R/Figure_wet_dry_2016.R
In lbusett/phenoricesrv:
Defines functions
plot_dates
# FIgure 3
#
library(raster)
library(sprawl)
library(ggspatial)
library(gridExtra)
library(magrittr)
library(tidyr)
library(data.table)
library(lubridate)
library(mapedit)
library(wrapr)
library(mapview)
res_folder <- "/home/lb/nr_working/shared/PhenoRice/Processing/Senegal/Final/Outputs_MaskIrrig/"
setwd(res_folder)
in_2016 <- read_rast("2016/Phenorice_out_2015_321_2017_089.dat")
# names(in_2016) <- c("Sowing_Date_Dry", "Sowing_Date_Wet")
# ext <- select_extent(in_2016[[1]], transparency = 0.5)
#
# "Flowering_Date_Wet", "Flowering_Date_Dry",
# "Harvesting_Date_Wet", "Harvesting_Date_Dry")
sen_borders <- get_boundaries("SEN", 2) %>%
tibble::as_tibble() %>%
sf::st_as_sf() %>%
sf::st_transform(get_proj4string(in_2016))
mau_borders <- get_boundaries("MRT", 2) %>%
tibble::as_tibble() %>%
sf::st_as_sf() %>%
sf::st_transform(get_proj4string(in_2016))
borders <- rbind(sen_borders, mau_borders) %.>%
dplyr::mutate(.,
lon = purrr::map_dbl(geometry, ~sf::st_centroid(.x)[[1]]),
lat = purrr::map_dbl(geometry, ~sf::st_centroid(.x)[[2]])
) %>%
sf::st_as_sf()
# save(ext, file = "/home/lb/Source/git/phenoricesrv/extent_maps.RData")
sow_dry <- in_2016[[2]]
sow_fish <- create_fishnet(sow_dry, cellsize = 5000, shape = "hex")
in_rast <- in_2016[[c(2,3,4,5,6,7)]]
names(in_rast) <- c("Sow_Dry" ,"Sow_Wet", "Head_Dry", "Head_Wet", "Harv_Dry",
"Harv_Wet")
aggr_data <- extract_rast(in_rast, sow_fish, full_data = FALSE)$stats
aggr_data_filt <- aggr_data %>%
dplyr::filter(avg > 0, n_pix_val > 1) %.>%
dplyr::mutate(.,
lon = purrr::map_dbl(geometry, ~sf::st_centroid(.x)[[1]]),
lat = purrr::map_dbl(geometry, ~sf::st_centroid(.x)[[2]])
) %>%
sf::st_as_sf()
# ____________________________________________________________________________
# Sow_dry ####
data_ds <- dplyr::filter(aggr_data_filt, band_name == "Sow_Dry") %>%
dplyr::mutate(rice_area = log(0.01 + n_pix_val * 231.656^2 / 10000)) %>%
dplyr::mutate(rice_area = rice_area / max(rice_area))
labels <- as.Date("2016-02-15") %m+% days(c(0, 15, 30, 46, 60, 75))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
zlims <- quantile(data_ds$avg, probs = c(0.02, 0.98))
p_dry_sow <- plot_dates(data_ds, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Sowing Date - Dry Season 2016") +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
# ____________________________________________________________________________
# Sow_wet ####
data_ws <- dplyr::filter(aggr_data_filt, band_name == "Sow_Wet")%>%
dplyr::mutate(rice_area = log(0.01 + n_pix_val * 231.656^2 / 10000)) %>%
dplyr::mutate(rice_area = rice_area / max(rice_area))
labels <- as.Date("2016-07-15") %m+% days(c(0, 15, 30, 46, 60, 75))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
zlims <- quantile(data_ws$avg, probs = c(0.02,0.98))
p_wet_sow <- plot_dates(data_ws, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Sowing Date - Wet Season 2016") +
# theme(legend.box.spacing = unit(0, "mm")) +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
# ____________________________________________________________________________
# Head_dry ####
data_ds <- dplyr::filter(aggr_data_filt, band_name == "Head_Dry")
labels <- as.Date("2016-05-01") %m+% days(c(0, 14, 31, 47, 61, 76))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
# zlims <- quantile(data_ds$avg, probs = c(0.02,0.98))
p_dry_head <- plot_dates(data_ds, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Flowering Date - Dry Season 2016") +
