具有 1 维密度图对齐的密度热图
Density Heatmap with 1 Dimension Density Plot Alignment
我正在使用 this post in order to create a density heatmap on a map paired with the one dimensional x and y density plots. I was able to produce the following image: Density Heatmap
中概述的方法
但是，我很难将顶部密度图中的阴影区域与地图上的热图对齐。我发现这与我在代码中应用墨卡托投影来生成热图这一事实有关，而顶部和右侧的密度图仅使用数据中的坐标。
有什么方法可以使热图中的投影坐标与一维密度图中的非投影坐标对齐？
下面是我的代码的相关部分（我使用 grid/gtable 包来组合不同的图形）。
编辑：数据由三列组成：UniqueID、Lon 和 Lat。在这种情况下，所有 Lon/Lat 对都是 in/around 纽约市，但出于故障排除目的，只要可以投影，确切的对并不重要。
library(gtable)
library(ggplot2)
library(ggmap)
ny <- get_map(location = "Washington Heights, New York City", zoom = 12, color = "bw")
ggm <- ggmap(ny, extent = "normal", maprange = F) %+% data +
aes(x = Lon, y = Lat) +
stat_density2d(aes(fill = ..level..,
alpha = ..level..), color = "darkgreen",
geom = "polygon", show.legend = TRUE) +
geom_polygon(aes(x, y),
data.frame(x = c(Inf, Inf, -73.90, -73.90), y = c(Inf, 40.84, 40.84, Inf)),
alpha = 0.5, colour = NA, fill = "red") +
coord_map(projection = "mercator",
xlim = c(attr(ny, "bb")$ll.lon, attr(ny, "bb")$ur.lon),
ylim = c(attr(ny, "bb")$ll.lat, attr(ny, "bb")$ur.lat))
xd <- data.frame(density(data$Lon)[c("x", "y")])
gg1 <- ggplot(xd, aes(x, y)) +
theme(panel.grid.minor = element_line(colour = NA),
panel.background = element_rect(fill = NA, colour = NA)) +
labs(y = "Density") +
geom_area(data = subset(xd, x > -73.90), fill = "red") +
geom_line() +
coord_cartesian(c(attr(ny, "bb")$ll.lon, attr(ny, "bb")$ur.lon))
image <- gtable_filter(ggplotGrob(ggm), pattern = "panel", trim = TRUE, fixed=TRUE)
image <- gtable_add_cols(image, unit(0.2, "null"), 1)
image <- gtable_add_grob(image, gtable_filter(ggplotGrob(gg1), pattern = "panel", trim = TRUE, fixed=TRUE), 1, 1)
我认为问题不在于投影。如果您检查顶部密度图的 x-range 和地图的 x-range，我认为它们不一样。同样，右侧密度图的 y-range 与地图的 y-range 相比。请参阅底部的代码。范围不相同的原因是，默认情况下，ggmap 没有轴的扩展因子，而 ggplot 默认情况下有扩展因子。在两个密度图中设置 expand = c(0,0)。
似乎还有一个问题。需要翻转正确的密度图，但翻转会干扰通过 coord_cartesian 设置的限制。如果我使用 xlim（和 ylim）设置限制，则限制在翻转后仍然存在。
library(ggmap)
library(gtable)
library(ggplot2)
library(grid)
ny <- get_map(location = "Washington Heights, New York City", zoom = 12, color = "bw")
# Pretend data
set.seed(5126)
df = data.frame(Lon = rnorm(100, mean = -73.90, sd = .015), Lat = rnorm(100, mean = 40.84, sd = .015))
# Map
ggm <- ggmap(ny, extent = "normal", maprange = F) %+% df +
aes(x = Lon, y = Lat) +
stat_density2d(aes(fill = ..level..,
alpha = ..level..),
geom = "polygon", show.legend = TRUE) +
geom_polygon(aes(x, y),
data.frame(x = c(Inf, Inf, -73.90, -73.90), y = c(Inf, 40.84, 40.84, Inf)),
alpha = 0.5, colour = NA, fill = "red") + geom_point() +
coord_map(projection = "mercator",
xlim = c(attr(ny, "bb")$ll.lon, attr(ny, "bb")$ur.lon),
ylim = c(attr(ny, "bb")$ll.lat, attr(ny, "bb")$ur.lat))
# Top density plot
xd <- data.frame(density(df$Lon)[c("x", "y")])
gg1 <- ggplot(xd, aes(x, y)) +
theme(panel.grid.minor = element_line(colour = NA),
