CRAN Package Check Results for Package reservr

Last updated on 2024-06-20 08:54:57 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.0.2 185.69 151.22 336.91 ERROR
r-devel-linux-x86_64-debian-gcc 0.0.2 127.41 111.20 238.61 ERROR
r-devel-linux-x86_64-fedora-clang 0.0.2 461.84 ERROR
r-devel-linux-x86_64-fedora-gcc 0.0.2 497.54 ERROR
r-devel-windows-x86_64 0.0.2 134.00 214.00 348.00 ERROR
r-patched-linux-x86_64 0.0.2 119.92 183.92 303.84 NOTE
r-release-linux-x86_64 0.0.2 114.46 186.31 300.77 NOTE
r-release-macos-arm64 0.0.2 118.00 NOTE
r-release-macos-x86_64 0.0.2 317.00 NOTE
r-release-windows-x86_64 0.0.2 125.00 253.00 378.00 NOTE
r-oldrel-macos-arm64 0.0.2 124.00 NOTE
r-oldrel-macos-x86_64 0.0.2 444.00 NOTE
r-oldrel-windows-x86_64 0.0.2 173.00 257.00 430.00 NOTE

Additional issues

clang-UBSAN gcc-UBSAN valgrind

Check Details

Version: 0.0.2
Check: for GNU extensions in Makefiles
Result: NOTE GNU make is a SystemRequirements. Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64

Version: 0.0.2
Check: examples
Result: ERROR Running examples in ‘reservr-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: fit_erlang_mixture > ### Title: Fit an Erlang mixture using an ECME-Algorithm > ### Aliases: fit_erlang_mixture > > ### ** Examples > > dist <- dist_erlangmix(list(NULL, NULL, NULL)) > params <- list( + shapes = list(1L, 4L, 12L), + scale = 2.0, + probs = list(0.5, 0.3, 0.2) + ) > x <- dist$sample(100L, with_params = params) > fit_erlang_mixture(dist, x, init = "kmeans") *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: pgamma_diff_matrix(obs$xmin[i_cens], obs$xmax[i_cens], shapes, scale) 2: .erlang_dens_mat(obs, shapes, scale, i_obs, i_cens) 3: .erlang_em(obs = obs, probs = as.numeric(params$probs), shapes = shapes, scale = params$scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 4: em_fit(shapes, list(probs = as.list(probs), scale = scale)) 5: .erlang_shape_search(obs = obs, probs = probs, shapes = shapes, scale = scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 6: fit_erlang_mixture(dist, x, init = "kmeans") An irrecoverable exception occurred. R is aborting now ... Segmentation fault Examples with CPU (user + system) or elapsed time > 5s user system elapsed fit_dist 6.395 0.094 7.605 Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.0.2
Check: tests
Result: ERROR Running ‘testthat.R’ [10s/13s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(reservr) > > test_check("reservr") ── Skip ('/home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/reservr.Rcheck/tests/testthat/helpers.R:13:3'): set floatx to 64-bit ── Reason: TensorFlow not available for testing *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: pgamma_diff_matrix(obs$xmin[i_cens], obs$xmax[i_cens], shapes, scale) 2: .erlang_dens_mat(obs, shapes, scale, i_obs, i_cens) 3: .erlang_em(obs = obs, probs = as.numeric(params$probs), shapes = shapes, scale = params$scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 4: em_fit(shapes, list(probs = as.list(probs), scale = scale)) 5: .erlang_shape_search(obs = obs, probs = probs, shapes = shapes, scale = scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 6: fit_dist.ErlangMixtureDistribution(dist = object, obs = obs, start = start, ...) 7: fit_dist(dist = object, obs = obs, start = start, ...) 8: fit.Distribution(dist, x, init = "shapes", shapes = as.numeric(params$shapes)) 9: fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes)) 10: eval_bare(quo_get_expr(.quo), quo_get_env(.quo)) 11: withVisible(code) 12: withCallingHandlers(withVisible(code), warning = handle_warning, message = handle_message) 13: force(code) 14: withr::with_output_sink(path, withCallingHandlers(withVisible(code), warning = handle_warning, message = handle_message)) 15: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), ...) 