log_prob(Eigen::Matrix<T_,-1,1>& params_r, std::ostream* pstream = nullptr) const {\n Eigen::Matrix<int,-1,1> params_i;\n return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);\n }\n template <bool propto__, bool jacobian__, typename T_> inline T_\n log_prob(std::vector<T_>& params_r, std::vector<int>& params_i,\n std::ostream* pstream = nullptr) const {\n return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);\n }\n inline void\n transform_inits(const stan::io::var_context& context,\n Eigen::Matrix<double,-1,1>& params_r, std::ostream*\n pstream = nullptr) const final {\n std::vector<double> params_r_vec(params_r.size());\n std::vector<int> params_i;\n transform_inits(context, params_i, params_r_vec, pstream);\n params_r = Eigen::Map<Eigen::Matrix<double,-1,1>>(params_r_vec.data(),\n params_r_vec.size());\n }\n inline void\n transform_inits(const stan::io::var_context& context, std::vector<int>&\n params_i, std::vector<double>& vars, std::ostream*\n pstream__ = nullptr) const {\n vars.resize(num_params_r__);\n transform_inits_impl(context, vars, pstream__);\n }\n inline void\n unconstrain_array(const std::vector<double>& params_constrained,\n std::vector<double>& params_unconstrained, std::ostream*\n pstream = nullptr) const {\n const std::vector<int> params_i;\n params_unconstrained = std::vector<double>(num_params_r__,\n std::numeric_limits<double>::quiet_NaN());\n unconstrain_array_impl(params_constrained, params_i,\n params_unconstrained, pstream);\n }\n inline void\n unconstrain_array(const Eigen::Matrix<double,-1,1>& params_constrained,\n Eigen::Matrix<double,-1,1>& params_unconstrained,\n std::ostream* pstream = nullptr) const {\n const std::vector<int> params_i;\n params_unconstrained = Eigen::Matrix<double,-1,1>::Constant(num_params_r__,\n std::numeric_limits<double>::quiet_NaN());\n unconstrain_array_impl(params_constrained, params_i,\n params_unconstrained, pstream);\n }\n};\n}\nusing stan_model = modelaa9c6a27673f_rbmi_mmrm_namespace::modelaa9c6a27673f_rbmi_mmrm;\n#ifndef USING_R\n// Boilerplate\nstan::model::model_base&\nnew_model(stan::io::var_context& data_context, unsigned int seed,\n std::ostream* msg_stream) {\n stan_model* m = new stan_model(data_context, seed, msg_stream);\n return *m;\n}\nstan::math::profile_map& get_stan_profile_data() {\n return modelaa9c6a27673f_rbmi_mmrm_namespace::profiles__;\n}\n#endif\n#endif"), mk_cppmodule = function (object) { prep_call_sampler(object) model_cppname <- object@model_cpp$model_cppname mod <- get("module", envir = object@dso@.CXXDSOMISC, inherits = FALSE) eval(call("$", mod, paste("stan_fit4", model_cppname, sep = ""))) }, dso = new("cxxdso", sig = list(fileaa9c5c0bb1fd = character(0)), dso_saved = TRUE, dso_filename = "fileaa9c5c0bb1fd", modulename = "stan_fit4modelaa9c6a27673f_rbmi_mmrm_mod", system = "x86_64, darwin20", cxxflags = "CXXFLAGS = -falign-functions=64 -Wall -g -O2 $(LTO)", .CXXDSOMISC = <environment>)), data = list(N = 340L, P = 8L, G = 1L, n_visit = 3L, n_pat = 2L, pat_G = c(1, 1), pat_n_pt = c(60, 80), pat_n_visit = c(3, 2), pat_sigma_index = list( c(1, 2, 3), c(1, 2, 999)), y = c(0.574036883477536, 0.139105398171835, 0.176977232131814, -1.16935503183362, -1.21591438062592, -1.08964625296442, -1.58121597188229, -1.03382417471284, -0.813329718686652, -0.659208380311965, -0.596830231476417, -0.428690642917848, 1.19340919052579, 1.19324384350827, 1.14076998750238, 0.508301722783451, 0.285101803715272, -0.080275904172036, 0.420951505580432, 0.729295857616047, 0.606493590677628, 1.36133467580718, 0.785097805390841, 0.850728879541265, 1.59518647362531, 1.99123113996823, 1.62317993728234, -1.01500989395391, -1.29590087043236, -1.09167466441661, -1.92326503149754, -1.6438232242331, -2.09494484800456, -0.916339955699448, -1.21279752527853, -0.824654473194631, 0.160587572122124, 0.533787595446638, 0.509785626882552, 0.625441265387049, 0.869595429439695, 0.606754094352448, 0.416887452319262, 0.0527870943089152, -0.290746253299322, -0.0405562348050075, 0.138363916063878, 0.199662379261492, -0.0292589587575427, 0.184625776371717, 0.596974269230419, 0.460701441061857, 0.606107749594927, 0.675147663778399, 1.66002871020651, 1.84142634216536, 1.99191103632866, 1.10904044059033, 0.414249192109747, 0.672496352831966, 0.789592735008045, 0.677931435319177, 0.543093801624015, -0.899674446856585, -0.98731077385762, -1.31298117495064, -0.790921720329644, -0.407036721173524, -0.221080281874233, 1.43428989449746, 1.46018790177788, 1.29835543116011, 1.93804574039781, 1.67293427649682, 1.58849553103043, -1.01450332611738, -0.842813717586719, -0.629379340054354, -0.267415091390975, -0.657913697591214, -0.595234267484234, 0.120679904254403, 0.178945058091685, 0.258466389498271, -0.449519107207705, -0.418311943730978, -0.607987725151117, 0.475470586549514, 0.465961733342575, 0.628255437173784, -0.269181976386959, -0.489283917847538, -0.480553495290893, 0.0126097945506521, 0.188893941324742, -0.00785768753235569, -1.64359171150621, -1.51956953580399, -1.83648421907106, -0.334174407608112, 0.173961399031304, 0.512090615451255, 0.815812442864812, 1.00796572845926, 1.08799807363422, -0.499836503819652, -0.194917201294718, -0.347531934556113, 0.0967719422298859, 0.0448422069391228, -0.0380229372755732, 0.89027308837742, 0.923859648959303, 0.693773508152388, 0.0200206385163762, 