# theme(legend.box.spacing = unit(0, "mm")) +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
# ____________________________________________________________________________
# Head_wet ####
data_ws <- dplyr::filter(aggr_data_filt, band_name == "Head_Wet")
labels <- as.Date("2016-09-15") %m+% days(c(0, 16, 31, 47, 61, 77))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
zlims <- quantile(data_ws$avg, probs = c(0.02,0.98))
p_wet_head <- plot_dates(data_ws, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Harvesting Date - Wet Season 2016") +
# theme(legend.box.spacing = unit(0, "mm")) +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
# ____________________________________________________________________________
# Harv_dry ####
data_ds <- dplyr::filter(aggr_data_filt, band_name == "Harv_Dry")
labels <- as.Date("2016-06-15") %m+% days(c(0, 16, 31, 47, 61, 76))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
zlims <- quantile(data_ds$avg, probs = c(0.02,0.98))
p_dry_harv <- plot_dates(data_ds, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Harvesting Date - Dry Season 2016") +
# theme(legend.box.spacing = unit(0, "mm")) +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
# ____________________________________________________________________________
# Harv_wet ####
data_ws <- dplyr::filter(aggr_data_filt, band_name == "Harv_Wet")
labels <- as.Date("2016-10-15") %m+% days(c(0, 16, 31, 47, 61, 77))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
zlims <- quantile(data_ws$avg, probs = c(0.02,0.98))
p_wet_harv <- plot_dates(data_ws, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Flowering Date - Wet Season 2016") +
# theme(legend.box.spacing = unit(0, "mm")) +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/sow_dry_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_dry_sow)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/sow_wet_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_wet_sow)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/head_dry_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_dry_head)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/head_wet_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_wet_head)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/harv_wet_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_dry_harv)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/harv_dry_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_wet_harv)
library(gridExtra)
grid.arrange(p_dry_sow, p_wet_sow, p_dry_head, p_wet_head, p_dry_harv, p_wet_harv,
ncol = 2)
plot_dates <- function(in_data, var, borders, leg_labels, leg_breaks, title) {
plot <- ggplot() +
geom_sf(data = borders, fill = "grey95", size = 0.3) +
geom_sf(data = in_data, aes_string(fill = var), size = 0.1) +
# geom_text(data = borders, aes(label = NAME_2, x = lon, y = lat), size = 2.5) +
xlim(get_extent(in_data)@extent[c(1,3)]) +
ylim(get_extent(in_data)@extent[c(2,4)]) +
ggplot2::theme_bw() +
scale_fill_distiller(type = "div",
palette = "RdYlGn",
labels = leg_labels,
limits = c(min(leg_breaks),max(leg_breaks)),
oob = scales::squish,
breaks = leg_breaks,
direction = 1) +
ggplot2::theme(legend.position = "bottom") +
ggplot2::guides(
fill = ggplot2::guide_colourbar(title = "",
title.position = "bottom",
title.hjust = 0.5,
label.position = "top",
label.hjust = 0.5,
barwidth = unit(0.5, "npc"))) +
geom_text(data = borders, aes(label = NAME_2, x = lon, y = lat), size = 2) +
