如何在通过 ggarrange 创建的图表周围添加边框并在组合图表之间增加 space
How to add a border around a chart created via ggarrange and increase space between combined charts
我正在尝试绘制 Numa 节点 CPU 和内存使用情况。
我的示例中有 4 个 numa 节点，每个节点有 CPU 和内存使用图表。
问题是 - 在每个节点中可能有许多 CPU 值（每个核心 1 条，在我的示例中为 20 个核心）并且只有一个内存值，所以我不得不使用不同宽度的图表（CPU 图表比内存更宽）。由于该注释文本 (NUMA XX) 现在看起来不像是图表的中间。我真的不能说是哪个节点的内存条。
我想我需要使用边框或背景颜色将 numa 节点彼此分开，以便 CPU 和每个 Numa 节点的内存在一起。另外我认为我需要减少 CPU 和 numa 节点内的内存之间的 space 并增加 numa 节点之间的 space 。怎么做？
我的代码：
library(dplyr)
library(ggplot2)
library(ggpubr)
library(tidyr)
memory_df <- structure(list(NumaNode = c("00", "00", "01", "01", "02", "02", "03", "03"),
CounterName = c("TotalMemory", "UsedMemory", "TotalMemory",
"UsedMemory", "TotalMemory", "UsedMemory", "TotalMemory", "UsedMemory"),
Value = c(48, 45.55, 48, 46.38, 48, 46.54, 48, 47.39)),
row.names = c(NA, -8L),
class = c("tbl_df", "tbl", "data.frame"))
memory_y_scale <- memory_df %>% filter(CounterName=='TotalMemory') %>% select (Value) %>% max() + 6
cpu_df <- structure(list(NumaNode = c("00", "00", "00", "00", "00", "00",
"00", "00", "00", "00", "00", "00", "00", "00", "00", "00", "00",
"00", "00", "00", "01", "01", "01", "01", "01", "01", "01", "01",
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01",
"01"), Counter = c("00", "01", "10", "11", "12", "13", "14",
"15", "16", "17", "18", "19", "02", "03", "04", "05", "06", "07",
"08", "09", "00", "01", "10", "11", "12", "13", "14", "15", "16",
"17", "18", "19", "02", "03", "04", "05", "06", "07", "08", "09"
), Value = c(10.79, 5.85, 9.55, 9.71, 9.77, 4.73, 4.62, 10.92,
3.55, 10.3, 1.38, 6.28, 5.42, 4.45, 10.09, 3.42, 10.14, 4.34,
9.48, 4.17, 5.2, 3.85, 10.17, 8.49, 10.36, 8.06, 10.01, 8.42,
9.12, 7.6, 1.98, 2.41, 4.72, 3.19, 4.74, 3.66, 4.28, 9.83, 5.78,
10.18)), row.names = c(NA, -40L), class = c("tbl_df", "tbl",
"data.frame"))
# plot function =======================================================================
plot_numa = function(num){
# memory plot =====================
memory_filtered_df = memory_df %>% filter(str_detect(NumaNode, num))
memory_plot <- memory_filtered_df %>%
filter(str_detect(CounterName, "Memory")) %>%
pivot_wider(names_from = CounterName, values_from = Value) %>%
ggplot(aes(x = "") ) +
geom_col(aes(y = TotalMemory), fill = "white", color = "black") +
geom_col(aes(y = UsedMemory), fill = "#00FF66FF", color = "black") +
geom_text(aes(label = paste(TotalMemory, "GB"), y = TotalMemory + 5 ), color = "black") +
geom_text(aes(
label = paste(UsedMemory, "GB"),
y = ifelse((TotalMemory-UsedMemory > 10), UsedMemory + 5, UsedMemory - 4)),
color = "black") +
theme_bw() +
ylim(0, memory_y_scale) +
labs(x = "Memory", y = "")
# cpu plot =====================
cpu_filtered_df <- cpu_df %>% filter(str_detect(NumaNode, num))
if (nrow (cpu_filtered_df) == 0 ) {
cpu_filtered_df <- cpu_df %>% filter(str_detect(NumaNode, "00"))
}
cpu_plot <- cpu_filtered_df %>%
ggplot(aes(x = Counter)) +
geom_col(aes(y = 100), fill = "white", color = "white", alpha = 0) +
geom_col(aes(y = Value), fill = "#00AFBB", color = "black") +
theme_bw() +
labs(x = "CPU, % Processor Time", y = "")
ggpubr::ggarrange(cpu_plot, memory_plot, ncol = 2, widths = c(4,1)) %>%
ggpubr::annotate_figure(top = paste(" NUMA",num))
}
numa_numbers <- unique(memory_df$NumaNode)
ggpubr::ggarrange(plotlist = map(.x = numa_numbers, .f = ~plot_numa(num = .x)))
这是我想要的边框示例。我对此不满意，因为 4 个图块彼此太靠近并且边框被覆盖。
请在下面找到一些代码，对于间距部分，在 theme() 中使用 plot.margin。我还更改了第 76 行，widths: ggpubr::ggarrange(cpu_plot, memory_plot, ncol = 2, widths = c(2,1)) %>% .