0.139715592410514, 0.355610280019225, -0.554244284647314, -0.337491541079209, -0.0476717323926215, 1.74097877156221, 1.74584951452271, 1.87453426708686, 1.53665210908614, 1.27351842521603, 0.782842422447314, 0.780226954526566, 0.533531436107968, 0.471968788026106, -1.50987360873711, -1.4213975714265, -1.32130245857978, -1.53643170343886, -1.96117485895016, -1.63868589576792, -0.0924369697453538, -0.236384532458898, -0.416943554508815, 0.524748546809872, 1.01066900867255, 1.03925121395702, -1.47575422517021, -1.84351894914451, -1.96406505049471, -0.958450708965594, -1.00073327233577, -1.15403786283949, 1.30985852929418, 0.677518704253333, 0.633123295459129, -1.00859795137567, -0.486351090482834, -0.629987247106474, -0.703803757755735, -0.423015811624416, -0.68260822611802, 1.29970709660456, 0.950166424412677, 0.700867866424596, 0.885973022497435, 0.69557127871005, 0.683167942482159, -0.448047722773281, -0.345122636504496, -0.44919578758697, -0.350389882825743, 0.218778679169879, 0.460591876155823, -1.13643984701411, -1.37594847426891, -1.38924924598483, 1.05497189150375, 1.44213159591197, 1.44244341883156, 0.989297127175544, 1.28938706033795, 0.974021459136989, 0.0997949939225535, 0.0977838256866348, 0.152771705034039, 0.0563099671794369, -0.109302500409893, -0.770343945290974, -0.840203655711169, -1.06621935574191, -0.818506844251997, 0.483309359293258, -0.077312553568267, -1.82787954030716, -1.51850241691396, 0.385765772873327, 0.318930612816827, 0.0529827480329966, -0.256048504100078, 0.755705549841678, 0.841931688341897, 0.712085742232759, 0.644772892574503, -1.14155231656161, -1.4428233579315, -1.05021841671635, -1.39451198199354, -0.267077536825949, -0.707269786974737, -1.45623361118695, -1.14058269087304, -0.768761960571674, -0.570612606157713, -0.764238909934079, -1.27539783051645, -0.845195950602966, -1.35937750037253, -0.403679174325962, -0.181315302498918, -0.138311056457262, -0.0706441028516794, 0.508084112959793, 0.620362254164868, 0.480866966820087, 0.576196611808272, -1.14455494641288, -1.35096340386058, 0.550675910279237, 0.825037960508207, 1.61286207896739, 1.67916701468662, -0.0647658829962172, -0.266749386462743, -0.282320438961451, -0.774105813761362, -0.361641848210371, -0.0216017435394257, 1.42387705128602, 1.23207105462671, 0.265776870737417, 0.515102201270055, 0.771782662506529, 0.702063509689375, 0.616876705707196, 0.789738509590256, 0.971362277748469, 0.738026162904697, 0.534226435971703, 0.045703700581884, -1.14177405496358, -0.787101784899203, -0.872756204009667, -1.09360825060612, -0.968020452649131, -0.801211978871774, 1.52141486581132, 1.40439441624722, 1.79137191952656, 1.47694519657773, -1.9360028677803, -1.12357338931634, -0.442997879839818, -0.564318885154016, 0.000626204404452472, -0.27075649131444, -2.48336093478472, -1.92707335118885, 0.366175672975573, -0.232532349854313, 0.445155531890445, 0.769878306810777, -1.60791560029354, -1.71327349294041, -0.296398526983666, -0.367067711718188, -0.838340929698702, -1.43768210681618, -0.14561552296282, -0.0941334404913737, -0.0164394933059202, 0.0218434792651633, 1.07286404251878, 1.18723665035218, -0.138595585019409, 0.0131822076110258, -0.399908316171867, -0.868639920226593, 0.7981208661895, 0.719218310535082, 0.914826810253791, 0.705606688741132, 2.27692308241729, 2.20307732877354, -1.38708681157136, -1.25624461004343, 0.0942383865047231, 0.619729596216058, -1.97029658377716, -2.12452350098981, -0.546587071142227, -0.965112515688056, -0.0103825230207238, 0.275006295304356, 1.39505387642203, 1.13837400657299, 0.653655010243044, 0.592910348706071, 2.26190956828622, 2.20569250608316, -0.979542016063513, -0.948366938019486, 0.0839816881469963, 0.496574287039973, 0.547933703350616, 0.492939941225062, -0.375076840950679, -0.483574365532446, 1.3297009420447, 1.69844054391049, -1.13265693702497, -0.849277428071457, -1.13312754672772, -0.666195857133899, 0.459008637041986, 0.595690989575909, 1.50283257817443, 1.73920182026267, -0.300363476632086, -0.00897291528474771, -1.40333016095241, -1.19317961021338, -0.600226062637804, -0.325957148423221, 0.870433641965308, 0.130170018966925, -1.77311671749508, -1.19314004127747, 1.7640917533291, 1.44334725535403, -0.871065290131151, -1.32437155254469, 0.853886175567914, 0.646816118526293, 0.294983239652497, -0.326121365030516), Q = c(-0.99852832885673, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.998528328856729, -0.958225137302622, -0.958225137302671, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, 1.04052668283787, 1.04052668283787, 1.04052668283787, 1.04052668283787, -0.958225137302672, -0.958225137302672, -0.825360566675442, 1.20365082640164, -0.825360566675414, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.825360566675413, 1.20365082640164, -0.825360566675413, -0.846458740670183, 1.18255265240687, -0.846458740670183, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.846458740670183, 1.18255265240687, -0.846458740670183, 1.18255265240687, -0.825360566675413, 1.20365082640164, -0.876442111269587, -0.024403432792697, 1.96548118704492, -0.826199749637548, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.876442111269578, -0.0244034327926988, 1.96548118704497, -0.826199749637549, 0.0258389288393301, 2.015723548677, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.826199749637549, 