16: quasi_capture(enquo(object), NULL, evaluate_promise) 17: expect_silent(fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes))) 18: eval(code, test_env) 19: eval(code, test_env) 20: 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) 21: doTryCatch(return(expr), name, parentenv, handler) 22: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 23: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) 24: doTryCatch(return(expr), name, parentenv, handler) 25: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) 26: tryCatchList(expr, classes, parentenv, handlers) 27: 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) { }) 28: test_code(desc, code, env = parent.frame(), default_reporter = local_interactive_reporter()) 29: test_that("erlang mixture distribution works", { set.seed(1337L) dist <- dist_erlangmix(list(NULL, NULL, NULL)) params <- list(shapes = list(1L, 4L, 12L), scale = 2, probs = list(0.5, 0.3, 0.2)) alt_params <- list(shapes = list(2L, 6L, 100L), scale = 0.1, probs = list(0.7, 0.2, 0.1)) x <- dist$sample(100L, with_params = params) expect_silent(fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes))) expect_silent(fit(dist, x, init = "fan", spread = 3L)) expect_silent(fit(dist, x, init = "kmeans")) expect_silent(fit(dist, x, init = "cmm")) expect_identical(dist$get_type(), "continuous") expect_density(dist, function(x, log = FALSE, ...) { params <- list(...) res <- (params$probs[[1L]] * dgamma(x, shape = params$shapes[[1L]], scale = params$scale) + params$probs[[2L]] * dgamma(x, shape = params$shapes[[2L]], scale = params$scale) + params$probs[[3L]] * dgamma(x, shape = params$shapes[[3L]], scale = params$scale))/sum(as.numeric(params$probs)) if (log) log(res) else res }, params, x) expect_probability(dist, function(q, lower.tail = TRUE, log.p = FALSE, ...) { params <- list(...) res <- (params$probs[[1L]] * pgamma(q, shape = params$shapes[[1L]], scale = params$scale, lower.tail = lower.tail) + params$probs[[2L]] * pgamma(q, shape = params$shapes[[2L]], scale = params$scale, lower.tail = lower.tail) + params$probs[[3L]] * pgamma(q, shape = params$shapes[[3L]], scale = params$scale, lower.tail = lower.tail))/sum(as.numeric(params$probs)) if (log.p) log(res) else res }, params, x) expect_identical(dist$is_in_support(x), rep_len(TRUE, length(x))) expect_diff_density(dist, x, params) expect_diff_density(dist, x, alt_params) expect_tf_logdensity(dist, params, x) expect_tf_logdensity(dist, alt_params, x, tolerance = 1e-05) expect_tf_logprobability(dist, params, x, x + 1) expect_tf_logprobability(dist, params, x, rep_len(Inf, 100L)) expect_tf_logprobability(dist, params, rep_len(0, 100L), x) x_alt <- dist$sample(100L, with_params = alt_params) expect_tf_logprobability(dist, alt_params, x_alt, x_alt + 1) expect_iprobability(dist, params, x, x + 1) expect_iprobability(dist, params, 0, x) expect_iprobability(dist, params, x, Inf) dist$default_params$shapes <- params$shapes expect_tf_fit(dist, params[c("scale", "probs")], I_POSITIVE_REALS)}) 30: eval(code, test_env) 31: eval(code, test_env) 32: 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) 33: doTryCatch(return(expr), name, parentenv, handler) 34: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 35: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) 36: doTryCatch(return(expr), name, parentenv, handler) 37: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) 38: tryCatchList(expr, classes, parentenv, handlers) 39: 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) { }) 40: test_code(test = NULL, code = exprs, env = env, default_reporter = StopReporter$new()) 41: source_file(path, env = env(env), desc = desc, error_call = error_call) 42: FUN(X[[i]], ...) 43: lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call) 44: doTryCatch(return(expr), name, parentenv, handler) 45: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 46: tryCatchList(expr, classes, parentenv, handlers) 47: tryCatch(code, testthat_abort_reporter = function(cnd) { cat(conditionMessage(cnd), "\n") NULL}) 48: with_reporter(reporters$multi, lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call)) 49: 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) 50: 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) 51: test_dir("testthat", package = package, reporter = reporter, ..., load_package = "installed") 52: test_check("reservr") An irrecoverable exception occurred. R is aborting now ... Segmentation fault Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.0.2
Check: examples