library(ggpubr)
library(tidyverse)
memory_df <- structure(list(NumaNode = c("00", "00", "01", "01", "02", "02", "03", "03"),
CounterName = c("TotalMemory", "UsedMemory", "TotalMemory",
"UsedMemory", "TotalMemory", "UsedMemory", "TotalMemory", "UsedMemory"),
Value = c(48, 45.55, 48, 46.38, 48, 46.54, 48, 47.39)),
row.names = c(NA, -8L),
class = c("tbl_df", "tbl", "data.frame"))
memory_y_scale <- memory_df %>% filter(CounterName=='TotalMemory') %>% select (Value) %>% max() + 6
cpu_df <- structure(list(NumaNode = c("00", "00", "00", "00", "00", "00",
"00", "00", "00", "00", "00", "00", "00", "00", "00", "00", "00",
"00", "00", "00", "01", "01", "01", "01", "01", "01", "01", "01",
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01",
"01"), Counter = c("00", "01", "10", "11", "12", "13", "14",
"15", "16", "17", "18", "19", "02", "03", "04", "05", "06", "07",
"08", "09", "00", "01", "10", "11", "12", "13", "14", "15", "16",
"17", "18", "19", "02", "03", "04", "05", "06", "07", "08", "09"
), Value = c(10.79, 5.85, 9.55, 9.71, 9.77, 4.73, 4.62, 10.92,
3.55, 10.3, 1.38, 6.28, 5.42, 4.45, 10.09, 3.42, 10.14, 4.34,
9.48, 4.17, 5.2, 3.85, 10.17, 8.49, 10.36, 8.06, 10.01, 8.42,
9.12, 7.6, 1.98, 2.41, 4.72, 3.19, 4.74, 3.66, 4.28, 9.83, 5.78,
10.18)), row.names = c(NA, -40L), class = c("tbl_df", "tbl",
"data.frame"))
# plot function =======================================================================
plot_numa = function(num){
# memory plot =====================
memory_filtered_df = memory_df %>% filter(str_detect(NumaNode, num))
memory_plot <- memory_filtered_df %>%
filter(str_detect(CounterName, "Memory")) %>%
pivot_wider(names_from = CounterName, values_from = Value) %>%
ggplot(aes(x = "") ) +
geom_col(aes(y = TotalMemory), fill = "white", color = "black") +
geom_col(aes(y = UsedMemory), fill = "#00FF66FF", color = "black") +
geom_text(aes(label = paste(TotalMemory, "GB"), y = TotalMemory + 5 ), color = "black") +
geom_text(aes(
label = paste(UsedMemory, "GB"),
y = ifelse((TotalMemory-UsedMemory > 10), UsedMemory + 5, UsedMemory - 4)),
color = "black") +
theme_bw() +
ylim(0, memory_y_scale) +
labs(x = "Memory", y = "") +
theme(plot.margin = unit(c(0.01,2,2,0.01), "cm"))
# cpu plot =====================
cpu_filtered_df <- cpu_df %>% filter(str_detect(NumaNode, num))
if (nrow (cpu_filtered_df) == 0 ) {
cpu_filtered_df <- cpu_df %>% filter(str_detect(NumaNode, "00"))
}
cpu_plot <- cpu_filtered_df %>%
ggplot(aes(x = Counter)) +
geom_col(aes(y = 100), fill = "white", color = "white", alpha = 0) +
geom_col(aes(y = Value), fill = "#00AFBB", color = "black") +
theme_bw() +
labs(x = "CPU, % Processor Time", y = "") +
theme(plot.margin = unit(c(0.01,0.01,2,0), "cm"))
ggpubr::ggarrange(cpu_plot, memory_plot, ncol = 2, widths = c(2,1)) %>%
ggpubr::annotate_figure(top = paste(" NUMA",num))
}
numa_numbers <- unique(memory_df$NumaNode)
ggpubr::ggarrange(plotlist = map(.x = numa_numbers, .f = ~plot_numa(num = .x)))
以及输出：
我正在尝试绘制 Numa 节点 CPU 和内存使用情况。
我的示例中有 4 个 numa 节点，每个节点有 CPU 和内存使用图表。
问题是 - 在每个节点中可能有许多 CPU 值（每个核心 1 条，在我的示例中为 20 个核心）并且只有一个内存值，所以我不得不使用不同宽度的图表（CPU 图表比内存更宽）。由于该注释文本 (NUMA XX) 现在看起来不像是图表的中间。我真的不能说是哪个节点的内存条。