0.0258389288393301, -0.826199749637549, 0.0258389288393301, -0.876442111269578, -0.0244034327926988, -0.377816532241714, -0.377816532241718, -0.457024666869012, -1.12880551077197, -1.12880551077196, -1.20801364539926, -0.220331575027453, -0.220331575027453, -0.29953970965475, 0.183702853067903, 0.183702853067903, 0.104494718440605, 1.12384497625067, 1.12384497625067, 1.04463684162337, 1.24707949620404, 1.24707949620404, 1.16787136157674, -0.610672320738653, -0.610672320738653, -0.689880455365951, 0.815513912349393, 0.815513912349393, 0.736305777722095, 1.07768856337481, 1.07768856337481, 0.99848042874751, -0.116268012873417, -0.116268012873417, -0.195476147500715, -1.75570733327889, -1.75570733327889, -1.83491546790618, 0.38821352691705, 0.388213526917049, 0.309005392289752, 2.38726637449642, 2.38726637449642, 2.30805823986912, 0.0978089234405026, 0.0978089234405023, 0.0186007888132049, 0.480311137245768, 0.480311137245767, 0.40110300261847, -1.36360112479173, -1.36360112479173, -1.44280925941902, 1.93535965542202, 1.93535965542202, 1.85615152079472, 0.394010340671377, 0.394010340671377, 0.314802206044079, 1.61374775950545, 1.61374775950545, 1.53453962487815, -0.964178039762375, -0.964178039762375, -1.04338617438967, -0.798757765014893, -0.798757765014893, -0.87796589964219, -1.0944257408576, -1.0944257408576, -1.1736338754849, 0.377586753964714, 0.377586753964714, 0.298378619337416, 1.37498679426785, 1.37498679426785, 1.29577865964055, 1.68915587438649, 1.68915587438649, 1.6099477397592, 0.992596467936866, 0.992596467936865, 0.913388333309568, -0.323261319416317, -0.323261319416317, -0.402469454043615, -1.53070167383635, -1.53070167383635, -1.60990980846365, 0.985012371873182, 0.985012371873181, 0.905804237245884, -0.83124291903249, -0.83124291903249, -0.910451053659788, 0.875900958465542, 0.875900958465542, 0.796692823838244, -0.599874960211679, -0.59987496021168, -0.679083094838977, -1.21249941889568, -1.21249941889568, -1.29170755352297, 0.10152732719712, 0.10152732719712, 0.0223191925698222, 0.273641473500582, 0.273641473500581, 0.194433338873284, 0.132099054317715, 0.132099054317715, 0.0528909196904172, -0.834302902018013, -0.834302902018014, -0.913511036645311, 0.719369062657609, 0.719369062657609, 0.640160928030311, -1.14019031831383, -1.14019031831383, -1.21939845294113, -0.986131847575652, -0.986131847575652, -1.06533998220295, 1.121130179697, 1.121130179697, 1.0419220450697, 0.901558128109497, 0.901558128109497, 0.822349993482199, -0.786141113615663, -0.786141113615663, -0.865349248242961, -0.713749729008484, -0.713749729008484, -0.792957863635781, -1.21024198127622, -1.21024198127622, -1.28945011590352, -1.48456568414046, -1.48456568414046, -1.56377381876776, 1.07705092477044, 1.07705092477044, 0.99784279014314, -1.51414471003321, -1.51414471003321, -1.59335284466051, 0.197021223835606, 0.197021223835606, 0.117813089208309, -0.992651143019504, -0.992651143019504, -1.0718592776468, -0.214255998107591, -0.214255998107591, -0.293464132734889, 0.855083280875347, 0.855083280875347, 0.77587514624805, 0.424765963693628, 0.424765963693628, 0.34555782906633, 0.364243987733107, 0.364243987733107, 0.285035853105809, 0.148975237666157, 0.148975237666156, 0.0697671030388588, -0.057416806838183, -0.0574168068381832, -0.136624941465481, -0.469756237118641, -0.469756237118641, -0.548964371745938, 1.07464366058924, 1.07464366058924, 0.995435525961942, 0.220197215402141, 0.22019721540214, 0.140989080774843, 2.43308733556931, 2.43308733556931, 2.35387920094201, -0.792463299943419, -0.792463299943419, 0.398667166152911, 0.398667166152911, -0.507624730755423, -0.507624730755423, -1.14063678811883, -1.14063678811883, -0.610719518834707, -0.610719518834707, 0.0372742888124956, 0.0372742888124953, 1.60469817459311, 1.60469817459311, -0.335089450474223, -0.335089450474223, 0.398797186950103, 0.398797186950103, -1.47882967397224, -1.47882967397224, -0.667444462142149, -0.66744446214215, -0.649446871595376, -0.649446871595376, -0.279713473009783, -0.279713473009783, 0.109041394826028, 0.109041394826028, -1.47272080463623, -1.47272080463623, -0.463549540361751, -0.463549540361752, -1.00365185771742, -1.00365185771742, -0.808089317383245, -0.808089317383245, 0.145106160657612, 0.145106160657612, 0.190373516579835, 0.190373516579835, -1.11324014885282, -1.11324014885282, 0.0373498895331294, 0.0373498895331292, 0.934861192278438, 0.934861192278438, 0.526171571037054, 0.526171571037054, -0.127064672854489, -0.127064672854489, 0.107735669014991, 0.107735669014991, 1.63023634780781, 1.63023634780781, -1.01842798000048, -1.01842798000048, 0.0915540560676067, 0.0915540560676064, -0.69105660373921, -0.69105660373921, -0.510325739757003, -0.510325739757004, -0.758316424407092, -0.758316424407092, 0.66850966666813, 0.66850966666813, 0.207547505355721, 0.207547505355721, -0.957302855842871, -0.957302855842871, 0.871306376044677, 0.871306376044677, 0.854052678949774, 0.854052678949774, -1.02517751500326, -1.02517751500326, -0.14387122685017, -0.14387122685017, 0.0439935573727569, 0.0439935573727567, -1.13877102137595, -1.13877102137595, 1.36106121128242, 1.36106121128242, 0.07551027826328, 0.0755102782632798, -1.39505728407859, -1.39505728407859, -1.55223678517323, -1.55223678517323, -0.783810528384146, -0.783810528384147, -1.23550391017333, -1.23550391017333, -1.34099290537528, -1.34099290537528, 