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Try to get more info on failure #285

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Try to get more info on failure #285

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089f388
Try to get more info on failure
Bisaloo Apr 29, 2024
1adcd95
Check if Inf occurs on lower or upper
Bisaloo Apr 29, 2024
a9bae5c
Actually use upper
Bisaloo Apr 29, 2024
1c18b6e
Increase weibull lower bounds
Bisaloo Apr 30, 2024
b97f0c7
Increase lower even more?
Bisaloo Apr 30, 2024
82df973
Adjust bounds
Bisaloo Apr 30, 2024
7c77983
remove tryCatch in extract_param
joshwlambert May 1, 2024
4143bed
print parameter index in extract-bias vignette
joshwlambert May 1, 2024
73fd890
add stop call to extract_param
joshwlambert May 1, 2024
9fe4c10
remove print from vignette and change lower bound in extract_param va…
joshwlambert May 1, 2024
3bb0e0d
add stop to extract_param to check values
joshwlambert May 1, 2024
59be142
correct logical expr in if in extract_param
joshwlambert May 1, 2024
1c6345e
added while loop to extract-bias vignette to prevent incoherent values
joshwlambert May 1, 2024
8983aab
increase weibull lower bound
joshwlambert May 1, 2024
cbd2ec8
revert to lower value bound at 0
joshwlambert May 1, 2024
d13640d
Remove fail fast
Bisaloo May 1, 2024
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7 changes: 0 additions & 7 deletions .github/workflows/R-CMD-check.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -85,10 +85,3 @@ jobs:
with:
upload-snapshots: true
error-on: '"note"'

# fail-fast but only if rcmdcheck step fails
- name: Manual fail-fast
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
if: always() && steps.rcmdcheck.outcome == 'failure'
run: gh run cancel ${{ github.run_id }}
4 changes: 2 additions & 2 deletions R/extract_param.R
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Original file line number Diff line number Diff line change
Expand Up @@ -81,7 +81,7 @@ extract_param <- function(type = c("percentiles", "range"),
if (distribution == "norm") {
checkmate::assert_numeric(values)
} else {
checkmate::assert_numeric(values, lower = 1e-10)
checkmate::assert_numeric(values, lower = 0)
}

if (type == "percentiles") {
Expand Down Expand Up @@ -221,7 +221,7 @@ extract_param <- function(type = c("percentiles", "range"),
}
if (distribution == "weibull") {
names(param) <- c("shape", "scale")
lower <- c(1e-10, 1e-10)
lower <- c(1e-5, 1e-5)
}
if (distribution == "norm") {
names(param) <- c("mean", "sd")
Expand Down
156 changes: 85 additions & 71 deletions vignettes/extract-bias.Rmd
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Expand Up @@ -206,47 +206,54 @@
for (params_idx in seq_len(nrow(parameters_range))) {
dist <- as.character(parameters_range[params_idx, "dist"])
n_samples <- parameters_range[params_idx, "n_samples"]

if (dist == "lnorm") {
true_median <- do.call(
paste0("q", dist),
list(
p = 0.5,
meanlog = parameters_range[params_idx, "param_1"],
sdlog = parameters_range[params_idx, "param_2"]