Result: ERROR Running examples in ‘reservr-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: fit_erlang_mixture > ### Title: Fit an Erlang mixture using an ECME-Algorithm > ### Aliases: fit_erlang_mixture > > ### ** Examples > > dist <- dist_erlangmix(list(NULL, NULL, NULL)) > params <- list( + shapes = list(1L, 4L, 12L), + scale = 2.0, + probs = list(0.5, 0.3, 0.2) + ) > x <- dist$sample(100L, with_params = params) > fit_erlang_mixture(dist, x, init = "kmeans") *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: pgamma_diff_matrix(obs$xmin[i_cens], obs$xmax[i_cens], shapes, scale) 2: .erlang_dens_mat(obs, shapes, scale, i_obs, i_cens) 3: .erlang_em(obs = obs, probs = as.numeric(params$probs), shapes = shapes, scale = params$scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 4: em_fit(shapes, list(probs = as.list(probs), scale = scale)) 5: .erlang_shape_search(obs = obs, probs = probs, shapes = shapes, scale = scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 6: fit_erlang_mixture(dist, x, init = "kmeans") An irrecoverable exception occurred. R is aborting now ... Segmentation fault Examples with CPU (user + system) or elapsed time > 5s user system elapsed fit_dist 4.384 0.085 6.93 Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.0.2
Check: tests
Result: ERROR Running ‘testthat.R’ [7s/11s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(reservr) > > test_check("reservr") ── Skip ('/home/hornik/tmp/R.check/r-devel-gcc/Work/PKGS/reservr.Rcheck/tests/testthat/helpers.R:13:3'): set floatx to 64-bit ── Reason: TensorFlow not available for testing *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: pgamma_diff_matrix(obs$xmin[i_cens], obs$xmax[i_cens], shapes, scale) 2: .erlang_dens_mat(obs, shapes, scale, i_obs, i_cens) 3: .erlang_em(obs = obs, probs = as.numeric(params$probs), shapes = shapes, scale = params$scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 4: em_fit(shapes, list(probs = as.list(probs), scale = scale)) 5: .erlang_shape_search(obs = obs, probs = probs, shapes = shapes, scale = scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 6: fit_dist.ErlangMixtureDistribution(dist = object, obs = obs, start = start, ...) 7: fit_dist(dist = object, obs = obs, start = start, ...) 8: fit.Distribution(dist, x, init = "shapes", shapes = as.numeric(params$shapes)) 9: fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes)) 10: eval_bare(quo_get_expr(.quo), quo_get_env(.quo)) 11: withVisible(code) 12: withCallingHandlers(withVisible(code), warning = handle_warning, message = handle_message) 13: force(code) 14: withr::with_output_sink(path, withCallingHandlers(withVisible(code), warning = handle_warning, message = handle_message)) 15: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), ...) 16: quasi_capture(enquo(object), NULL, evaluate_promise) 17: expect_silent(fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes))) 18: eval(code, test_env) 19: eval(code, test_env) 20: 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) 21: doTryCatch(return(expr), name, parentenv, handler) 22: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 23: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) 24: doTryCatch(return(expr), name, parentenv, handler) 25: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) 26: tryCatchList(expr, classes, parentenv, handlers) 27: 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) { }) 28: test_code(desc, code, env = parent.frame(), default_reporter = local_interactive_reporter()) 29: test_that("erlang mixture distribution works", { set.seed(1337L) dist <- dist_erlangmix(list(NULL, NULL, NULL)) params <- list(shapes = list(1L, 4L, 12L), scale = 2, probs = list(0.5, 0.3, 0.2)) alt_params <- list(shapes = list(2L, 6L, 100L), scale = 0.1, probs = list(0.7, 0.2, 0.1)) x <- dist$sample(100L, with_params = params) expect_silent(fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes))) expect_silent(fit(dist, x, init = "fan", spread = 3L)) expect_silent(fit(dist, x, init = "kmeans")) expect_silent(fit(dist, x, init = "cmm")) expect_identical(dist$get_type(), "continuous") expect_density(dist, function(x, log = FALSE, ...) { params <- list(...) res <- (params$probs[[1L]] * dgamma(x, shape = params$shapes[[1L]], scale = params$scale) + params$probs[[2L]] * dgamma(x, shape = params$shapes[[2L]], scale = params$scale) + params$probs[[3L]] * dgamma(x, shape = params$shapes[[3L]], scale = params$scale))/sum(as.numeric(params$probs)) if (log) log(res) else res }, params, x) expect_probability(dist, function(q, lower.tail = TRUE, log.p = FALSE, ...) { params <- list(...) res <- (params$probs[[1L]] * pgamma(q, shape = params$shapes[[1L]], scale = params$scale, lower.tail = lower.tail) + params$probs[[2L]] * pgamma(q, shape = params$shapes[[2L]], scale = params$scale, lower.tail = lower.tail) + params$probs[[3L]] * pgamma(q, shape = params$shapes[[3L]], scale = params$scale, lower.tail = lower.tail))/sum(as.numeric(params$probs)) if (log.p) log(res) else res }, params, x) expect_identical(dist$is_in_support(x), rep_len(TRUE, length(x))) expect_diff_density(dist, x, params) expect_diff_density(dist, x, alt_params) expect_tf_logdensity(dist, params, x) expect_tf_logdensity(dist, alt_params, x, tolerance = 1e-05) expect_tf_logprobability(dist, params, x, x + 1) expect_tf_logprobability(dist, params, x, rep_len(Inf, 100L)) expect_tf_logprobability(dist, params, rep_len(0, 100L), x) x_alt <- dist$sample(100L, with_params = alt_params) expect_tf_logprobability(dist, alt_params, x_alt, x_alt + 1) expect_iprobability(dist, params, x, x + 1) expect_iprobability(dist, params, 0, x) expect_iprobability(dist, params, x, Inf) dist$default_params$shapes <- params$shapes expect_tf_fit(dist, params[c("scale", "probs")], I_POSITIVE_REALS)}) 30: eval(code, test_env) 31: eval(code, test_env) 32: 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) 33: doTryCatch(return(expr), name, parentenv, handler) 34: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 35: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) 36: doTryCatch(return(expr), name, parentenv, handler) 37: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) 38: tryCatchList(expr, classes, parentenv, handlers) 39: 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) { }) 40: test_code(test = NULL, code = exprs, env = env, default_reporter = StopReporter$new()) 41: source_file(path, env = env(env), desc = desc, error_call = error_call) 42: FUN(X[[i]], ...) 43: lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call) 44: doTryCatch(return(expr), name, parentenv, handler) 45: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 46: tryCatchList(expr, classes, parentenv, handlers) 47: tryCatch(code, testthat_abort_reporter = function(cnd) { cat(conditionMessage(cnd), "\n") NULL}) 48: with_reporter(reporters$multi, lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call)) 49: 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) 50: 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) 51: test_dir("testthat", package = package, reporter = reporter, ..., load_package = "installed") 52: test_check("reservr") An irrecoverable exception occurred. R is aborting now ... Segmentation fault Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.0.2
Check: examples
Result: ERROR Running examples in ‘reservr-Ex.R’ failed The error most likely occurred in: > ### Name: fit_erlang_mixture > ### Title: Fit an Erlang mixture using an ECME-Algorithm > ### Aliases: fit_erlang_mixture > > ### ** Examples > > dist <- dist_erlangmix(list(NULL, NULL, NULL)) > params <- list( + shapes = list(1L, 4L, 12L), + scale = 2.0, + probs = list(0.5, 0.3, 0.2) + ) > x <- dist$sample(100L, with_params = params) > fit_erlang_mixture(dist, x, init = "kmeans") *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: pgamma_diff_matrix(obs$xmin[i_cens], obs$xmax[i_cens], shapes, scale) 2: .erlang_dens_mat(obs, shapes, scale, i_obs, i_cens) 3: .erlang_em(obs = obs, probs = as.numeric(params$probs), shapes = shapes, scale = params$scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 4: em_fit(shapes, list(probs = as.list(probs), scale = scale)) 5: .erlang_shape_search(obs = obs, probs = probs, shapes = shapes, scale = scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 6: fit_erlang_mixture(dist, x, init = "kmeans") An irrecoverable exception occurred. R is aborting now ... Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Version: 0.0.2
Check: tests