0.282522679370366, 0.282522679370366, 1.05047246454719, 1.05047246454719, 0.406048469121015, 0.406048469121015, 0.239493257040229, 0.239493257040228, 0.534396153202169, 0.534396153202169, 2.04605670576315, 2.04605670576315, -0.0259943875448687, -0.0259943875448689, 1.56185162485783, 1.56185162485783, -1.89056227250461, -1.89056227250461, -0.819059954351738, -0.819059954351738, -0.481442518835015, -0.481442518835015, -0.0511676754622085, -0.0511676754622088, 2.24057972203455, 2.24057972203455, 1.5234804097995, 1.5234804097995, -0.344361395338917, -0.344361395338917, -0.0415535968630459, -0.0415535968630462, -0.0255793897214689, -0.0255793897214691, -0.0639754794004533, -0.0639754794004536, 1.29091591700363, 1.29091591700363, 0.678498611351185, 0.678498611351185, 1.04860191122785, 1.04860191122785, -0.768540785317964, -0.768540785317964, 1.30809002082778, 1.30809002082778, -0.47706971830725, -0.47706971830725, -1.38225666633996, -1.38225666633996, -0.898631124236369, -0.898631124236369, 0.673024870752781, 0.673024870752781, -0.410390025474452, -0.410390025474452, 1.85569424316007, 1.85569424316007, -1.42890995686216, -1.42890995686216, 2.09388845185187, 2.09388845185187, -0.769321140423713, -0.769321140423714, 0.928218267300235, 0.928218267300184, 0.865629305624082, -0.901905120181537, -0.901905120181534, -0.964494081857647, -0.949986114091021, -0.94998611409102, -1.01257507576713, -0.971369641027934, -0.971369641027932, -1.03395860270405, 0.848742814011857, 0.848742814011858, 0.786153852335745, -1.02764886257788, -1.02764886257788, -1.09023782425399, -1.06643981685835, -1.06643981685835, -1.12902877853447, 0.865061239254727, 0.865061239254728, 0.802472277578616, -1.1557963368333, -1.1557963368333, -1.21838529850942, 1.05148830018635, 1.05148830018635, 0.988899338510239, 1.13825564581723, 1.13825564581723, 1.07566668414112, 1.02478860866219, 1.0247886086622, 0.962199646986083, 0.918988712806694, 0.918988712806695, 0.856399751130582, 0.903045784372422, 0.903045784372423, 0.84045682269631, -0.987067638013804, -0.987067638013803, -1.04965659968992, -1.02659105090308, -1.02659105090308, -1.08918001257919, -1.06407609823243, -1.06407609823243, -1.12666505990854, 0.887369320824584, 0.887369320824586, 0.824780359148473, -1.18416727619675, -1.18416727619675, -1.24675623787286, -1.0477305224531, -1.04773052245309, -1.11031948412921, -1.0564853924716, -1.0564853924716, -1.11907435414771, -0.903724669915239, -0.903724669915238, -0.96631363159135, -0.981630948800652, -0.981630948800651, -1.04421991047676, 0.835451130291062, 0.835451130291064, 0.772862168614951, 0.818823727970098, 0.818823727970099, 0.756234766293987, 0.99280163428372, 0.992801634283721, 0.930212672607609, -0.944538556138783, -0.944538556138781, -1.00712751781489, -1.01774725234731, -1.01774725234731, -1.08033621402342, 0.993203022658554, 0.993203022658555, 0.930614060982442, -1.05476611530688, -1.05476611530688, -1.11735507698299, 0.998977745517508, 0.998977745517509, 0.936388783841396, 0.939970712255066, 0.939970712255067, 0.877381750578954, 1.1095063604548, 1.10950636045481, 1.04691739877869, 0.902848987809151, 0.902848987809153, 0.84026002613304, -1.11324213498986, -1.11324213498985, -1.17583109666597, -0.96863850936219, -0.968638509362189, -1.0312274710383, 0.952377813877598, 0.952377813877599, 0.889788852201486, 0.870149706574013, 0.870149706574014, 0.807560744897902, -1.03841507050665, -1.03841507050665, -1.10100403218276, 0.960413362636251, 0.960413362636252, 0.897824400960139, -1.15809548489647, -1.15809548489647, -1.22068444657258, 0.860507348107022, 0.860507348107023, 0.79791838643091, -1.05715312889772, -1.05715312889772, -1.11974209057384, 1.0831100271553, 1.0831100271553, 1.02052106547919, 1.10938688554181, 1.10938688554181, 1.0467979238657, 0.986792979394893, 0.986792979394894, 0.924204017718781, 0.85121938974584, 0.851219389745841, 0.788630428069729, 1.12547094109423, 1.12547094109423, 1.06288197941812, 1.03490746358836, 1.03490746358836, 0.972318501912247, -1.04622358312283, -1.04622358312283, -1.10881254479895, -0.950307664072134, -0.950307664072133, -1.01289662574825, 1.00007952135283, 1.00007952135283, 0.937490559676719, 0.885741579108468, 0.88574157910847, 0.823152617432357, 0.888944705409679, 0.888944705409681, 0.826355743733568, -0.96953168156765, -0.969531681567649, -1.03212064324376, 0.911261108003043, 0.911261108003044, 0.848672146326931, 1.07019666868025, 1.07019666868025, 1.00760770700414, -1.15563518531698, -1.15563518531698, -1.21822414699309, -1.1104135969911, -1.1104135969911, -1.17300255866722, 0.916563637894152, 0.916563637894153, 0.85397467621804, 0.950163452437635, 0.950163452437636, 1.02423534968067, 1.02423534968067, -0.934781120389717, -0.934781120389716, 0.968590538461504, 0.968590538461505, 1.07765715205019, 1.0776571520502, 0.906249580633761, 0.906249580633762, 0.960406144141665, 0.960406144141666, -1.08102504356151, -1.08102504356151, 0.887115976928059, 0.88711597692806, -0.883380087159851, -0.883380087159849, 1.08065932035285, 1.08065932035285, -0.927275181890372, -0.927275181890371, 1.06013865311795, 1.06013865311795, -0.967418182457954, -0.967418182457952, -0.883703399142486, -0.883703399142485, 1.06986817918019, 1.06986817918019, 0.961340609382444, 0.961340609382446, 0.950990459597437, 0.950990459597438, 