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file=vignettes/extract-bias.Rmd,line=209,col=1,[trailing_whitespace_linter] Trailing whitespace is superfluous.
# while loop to ensure values are min < median < max
resample_values <- TRUE
while (resample_values) {
if (dist == "lnorm") {
true_median <- do.call(
paste0("q", dist),
list(
p = 0.5,
meanlog = parameters_range[params_idx, "param_1"],
sdlog = parameters_range[params_idx, "param_2"]
)
)
)
true_range <- do.call(
paste0("r", dist),
list(
n = n_samples,
meanlog = parameters_range[params_idx, "param_1"],
sdlog = parameters_range[params_idx, "param_2"]
true_range <- do.call(
paste0("r", dist),
list(
n = n_samples,
meanlog = parameters_range[params_idx, "param_1"],
sdlog = parameters_range[params_idx, "param_2"]
)
)
)
true_range <- c(min(true_range), max(true_range))
} else {
true_median <- do.call(
paste0("q", dist),
list(
p = 0.5,
shape = parameters_range[params_idx, "param_1"],
scale = parameters_range[params_idx, "param_2"]
true_range <- c(min(true_range), max(true_range))
} else {
true_median <- do.call(
paste0("q", dist),
list(
p = 0.5,
shape = parameters_range[params_idx, "param_1"],
scale = parameters_range[params_idx, "param_2"]
)
)
)
true_range <- do.call(
paste0("r", dist),
list(
n = n_samples,
shape = parameters_range[params_idx, "param_1"],
scale = parameters_range[params_idx, "param_2"]
true_range <- do.call(
paste0("r", dist),
list(
n = n_samples,
shape = parameters_range[params_idx, "param_1"],
scale = parameters_range[params_idx, "param_2"]
)
)
)
true_range <- c(min(true_range), max(true_range))
true_range <- c(min(true_range), max(true_range))
}

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true_values <- c(true_median, true_range)
if (true_values[2] < true_values[1] && true_values[1] < true_values[3]) {
resample_values <- FALSE
}
}

true_values <- c(true_median, true_range)


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file=vignettes/extract-bias.Rmd,line=256,col=1,[trailing_whitespace_linter] Trailing whitespace is superfluous.
# message about stochastic optimisation suppressed
estim_params[[params_idx]] <- suppressMessages(
expr = extract_param(
Expand Down Expand Up @@ -393,46 +400,53 @@
dist <- as.character(parameters_range[params_idx, "dist"])
n_samples <- parameters_range[params_idx, "n_samples"]

if (dist == "lnorm") {
true_median <- do.call(
paste0("q", dist),
list(
p = 0.5,
meanlog = parameters_range[params_idx, "param_1"],
sdlog = parameters_range[params_idx, "param_2"]
# while loop to ensure values are min < median < max
resample_values <- TRUE
while (resample_values) {
if (dist == "lnorm") {
true_median <- do.call(
paste0("q", dist),
list(
p = 0.5,
meanlog = parameters_range[params_idx, "param_1"],
sdlog = parameters_range[params_idx, "param_2"]
)
)
)
true_range <- do.call(
paste0("r", dist),
list(
n = n_samples,
meanlog = parameters_range[params_idx, "param_1"],
sdlog = parameters_range[params_idx, "param_2"]
true_range <- do.call(
paste0("r", dist),
list(
n = n_samples,
meanlog = parameters_range[params_idx, "param_1"],
sdlog = parameters_range[params_idx, "param_2"]
)
)
)
true_range <- c(min(true_range), max(true_range))
} else {
true_median <- do.call(
paste0("q", dist),
list(
p = 0.5,
shape = parameters_range[params_idx, "param_1"],
scale = parameters_range[params_idx, "param_2"]
true_range <- c(min(true_range), max(true_range))
} else {
true_median <- do.call(
paste0("q", dist),
list(
p = 0.5,
shape = parameters_range[params_idx, "param_1"],
scale = parameters_range[params_idx, "param_2"]
)
)
)
true_range <- do.call(
paste0("r", dist),
list(
n = n_samples,
shape = parameters_range[params_idx, "param_1"],
scale = parameters_range[params_idx, "param_2"]
true_range <- do.call(
paste0("r", dist),
list(
n = n_samples,
shape = parameters_range[params_idx, "param_1"],
scale = parameters_range[params_idx, "param_2"]
)
)
)
true_range <- c(min(true_range), max(true_range))
true_range <- c(min(true_range), max(true_range))
}

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true_values <- c(true_median, true_range)
if (true_values[2] < true_values[1] && true_values[1] < true_values[3]) {
resample_values <- FALSE
}
}

true_values <- c(true_median, true_range)


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file=vignettes/extract-bias.Rmd,line=449,col=1,[trailing_whitespace_linter] Trailing whitespace is superfluous.
# message about stochastic optimisation suppressed
estim <- suppressMessages(
replicate(
Expand Down
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