Result: ERROR Running ‘testthat.R’ [13s/39s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(reservr) > > test_check("reservr") ── Skip ('/data/gannet/ripley/R/packages/tests-clang/reservr.Rcheck/tests/testthat/helpers.R:13:3'): set floatx to 64-bit ── Reason: TensorFlow not available for testing *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: pgamma_diff_matrix(obs$xmin[i_cens], obs$xmax[i_cens], shapes, scale) 2: .erlang_dens_mat(obs, shapes, scale, i_obs, i_cens) 3: .erlang_em(obs = obs, probs = as.numeric(params$probs), shapes = shapes, scale = params$scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 4: em_fit(shapes, list(probs = as.list(probs), scale = scale)) 5: .erlang_shape_search(obs = obs, probs = probs, shapes = shapes, scale = scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 6: fit_dist.ErlangMixtureDistribution(dist = object, obs = obs, start = start, ...) 7: fit_dist(dist = object, obs = obs, start = start, ...) 8: fit.Distribution(dist, x, init = "shapes", shapes = as.numeric(params$shapes)) 9: fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes)) 10: eval_bare(quo_get_expr(.quo), quo_get_env(.quo)) 11: withVisible(code) 12: withCallingHandlers(withVisible(code), warning = handle_warning, message = handle_message) 13: force(code) 14: withr::with_output_sink(path, withCallingHandlers(withVisible(code), warning = handle_warning, message = handle_message)) 15: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), ...) 16: quasi_capture(enquo(object), NULL, evaluate_promise) 17: expect_silent(fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes))) 18: eval(code, test_env) 19: eval(code, test_env) 20: 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) 21: doTryCatch(return(expr), name, parentenv, handler) 22: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 23: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) 24: doTryCatch(return(expr), name, parentenv, handler) 25: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) 26: tryCatchList(expr, classes, parentenv, handlers) 27: 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) { }) 28: test_code(desc, code, env = parent.frame(), default_reporter = local_interactive_reporter()) 29: test_that("erlang mixture distribution works", { set.seed(1337L) dist <- dist_erlangmix(list(NULL, NULL, NULL)) params <- list(shapes = list(1L, 4L, 12L), scale = 2, probs = list(0.5, 0.3, 0.2)) alt_params <- list(shapes = list(2L, 6L, 100L), scale = 0.1, probs = list(0.7, 0.2, 0.1)) x <- dist$sample(100L, with_params = params) expect_silent(fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes))) expect_silent(fit(dist, x, init = "fan", spread = 3L)) expect_silent(fit(dist, x, init = "kmeans")) expect_silent(fit(dist, x, init = "cmm")) expect_identical(dist$get_type(), "continuous") expect_density(dist, function(x, log = FALSE, ...) { params <- list(...) res <- (params$probs[[1L]] * dgamma(x, shape = params$shapes[[1L]], scale = params$scale) + params$probs[[2L]] * dgamma(x, shape = params$shapes[[2L]], scale = params$scale) + params$probs[[3L]] * dgamma(x, shape = params$shapes[[3L]], scale = params$scale))/sum(as.numeric(params$probs)) if (log) log(res) else res }, params, x) expect_probability(dist, function(q, lower.tail = TRUE, log.p = FALSE, ...) { params <- list(...) res <- (params$probs[[1L]] * pgamma(q, shape = params$shapes[[1L]], scale = params$scale, lower.tail = lower.tail) + params$probs[[2L]] * pgamma(q, shape = params$shapes[[2L]], scale = params$scale, lower.tail = lower.tail) + params$probs[[3L]] * pgamma(q, shape = params$shapes[[3L]], scale = params$scale, lower.tail = lower.tail))/sum(as.numeric(params$probs)) if (log.p) log(res) else res }, params, x) expect_identical(dist$is_in_support(x), rep_len(TRUE, length(x))) expect_diff_density(dist, x, params) expect_diff_density(dist, x, alt_params) expect_tf_logdensity(dist, params, x) expect_tf_logdensity(dist, alt_params, x, tolerance = 1e-05) expect_tf_logprobability(dist, params, x, x + 1) expect_tf_logprobability(dist, params, x, rep_len(Inf, 100L)) expect_tf_logprobability(dist, params, rep_len(0, 100L), x) x_alt <- dist$sample(100L, with_params = alt_params) expect_tf_logprobability(dist, alt_params, x_alt, x_alt + 1) expect_iprobability(dist, params, x, x + 1) expect_iprobability(dist, params, 0, x) expect_iprobability(dist, params, x, Inf) dist$default_params$shapes <- params$shapes expect_tf_fit(dist, params[c("scale", "probs")], I_POSITIVE_REALS)}) 30: eval(code, test_env) 31: eval(code, test_env) 32: 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) 33: doTryCatch(return(expr), name, parentenv, handler) 34: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 35: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) 36: doTryCatch(return(expr), name, parentenv, handler) 37: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) 38: tryCatchList(expr, classes, parentenv, handlers) 39: 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) { }) 40: test_code(test = NULL, code = exprs, env = env, default_reporter = StopReporter$new()) 41: source_file(path, env = env(env), desc = desc, error_call = error_call) 42: FUN(X[[i]], ...) 