panel.background = element_rect(fill = NA, colour = NA)) +
labs(y = "Density") +
geom_area(data = subset(xd, x > -73.90), fill = "red") +
geom_line() +
scale_x_continuous(limits = c(attr(ny, "bb")$ll.lon, attr(ny, "bb")$ur.lon), expand = c(0,0))
image <- gtable_filter(ggplotGrob(ggm), pattern = "panel", trim = TRUE, fixed=TRUE)
image <- gtable_add_rows(image, unit(0.2, "null"), 0)
image <- gtable_add_grob(image, gtable_filter(ggplotGrob(gg1), pattern = "panel", trim = TRUE, fixed=TRUE), 1, 1)
grid.newpage()
grid.draw(image)
# Right density plot
xd <- data.frame(density(df$Lat)[c("x", "y")])
gg2 <- ggplot(xd, aes(x, y)) +
theme(panel.grid.minor = element_line(colour = NA),
panel.background = element_rect(fill = NA, colour = NA)) +
labs(y = "Density") +
geom_area(data = subset(xd, x > 40.84), fill = "red") +
geom_line() +
scale_x_continuous(limits = c(attr(ny, "bb")$ll.lat, attr(ny, "bb")$ur.lat), expand = c(0,0)) +
coord_flip()
image <- gtable_add_cols(image, unit(0.2, "null"), 1)
image <- gtable_add_grob(image, gtable_filter(ggplotGrob(gg2), pattern = "panel", trim = TRUE, fixed=TRUE), 2, 2)
grid.newpage()
grid.draw(image)
编辑 更新到 ggplot2 ver 3.0.0
# Check that the ranges for the density plots are the same as the ranges for the map
top = ggplot_build(gg1)
right = ggplot_build(gg2)
map = ggplot_build(ggm)
top$layout$panel_params[[1]]$x.range
map$layout$panel_params[[1]]$x.range
right$layout$panel_params[[1]]$y.range
map$layout$panel_params[[1]]$y.range
我正在使用 this post in order to create a density heatmap on a map paired with the one dimensional x and y density plots. I was able to produce the following image: Density Heatmap
中概述的方法但是，我很难将顶部密度图中的阴影区域与地图上的热图对齐。我发现这与我在代码中应用墨卡托投影来生成热图这一事实有关，而顶部和右侧的密度图仅使用数据中的坐标。
有什么方法可以使热图中的投影坐标与一维密度图中的非投影坐标对齐？
下面是我的代码的相关部分（我使用 grid/gtable 包来组合不同的图形）。
编辑：数据由三列组成：UniqueID、Lon 和 Lat。在这种情况下，所有 Lon/Lat 对都是 in/around 纽约市，但出于故障排除目的，只要可以投影，确切的对并不重要。
library(gtable)
library(ggplot2)
library(ggmap)
ny <- get_map(location = "Washington Heights, New York City", zoom = 12, color = "bw")
ggm <- ggmap(ny, extent = "normal", maprange = F) %+% data +
aes(x = Lon, y = Lat) +
stat_density2d(aes(fill = ..level..,
alpha = ..level..), color = "darkgreen",
geom = "polygon", show.legend = TRUE) +
geom_polygon(aes(x, y),
data.frame(x = c(Inf, Inf, -73.90, -73.90), y = c(Inf, 40.84, 40.84, Inf)),
alpha = 0.5, colour = NA, fill = "red") +
coord_map(projection = "mercator",
xlim = c(attr(ny, "bb")$ll.lon, attr(ny, "bb")$ur.lon),
ylim = c(attr(ny, "bb")$ll.lat, attr(ny, "bb")$ur.lat))
xd <- data.frame(density(data$Lon)[c("x", "y")])
gg1 <- ggplot(xd, aes(x, y)) +
theme(panel.grid.minor = element_line(colour = NA),
panel.background = element_rect(fill = NA, colour = NA)) +
labs(y = "Density") +
geom_area(data = subset(xd, x > -73.90), fill = "red") +
geom_line() +
coord_cartesian(c(attr(ny, "bb")$ll.lon, attr(ny, "bb")$ur.lon))
