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Quickfix/efvignette/logscale #308

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51bf1a1
Change axis label to specify log scale
kristinawlai Oct 12, 2024
db6da49
increment version
kristinawlai Oct 12, 2024
2f532a7
remove extra white space for linting
kristinawlai Oct 12, 2024
6c39a26
Merge branch 'main' into Quickfix/EFvignette/logscale
d-morrison Oct 15, 2024
1c34e3f
Merge branch 'main' into Quickfix/EFvignette/logscale
d-morrison Oct 15, 2024
ea992a9
Update log scaling to built in option
kristinawlai Oct 30, 2024
cb63edc
Merge branch 'Quickfix/EFvignette/logscale' of https://github.com/UCD…
kristinawlai Oct 30, 2024
50e6373
draft bar plot
kristinawlai Dec 20, 2024
bc07522
Merge branch 'main' into Quickfix/EFvignette/logscale
d-morrison Jan 28, 2025
66c8301
Merge branch 'main' into Quickfix/EFvignette/logscale
kaiemjoy Feb 3, 2025
3900b89
Merge branch 'main' into Quickfix/EFvignette/logscale
d-morrison Feb 3, 2025
9fe73c2
Merge branch 'main' into Quickfix/EFvignette/logscale
kristinawlai Feb 3, 2025
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29 changes: 29 additions & 0 deletions R/autoplot.summary.seroincidence.by.bar.R
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#' Create bar plot for stratified seroincidence results
#'
#'
#' @return a [ggplot2::ggplot()] object

autoplot.seroincidence.by.bar <- function(est_country_agedf, ageCat, incidence.rate, Country, CI.lwr, CI.upr, country_pal) {

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file=R/autoplot.summary.seroincidence.by.bar.R,line=6,col=103,[object_name_linter] Variable and function name style should match snake_case or symbols.
ggplot(est_country_agedf,
aes(
y = fct_rev(ageCat),

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x = incidence.rate * 1000, #rescale incidence
fill = Country
)) +
geom_bar(stat = "identity",

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position = position_dodge2(reverse = TRUE),

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file=R/autoplot.summary.seroincidence.by.bar.R,line=14,col=25,[object_usage_linter] no visible global function definition for 'position_dodge2'
show.legend = TRUE) +
geom_errorbar(
aes(xmin = CI.lwr * 1000, xmax = CI.upr * 1000), #rescale CIs
position = position_dodge2(reverse = TRUE)
) +
labs(title = "Enteric Fever Seroincidence by Country and Age",
x = "Seroincidence rate per 1000 person-years",
y = "Age Category",
fill = "Country") +
theme_linedraw() +
theme(axis.text.y = element_text(size = 11),
axis.text.x = element_text(size = 11)) +
scale_x_continuous(expand = c(0, 10)) +
scale_fill_manual(values = country_pal)

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}
15 changes: 8 additions & 7 deletions vignettes/articles/enteric_fever_example.Rmd
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Expand Up @@ -7,9 +7,11 @@ output:
toc: true
vignette: >
%\VignetteIndexEntry{Enteric Fever Seroincidence Vignette}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
%\VignetteEngine{knitr::rmarkdown}
bibliography: ../references.bib
editor_options:
chunk_output_type: console
---
## Introduction

Expand Down Expand Up @@ -154,9 +156,9 @@ We see that across countries, our data is highly skewed with the majority of res

xs_data %>%
mutate(Country = fct_relevel(Country, "Bangladesh", "Pakistan", "Nepal")) %>%
autoplot(strata = "Country", type = "density") +
autoplot(strata = "Country", type = "density", log = TRUE) +
scale_fill_manual(values = country_pal) +
scale_x_log10(labels = scales::label_comma())
labs(x = "Log Antibody Response Value")

```

Expand Down Expand Up @@ -281,15 +283,14 @@ ggplot(est_country_agedf,
fill = Country
)) +
geom_bar(stat = "identity",
position = position_dodge(),
position = position_dodge2(reverse = TRUE),
show.legend = TRUE) +
geom_errorbar(
aes(xmin = CI.lwr * 1000, xmax = CI.upr * 1000), #rescale CIs
position = position_dodge(width = 0.9),
width = .2
position = position_dodge2(reverse = TRUE)
) +
labs(title = "Enteric Fever Seroincidence by Country and Age",
x = "Seroincidence rate per 1000 person-years",
x = "Seroconversion rate per 1000 person-years",
y = "Age Category",
fill = "Country") +
theme_linedraw() +
Expand Down
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