使用R将多个时间序列一个绘制在另一个之下

Question

我想得到一个类似于这个的情节，让eeg时间序列的每个频道都低于另一个，同时尽可能使用绘图空间，因为有64个频道。这是图像。第1,2和4列对我来说很有趣：

我正在使用gg plot和facet wrap，它在标签和轴上浪费了太多空间。像第一个柱子这样的简单图表足以将不同的通道相互比较。

这是我目前的代码：

library(ggplot2)
library(reshape2)

X1 <- c(1,2,3,4,5,6,7,8,9,19)
X2 <- c(1,4,2,4,1,4,1,4,1,4)
X3 <- c(1,2,3,4,5,6,7,8,9,10)
X4 <- c(1,2,3,4,5,6,7,8,9,1)
X5 <- c(1,4,2,4,1,4,1,4,1,4)
X6 <- c(1,2,3,4,5,6,7,8,9,10)
X7 <- c(1,2,3,4,5,6,7,8,9,11)
X8 <- c(1,4,2,4,1,4,1,4,1,4)
X9 <- c(1,2,3,4,5,6,7,8,9,10)
X10 <- c(1,2,3,4,5,6,7,8,9,10)

icaFrame <- data.frame(X1, X2, X3, X4, X5, X6, X7, X8, X9, X10)

scale <- rep.int(c(1:10),10)


df_melt = melt(icaFrame[,1:10])
ggplot(df_melt, aes(x = scale, y = value)) + 
  geom_line() + 
  facet_wrap(~ variable, scales = 'free_y', ncol = 1)

那么我怎样才能创建这样一个简单的图，每个时间序列使用R绘制在另一个之下？

Answer 1

编辑：如果不规则间距可以，在底部添加另一种方法，以实现更紧密的包装。

这是另一种允许您更紧密地挤压并允许重叠的方法：

scaling_factor = 2.5  # Adjust this to make more or less room between series

ggplot(df_melt, aes(x = scale, group = variable,
                    y = value + as.numeric(variable) * scaling_factor)) + 
  geom_line() +
  scale_y_continuous(breaks = (as.numeric(df_melt$variable) + 0.5) * scaling_factor,
                     labels = df_melt$variable, minor_breaks = NULL) +
  labs(y="")

---

这是另一种方法，它找到每个系列之间的最小必要间距，以避免任何重叠。

library(dplyr)
min_space = 2
vertical_shift <- df_melt %>%
  # Add scale as a variable for use in next step
  group_by(variable) %>% mutate(scale = row_number()) %>% ungroup() %>%
  # Group by scale and track gap vs. prior variable
  group_by(scale) %>% mutate(gap = value - lag(value, default = 0)) %>% ungroup() %>%
  # Group by variable and find minimum gap
  group_by(variable) %>% 
  summarize(gap_needed_below = 1 - min(gap) + min_space) %>%
  ungroup() %>%
  mutate(cuml_gap = cumsum(gap_needed_below))

df_melt %>%
  group_by(variable) %>% mutate(scale = row_number()) %>% ungroup() %>%
  left_join(vertical_shift) %>%
  mutate(shifted_value = value + cuml_gap) %>%
ggplot(aes(x = scale, group = variable,
           y = shifted_value)) + 
  geom_line() +
  scale_y_continuous(breaks = vertical_shift_headers$cuml_gap + 1,
                     labels = vertical_shift_headers$variable,
                     minor_breaks = NULL) +
  labs(y="")

Answer 2

我觉得你很亲密。我将使用data.table来获取标记y轴所需的数字，但您可以使用任何其他基础或dplyr工具。我还将使用一些虚拟数据，这些数据可以让我们更好地查看结果（与您粘贴的图像不同，您的数据会越过值）。

# load libraries

library(data.table)
library(ggplot2)

# create dummy data

set.seed(1)
dt <- data.table(time = 1:10, 
                 EOG = sample(1:5, 10, TRUE), 
                 Pz = sample(6:10, 10, TRUE), 
                 Cz = sample(15:21, 10, TRUE))

# melt that data

melt_dt <- melt(dt, id.vars = 1)

# find mean values for each variable

crossings <- melt_dt[, mean(value), by = variable]

现在，绘制整个事情：

ggplot(melt_dt, 
       aes(x = time, 
           y = value, 
           group = variable))+
   geom_line()+
   scale_y_continuous(breaks = crossings$V1, 
                      labels = crossings$variable)

哪个产生：

Answer 3

我想我能够使用facet获得接近第一列的东西。要将构面的名称放在y轴上，请在构面函数中使用strip.position = 'left'。这将节省大量空间。

然后，为了更接近第一列，您需要使用theme()元素。

library(ggplot2)
library(reshape2)

X1 <- c(1,2,3,4,5,6,7,8,9,19)
X2 <- c(1,4,2,4,1,4,1,4,1,4)
X3 <- c(1,2,3,4,5,6,7,8,9,10)
X4 <- c(1,2,3,4,5,6,7,8,9,1)
X5 <- c(1,4,2,4,1,4,1,4,1,4)
X6 <- c(1,2,3,4,5,6,7,8,9,10)
X7 <- c(1,2,3,4,5,6,7,8,9,11)
X8 <- c(1,4,2,4,1,4,1,4,1,4)
X9 <- c(1,2,3,4,5,6,7,8,9,10)
X10 <- c(1,2,3,4,5,6,7,8,9,10)

icaFrame <- data.frame(X1, X2, X3, X4, X5, X6, X7, X8, X9, X10)

scale <- rep.int(c(1:10),10)

df_melt <- melt(icaFrame[,1:10])

ggplot(df_melt, aes(x = scale, y = value)) + 
  geom_line() + 
  # remove extra space in x axis
  scale_x_continuous(expand=c(0,0)) +
  # standard black and white background theme 
  theme_bw() +
  # customized theme elements (you can play around with them to get a better look:
  theme(axis.title = element_blank(),              # remove labels from axis
        panel.spacing = unit(0, units = 'points'), # remove spacing between facet panels
        panel.border = element_blank(),            # remove border in each facet
        panel.grid.major.y=element_blank(),        # remove grid lines from y axis
        panel.grid.minor.y=element_blank(),
        axis.line = element_line(),                # add axis lines to x and y
        axis.text.y=element_blank(),               # remove tick labels from y axis
        axis.ticks.y = element_blank(),            # remove tick lines from y axis
        strip.background = element_blank(),        # remove gray box from facet title
        # change rotation and alignment of text in facet title
        strip.text.y = element_text(angle = 180,   
                                  face = 'bold',
                                  hjust=1,
                                  vjust=0.5),
        # place facet title to the left of y axis
        strip.placement = 'outside'
        ) +
  # call facet_wrap with argument strip.position = 'left'
  facet_wrap(~ variable, scales = 'free_y', ncol = 1, strip.position = 'left')

My resulting plot