image <- gtable_filter(ggplotGrob(ggm), pattern = "panel", trim = TRUE, fixed=TRUE)
image <- gtable_add_cols(image, unit(0.2, "null"), 1)
image <- gtable_add_grob(image, gtable_filter(ggplotGrob(gg1), pattern = "panel", trim = TRUE, fixed=TRUE), 1, 1)
我认为问题不在于投影。如果您检查顶部密度图的 x-range 和地图的 x-range，我认为它们不一样。同样，右侧密度图的 y-range 与地图的 y-range 相比。请参阅底部的代码。范围不相同的原因是，默认情况下，ggmap 没有轴的扩展因子，而 ggplot 默认情况下有扩展因子。在两个密度图中设置 expand = c(0,0)。
似乎还有一个问题。需要翻转正确的密度图，但翻转会干扰通过 coord_cartesian 设置的限制。如果我使用 xlim（和 ylim）设置限制，则限制在翻转后仍然存在。
library(ggmap)
library(gtable)
library(ggplot2)
library(grid)
ny <- get_map(location = "Washington Heights, New York City", zoom = 12, color = "bw")
# Pretend data
set.seed(5126)
df = data.frame(Lon = rnorm(100, mean = -73.90, sd = .015), Lat = rnorm(100, mean = 40.84, sd = .015))
# Map
ggm <- ggmap(ny, extent = "normal", maprange = F) %+% df +
aes(x = Lon, y = Lat) +
stat_density2d(aes(fill = ..level..,
alpha = ..level..),
geom = "polygon", show.legend = TRUE) +
geom_polygon(aes(x, y),
data.frame(x = c(Inf, Inf, -73.90, -73.90), y = c(Inf, 40.84, 40.84, Inf)),
alpha = 0.5, colour = NA, fill = "red") + geom_point() +
coord_map(projection = "mercator",
xlim = c(attr(ny, "bb")$ll.lon, attr(ny, "bb")$ur.lon),
ylim = c(attr(ny, "bb")$ll.lat, attr(ny, "bb")$ur.lat))
# Top density plot
xd <- data.frame(density(df$Lon)[c("x", "y")])
gg1 <- ggplot(xd, aes(x, y)) +
theme(panel.grid.minor = element_line(colour = NA),
panel.background = element_rect(fill = NA, colour = NA)) +
labs(y = "Density") +
geom_area(data = subset(xd, x > -73.90), fill = "red") +
geom_line() +
scale_x_continuous(limits = c(attr(ny, "bb")$ll.lon, attr(ny, "bb")$ur.lon), expand = c(0,0))
image <- gtable_filter(ggplotGrob(ggm), pattern = "panel", trim = TRUE, fixed=TRUE)
image <- gtable_add_rows(image, unit(0.2, "null"), 0)
image <- gtable_add_grob(image, gtable_filter(ggplotGrob(gg1), pattern = "panel", trim = TRUE, fixed=TRUE), 1, 1)
grid.newpage()
grid.draw(image)
# Right density plot
xd <- data.frame(density(df$Lat)[c("x", "y")])
gg2 <- ggplot(xd, aes(x, y)) +
theme(panel.grid.minor = element_line(colour = NA),
panel.background = element_rect(fill = NA, colour = NA)) +
labs(y = "Density") +
geom_area(data = subset(xd, x > 40.84), fill = "red") +
geom_line() +
scale_x_continuous(limits = c(attr(ny, "bb")$ll.lat, attr(ny, "bb")$ur.lat), expand = c(0,0)) +
coord_flip()
image <- gtable_add_cols(image, unit(0.2, "null"), 1)
image <- gtable_add_grob(image, gtable_filter(ggplotGrob(gg2), pattern = "panel", trim = TRUE, fixed=TRUE), 2, 2)
grid.newpage()
grid.draw(image)
编辑 更新到 ggplot2 ver 3.0.0
# Check that the ranges for the density plots are the same as the ranges for the map
top = ggplot_build(gg1)
right = ggplot_build(gg2)
map = ggplot_build(ggm)
top$layout$panel_params[[1]]$x.range
map$layout$panel_params[[1]]$x.range
right$layout$panel_params[[1]]$y.range
map$layout$panel_params[[1]]$y.range