ggplot2中二阶多项式的系数提取

Question

我一直在研究并且没有找到解决方案的是从正在生成的二阶多项式中提取系数。我不一定需要y = A + Bx Cx ^ 2的所有系数（主要只需要C），但我不确定如何从变量plot_5访问信息。我已经阅读了一些关于summary，str，lm和posts的内容，其中用户说这个任务还没有在ggplot2中实现，因为ggplot2用于可视化。我想要做的是在Infil_Data2（“coef”）中创建一个新变量，并从特定的站点ID重复系数值。

例如，下面的数据框将添加一个名为“coef”的新变量，前11行为0.00854，接下来的11行为0.0154，最后剩下的11行为0.00839。行号并不是那么重要，因为数据将相应地分组。

    library(purrr)
    library(tidyverse)
    library(ggpmisc)

    plot_5 <-
      Infil_Data2 %>% 
      split(.$Site_ID) %>% 
      map2(names(.),
           ~ggplot(.x, aes(Sqrt_Time.x, Cal_Vol_cm)) + 
             geom_point() +
             labs(title = paste(.y)) +
             theme(plot.title = element_text(hjust = 0.5)) + 
             stat_smooth(mapping = aes(x = Sqrt_Time.x, y = Cal_Vol_cm?),
                         method = "lm", se = FALSE, 
                         formula = y ~ poly(x, 2, raw = TRUE),
                         #check raw = TRUE, some say raw = FALSE gives a better fit
                         color = "red") +
             theme(plot.margin = unit(c(1, 5, 1, 1), "cm")) +
             stat_poly_eq(aes(label = paste(..eq.label.., ..rr.label..,         sep = "~~~")),
                          label.x.npc = "left", label.y.npc = 0.90, #set the position of the eq
                          formula = y ~ poly(x, 2, raw = TRUE), parse = TRUE, rr.digits = 3))

    pdf("allplots5.pdf", onefile = TRUE)
    walk(plot_5, print)
    dev.off()

    Infil_Data2 <-
        structure(list(Time = c(0L, 30L, 60L, 90L, 120L, 150L, 180L, 
        210L, 240L, 270L, 300L, 0L, 30L, 60L, 90L, 120L, 150L, 180L, 
        210L, 240L, 270L, 300L, 0L, 30L, 60L, 90L, 120L, 150L, 180L, 
        210L, 240L, 270L, 300L), Site_ID = c("H1", "H1", "H1", "H1", 
        "H1", "H1", "H1", "H1", "H1", "H1", "H1", "H2", "H2", "H2", "H2", 
        "H2", "H2", "H2", "H2", "H2", "H2", "H2", "H3", "H3", "H3", "H3", 
        "H3", "H3", "H3", "H3", "H3", "H3", "H3"), Vol_mL = c(63, 62, 
        60, 59, 58, 56, 54, 52.5, 50, 48.5, 46.5, 82, 77, 73, 68, 65, 
        51, 56, 52, 47.5, 42.5, 37.5, 69, 67, 65, 63, 61, 60, 58, 56, 
        54, 51.5, 49), Sqrt_Time.x = c(0, 5.477225575, 7.745966692, 9.486832981, 
        10.95445115, 12.24744871, 13.41640786, 14.49137675, 15.49193338, 
        16.43167673, 17.32050808, 0, 5.477225575, 7.745966692, 9.486832981, 
        10.95445115, 12.24744871, 13.41640786, 14.49137675, 15.49193338, 
        16.43167673, 17.32050808, 0, 5.477225575, 7.745966692, 9.486832981, 
        10.95445115, 12.24744871, 13.41640786, 14.49137675, 15.49193338, 
        16.43167673, 17.32050808), Cal_Vol_cm = c(0, 0.124339799, 0.373019398, 
        0.497359197, 0.621698996, 0.870378595, 1.119058194, 1.305567893, 
        1.616417391, 1.80292709, 2.051606688, 0, 0.621698996, 1.119058194, 
        1.74075719, 2.113776588, 3.854533778, 3.232834782, 3.730193979, 
        4.289723076, 4.911422072, 5.533121068, 0, 0.248679599, 0.497359197, 
        0.746038796, 0.994718394, 1.119058194, 1.367737792, 1.616417391, 
        1.865096989, 2.175946488, 2.486795986)), row.names = c(NA, 33L
        ), class = "data.frame")

Answer 1

我没有您的数据，但这里是使用broom从lm中提取系数的示例：

library(tidyverse)
library(broom)

lm(mpg ~ wt + I(wt^2), data = mtcars) %>%
  tidy() %>%
  filter(term == "I(wt^2)") %>%
  pull(estimate)
# [1] 1.171087

EDIT, adding application to provided data:

或者，与您的Infil_Data2：

lm(Cal_Vol_cm ~ poly(Sqrt_Time.x, 2, raw = TRUE), data = Infil_Data2) %>%
  tidy() %>%
  slice(3) %>%  # In this case, coefficient "C" is in third row
  pull(estimate)
# [1] 0.01078006