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graficos_flexao_madeira.R
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# Flexão - MOE
flexao <- read.table(
"C:/Users/Annie de Lima/Downloads/Estatística/stat_debs/flex_mad.txt",
header = T)
names <- flexao$especie
value <- flexao$MOE
data <- data.frame(names,value)
# Plot
data %>%
ggplot( aes(x=names, y=value, fill=names)) +
geom_boxplot() +
scale_fill_viridis(discrete = TRUE) +
theme_bw() +
theme(
legend.position="none",
plot.title = element_text(size=11)
) +
ggtitle("Flexão") +
ylab("MOE (MPa)") + xlab("Espécies")+coord_flip ()
# Plot better results
data %>%
ggplot( aes(x=names, y=value, fill=names)) +
geom_boxplot() +
scale_fill_viridis(discrete = TRUE) +
geom_jitter(color="red", size=1.0, alpha=0.5) +
theme_bw() +
theme(
legend.position="none",
plot.title = element_text(size=11)
) +
ggtitle("Flexão") +
ylab("MOE (MPa)") + xlab("Espécies")+coord_flip ()
# sample size
sample_size = data %>% group_by(names) %>% summarize(num=n())
# Plot
data %>%
left_join(sample_size) %>%
mutate(myaxis = paste0(names, "\n", "n=", num)) %>%
ggplot( aes(x=myaxis, y=value, fill=names)) +
geom_violin(width=1.4) +
geom_boxplot(width=0.1, color="red", alpha=0.2) +
scale_fill_viridis(discrete = TRUE) +
theme_bw() +
theme(
legend.position="none",
plot.title = element_text(size=12)
) +
ggtitle("Flexão") +
ylab("MOE (MPa)") + xlab("Espécies")
# Code coming from @drob:
# https://gist.github.com/dgrtwo/eb7750e74997891d7c20#file-geom_flat_violin-r
"%||%" <- function(a, b) {
if (!is.null(a)) a else b
}
geom_flat_violin <- function(mapping = NULL, data = NULL, stat = "ydensity",
position = "dodge", trim = TRUE, scale = "area",
show.legend = NA, inherit.aes = TRUE, ...) {
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomFlatViolin,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
trim = trim,
scale = scale,
...
)
)
}
#' @rdname ggplot2-ggproto
#' @format NULL
#' @usage NULL
#' @export
GeomFlatViolin <-
ggproto("GeomFlatViolin", Geom,
setup_data = function(data, params) {
data$width <- data$width %||%
params$width %||% (resolution(data$x, FALSE) * 0.9)
# ymin, ymax, xmin, and xmax define the bounding rectangle for each group
data %>%
group_by(group) %>%
mutate(ymin = min(y),
ymax = max(y),
xmin = x,
xmax = x + width / 2)
},
draw_group = function(data, panel_scales, coord) {
# Find the points for the line to go all the way around
data <- transform(data, xminv = x,
xmaxv = x + violinwidth * (xmax - x))
# Make sure it's sorted properly to draw the outline
newdata <- rbind(plyr::arrange(transform(data, x = xminv), y),
plyr::arrange(transform(data, x = xmaxv), -y))
# Close the polygon: set first and last point the same
# Needed for coord_polar and such
newdata <- rbind(newdata, newdata[1,])
ggplot2:::ggname("geom_flat_violin",
GeomPolygon$draw_panel
(newdata, panel_scales, coord))
},
draw_key = draw_key_polygon,
default_aes = aes(weight = 1,
colour = "grey20",
fill = "white", size = 0.5,
alpha = NA, linetype = "solid"),
required_aes = c("x", "y")
)
# Final plot inspired from @jbburant: https://gist.github.com/jbburant/b3bd4961f3f5b03aeb542ed33a8fe062
data %>%
sample_frac(0.4) %>%
ggplot(aes(x = names, y = value, fill = names)) +
geom_flat_violin(scale = "count", trim = FALSE, width=2) +
scale_fill_viridis(discrete = TRUE) +
stat_summary(fun.data = mean_sdl,
fun.args = list(mult = 1),
geom = "pointrange",
position = position_nudge(4.9)) +
geom_dotplot(binaxis = "y",
dotsize = 1.2,
stackdir = "down",
binwidth = 0.3,
position = position_nudge(-0.025)) +
theme_bw() +
theme(
legend.position = "none"