0.900542577527299, 0.9005425775273, 0.898146802173973, 0.898146802173975, -0.902728917147178, -0.902728917147177, 0.906245579464717, 0.906245579464718, -1.14823719651062, -1.14823719651062, -0.98949480202044, -0.989494802020438, -0.95492226600347, -0.954922266003468, -0.967349076903795, -0.967349076903794, 0.821942044618619, 0.82194204461862, -1.04485934371747, -1.04485934371747, 0.903376823302905, 0.903376823302906, -1.06218547771961, -1.06218547771961, -1.07175066085639, -1.07175066085638, 0.948356228641671, 0.948356228641673, 1.00995393211511, 1.00995393211511, 1.03435036001307, 1.03435036001307, -0.910981900243858, -0.910981900243856, -1.14487355710169, -1.14487355710169, -1.14396040497669, -1.14396040497669, -0.907389633096397, -0.907389633096396, -0.954032778932337, -0.954032778932336, -0.963975524883135, -0.963975524883134, 1.1056042841347, 1.1056042841347, 0.973300633337403, 0.973300633337404, -1.10275603911339, -1.10275603911339, -0.887813741896416, -0.887813741896414, 0.990374473226015, 0.990374473226016, -0.920163983748597, -0.920163983748596, 0.973611382030312, 0.973611382030313, -1.02778759118596, -1.02778759118596, -1.11371217291668, -1.11371217291668, -1.01724343307714, -1.01724343307713, 1.02384469413284, 1.02384469413285, -1.11143484022547, -1.11143484022547, 0.879939400018172, 0.879939400018173, -1.20704723234541, -1.20704723234541, 1.04671056748668, 1.04671056748668, -1.04430818124978, -1.04430818124978, 1.14539284508785, 1.14539284508785, -0.918298407457879, -0.918298407457877, 0.933702673879424, 0.933702673879425, -1.09605160689812, -1.09605160689812, -1.0802298739066, -1.0802298739066, -1.17938987563448, -1.17938987563448, 1.06356014518004, 1.06356014518004, 0.910421547425474, 0.910421547425475, 0.909576112321545, 0.909576112321546, -0.958261262321214, -0.958261262321213, -1.1670813970731, -1.1670813970731, 1.00942526709835, 1.00942526709835, 0.989837545528036, 0.989837545528038, -1.05808462648328, -1.05808462648328, -1.1679903367233, -1.1679903367233, 0.933471243359218, 0.933471243359219, -0.888491214743256, -0.888491214743254, 0.955782385807506, 0.955782385807507, -0.997267014663429, -0.997267014663428, 1.0670547112193, 1.0670547112193, 0.8100096828119, 0.810009682811901, -0.886022088784659, -0.886022088784658, -1.07246623667859, -1.07246623667859, 0.948938653368405, 0.948938653368406, 0.822922780507105, -1.1501950067864, 0.761524154870805, -0.884042163308671, 1.20514137617857, -0.945440788944958, -0.8764883205467, 1.21269521894054, -0.937886946182985, -0.873128826762482, 1.21605471272476, -0.93452745239877, 0.835408900879507, -1.137708886414, 0.774010275243219, -0.864286988110919, 1.22489655137632, -0.925685613747207, 0.79384135565294, -1.17927643164056, 0.732442730016652, 0.832845168136384, -1.14027261915712, 0.771446542500097, 0.807879857080727, -1.16523793021277, 0.746481231444439, -0.848477786323998, 1.24070575316324, -0.909876411960286, -0.862109511304625, 1.22707402818261, -0.923508136940912, -0.844283087854447, 1.24490045163279, -0.905681713490735, -0.827661223110346, 1.26152231637689, -0.889059848746634, 0.826877544385839, -1.14624024290766, 0.765478918749551, -0.870662567409932, 1.21852097207731, -0.93206119304622, 0.78758085045516, -1.18553693683834, 0.726182224818872, -0.858564027996871, 1.23061951149037, -0.919962653633159, 0.829340420692578, -1.14377736660092, 0.76794179505629, 0.812337119660705, -1.1607806676328, 0.750938494024418, 0.79090200152081, -1.18221578577269, 0.729503375884522, 0.792277449616699, -1.1808403376768, 0.730878823980412, -0.883756299987876, 1.20542723949936, -0.945154925624164, -0.87151670731268, 1.21766683217456, -0.932915332948968, 0.837497112472174, -1.13562067482133, 0.776098486835886, 0.840109387561767, -1.13300839973174, 0.778710761925479, -0.839257722211194, 1.24992581727604, -0.900656347847481, -0.87734416800038, 1.21183937148686, -0.938742793636667, 0.786191431096763, -1.18692635619674, 0.724792805460476, -0.839320782984764, 1.24986275650247, -0.900719408621052, 0.792007339780971, -1.18111044751253, 0.730608714144683, -0.840228030213318, 1.24895550927392, -0.901626655849606, 0.821076393524696, -1.15204139376881, 0.759677767888408, -0.857592808061018, 1.23159073142622, -0.918991433697306, 0.826908462430042, -1.14620932486346, 0.765509836793755, 0.801194309976777, -1.17192347731673, 0.739795684340489, -0.873557905645587, 1.21562563384165, -0.934956531281875, 0.819127155641534, -1.15399063165197, 0.757728530005247, 0.832045736200728, -1.14107205109277, 0.770647110564441, 0.789438482289227, -1.18367930500428, 0.728039856652939, 0.817864717682301, -1.1552530696112, 0.756466092046013, 0.808241068477237, -1.16487671881626, 0.74684244284095, 0.833560614613004, -1.1395571726805, 0.772161988976716, 0.792382355434139, -1.18073543185936, 0.730983729797852, -0.853445769178827, 1.23573777030841, -0.914844394815115, -0.857574037760461, 1.23160950172678, -0.918972663396749, 0.813720305079455, -1.15939748221405, 0.752321679443167, 0.835019814420149, -1.13809797287335, 0.773621188783862, -0.860100949472114, 1.22908259001512, -0.921499575108402, -0.845872827018062, 1.24331071246918, -0.90727145265435, 0.790665251365976, -1.18245253592753, 0.729266625729689, -0.876437802913846, 1.21274573657339, -0.937836428550134, -0.840401126498196, 1.24878241298904, -0.901799752134484, 