geom_sf(data = borders, fill = "transparent", size = 0.2) +
theme(panel.ontop = T, panel.background = element_rect(fill = "transparent",
color = "grey30")) +
theme(legend.margin = margin(0,0,0,0, unit = "cm")) +
theme(plot.margin = margin(0.1,0.1,0.1,0.1, unit = "cm"),
panel.grid.major = element_line(color = "grey45", size = 0.5))+
labs(title = title,
x = "", y = "") +
theme(legend.box.spacing = unit(0, "mm")) +
geom_sf(data = river, color = "#378DD4", alpha = 0.1, size = 0.2)
plot
}
# aggr_data_filt <- sf::st_transform(aggr_data_filt, "+init=epsg:3857")
data(World)
data(rivers)
data(land)
plot_gg <- tm_shape(aggr_data_filt, bbox = as(get_extent(aggr_data_filt), "Extent")) +
tm_polygons("avg", colorNA = "transparent", palette = "RdYlGn", style = "cont",
auto.palette.mapping = FALSE, title = "",
breaks = breaks, labels = labels,
legend.is.portrait = FALSE) +
# tm_shape(land, bbox = as(get_extent(aggr_data_filt), "Extent")) +
# tm_raster("cover_cls", bbox = as(get_extent(aggr_data_filt), "Extent")) +
tm_shape(sen_borders) +
tm_borders() +
tm_text("NAME_2", size = 0.7) +
tm_shape(mau_borders) +
tm_borders() +
tm_text("NAME_2", size = 0.7) +
tm_legend(legend.bg.color = "white",
legend.bg.alpha = 1,
legend.frame = T,
# legend.position = c("center","bottom"),
# legend.width = 50,
legend.just = "center",
legend.position = c("right","top")) +
tm_scale_bar()
ggplot2::labs(title = "New plot title")
sow_dry_plot <- plot_rast_gg(sow_dry, basemap = "stamenbw",
xlims = c(-1830000, -1700000),
ylims = c(1825000, 1875000), scalebar_dist = 25,
palette_type = "diverging", zlims = c(0.02, 0.98),
zlims_type = "percs",
band_names = "Sowing Date - dry Season 2016",
leg_breaks = breaks,
leg_labels = labels,
leg_type = "continuous",
palette_name = "RdYlGn",
title = "Sowing Dates - Dry Season 2016")
sow_dry_plot + ggplot2::theme(legend.position = "bottom") +
ggplot2::guides(fill = ggplot2::guide_colourbar(title = "",
title.position = "top",
title.hjust = 0.5,
label.position = "bottom",
label.hjust = 0.5, barwidth = unit(0.8, "npc")))
sow_dry_plot + ggplot2::theme(legend.position = "bottom") +
ggplot2::guides(fill = ggplot2::guide_legend(title = "",
title.position = "top",
title.hjust = 0.5,
label.position = "bottom",
label.hjust = 0.5, keywidth = 5))
myext <- new("sprawlext", extent = c(-1830000,1825000,-1700000, 1875000 ))
sow_wet <- crop(in_2016[[3]],
labels <- as.Date("2016-07-01") %m+% days(c(0,15, 29, 45))
breaks <- datetodoy(labels)
labels <- format(labels, "%d\ %B")
sow_wet_plot <- plot_rast_gg(sow_wet, basemap = "stamenbw",
xlims = c(-1830000, -1700000),
ylims = c(1825000, 1875000), scalebar_dist = 25,
palette_type = "diverging", zlims = c(0.02, 0.98),
zlims_type = "percs",
band_names = "Sowing Date - wet Season 2016",
# leg_breaks = breaks,
# leg_labels = labels,
leg_type = "continuous",
palette_name = "RdYlGn",
na.color = "transparent", oob_style = "expand",
title = "Sowing Dates - Wet Season 2016"
)
sow_wet_plot + ggplot2::theme(legend.position = "bottom") +
ggplot2::guides(fill = ggplot2::guide_colourbar(title = "",
title.position = "top",
title.hjust = 0.5,
label.position = "bottom",
label.hjust = 0.5, barwidth = unit(0.8, "npc")))
sow_wet_plot + ggplot2::theme(legend.position = "bottom") +
ggplot2::guides(fill = ggplot2::guide_legend(title = "",
title.position = "top",
title.hjust = 0.5,
label.position = "bottom",
label.hjust = 0.5, keywidth = 5))
lbusett/phenoricesrv documentation built on May 20, 2019, 2:09 p.m.
