Nothing
## ----setup, include = FALSE---------------------------------------------------
library(dplyr)
library(tidyr)
library(forcats)
library(ggplot2)
library(tidypaleo)
theme_set(theme_paleo(8))
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.height = 3,
fig.width = 6,
dpi = 96
)
## ---- eval=FALSE--------------------------------------------------------------
# library(tidyverse)
# library(tidypaleo)
# theme_set(theme_paleo(8))
## -----------------------------------------------------------------------------
data("long_lake_plottable")
data("alta_lake_geochem")
data("keji_lakes_plottable")
data("halifax_lakes_plottable")
## -----------------------------------------------------------------------------
alta_lake_geochem
## -----------------------------------------------------------------------------
alta_plot <- ggplot(alta_lake_geochem, aes(x = value, y = depth)) +
geom_lineh() +
geom_point() +
scale_y_reverse() +
facet_geochem_gridh(vars(param)) +
labs(x = NULL, y = "Depth (cm)")
alta_plot
## -----------------------------------------------------------------------------
alta_plot +
geom_hline(yintercept = c(4, 16), col = "red", lty = 2, alpha = 0.7)
## -----------------------------------------------------------------------------
zone_data <- tibble(ymin = 4, ymax = 16, xmin = -Inf, xmax = Inf)
alta_plot +
geom_rect(
mapping = aes(ymin = ymin, ymax = ymax, xmin = xmin, xmax = xmax),
data = zone_data,
alpha = 0.2,
fill = "blue",
inherit.aes = FALSE
)
## -----------------------------------------------------------------------------
cu_standard_data <- tibble(param = "Cu", xmin = 35.7, xmax = Inf, ymin = -Inf, ymax = Inf)
alta_plot +
geom_rect(
mapping = aes(ymin = ymin, ymax = ymax, xmin = xmin, xmax = xmax),
data = cu_standard_data,
alpha = 0.2,
fill = "red",
inherit.aes = FALSE
)
## ---- warning=FALSE-----------------------------------------------------------
alta_plot +
geom_errorbarh(aes(xmin = value - stdev, xmax = value + stdev), height = 0.5)
## ---- eval=FALSE--------------------------------------------------------------
# alta_lake_geochem %>%
# mutate(param = fct_relevel(param, "Ti", "Cu", "C/N")) %>%
# ggplot(aes(x = value, y = depth)) +
# ...
## ---- echo=FALSE--------------------------------------------------------------
alta_lake_geochem %>%
mutate(param = fct_relevel(param, "Ti", "Cu", "C/N")) %>%
ggplot(aes(x = value, y = depth)) +
geom_lineh() +
geom_point() +
scale_y_reverse() +
facet_geochem_gridh(vars(param)) +
labs(x = NULL, y = "Depth (cm)")