43: lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call) 44: doTryCatch(return(expr), name, parentenv, handler) 45: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 46: tryCatchList(expr, classes, parentenv, handlers) 47: tryCatch(code, testthat_abort_reporter = function(cnd) { cat(conditionMessage(cnd), "\n") NULL}) 48: with_reporter(reporters$multi, lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call)) 49: 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) 50: 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) 51: test_dir("testthat", package = package, reporter = reporter, ..., load_package = "installed") 52: test_check("reservr") An irrecoverable exception occurred. R is aborting now ... Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.0.2
Check: tests
Result: ERROR Running ‘testthat.R’ [13s/37s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(reservr) > > test_check("reservr") ── Skip ('/data/gannet/ripley/R/packages/tests-devel/reservr.Rcheck/tests/testthat/helpers.R:13:3'): set floatx to 64-bit ── Reason: TensorFlow not available for testing *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: pgamma_diff_matrix(obs$xmin[i_cens], obs$xmax[i_cens], shapes, scale) 2: .erlang_dens_mat(obs, shapes, scale, i_obs, i_cens) 3: .erlang_em(obs = obs, probs = as.numeric(params$probs), shapes = shapes, scale = params$scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 4: em_fit(shapes, list(probs = as.list(probs), scale = scale)) 5: .erlang_shape_search(obs = obs, probs = probs, shapes = shapes, scale = scale, min_iter = min_iter, max_iter = max_iter, skip_first_e = skip_first_e, tolerance = tolerance, trace = trace, parallel = parallel) 6: fit_dist.ErlangMixtureDistribution(dist = object, obs = obs, start = start, ...) 7: fit_dist(dist = object, obs = obs, start = start, ...) 8: fit.Distribution(dist, x, init = "shapes", shapes = as.numeric(params$shapes)) 9: fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes)) 10: eval_bare(quo_get_expr(.quo), quo_get_env(.quo)) 11: withVisible(code) 12: withCallingHandlers(withVisible(code), warning = handle_warning, message = handle_message) 13: force(code) 14: withr::with_output_sink(path, withCallingHandlers(withVisible(code), warning = handle_warning, message = handle_message)) 15: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), ...) 16: quasi_capture(enquo(object), NULL, evaluate_promise) 17: expect_silent(fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes))) 18: eval(code, test_env) 19: eval(code, test_env) 20: 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) 21: doTryCatch(return(expr), name, parentenv, handler) 22: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 23: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) 24: doTryCatch(return(expr), name, parentenv, handler) 25: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) 26: tryCatchList(expr, classes, parentenv, handlers) 27: 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) { }) 28: test_code(desc, code, env = parent.frame(), default_reporter = local_interactive_reporter()) 29: test_that("erlang mixture distribution works", { set.seed(1337L) dist <- dist_erlangmix(list(NULL, NULL, NULL)) params <- list(shapes = list(1L, 4L, 12L), scale = 2, probs = list(0.5, 0.3, 0.2)) alt_params <- list(shapes = list(2L, 6L, 100L), scale = 0.1, probs = list(0.7, 0.2, 0.1)) x <- dist$sample(100L, with_params = params) expect_silent(fit(dist, x, init = "shapes", shapes = as.numeric(params$shapes))) expect_silent(fit(dist, x, init = "fan", spread = 3L)) expect_silent(fit(dist, x, init = "kmeans")) expect_silent(fit(dist, x, init = "cmm")) expect_identical(dist$get_type(), "continuous") expect_density(dist, function(x, log = FALSE, ...) { params <- list(...) res <- (params$probs[[1L]] * dgamma(x, shape = params$shapes[[1L]], scale = params$scale) + params$probs[[2L]] * dgamma(x, shape = params$shapes[[2L]], scale = params$scale) + params$probs[[3L]] * dgamma(x, shape = params$shapes[[3L]], scale = params$scale))/sum(as.numeric(params$probs)) if (log) log(res) else res }, params, x) expect_probability(dist, function(q, lower.tail = TRUE, log.p = FALSE, ...) { params <- list(...) res <- (params$probs[[1L]] * pgamma(q, shape = params$shapes[[1L]], scale = params$scale, lower.tail = lower.tail) + params$probs[[2L]] * pgamma(q, shape = params$shapes[[2L]], scale = params$scale, lower.tail = lower.tail) + params$probs[[3L]] * pgamma(q, shape = params$shapes[[3L]], scale = params$scale, lower.tail = lower.tail))/sum(as.numeric(params$probs)) if (log.p) log(res) else res }, params, x) expect_identical(dist$is_in_support(x), rep_len(TRUE, length(x))) expect_diff_density(dist, x, params) expect_diff_density(dist, x, alt_params) expect_tf_logdensity(dist, params, x) expect_tf_logdensity(dist, alt_params, x, tolerance = 1e-05) expect_tf_logprobability(dist, params, x, x + 1) expect_tf_logprobability(dist, params, x, rep_len(Inf, 100L)) expect_tf_logprobability(dist, params, rep_len(0, 100L), x) x_alt <- dist$sample(100L, with_params = alt_params) expect_tf_logprobability(dist, alt_params, x_alt, x_alt + 1) expect_iprobability(dist, params, x, x + 1) expect_iprobability(dist, params, 0, x) expect_iprobability(dist, params, x, Inf) dist$default_params$shapes <- params$shapes expect_tf_fit(dist, params[c("scale", "probs")], I_POSITIVE_REALS)}) 30: eval(code, test_env) 31: eval(code, test_env) 32: 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) 33: doTryCatch(return(expr), name, parentenv, handler) 34: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 35: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) 36: doTryCatch(return(expr), name, parentenv, handler) 37: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) 38: tryCatchList(expr, classes, parentenv, handlers) 39: 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) { }) 40: test_code(test = NULL, code = exprs, env = env, default_reporter = StopReporter$new()) 41: source_file(path, env = env(env), desc = desc, error_call = error_call) 42: FUN(X[[i]], ...) 43: lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call) 44: doTryCatch(return(expr), name, parentenv, handler) 45: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 46: tryCatchList(expr, classes, parentenv, handlers) 47: tryCatch(code, testthat_abort_reporter = function(cnd) { cat(conditionMessage(cnd), "\n") NULL}) 48: with_reporter(reporters$multi, lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call)) 49: 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) 50: 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) 51: test_dir("testthat", package = package, reporter = reporter, ..., load_package = "installed") 52: test_check("reservr") An irrecoverable exception occurred. R is aborting now ... Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 0.0.2
Check: examples
Result: ERROR Running examples in 'reservr-Ex.R' failed The error most likely occurred in: > ### Name: fit_erlang_mixture > ### Title: Fit an Erlang mixture using an ECME-Algorithm > ### Aliases: fit_erlang_mixture > > ### ** Examples > > dist <- dist_erlangmix(list(NULL, NULL, NULL)) > params <- list( + shapes = list(1L, 4L, 12L), + scale = 2.0, + probs = list(0.5, 0.3, 0.2) + ) > x <- dist$sample(100L, with_params = params) > fit_erlang_mixture(dist, x, init = "kmeans") Flavor: r-devel-windows-x86_64

Version: 0.0.2
Check: tests
Result: ERROR Running 'testthat.R' [16s] Running the tests in 'tests/testthat.R' failed. Complete output: > library(testthat) > library(reservr) > > test_check("reservr") ── Skip ('D:\RCompile\CRANpkg\local\4.5\reservr.Rcheck\tests\testthat\helpers.R:13:3'): set floatx to 64-bit ── Reason: TensorFlow not available for testing Flavor: r-devel-windows-x86_64

Version: 0.0.2
Check: installed package size
Result: NOTE installed size is 16.1Mb sub-directories of 1Mb or more: R 2.1Mb libs 13.5Mb Flavors: r-release-macos-arm64, r-release-macos-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64