0.829596149702751, -1.14352163759075, 0.768197524066464, 0.829092917334643, -1.14402486995886, 0.767694291698356, -0.873417582373317, 1.21576595711392, -0.934816208009604, 0.825586862602903, -1.1475309246906, 0.764188236966615, -0.851416994989318, 1.23776654449792, -0.912815620625605, 0.807854539109608, -1.16526324818389, 0.74645591347332, 0.800749927913273, -1.17236785938023, 0.739351302276985, -0.827280227771318, 1.26190331171592, -0.888678853407606, 0.819475046497683, -1.15364274079582, -0.844196167202163, 1.24498737228508, -0.878877125816253, 1.21030641367099, 0.816580029172383, -1.15653775812112, -0.852589086365194, 1.23659445312204, 0.826374206762554, -1.14674358053095, -0.834168176034367, 1.25501536345287, 0.79613279142007, -1.17698499587343, 0.829380222697559, -1.14373756459594, -0.886952568756393, 1.20223097073085, -0.853060746900039, 1.2361227925872, -0.880056358494176, 1.20912718099306, -0.849836814092931, 1.23934672539431, -0.873749627088995, 1.21543391239824, -0.886901774301426, 1.20228176518581, -0.851365387112054, 1.23781815237518, 0.817719041073879, -1.15539874621962, 0.819345118192542, -1.15377266910096, 0.827270814769233, -1.14584697252427, 0.827647206953348, -1.14547058034015, -0.883912739346304, 1.20527080014094, 0.826374835372726, -1.14674295192078, 0.806692266043805, -1.1664255212497, -0.870281243860378, 1.21890229562686, -0.875712818370806, 1.21347072111643, -0.873760484029496, 1.21542305545774, 0.839619479352104, -1.1334983079414, 0.790450920314975, -1.18266686697853, 0.826825535976161, -1.14629225131734, 0.793172970781972, -1.17994481651153, 0.794675724438452, -1.17844206285505, 0.819758973331977, -1.15335881396153, -0.841952461863805, 1.24723107762343, -0.845785302354621, 1.24339823713262, -0.882616141011691, 1.20656739847555, 0.8061638160028, -1.1669539712907, 0.806020353752768, -1.16709743354073, -0.883180509985469, 1.20600302950177, -0.875852562684054, 1.21333097680318, -0.874290491407491, 1.21489304807975, -0.856979766013203, 1.23220377347404, -0.836193985735054, 1.25298955375218, 0.799546874826271, -1.17357091246723, -0.886256012216735, 1.2029275272705, 0.813157628665065, -1.15996015862844, -0.881173574846094, 1.20800996464114, 0.81579122137605, -1.15732656591745, 0.787768834862726, -1.18534895243078, 0.801268156049886, -1.17184963124362, -0.865921750039247, 1.22326178944799, -0.844134792626839, 1.2450487468604, 0.800910371992874, -1.17220741530063, 0.830507710487194, -1.14261007680631, 0.815931712390488, -1.15718607490301, -0.847727172856231, 1.24145636663101, -0.861669698751094, 1.22751384073614, -0.863230812606188, 1.22595272688105, -0.881466669243999, 1.20771687024324, 0.82206114388998, -1.15105664340352, 0.798493564096925, -1.17462422319658, -0.856026162792076, 1.23315737669516, 0.811586558373925, -1.16153122891958, -0.850374353169121, 1.23880918631812, 0.825718763133163, -1.14739902416034, 0.825851586590444, -1.14726620070306, -0.875188239922729, 1.21399529956451, 0.809652814827218, -1.16346497246628, -0.841869405086362, 1.24731413440088, -0.83879204422552, 1.25039149526172, 0.792528699877594, -1.18058908741591, 0.809795615269543, -1.16332217202396, 0.822097503158327, -1.15102028413518, -0.886149576743081, 1.20303396274416, 0.818592274830236, -1.15452551246327, -0.869060177749967, 1.22012336173727, -0.850923372651362, 1.23826016683588, 0.841494132464238, -1.13162365482926, -0.886537492793357, 1.20264604669388, -0.857245881647968, 1.23193765783927, 0.819667470547847, -1.15345031674566, 0.803861462573047, -0.0211329139384156, -1.82131769404675, -0.820744084523179, 0.0527793729593497, 2.26118636758273, -0.838810415568061, 0.0347130419146569, 2.24312003653804, -0.846845230265783, 0.026678227216929, 2.23508522184031, 0.77399873028981, -0.0509956462216396, -1.85118042633002, -0.867992027883424, 0.00553142959928859, 2.21393842422267, 0.873414756866236, 0.0484203803547872, -1.75176439975359, 0.780130343815119, -0.0448640326963297, -1.84504881280471, 0.839839234822993, 0.0148448583115435, -1.78533992179684, -0.905802488338423, -0.0322790308557106, 2.17612796376767, -0.873199843039792, 0.000323614442920459, 2.2087306090663, -0.915834840555904, -0.0423113830731918, 2.16609561155019, -0.95558892606041, -0.0820654685776981, 2.12634152604568, 0.79440295573263, -0.0305914207788192, -1.8307762008872, -0.852743719195093, 0.0207797382876193, 2.229186732911, 0.888387845792513, 0.0633934692810632, -1.73679131082732, -0.881679484087365, -0.00815602660465274, 2.20025096801873, 0.788512557946793, -0.0364818185646559, -1.83666659867304, 0.829178914789803, 0.0041845382783543, -1.79600024183003, 0.88044473438655, 0.0554503578751003, -1.74473442223328, 0.87715511062575, 0.0521607341143012, -1.74802404599408, -0.82142777646, 0.0520956810227126, 2.26050267564609, -0.850700894803883, 0.0228225626788291, 2.23122955730221, 0.769004408444191, -0.0559899680672583, -1.85617474817564, 0.762756697439936, -0.0622376790715132, -1.86242245917989, -0.927853878043513, -0.0543304205608001, 2.15407657406258, -0.836763507271285, 0.0367599502114277, 2.24516694483481, 0.891710884261762, 0.0667165077503133, -1.73346827235807, -0.927703057216662, -0.0541795997339494, 2.15422739488943, 0.877801125358181, 0.0528067488467312, -1.74737803126165, -0.925533217403083, -0.0520097599203713, 2.15639723470301, 