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Defines functions plot_dates
# FIgure 3
#
library(raster)
library(sprawl)
library(ggspatial)
library(gridExtra)
library(magrittr)
library(tidyr)
library(data.table)
library(lubridate)
library(mapedit)
library(wrapr)
library(mapview)
res_folder <- "/home/lb/nr_working/shared/PhenoRice/Processing/Senegal/Final/Outputs_MaskIrrig/"
setwd(res_folder)
in_2016 <- read_rast("2016/Phenorice_out_2015_321_2017_089.dat")
# names(in_2016) <- c("Sowing_Date_Dry", "Sowing_Date_Wet")
# ext <- select_extent(in_2016[[1]], transparency = 0.5)
#
# "Flowering_Date_Wet", "Flowering_Date_Dry",
# "Harvesting_Date_Wet", "Harvesting_Date_Dry")
sen_borders <- get_boundaries("SEN", 2) %>%
tibble::as_tibble() %>%
sf::st_as_sf() %>%
sf::st_transform(get_proj4string(in_2016))
mau_borders <- get_boundaries("MRT", 2) %>%
tibble::as_tibble() %>%
sf::st_as_sf() %>%
sf::st_transform(get_proj4string(in_2016))
borders <- rbind(sen_borders, mau_borders) %.>%
dplyr::mutate(.,
lon = purrr::map_dbl(geometry, ~sf::st_centroid(.x)[[1]]),
lat = purrr::map_dbl(geometry, ~sf::st_centroid(.x)[[2]])
) %>%
sf::st_as_sf()
# save(ext, file = "/home/lb/Source/git/phenoricesrv/extent_maps.RData")
sow_dry <- in_2016[[2]]
sow_fish <- create_fishnet(sow_dry, cellsize = 5000, shape = "hex")
in_rast <- in_2016[[c(2,3,4,5,6,7)]]
names(in_rast) <- c("Sow_Dry" ,"Sow_Wet", "Head_Dry", "Head_Wet", "Harv_Dry",
"Harv_Wet")
aggr_data <- extract_rast(in_rast, sow_fish, full_data = FALSE)$stats
aggr_data_filt <- aggr_data %>%
dplyr::filter(avg > 0, n_pix_val > 1) %.>%
dplyr::mutate(.,
lon = purrr::map_dbl(geometry, ~sf::st_centroid(.x)[[1]]),
lat = purrr::map_dbl(geometry, ~sf::st_centroid(.x)[[2]])
) %>%
sf::st_as_sf()
# ____________________________________________________________________________
# Sow_dry ####
data_ds <- dplyr::filter(aggr_data_filt, band_name == "Sow_Dry") %>%
dplyr::mutate(rice_area = log(0.01 + n_pix_val * 231.656^2 / 10000)) %>%
dplyr::mutate(rice_area = rice_area / max(rice_area))
labels <- as.Date("2016-02-15") %m+% days(c(0, 15, 30, 46, 60, 75))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
zlims <- quantile(data_ds$avg, probs = c(0.02, 0.98))
p_dry_sow <- plot_dates(data_ds, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Sowing Date - Dry Season 2016") +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
# ____________________________________________________________________________
# Sow_wet ####
data_ws <- dplyr::filter(aggr_data_filt, band_name == "Sow_Wet")%>%
dplyr::mutate(rice_area = log(0.01 + n_pix_val * 231.656^2 / 10000)) %>%
dplyr::mutate(rice_area = rice_area / max(rice_area))
labels <- as.Date("2016-07-15") %m+% days(c(0, 15, 30, 46, 60, 75))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
zlims <- quantile(data_ws$avg, probs = c(0.02,0.98))
p_wet_sow <- plot_dates(data_ws, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Sowing Date - Wet Season 2016") +
# theme(legend.box.spacing = unit(0, "mm")) +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
# ____________________________________________________________________________
# Head_dry ####
data_ds <- dplyr::filter(aggr_data_filt, band_name == "Head_Dry")
labels <- as.Date("2016-05-01") %m+% days(c(0, 14, 31, 47, 61, 76))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
# zlims <- quantile(data_ds$avg, probs = c(0.02,0.98))
p_dry_head <- plot_dates(data_ds, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Flowering Date - Dry Season 2016") +
