r - 如何在同一包装上组合条形图
问题描述
我需要在相同的包裹上显示每个 Numa 节点的内存和 CPU 使用情况,因此架构是可见的。像这样的东西:
这是我的代码:
library(tidyr)
library(ggplot2)
numa.nodes <- tibble (
numa_name = c("numa_01","numa_01","numa_01","numa_01","numa_01","numa_01","numa_02","numa_02","numa_02","numa_02"),
counter_name =c("cpu01","cpu02","cpu03","cpu04","memory_used","memory_total","cpu01","cpu02","memory_used","memory_total"),
value = c(sample(0:100,4), sample(0:32,1), 32, sample(0:100,1), sample(0:100,1), sample(0:128,1), 128)
)
numa.nodes <- numa.nodes %>% add_row(
numa_name = c("numa_03","numa_03","numa_03","numa_03","numa_03","numa_03","numa_04","numa_04","numa_04","numa_04"),
counter_name =c("cpu01","cpu02","cpu03","cpu04","memory_used","memory_total","cpu01","cpu02","memory_used","memory_total"),
value = c(sample(0:100,4), sample(0:32,1), 32, sample(0:100,1), sample(0:100,1), sample(0:128,1), 128)
)
numa.nodes <- numa.nodes %>% mutate(counter_name=factor(counter_name,levels = unique(counter_name),ordered = T))
print(numa.nodes)
cpu_p <- numa.nodes %>% filter(counter_name != c("memory_used", "memory_total")) %>%
ggplot() +
aes(x = counter_name, y = value, label = value) +
geom_bar(stat = 'identity', fill = "#00AFBB", color='black') +
geom_bar(stat = 'identity',aes(y=100),alpha=0.2,fill='white',color='black') +
facet_wrap(vars(numa_name), strip.position = 'bottom', scales = "free_x")+
geom_text(size = 3, position = position_stack(vjust = 0.5)) +
theme_bw()+
theme(strip.placement = 'outside',
strip.background = element_blank(),
legend.position = 'none',
axis.text = element_text(color='black',face='bold'),
axis.title = element_text(color='black',face='bold'),
legend.text = element_text(color='black',face='bold'),
legend.title = element_text(color='black',face='bold'),
strip.text = element_text(color='black',face='bold')) +
labs(x='CPU',y="Usage %")
mem_p <- numa.nodes %>% filter(counter_name == c("memory_used", "memory_total")) %>%
pivot_wider(names_from = counter_name,values_from=value) %>%
ggplot(aes(x=numa_name,y=memory_total)) +
geom_bar(stat = 'identity',aes(fill='memory_total'),color='black')+
geom_bar(stat = 'identity',aes(y=memory_used,fill='memory_used'),color='black') +
facet_wrap(vars(numa_name), strip.position = 'bottom', scales = "free_x")+
theme_bw()+
geom_text(aes(y=memory_total,
label=memory_total),size = 3) +
geom_text(aes(y=memory_used,label=memory_used),
position = position_stack(vjust = 0.5),
size=3)+
theme(strip.placement = 'outside',
strip.background = element_blank(),
legend.position = 'top',
axis.text = element_text(color='black',face='bold'),
axis.title = element_text(color='black',face='bold'),
legend.text = element_text(color='black',face='bold'),
legend.title = element_text(color='black',face='bold'),
strip.text = element_text(color='black',face='bold'),
axis.text.x = element_blank(),
axis.ticks.x = element_blank()) +
labs(x='Memory',y="Usage %")+
labs(fill='Counter')
library("ggpubr")
ggarrange (cpu_p, mem_p)
不幸的是,我的代码有两个问题。
- 我的结果绘制 - 不是每个节点的 CPU 和内存一起。我需要以某种方式组合内存+CPU。
- 奇怪的是,我在看起来非常相似的图表上处理又高又宽的数据。
问题是:
- CPU 的数量可能是 1-8,如果我对 CPU 使用旋转,对于某些 numa 节点,我将有 N/A,
- CPU 的比例是 100%,我使用 y=100 来显示比例,内存的比例是总内存(使用的内存分层在总内存上),
- 我不能使用质押,也不能将计数器从左到右放置 - 内存和 cpu 数据似乎以不同的方式处理。
是否可以显示相邻的每个 Numa 节点的 CPU 和内存?还有任何方法可以使用高或宽数据,而不是两者?
解决方案
我采用了一种编程方法,使用 ggpubr 包来安排绘图:
library(tidyverse)
library(ggpubr)
plot_numa = function(num){
df = numa.nodes %>% filter(str_detect(numa_name, num))
cpu_plot = df %>%
filter(str_detect(counter_name, "cpu")) %>%
ggplot(aes(x = counter_name)) +
geom_col(aes(y = 100), fill = "white", color = "black") +
geom_col(aes(y = value), fill = "black", color = "black") +
geom_text(aes(y = value, label = paste0(value,"%")), nudge_y = 5, color = "black") +
theme_bw() +
labs(x = "CPU", y = "")
memory_plot = df %>%
filter(str_detect(counter_name, "memory")) %>%
pivot_wider(names_from = counter_name, values_from = value) %>%
ggplot(aes(x = "")) +
geom_col(aes(y = memory_total), fill = "white", color = "black") +
geom_col(aes(y = memory_used), fill = "black", color = "black") +
geom_text(aes(label = paste(memory_total, "GB"), y = memory_total), nudge_y = -2, color = "black") +
geom_text(aes(label = paste(memory_used, "GB"), y = memory_used), nudge_y = -2, color = "white") +
theme_bw() +
labs(x = "Memory", y = "")
ggpubr::ggarrange(cpu_plot, memory_plot, ncol = 2) %>% ggpubr::annotate_figure(top = paste("NUMA",num))
}
ggpubr::ggarrange(plotlist = map(.x = c("01","02","03","04"), .f = ~plot_numa(num = .x)))
这输出:
您可以根据需要进行改进,但这可以帮助您实现很多目标。
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