0.808277418731149, -0.0167169577802998, -1.81690173788868, -0.884002325776186, -0.0104788682934731, 2.19792812632991, 0.794329009843176, -0.0306653666682737, -1.83085014677665, 0.855828885521429, 0.0308345090099801, -1.7693502710984, -0.845819013359934, 0.0277044441227784, 2.23611143874616, 0.812939360737585, -0.0120550157738646, -1.81223979588224, 0.782042324571453, -0.0429520519399964, -1.84313683204838, 0.883944995612685, 0.0589506191012357, -1.74123416100714, 0.815958701067214, -0.00903567544423477, -1.80922045555261, 0.838975334835647, 0.0139809583241984, -1.78620382178418, 0.778419228916563, -0.0465751475948864, -1.84675992770327, 0.876904210085971, 0.0519098335745217, -1.74827494653386, -0.893920691786934, -0.0203972343042217, 2.18800976031916, -0.884047218220252, -0.010523760737539, 2.19788323388584, 0.825870785873341, 0.000876409361892246, -1.79930837074649, 0.774929298346527, -0.0500650781649221, -1.8502498582733, -0.878003668606899, -0.00448021112418726, 2.20392678349919, -0.91203270237146, -0.0385092448887477, 2.16989774973463, 0.88101096362998, 0.0560165871185309, -1.74416819298985, -0.838931237288528, 0.0345922201941843, 2.24299921481756, -0.925119227479842, -0.0515957699971294, 2.15681122462625, 0.787900937464197, -0.0370934390472518, -1.83727821915563, 0.789104505348933, -0.0358898711625159, -1.8360746512709, -0.846154620913599, 0.0273688365691129, 2.23577583119249, 0.797489846087465, -0.0275045304239841, -1.82768931053236, -0.898772858727331, -0.025249401244619, 2.18315759337876, 0.839899787161985, 0.0149054106505359, -1.78527936945784, 0.856891702649422, 0.0318973261379731, -1.76828745397041, -0.956500142793173, -0.0829766853104602, 2.12543030931292, 0.812107319143305, -0.0128870573681433, -0.916042726439721, -0.0425192689570086, -0.83309717157278, 0.0404262859099321, 0.81903125746544, -0.00596311904600874, -0.895969597992568, -0.0224461405098556, 0.795606775353457, -0.0293876011579923, -0.940026414459111, -0.0665029569763992, 0.867934389000357, 0.0429400124889075, 0.788417364517319, -0.0365770119941302, -0.813783342825435, 0.0597401146572771, -0.894841539647731, -0.0213180821650186, -0.830276831169969, 0.0432466263127437, -0.902552136650396, -0.0290286791676837, -0.845360478125072, 0.0281629793576404, -0.813904826614228, 0.059618630868485, -0.898896287957265, -0.025372830474553, 0.816307112056978, -0.00868726445447075, 0.812418065322002, -0.0125763111894468, 0.793462381092629, -0.0315319954188206, 0.792562173606831, -0.0324322029046178, -0.821053624478443, 0.0524698330042695, 0.795605271922712, -0.0293891045887376, 0.842679565697599, 0.0176851891861495, -0.853655720900511, 0.0198677365822016, -0.840665164134714, 0.0328582933479981, -0.845334511860298, 0.0281889456224142, 0.763928398278325, -0.0610659782331235, 0.881523573680594, 0.0565291971691448, 0.794527342905617, -0.0304670336058325, 0.875013315735499, 0.0500189392240497, 0.871419218546547, 0.0464248420350977, 0.81142825865152, -0.0135661178599293, -0.921408938669288, -0.047885481186576, -0.912242032853194, -0.0387185753704815, -0.824154665297431, 0.0493687921852809, 0.843943446040652, 0.0189490695292029, 0.844286561006527, 0.0192921844950779, -0.822804878568622, 0.0507185789140902, -0.840330941262423, 0.0331925162202896, -0.844066906874501, 0.0294565506082113, -0.885468522641695, -0.011945065158983, -0.935181337610223, -0.0616578801275106, 0.859769013710692, 0.0347746371992431, -0.81544927914862, 0.0580741783340921, 0.827216524551485, 0.00222214804003571, -0.827604813615682, 0.0459186438670304, 0.820917828741576, -0.0040765477698727, 0.887938248329957, 0.0629438718185078, 0.855652269771647, 0.0306578932601976, -0.86408220991301, 0.00944124756970293, -0.916189514429685, -0.0426660569469729, 0.856507972679448, 0.0315135961679986, 0.785720781030177, -0.0392735954812725, 0.820581820003289, -0.00441255650816027, -0.90759771122333, -0.0340742537406174, -0.874251731388556, -0.00072827390584424, -0.870518055616725, 0.0030054018659874, -0.826903827298288, 0.0466196301844241, 0.805922216662982, -0.0190721598484675, 0.862288189834544, 0.0372938133230945, -0.887749230887956, -0.014225773405243, 0.830974012874789, 0.00597963636334023, -0.901266518296148, -0.0277430608134351, 0.797174382988782, -0.0278199935226667, 0.796856712549333, -0.028137663962116, -0.841919784888747, 0.0316036725939652, 0.835598897476072, 0.0106045209646224, -0.921607583423233, -0.0480841259405207, -0.928967628079688, -0.0554441705969753, 0.876554201852371, 0.0515598253409218, 0.835257365338632, 0.0102629888271829, 0.805835257137982, -0.0191591193734673, -0.815703838127743, 0.0578196193549695, 0.814218621388206, -0.0107757551232429, -0.856576113245609, 0.0169473442371033, -0.899953442550635, -0.0264299850679229, 0.759444838746444, -0.0655495377650052, -0.814776069308258, 0.058747388174454, -0.884832060736767, -0.0113086032540545, 0.811647103501974, -0.0133472730094756 ), R = c(-1.00147384015129, 0, 0, 0, 0, 0, 0, 0, -0.521355499137583, -0.500312239830598, 0, 0, 0, 0, 0, 0, -0.412371581238766, 0.00520237329552464, 0.492850855057777, 0, 0, 0, 0, 0, -0.176730677673757, -0.0104047465910492, -0.147761901765143, 0.351874380491925, 0, 0, 0, 0, -0.0148145536477168, -0.0628921007447697, -0.0117315667981618, 0.0279370916994833, 1.00236007528132, 0, 0, 0, -0.480118341013706, 0.0345264174379645, 0.00491668361530068, -0.0117083969584963, -0.0263704470162966, -0.498260577419346, 