## ---- eval=FALSE--------------------------------------------------------------
# alta_lake_geochem %>%
# filter(param %in% c("d15N", "d13C", "C/N")) %>%
# ggplot(aes(x = value, y = depth)) +
# ...
## ---- echo=FALSE--------------------------------------------------------------
alta_lake_geochem %>%
filter(param %in% c("d15N", "d13C", "C/N")) %>%
ggplot(aes(x = value, y = depth)) +
geom_lineh() +
geom_point() +
scale_y_reverse() +
facet_geochem_gridh(vars(param)) +
labs(x = NULL, y = "Depth (cm)")
## ---- message=FALSE-----------------------------------------------------------
alta_adm <- age_depth_model(
alta_lake_bacon_ages,
depth = depth_cm,
age = 1950 - age_weighted_mean_year_BP
)
alta_plot +
scale_y_depth_age(
alta_adm,
age_name = "Age (Year AD)"
)
## -----------------------------------------------------------------------------
alta_plot +
facet_geochem_gridh(
vars(param),
units = c("C/N" = NA, "Cu" = "ppm", "d13C" = "‰", "d15N" = "‰"),
default_units = "%"
)
## -----------------------------------------------------------------------------
combined_data <- bind_rows(long_lake_plottable, alta_lake_geochem)
combined_data
## ---- fig.height=6------------------------------------------------------------
ggplot(combined_data, aes(x = value, y = depth)) +
geom_lineh() +
geom_point() +
scale_y_reverse() +
facet_geochem_gridh(vars(param), grouping = vars(location), scales = "free") +
labs(x = NULL, y = "Depth (cm)")
## ---- fig.height=6------------------------------------------------------------
alta_plot_1 <- combined_data %>%
filter(location == "ALGC2") %>%
ggplot(aes(x = value, y = depth)) +
geom_lineh() +
geom_point() +
scale_y_reverse() +
facet_geochem_gridh(vars(param), scales = "free") +
labs(x = NULL, y = "Depth (cm)", title = "Alta Lake")
long_plot_2 <- combined_data %>%
filter(location == "LL PC2") %>%
ggplot(aes(x = value, y = depth)) +
geom_lineh() +
geom_point() +
scale_y_reverse() +
facet_geochem_gridh(vars(param), scales = "free") +
labs(x = NULL, y = "Depth (cm)", title = "Long Lake")
library(patchwork)
wrap_plots(alta_plot_1, long_plot_2, ncol = 1)
## -----------------------------------------------------------------------------
coniss <- alta_lake_geochem %>%
nested_data(qualifiers = c(age, depth), key = param, value = value, trans = scale) %>%
nested_chclust_coniss()
alta_plot +
layer_dendrogram(coniss, aes(y = depth), param = "CONISS") +
layer_zone_boundaries(coniss, aes(y = depth))
## -----------------------------------------------------------------------------
alta_plot +
facet_geochem_wraph(vars(param), rotate_axis_labels = 0, ncol = 4)
## ---- fig.width=3, fig.height=5-----------------------------------------------
ggplot(alta_lake_geochem, aes(x = age, y = value)) +
geom_line() +
geom_point() +
scale_y_reverse() +
facet_geochem_grid(vars(param)) +
labs(x = "Age (Year AD)", y = NULL)
## -----------------------------------------------------------------------------
data("keji_lakes_plottable")
keji_lakes_plottable
## ---- fig.height=6------------------------------------------------------------
keji_plot <- ggplot(keji_lakes_plottable, aes(x = rel_abund, y = depth)) +
geom_col_segsh() +
scale_y_reverse() +
facet_abundanceh(vars(taxon), grouping = vars(location)) +
labs(x = "Relative abundance (%)", y = "Depth (cm)")
keji_plot
## ---- fig.height=6------------------------------------------------------------
ggplot(keji_lakes_plottable, aes(x = rel_abund, y = depth)) +
geom_areah() +
scale_y_reverse() +
facet_abundanceh(vars(taxon), grouping = vars(location)) +
labs(x = "Relative abundance (%)", y = "Depth (cm)")
## ---- fig.height=6------------------------------------------------------------
ggplot(keji_lakes_plottable, aes(x = rel_abund, y = depth)) +
geom_col_segsh() +
geom_lineh() +
scale_y_reverse() +
facet_abundanceh(vars(taxon), grouping = vars(location)) +
labs(x = "Relative abundance (%)", y = "Depth (cm)")
## ---- fig.height=6------------------------------------------------------------
keji_plot +