我想我需要使用边框或背景颜色将 numa 节点彼此分开，以便 CPU 和每个 Numa 节点的内存在一起。另外我认为我需要减少 CPU 和 numa 节点内的内存之间的 space 并增加 numa 节点之间的 space 。怎么做？
我的代码：
library(dplyr)
library(ggplot2)
library(ggpubr)
library(tidyr)
memory_df <- structure(list(NumaNode = c("00", "00", "01", "01", "02", "02", "03", "03"),
CounterName = c("TotalMemory", "UsedMemory", "TotalMemory",
"UsedMemory", "TotalMemory", "UsedMemory", "TotalMemory", "UsedMemory"),
Value = c(48, 45.55, 48, 46.38, 48, 46.54, 48, 47.39)),
row.names = c(NA, -8L),
class = c("tbl_df", "tbl", "data.frame"))
memory_y_scale <- memory_df %>% filter(CounterName=='TotalMemory') %>% select (Value) %>% max() + 6
cpu_df <- structure(list(NumaNode = c("00", "00", "00", "00", "00", "00",
"00", "00", "00", "00", "00", "00", "00", "00", "00", "00", "00",
"00", "00", "00", "01", "01", "01", "01", "01", "01", "01", "01",
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01",
"01"), Counter = c("00", "01", "10", "11", "12", "13", "14",
"15", "16", "17", "18", "19", "02", "03", "04", "05", "06", "07",
"08", "09", "00", "01", "10", "11", "12", "13", "14", "15", "16",
"17", "18", "19", "02", "03", "04", "05", "06", "07", "08", "09"
), Value = c(10.79, 5.85, 9.55, 9.71, 9.77, 4.73, 4.62, 10.92,
3.55, 10.3, 1.38, 6.28, 5.42, 4.45, 10.09, 3.42, 10.14, 4.34,
9.48, 4.17, 5.2, 3.85, 10.17, 8.49, 10.36, 8.06, 10.01, 8.42,
9.12, 7.6, 1.98, 2.41, 4.72, 3.19, 4.74, 3.66, 4.28, 9.83, 5.78,
10.18)), row.names = c(NA, -40L), class = c("tbl_df", "tbl",
"data.frame"))
# plot function =======================================================================
plot_numa = function(num){
# memory plot =====================
memory_filtered_df = memory_df %>% filter(str_detect(NumaNode, num))
memory_plot <- memory_filtered_df %>%
filter(str_detect(CounterName, "Memory")) %>%
pivot_wider(names_from = CounterName, values_from = Value) %>%
ggplot(aes(x = "") ) +
geom_col(aes(y = TotalMemory), fill = "white", color = "black") +
geom_col(aes(y = UsedMemory), fill = "#00FF66FF", color = "black") +
geom_text(aes(label = paste(TotalMemory, "GB"), y = TotalMemory + 5 ), color = "black") +
geom_text(aes(
label = paste(UsedMemory, "GB"),
y = ifelse((TotalMemory-UsedMemory > 10), UsedMemory + 5, UsedMemory - 4)),
color = "black") +
theme_bw() +
ylim(0, memory_y_scale) +
labs(x = "Memory", y = "")
# cpu plot =====================
cpu_filtered_df <- cpu_df %>% filter(str_detect(NumaNode, num))
if (nrow (cpu_filtered_df) == 0 ) {
cpu_filtered_df <- cpu_df %>% filter(str_detect(NumaNode, "00"))
}
cpu_plot <- cpu_filtered_df %>%
ggplot(aes(x = Counter)) +
geom_col(aes(y = 100), fill = "white", color = "white", alpha = 0) +
geom_col(aes(y = Value), fill = "#00AFBB", color = "black") +
theme_bw() +
labs(x = "CPU, % Processor Time", y = "")
ggpubr::ggarrange(cpu_plot, memory_plot, ncol = 2, widths = c(4,1)) %>%
ggpubr::annotate_figure(top = paste(" NUMA",num))
}
numa_numbers <- unique(memory_df$NumaNode)
ggpubr::ggarrange(plotlist = map(.x = numa_numbers, .f = ~plot_numa(num = .x)))
这是我想要的边框示例。我对此不满意，因为 4 个图块彼此太靠近并且边框被覆盖。
请在下面找到一些代码，对于间距部分，在 theme() 中使用 plot.margin。我还更改了第 76 行，widths: ggpubr::ggarrange(cpu_plot, memory_plot, ncol = 2, widths = c(2,1)) %>% .