# theme(legend.box.spacing = unit(0, "mm")) +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
# ____________________________________________________________________________
# Head_wet ####
data_ws <- dplyr::filter(aggr_data_filt, band_name == "Head_Wet")
labels <- as.Date("2016-09-15") %m+% days(c(0, 16, 31, 47, 61, 77))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
zlims <- quantile(data_ws$avg, probs = c(0.02,0.98))
p_wet_head <- plot_dates(data_ws, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Harvesting Date - Wet Season 2016") +
# theme(legend.box.spacing = unit(0, "mm")) +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
# ____________________________________________________________________________
# Harv_dry ####
data_ds <- dplyr::filter(aggr_data_filt, band_name == "Harv_Dry")
labels <- as.Date("2016-06-15") %m+% days(c(0, 16, 31, 47, 61, 76))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
zlims <- quantile(data_ds$avg, probs = c(0.02,0.98))
p_dry_harv <- plot_dates(data_ds, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Harvesting Date - Dry Season 2016") +
# theme(legend.box.spacing = unit(0, "mm")) +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
# ____________________________________________________________________________
# Harv_wet ####
data_ws <- dplyr::filter(aggr_data_filt, band_name == "Harv_Wet")
labels <- as.Date("2016-10-15") %m+% days(c(0, 16, 31, 47, 61, 77))
breaks <- datetodoy(labels)
labels <- format(labels, "%d/%m")
zlims <- quantile(data_ws$avg, probs = c(0.02,0.98))
p_wet_harv <- plot_dates(data_ws, "avg",borders,
leg_labels = labels, leg_breaks = breaks,
title = "Average Flowering Date - Wet Season 2016") +
# theme(legend.box.spacing = unit(0, "mm")) +
xlim(-1756882 ,-1292967 ) + ylim(1633301, 1875359)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/sow_dry_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_dry_sow)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/sow_wet_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_wet_sow)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/head_dry_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_dry_head)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/head_wet_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_wet_head)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/harv_wet_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_dry_harv)
ggsave(filename = "/home/lb/Google_Drive/IREA/Conference&paper/PhenoRice_SRV/Manuscript/Figures/harv_dry_16.tiff",
dpi = 400, width = 6.57, height = 4.23, plot = p_wet_harv)
library(gridExtra)
grid.arrange(p_dry_sow, p_wet_sow, p_dry_head, p_wet_head, p_dry_harv, p_wet_harv,
ncol = 2)
plot_dates <- function(in_data, var, borders, leg_labels, leg_breaks, title) {
plot <- ggplot() +
geom_sf(data = borders, fill = "grey95", size = 0.3) +
geom_sf(data = in_data, aes_string(fill = var), size = 0.1) +
# geom_text(data = borders, aes(label = NAME_2, x = lon, y = lat), size = 2.5) +
xlim(get_extent(in_data)@extent[c(1,3)]) +
ylim(get_extent(in_data)@extent[c(2,4)]) +
ggplot2::theme_bw() +
scale_fill_distiller(type = "div",
palette = "RdYlGn",
labels = leg_labels,
limits = c(min(leg_breaks),max(leg_breaks)),
oob = scales::squish,
breaks = leg_breaks,
direction = 1) +
ggplot2::theme(legend.position = "bottom") +
ggplot2::guides(
fill = ggplot2::guide_colourbar(title = "",
title.position = "bottom",
title.hjust = 0.5,
label.position = "top",
label.hjust = 0.5,
barwidth = unit(0.5, "npc"))) +