0, 0, -0.212076813208509, -0.203516843320922, 0.25564265339504, -0.00518302997367062, 0.00222305092368008, 0.00332949514226805, -0.246165884693855, 0, -0.0972018727205666, -0.0932785531887564, -0.0803448339241552, 0.191330027057476, -0.00444610184736015, -0.00665899028453591, 0.0732625048297967, -0.175220044568803), Sigma_init = list( c(0.135928026518976, 0.0348523498539469, 0.00728419213566572, 0.0348523498539469, 0.0345033646543252, 0.00223741352686764, 0.00728419213566572, 0.00223741352686764, 0.0129045826930864 ))), pars = c("beta", "Sigma"), chains = 1, warmup = 200, thin = 2, iter = 204, init = list(list(theta = c(-5.9502531301265e-05, -0.745820423193819, -0.00612121696522099, 0.00358076868728952, 0.552831864322152, -0.281246666814181, -0.00509794025644147, -0.00632342582509301), sigma = list(Placebo = c(0.135928026518976, 0.0348523498539469, 0.00728419213566572, 0.0348523498539469, 0.0345033646543252, 0.00223741352686764, 0.00728419213566572, 0.00223741352686764, 0.0129045826930864), TRT = c(0.135928026518976, 0.0348523498539469, 0.00728419213566572, 0.0348523498539469, 0.0345033646543252, 0.00223741352686764, 0.00728419213566572, 0.00223741352686764, 0.0129045826930864)))), refresh = 0, seed = 2053082391L)
11: do.call(rstan::sampling, sampling_args)
12: doWithOneRestart(return(expr), restart)
13: withOneRestart(expr, restarts[[1L]])
14: withRestarts(expr, muffleStop = function() list())
15: withCallingHandlers(withRestarts(expr, muffleStop = function() list()), message = function(m) { env$message <- c(env$message, m$message) invokeRestart("muffleMessage") }, warning = function(w) { env$warning <- c(env$warning, w$message) invokeRestart("muffleWarning") }, error = function(e) { env$error <- c(env$error, e$message) invokeRestart("muffleStop") })
16: record({ do.call(rstan::sampling, sampling_args)})
17: fit_mcmc(designmat = model_df_scaled[, -1, drop = FALSE], outcome = model_df_scaled[, 1, drop = TRUE], group = data2[[vars$group]], visit = data2[[vars$visit]], subjid = data2[[vars$subjid]], method = method, quiet = quiet)
18: draws.bayes(d$dat, d$dat_ice, d$vars, meth, quiet = TRUE)
19: draws(d$dat, d$dat_ice, d$vars, meth, quiet = TRUE)
20: withCallingHandlers(expr, warning = function(w) if (inherits(w, classes)) tryInvokeRestart("muffleWarning"))
21: suppressWarnings({ draws(d$dat, d$dat_ice, d$vars, meth, quiet = TRUE)})
22: eval(code, test_env)
23: eval(code, test_env)
24: withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error)
25: doTryCatch(return(expr), name, parentenv, handler)
26: tryCatchOne(expr, names, parentenv, handlers[[1L]])
27: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
28: doTryCatch(return(expr), name, parentenv, handler)
29: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]])
30: tryCatchList(expr, classes, parentenv, handlers)
31: tryCatch(withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error), error = handle_fatal, skip = function(e) { })
32: test_code(desc, code, env = parent.frame(), default_reporter = local_interactive_reporter())
33: test_that("bayes", { set.seed(40123) d <- get_data(140) meth <- method_bayes(n_samples = 2, burn_in = 200, burn_between = 2) dobj <- suppressWarnings({ draws(d$dat, d$dat_ice, d$vars, meth, quiet = TRUE) }) standard_checks(dobj, d, meth) expect_length(dobj$samples, 2) expect_true(all(vapply(dobj$samples, function(x) all(x$ids == levels(d$dat$id)), logical(1))))})
34: eval(code, test_env)
35: eval(code, test_env)
36: withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error)
37: doTryCatch(return(expr), name, parentenv, handler)
38: tryCatchOne(expr, names, parentenv, handlers[[1L]])
39: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
40: doTryCatch(return(expr), name, parentenv, handler)
41: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]])
42: tryCatchList(expr, classes, parentenv, handlers)
43: tryCatch(withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error), error = handle_fatal, skip = function(e) { })
44: test_code(test = NULL, code = exprs, env = env, default_reporter = StopReporter$new())
45: source_file(path, env = env(env), desc = desc, error_call = error_call)
46: FUN(X[[i]], ...)
47: lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call)
48: doTryCatch(return(expr), name, parentenv, handler)
49: tryCatchOne(expr, names, parentenv, handlers[[1L]])
50: tryCatchList(expr, classes, parentenv, handlers)
51: tryCatch(code, testthat_abort_reporter = function(cnd) { cat(conditionMessage(cnd), "\n") NULL})
52: with_reporter(reporters$multi, lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call))
53: test_files_serial(test_dir = test_dir, test_package = test_package, test_paths = test_paths, load_helpers = load_helpers, reporter = reporter, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, desc = desc, load_package = load_package, error_call = error_call)
54: test_files(test_dir = path, test_paths = test_paths, test_package = package, reporter = reporter, load_helpers = load_helpers, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, load_package = load_package, parallel = parallel)
55: test_dir("testthat", package = package, reporter = reporter, ..., load_package = "installed")
56: test_check("rbmi")
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-release-macos-x86_64