library(ggpubr)
library(tidyverse)
memory_df <- structure(list(NumaNode = c("00", "00", "01", "01", "02", "02", "03", "03"),
CounterName = c("TotalMemory", "UsedMemory", "TotalMemory",
"UsedMemory", "TotalMemory", "UsedMemory", "TotalMemory", "UsedMemory"),
Value = c(48, 45.55, 48, 46.38, 48, 46.54, 48, 47.39)),
row.names = c(NA, -8L),
class = c("tbl_df", "tbl", "data.frame"))
memory_y_scale <- memory_df %>% filter(CounterName=='TotalMemory') %>% select (Value) %>% max() + 6
cpu_df <- structure(list(NumaNode = c("00", "00", "00", "00", "00", "00",
"00", "00", "00", "00", "00", "00", "00", "00", "00", "00", "00",
"00", "00", "00", "01", "01", "01", "01", "01", "01", "01", "01",
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01",
"01"), Counter = c("00", "01", "10", "11", "12", "13", "14",
"15", "16", "17", "18", "19", "02", "03", "04", "05", "06", "07",
"08", "09", "00", "01", "10", "11", "12", "13", "14", "15", "16",
"17", "18", "19", "02", "03", "04", "05", "06", "07", "08", "09"
), Value = c(10.79, 5.85, 9.55, 9.71, 9.77, 4.73, 4.62, 10.92,
3.55, 10.3, 1.38, 6.28, 5.42, 4.45, 10.09, 3.42, 10.14, 4.34,
9.48, 4.17, 5.2, 3.85, 10.17, 8.49, 10.36, 8.06, 10.01, 8.42,
9.12, 7.6, 1.98, 2.41, 4.72, 3.19, 4.74, 3.66, 4.28, 9.83, 5.78,
10.18)), row.names = c(NA, -40L), class = c("tbl_df", "tbl",
"data.frame"))
# plot function =======================================================================
plot_numa = function(num){
# memory plot =====================
memory_filtered_df = memory_df %>% filter(str_detect(NumaNode, num))
memory_plot <- memory_filtered_df %>%
filter(str_detect(CounterName, "Memory")) %>%
pivot_wider(names_from = CounterName, values_from = Value) %>%
ggplot(aes(x = "") ) +
geom_col(aes(y = TotalMemory), fill = "white", color = "black") +
geom_col(aes(y = UsedMemory), fill = "#00FF66FF", color = "black") +
geom_text(aes(label = paste(TotalMemory, "GB"), y = TotalMemory + 5 ), color = "black") +
geom_text(aes(
label = paste(UsedMemory, "GB"),
y = ifelse((TotalMemory-UsedMemory > 10), UsedMemory + 5, UsedMemory - 4)),
color = "black") +
theme_bw() +
ylim(0, memory_y_scale) +
labs(x = "Memory", y = "") +
theme(plot.margin = unit(c(0.01,2,2,0.01), "cm"))
# cpu plot =====================
cpu_filtered_df <- cpu_df %>% filter(str_detect(NumaNode, num))
if (nrow (cpu_filtered_df) == 0 ) {
cpu_filtered_df <- cpu_df %>% filter(str_detect(NumaNode, "00"))
}
cpu_plot <- cpu_filtered_df %>%
ggplot(aes(x = Counter)) +
geom_col(aes(y = 100), fill = "white", color = "white", alpha = 0) +
geom_col(aes(y = Value), fill = "#00AFBB", color = "black") +
theme_bw() +
labs(x = "CPU, % Processor Time", y = "") +
theme(plot.margin = unit(c(0.01,0.01,2,0), "cm"))
ggpubr::ggarrange(cpu_plot, memory_plot, ncol = 2, widths = c(2,1)) %>%
ggpubr::annotate_figure(top = paste(" NUMA",num))
}
numa_numbers <- unique(memory_df$NumaNode)
ggpubr::ggarrange(plotlist = map(.x = numa_numbers, .f = ~plot_numa(num = .x)))
以及输出：