geom_text(data = borders, aes(label = NAME_2, x = lon, y = lat), size = 2) +
geom_sf(data = borders, fill = "transparent", size = 0.2) +
theme(panel.ontop = T, panel.background = element_rect(fill = "transparent",
color = "grey30")) +
theme(legend.margin = margin(0,0,0,0, unit = "cm")) +
theme(plot.margin = margin(0.1,0.1,0.1,0.1, unit = "cm"),
panel.grid.major = element_line(color = "grey45", size = 0.5))+
labs(title = title,
x = "", y = "") +
theme(legend.box.spacing = unit(0, "mm")) +
geom_sf(data = river, color = "#378DD4", alpha = 0.1, size = 0.2)
plot
}
# aggr_data_filt <- sf::st_transform(aggr_data_filt, "+init=epsg:3857")
data(World)
data(rivers)
data(land)
plot_gg <- tm_shape(aggr_data_filt, bbox = as(get_extent(aggr_data_filt), "Extent")) +
tm_polygons("avg", colorNA = "transparent", palette = "RdYlGn", style = "cont",
auto.palette.mapping = FALSE, title = "",
breaks = breaks, labels = labels,
legend.is.portrait = FALSE) +
# tm_shape(land, bbox = as(get_extent(aggr_data_filt), "Extent")) +
# tm_raster("cover_cls", bbox = as(get_extent(aggr_data_filt), "Extent")) +
tm_shape(sen_borders) +
tm_borders() +
tm_text("NAME_2", size = 0.7) +
tm_shape(mau_borders) +
tm_borders() +
tm_text("NAME_2", size = 0.7) +
tm_legend(legend.bg.color = "white",
legend.bg.alpha = 1,
legend.frame = T,
# legend.position = c("center","bottom"),
# legend.width = 50,
legend.just = "center",
legend.position = c("right","top")) +
tm_scale_bar()
ggplot2::labs(title = "New plot title")
sow_dry_plot <- plot_rast_gg(sow_dry, basemap = "stamenbw",
xlims = c(-1830000, -1700000),
ylims = c(1825000, 1875000), scalebar_dist = 25,
palette_type = "diverging", zlims = c(0.02, 0.98),
zlims_type = "percs",
band_names = "Sowing Date - dry Season 2016",
leg_breaks = breaks,
leg_labels = labels,
leg_type = "continuous",
palette_name = "RdYlGn",
title = "Sowing Dates - Dry Season 2016")
sow_dry_plot + ggplot2::theme(legend.position = "bottom") +
ggplot2::guides(fill = ggplot2::guide_colourbar(title = "",
title.position = "top",
title.hjust = 0.5,
label.position = "bottom",
label.hjust = 0.5, barwidth = unit(0.8, "npc")))
sow_dry_plot + ggplot2::theme(legend.position = "bottom") +
ggplot2::guides(fill = ggplot2::guide_legend(title = "",
title.position = "top",
title.hjust = 0.5,
label.position = "bottom",
label.hjust = 0.5, keywidth = 5))
myext <- new("sprawlext", extent = c(-1830000,1825000,-1700000, 1875000 ))
sow_wet <- crop(in_2016[[3]],
labels <- as.Date("2016-07-01") %m+% days(c(0,15, 29, 45))
breaks <- datetodoy(labels)
labels <- format(labels, "%d\ %B")
sow_wet_plot <- plot_rast_gg(sow_wet, basemap = "stamenbw",
xlims = c(-1830000, -1700000),
ylims = c(1825000, 1875000), scalebar_dist = 25,
palette_type = "diverging", zlims = c(0.02, 0.98),
zlims_type = "percs",
band_names = "Sowing Date - wet Season 2016",
# leg_breaks = breaks,
# leg_labels = labels,
leg_type = "continuous",
palette_name = "RdYlGn",
na.color = "transparent", oob_style = "expand",
title = "Sowing Dates - Wet Season 2016"
)
sow_wet_plot + ggplot2::theme(legend.position = "bottom") +
ggplot2::guides(fill = ggplot2::guide_colourbar(title = "",
title.position = "top",
title.hjust = 0.5,
label.position = "bottom",
label.hjust = 0.5, barwidth = unit(0.8, "npc")))
sow_wet_plot + ggplot2::theme(legend.position = "bottom") +
ggplot2::guides(fill = ggplot2::guide_legend(title = "",
title.position = "top",
title.hjust = 0.5,
label.position = "bottom",
label.hjust = 0.5, keywidth = 5))
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