geom_lineh_exaggerate(exaggerate_x = 5, col = "grey70", lty = 2)
## ---- fig.height=6------------------------------------------------------------
keji_pca_scores <- keji_lakes_plottable %>%
group_by(location) %>%
nested_data(qualifiers = depth, key = taxon, value = rel_abund, trans = sqrt) %>%
nested_prcomp() %>%
unnest(qualifiers, scores) %>%
gather(key = component, value = value, starts_with("PC")) %>%
filter(component %in% c("PC1", "PC2"))
keji_pca_plot <- ggplot(keji_pca_scores, aes(x = value, y = depth)) +
geom_lineh() +
geom_point() +
scale_y_reverse() +
facet_geochem_gridh(vars(component), grouping = vars(location)) +
labs(x = NULL)
library(patchwork)
wrap_plots(
keji_plot +
theme(strip.background = element_blank(), strip.text.y = element_blank()),
keji_pca_plot +
theme(axis.text.y.left = element_blank(), axis.ticks.y.left = element_blank()) +
labs(y = NULL),
nrow = 1,
widths = c(4, 1)
)
## ---- fig.height=6------------------------------------------------------------
keji_coniss <- keji_lakes_plottable %>%
group_by(location) %>%
nested_data(qualifiers = depth, key = taxon, value = rel_abund) %>%
nested_chclust_coniss()
library(patchwork)
# method 1: use existing non-abundance plot
wrap_plots(
keji_plot +
theme(strip.background = element_blank(), strip.text.y = element_blank()),
keji_pca_plot +
layer_dendrogram(keji_coniss, component = "CONISS", aes(y = depth)) +
theme(axis.text.y.left = element_blank(), axis.ticks.y.left = element_blank()) +
labs(y = NULL),
nrow = 1,
widths = c(2, 1)
)
## ---- fig.height=6------------------------------------------------------------
# method 2: create a standalone plot for CONISS
coniss_plot <- ggplot() +
layer_dendrogram(keji_coniss, aes(y = depth)) +
scale_y_reverse() +
facet_geochem_gridh(vars("CONISS"), grouping = vars(location)) +
labs(x = NULL)
wrap_plots(
keji_plot +
theme(strip.background = element_blank(), strip.text.y = element_blank()),
coniss_plot +
theme(axis.text.y.left = element_blank(), axis.ticks.y.left = element_blank()) +
labs(y = NULL),
nrow = 1,
widths = c(6, 1)
)
## -----------------------------------------------------------------------------
data("halifax_lakes_plottable")
halifax_lakes_plottable
## -----------------------------------------------------------------------------
halifax_plot <- ggplot(halifax_lakes_plottable, aes(x = rel_abund, y = location, fill = sample_type)) +
geom_colh(width = 0.5, position = "dodgev") +
facet_abundanceh(vars(taxon)) +
labs(x = "Relative abundance (%)", y = NULL, fill = "Sample Type")
halifax_plot
## ---- eval=FALSE--------------------------------------------------------------
# halifax_lakes_plottable %>%
# mutate(location = fct_relevel(location, "Bell Lake", "Bayers", "Little Springfield") %>% fct_rev()) %>%
# ggplot(aes(x = rel_abund, y = location, fill = sample_type)) +
# ...
## ---- echo=FALSE--------------------------------------------------------------
halifax_lakes_plottable %>%
mutate(location = fct_relevel(location, "Bell Lake", "Bayers", "Little Springfield") %>% fct_rev()) %>%
ggplot(aes(x = rel_abund, y = location, fill = sample_type)) +
geom_colh(width = 0.5, position = "dodgev") +
facet_abundanceh(vars(taxon)) +
labs(x = "Relative abundance (%)", y = NULL, fill = "Sample Type")
## -----------------------------------------------------------------------------
halifax_clust <- halifax_lakes_plottable %>%
filter(sample_type == "top") %>%
nested_data(qualifiers = location, key = taxon, value = rel_abund) %>%
nested_hclust(method = "average")
dendro_order <- halifax_clust %>%
unnest(qualifiers, dendro_order) %>%
arrange(dendro_order) %>%
pull(location)
library(patchwork)
wrap_plots(
halifax_plot +
scale_y_discrete(limits = dendro_order) +
theme(legend.position = "left"),
ggplot() +
layer_dendrogram(halifax_clust, aes(y = location)) +
scale_y_discrete(limits = dendro_order) +
labs(x = "Dispersion", y = NULL) +
theme(axis.text.y.left = element_blank(), axis.ticks.y.left = element_blank()),
widths = c(4, 1)
)
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