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Loading mkin
Loading required package: testthat
Testing mkin
✔ | OK F W S | Context
⠏ | 0 | Calculation of FOCUS chi2 error levels
⠋ | 1 | Calculation of FOCUS chi2 error levels
⠙ | 2 | Calculation of FOCUS chi2 error levels
✔ | 2 | Calculation of FOCUS chi2 error levels [2.2 s]
⠏ | 0 | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠋ | 1 | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠙ | 2 | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠹ | 3 | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠸ | 4 | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠼ | 5 | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠴ | 6 | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠦ | 7 | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠧ | 8 | Results for FOCUS D established in expertise for UBA (Ranke 2014)
✔ | 8 | Results for FOCUS D established in expertise for UBA (Ranke 2014) [6.5 s]
⠏ | 0 | Iteratively reweighted least squares (IRLS) fitting
⠋ | 0 1 | Iteratively reweighted least squares (IRLS) fitting
⠙ | 1 1 | Iteratively reweighted least squares (IRLS) fitting
⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting
⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting
⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting
⠸ | 1 1 2 | Iteratively reweighted least squares (IRLS) fitting
⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting
⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting
⠸ | 1 1 2 | Iteratively reweighted least squares (IRLS) fitting
⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting
⠼ | 1 1 3 | Iteratively reweighted least squares (IRLS) fitting
⠴ | 1 1 4 | Iteratively reweighted least squares (IRLS) fitting
⠹ | 1 1 1 | Iteratively reweighted least squares (IRLS) fitting
⠹ | 2 1 | Iteratively reweighted least squares (IRLS) fitting
⠸ | 3 1 | Iteratively reweighted least squares (IRLS) fitting
⠼ | 4 1 | Iteratively reweighted least squares (IRLS) fitting
⠴ | 5 1 | Iteratively reweighted least squares (IRLS) fitting
⠦ | 6 1 | Iteratively reweighted least squares (IRLS) fitting
⠧ | 7 1 | Iteratively reweighted least squares (IRLS) fitting
✖ | 7 1 | Iteratively reweighted least squares (IRLS) fitting [172.0 s]
────────────────────────────────────────────────────────────────────────────────
test_irls.R:38: error: Reweighting method 'obs' works
Objekt 'tc_fit' nicht gefunden
1: mkinfit(m_synth_SFO_lin, SFO_lin_a, reweight.method = "obs", quiet = TRUE) at /home/jranke/git/mkin/tests/testthat/test_irls.R:38
2: system.time({
fit <- modFit(cost, c(state.ini.optim, transparms.optim), method = method.modFit,
control = control.modFit, lower = lower, upper = upper, ...)
if (!is.null(reweight.method)) {
if (!reweight.method %in% c("obs", "tc"))
stop("Only reweighting methods 'obs' and 'tc' are implemented")
if (reweight.method == "obs") {
if (!quiet) {
cat("IRLS based on variance estimates for each observed variable\n")
cat("Initial variance estimates are:\n")
print(signif(fit$var_ms_unweighted, 8))
}
}
if (reweight.method == "tc") {
tc_fit <- fit_error_model_mad_obs(cost(fit$par)$residuals, tc, 0)
if (is.character(tc_fit)) {
if (!quiet) {
cat(tc_fit, ".\n", "No reweighting will be performed.")
}
tc_fitted <- c(sigma_low = NA, rsd_high = NA)
}
else {
tc_fitted <- coef(tc_fit)
if (!quiet) {
cat("IRLS based on variance estimates according to the two component error model\n")
cat("Initial variance components are:\n")
print(signif(tc_fitted))
}
}
}
reweight.diff = 1
n.iter <- 0
if (!is.null(err))
observed$err.ini <- observed[[err]]
err = "err.irls"
while (reweight.diff > reweight.tol & n.iter < reweight.max.iter & !is.character(tc_fit)) {
n.iter <- n.iter + 1
if (reweight.method == "obs") {
sr_old <- fit$var_ms_unweighted
observed[err] <- sqrt(fit$var_ms_unweighted[as.character(observed$name)])
}
if (reweight.method == "tc") {
sr_old <- tc_fitted
tmp_predicted <- mkin_wide_to_long(out_predicted, time = "time")
tmp_data <- suppressMessages(join(observed, tmp_predicted, by = c("time",
"name")))
observed[err] <- predict(tc_fit, newdata = data.frame(obs = observed$value))
}
fit <- modFit(cost, fit$par, method = method.modFit, control = control.modFit,
lower = lower, upper = upper, ...)
