diff options
Diffstat (limited to 'tests/testthat/test_error_models.R')
| -rw-r--r-- | tests/testthat/test_error_models.R | 115 |
1 files changed, 40 insertions, 75 deletions
diff --git a/tests/testthat/test_error_models.R b/tests/testthat/test_error_models.R index c656f7d2..6bb93d48 100644 --- a/tests/testthat/test_error_models.R +++ b/tests/testthat/test_error_models.R @@ -178,84 +178,49 @@ test_that("Reweighting method 'tc' produces reasonable variance estimates", { expect_true(all(abs(tcf_met_2_15_tc_error_model_errors) < 0.10)) }) -test_that("The two-component error model finds the best known AIC values for parent models", { +test_that("The different error model fitting methods work for parent fits", { skip_on_cran() - library(parallel) - source("~/git/mkin/R/mkinfit.R") - source("~/git/mkin/R/mmkin.R") - f_9 <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data) - f_9 <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, - error_model = "tc", error_model_algorithm = "direct") - f_9 <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, - error_model = "tc", error_model_algorithm = "twostep") - f_9 <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, - error_model = "tc", error_model_algorithm = "threestep") - f_9 <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, - error_model = "tc", error_model_algorithm = "fourstep") - f_9 <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, - error_model = "tc", error_model_algorithm = "IRLS") - f_9 <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, - error_model = "tc", error_model_algorithm = "d_3") - AIC(f_9) - f_10 <- mkinfit("DFOP", experimental_data_for_UBA_2019[[10]]$data, - error_model = "tc", error_model_algorithm = "IRLS") - f_tc_exp_direct <- mmkin(c("SFO", "DFOP", "HS"), - lapply(experimental_data_for_UBA_2019, function(x) x$data), - error_model = "tc", - error_model_algorithm = "direct", - quiet = TRUE) - f_tc_exp_twostep <- mmkin(c("SFO", "DFOP", "HS"), - lapply(experimental_data_for_UBA_2019, function(x) x$data), - error_model = "tc", - error_model_algorithm = "twostep", - quiet = TRUE) - f_tc_exp_threestep <- mmkin(c("SFO", "DFOP", "HS"), - lapply(experimental_data_for_UBA_2019, function(x) x$data), - error_model = "tc", - error_model_algorithm = "threestep", - quiet = TRUE) - f_tc_exp_fourstep <- mmkin(c("SFO", "DFOP", "HS"), - lapply(experimental_data_for_UBA_2019, function(x) x$data), - error_model = "tc", - error_model_algorithm = "fourstep", - quiet = TRUE) - f_tc_exp_IRLS <- mmkin(c("SFO", "DFOP", "HS"), + + f_9_OLS <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, + quiet = TRUE) + expect_equivalent(round(AIC(f_9_OLS), 2), 137.43) + + f_9_direct <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, + error_model = "tc", error_model_algorithm = "direct", quiet = TRUE) + expect_equivalent(round(AIC(f_9_direct), 2), 134.94) + + f_9_twostep <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, + error_model = "tc", error_model_algorithm = "twostep", quiet = TRUE) + expect_equivalent(round(AIC(f_9_twostep), 2), 134.94) + + f_9_threestep <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, + error_model = "tc", error_model_algorithm = "threestep", quiet = TRUE) + expect_equivalent(round(AIC(f_9_threestep), 2), 139.43) + + f_9_fourstep <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, + error_model = "tc", error_model_algorithm = "fourstep", quiet = TRUE) + expect_equivalent(round(AIC(f_9_fourstep), 2), 139.43) + + f_9_IRLS <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, + error_model = "tc", error_model_algorithm = "IRLS", quiet = TRUE) + expect_equivalent(round(AIC(f_9_IRLS), 2), 139.43) + + f_9_d_3 <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data, + error_model = "tc", error_model_algorithm = "d_3", quiet = TRUE) + expect_equivalent(round(AIC(f_9_d_3), 2), 134.94) +}) + +test_that("The default error model algorithm finds the best known AIC values for parent fits", { + f_tc_exp_d_3 <- mmkin(c("SFO", "DFOP", "HS"), lapply(experimental_data_for_UBA_2019, function(x) x$data), error_model = "tc", - error_model_algorithm = "IRLS", + error_model_algorithm = "d_3", quiet = TRUE) - AIC_exp_direct <- lapply(f_tc_exp_direct, AIC) - AIC_exp_direct <- lapply(AIC_exp_direct, round, 1) - dim(AIC_exp_direct) <- dim(f_tc_exp_direct) - dimnames(AIC_exp_direct) <- dimnames(f_tc_exp_direct) - - AIC_exp_twostep <- lapply(f_tc_exp_twostep, AIC) - AIC_exp_twostep <- lapply(AIC_exp_twostep, round, 1) - dim(AIC_exp_twostep) <- dim(f_tc_exp_twostep) - dimnames(AIC_exp_twostep) <- dimnames(f_tc_exp_twostep) - - AIC_exp_threestep <- lapply(f_tc_exp_threestep, AIC) - AIC_exp_threestep <- lapply(AIC_exp_threestep, round, 1) - dim(AIC_exp_threestep) <- dim(f_tc_exp_threestep) - dimnames(AIC_exp_threestep) <- dimnames(f_tc_exp_threestep) - - AIC_exp_fourstep <- lapply(f_tc_exp_fourstep, AIC) - AIC_exp_fourstep <- lapply(AIC_exp_fourstep, round, 1) - dim(AIC_exp_fourstep) <- dim(f_tc_exp_fourstep) - dimnames(AIC_exp_fourstep) <- dimnames(f_tc_exp_fourstep) - - AIC_exp_IRLS <- lapply(f_tc_exp_IRLS, AIC) - AIC_exp_IRLS <- lapply(AIC_exp_IRLS, round, 1) - dim(AIC_exp_IRLS) <- dim(f_tc_exp_IRLS) - dimnames(AIC_exp_IRLS) <- dimnames(f_tc_exp_IRLS) - - AIC_exp <- lapply(f_tc_exp, AIC) - dim(AIC_exp) <- dim(f_tc_exp) - dimnames(AIC_exp) <- dimnames(f_tc_exp) - unlist(AIC_exp["SFO", c(9, 11, 12)]) - expect_equivalent(round(unlist(AIC_exp["SFO", c(9, 11, 12)]), 1), - c(134.9, 125.5, 82.0)) -}) - + AIC_exp_d_3 <- lapply(f_tc_exp_d_3, AIC) + AIC_exp_d_3 <- lapply(AIC_exp_d_3, round, 1) + dim(AIC_exp_d_3) <- dim(f_tc_exp_d_3) + dimnames(AIC_exp_d_3) <- dimnames(f_tc_exp_d_3) + expect_known_output(AIC_exp_d_3, "AIC_exp_d_3.out") +}) |