library(ggplot2)
library(readr)
library(latex2exp)

data_t1 <- read_csv(
  "m1,m2,a_measured
  0.055,0.060,0.380
  0.060,0.065,0.354
  0.065,0.070,0.323
  0.070,0.075,0.310
  0.075,0.080,0.303
  0.080,0.085,0.279
  0.065,0.075,0.649
  0.080,0.095,0.780"
)

a_theoretical <- function(m) {
  9.81 * m
}

m_from_masses <- function(m1, m2) {
  (m2 - m1) / (m1 + m2)
}

x_lab <- function() {
  TeX(r"($M$)")
}

y_lab <- function() {
  TeX(r"($a \ \small{m \cdot s^{-2}}$)")
}

lm_eqn <- function(df) {
  m <- lm(df)
  eq <- substitute(
    italic(y) == a + b %.% italic(x),
    list(a = format(unname(coef(m)[1]), digits = 3),
         b = format(unname(coef(m)[2]), digits = 3))
  )
  as.character(as.expression(eq))
}

data_t1["M"] <- m_from_masses(data_t1["m1"], data_t1["m2"])

data_t1["a"] <- data_t1$M * 9.8

plt <- ggplot(
  data = data_t1,
  mapping = aes(x = M, y = a_measured)
) +
  geom_point(
    col = "#D55E00",
    size = 2,
  ) +
  geom_smooth(
    se = FALSE,
    method = "lm",
    linewidth = 0.8,
    col = "#D55E00",
  ) +
  theme(
    axis.text = element_text(size = 14),
    axis.title = element_text(size = 20),
  ) +
  labs(
    x = x_lab(),
    y = y_lab(),
  ) +
  annotate("text",
    label = lm_eqn(data_t1[, c("a_measured", "M")]),
    x = 0.076,
    y = 0.58,
    size = 5,
    col = "#D55E00",
    parse = TRUE,
  ) +
  annotate("segment",
    x = min(data_t1$M),
    y = a_theoretical(min(data_t1$M)),
    xend = max(data_t1$M),
    yend = a_theoretical(max(data_t1$M)),
    linewidth = 0.8,
    col = "#0072B2",
  ) +
  annotate("text",
    label = "Theoretical",
    x = 0.068,
    y = 0.74,
    col = "#0072B2",
    size = 5,
  )

plt

ggsave("plot.pdf",
  plot = plt,
  device = cairo_pdf,
)