if (reweight.method == "obs") {
sr_new <- fit$var_ms_unweighted
}
if (reweight.method == "tc") {
tc_fit <- fit_error_model_mad_obs(cost(fit$par)$residuals, tc_fitted,
n.iter)
if (is.character(tc_fit)) {
if (!quiet) {
cat(tc_fit, ".\n")
}
break
}
else {
tc_fitted <- coef(tc_fit)
sr_new <- tc_fitted
}
}
reweight.diff = sum((sr_new - sr_old)^2)
if (!quiet) {
cat("Iteration", n.iter, "yields variance estimates:\n")
print(signif(sr_new, 8))
cat("Sum of squared differences to last variance (component) estimates:",
signif(reweight.diff, 2), "\n")
}
}
}
}) at /home/jranke/git/mkin/R/mkinfit.R:396
────────────────────────────────────────────────────────────────────────────────
⠏ | 0 | Model predictions with mkinpredict
⠋ | 1 | Model predictions with mkinpredict
⠙ | 2 | Model predictions with mkinpredict
⠹ | 3 | Model predictions with mkinpredict
✔ | 3 | Model predictions with mkinpredict [0.4 s]
⠏ | 0 | Fitting of parent only models
⠋ | 1 | Fitting of parent only models
⠙ | 2 | Fitting of parent only models
⠹ | 3 | Fitting of parent only models
⠸ | 4 | Fitting of parent only models
⠼ | 5 | Fitting of parent only models
⠴ | 6 | Fitting of parent only models
⠦ | 7 | Fitting of parent only models
⠧ | 8 | Fitting of parent only models
⠇ | 9 | Fitting of parent only models
⠏ | 10 | Fitting of parent only models
⠋ | 11 | Fitting of parent only models
⠙ | 12 | Fitting of parent only models
⠹ | 13 | Fitting of parent only models
⠸ | 14 | Fitting of parent only models
⠼ | 15 | Fitting of parent only models
⠴ | 16 | Fitting of parent only models
⠦ | 17 | Fitting of parent only models
⠧ | 18 | Fitting of parent only models
⠇ | 19 | Fitting of parent only models
⠏ | 20 | Fitting of parent only models
⠋ | 21 | Fitting of parent only models
✔ | 21 | Fitting of parent only models [22.1 s]
⠏ | 0 | Complex test case from Schaefer et al. (2007) Piacenza paper
⠋ | 1 | Complex test case from Schaefer et al. (2007) Piacenza paper
⠙ | 2 | Complex test case from Schaefer et al. (2007) Piacenza paper
✔ | 2 | Complex test case from Schaefer et al. (2007) Piacenza paper [5.2 s]
⠏ | 0 | Results for synthetic data established in expertise for UBA (Ranke 2014)
⠋ | 1 | Results for synthetic data established in expertise for UBA (Ranke 2014)
⠙ | 2 | Results for synthetic data established in expertise for UBA (Ranke 2014)
⠹ | 3 | Results for synthetic data established in expertise for UBA (Ranke 2014)
⠸ | 4 | Results for synthetic data established in expertise for UBA (Ranke 2014)
✔ | 4 | Results for synthetic data established in expertise for UBA (Ranke 2014) [6.5 s]
⠏ | 0 | Calculation of maximum time weighted average concentrations (TWAs)
⠋ | 1 | Calculation of maximum time weighted average concentrations (TWAs)
⠙ | 2 | Calculation of maximum time weighted average concentrations (TWAs)
⠹ | 3 | Calculation of maximum time weighted average concentrations (TWAs)
⠸ | 4 | Calculation of maximum time weighted average concentrations (TWAs)
⠼ | 5 | Calculation of maximum time weighted average concentrations (TWAs)
⠴ | 6 | Calculation of maximum time weighted average concentrations (TWAs)
⠦ | 7 | Calculation of maximum time weighted average concentrations (TWAs)
⠧ | 8 | Calculation of maximum time weighted average concentrations (TWAs)
✔ | 8 | Calculation of maximum time weighted average concentrations (TWAs) [7.6 s]
══ Results ═════════════════════════════════════════════════════════════════════
Duration: 222.6 s
OK: 55
Failed: 1
Warnings: 0
Skipped: 0
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