) +
ylab("MOE (MPa)")
# Ver: https://www.data-to-viz.com/caveat/boxplot.html para explicações
##-----
# Flexão - MOR
flexao <- read.table(
"C:/Users/Annie de Lima/Downloads/Estatística/stat_debs/flex_mad.txt",
header = T)
names <- flexao$especie
value <- flexao$MOR
data <- data.frame(names,value)
# Plot
data %>%
ggplot( aes(x=names, y=value, fill=names)) +
geom_boxplot() +
scale_fill_viridis(discrete = TRUE) +
theme_bw() +
theme(
legend.position="none",
plot.title = element_text(size=11)
) +
ggtitle("Flexão") +
ylab("MOR (MPa)") + xlab("Espécies")+coord_flip ()
# Plot better results
data %>%
ggplot( aes(x=names, y=value, fill=names)) +
geom_boxplot() +
scale_fill_viridis(discrete = TRUE) +
geom_jitter(color="red", size=1.0, alpha=0.5) +
theme_bw() +
theme(
legend.position="none",
plot.title = element_text(size=11)
) +
ggtitle("Flexão") +
ylab("MOR (MPa)") + xlab("Espécies")+coord_flip ()
# sample size
sample_size = data %>% group_by(names) %>% summarize(num=n())
# Plot
data %>%
left_join(sample_size) %>%
mutate(myaxis = paste0(names, "\n", "n=", num)) %>%
ggplot( aes(x=myaxis, y=value, fill=names)) +
geom_violin(width=1.4) +
geom_boxplot(width=0.1, color="red", alpha=0.2) +
scale_fill_viridis(discrete = TRUE) +
theme_bw() +
theme(
legend.position="none",
plot.title = element_text(size=12)
) +
ggtitle("Flexão") +
ylab("MOR (MPa)") + xlab("Espécies")
# Code coming from @drob:
# https://gist.github.com/dgrtwo/eb7750e74997891d7c20#file-geom_flat_violin-r
"%||%" <- function(a, b) {
if (!is.null(a)) a else b
}
geom_flat_violin <- function(mapping = NULL, data = NULL, stat = "ydensity",
position = "dodge", trim = TRUE, scale = "area",
show.legend = NA, inherit.aes = TRUE, ...) {
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomFlatViolin,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
trim = trim,
scale = scale,
...
)
)
}
#' @rdname ggplot2-ggproto
#' @format NULL
#' @usage NULL
#' @export
GeomFlatViolin <-
ggproto("GeomFlatViolin", Geom,
setup_data = function(data, params) {
data$width <- data$width %||%
params$width %||% (resolution(data$x, FALSE) * 0.9)
# ymin, ymax, xmin, and xmax define the bounding rectangle for each group
data %>%
group_by(group) %>%
mutate(ymin = min(y),
ymax = max(y),
xmin = x,
xmax = x + width / 2)
},
draw_group = function(data, panel_scales, coord) {
# Find the points for the line to go all the way around
data <- transform(data, xminv = x,
xmaxv = x + violinwidth * (xmax - x))
# Make sure it's sorted properly to draw the outline
newdata <- rbind(plyr::arrange(transform(data, x = xminv), y),
plyr::arrange(transform(data, x = xmaxv), -y))
# Close the polygon: set first and last point the same
# Needed for coord_polar and such
newdata <- rbind(newdata, newdata[1,])
ggplot2:::ggname("geom_flat_violin",
GeomPolygon$draw_panel
(newdata, panel_scales, coord))
},
draw_key = draw_key_polygon,
default_aes = aes(weight = 1,
colour = "grey20",
fill = "white", size = 0.5,
alpha = NA, linetype = "solid"),
required_aes = c("x", "y")
)
# Final plot inspired from @jbburant: https://gist.github.com/jbburant/b3bd4961f3f5b03aeb542ed33a8fe062
data %>%
sample_frac(0.4) %>%
ggplot(aes(x = names, y = value, fill = names)) +
geom_flat_violin(scale = "count", trim = FALSE, width=2) +
scale_fill_viridis(discrete = TRUE) +
stat_summary(fun.data = mean_sdl,
fun.args = list(mult = 1),
geom = "pointrange",
position = position_nudge(4.9)) +
geom_dotplot(binaxis = "y",
dotsize = 1.2,
stackdir = "down",
binwidth = 0.3,
position = position_nudge(-0.025)) +
theme_bw() +
theme(
legend.position = "none"
) +
ylab("MOR (MPa)")