battery_log.R

library(tidyverse)
library(readr)
library(ggtext)

battery_log <- read_csv("battery_log.csv",
                        col_names = FALSE,
                        locale = locale(encoding = "ASCII"))
# View(battery_log)

battery_log <- battery_log %>% rename(
  "date" = X1,
  "status" = X2,
  "capacity" = X3,
  "capacity_value" = X4,
  "rate" = X5,
  "voltage" = X6,
  "event_type" = X7
) %>%
  filter(status %in% c("Discharging", "Critical, Discharging")) %>%
  mutate(
    capacity_value = as.numeric(gsub(" ", "", capacity_value)),
    voltage = as.numeric(gsub(" ", "", voltage)),
    date = as.POSIXct(date, format = "%d.%m.%Y %H:%M:%S")
  )

battery_log <- readRDS("battery_log.Rds")

# saveRDS(battery_log, "battery_log.Rds")

battery_log <- battery_log %>%
  mutate(
    minutes_work = 1,
    new_battery = ifelse(date > as.Date("2023-07-30"), 
                         "new battery", "old battery"),
    capacity_numeric = parse_number(capacity),
    cycle_change = ifelse(
      capacity_numeric <= 100.0 &
        lag(capacity_numeric, default = -1) != 100.0
      &
        capacity_numeric > lag(capacity_numeric,
                               default = -1),
      1,
      0
    )
  ) %>%
  arrange(date) %>%
  mutate(ID = cumsum(cycle_change)) %>%
  group_by(ID) %>%
  mutate(minutes_work = cumsum(minutes_work), count = n()) %>%
  select(
    ID,
    new_battery,
    date,
    capacity,
    capacity_numeric,
    capacity_value,
    rate,
    voltage,
    event_type,
    minutes_work,
    count
  ) %>%
  filter(count > 30) %>%
  arrange(ID, date)

#график
battery_log %>%
  ggplot() +
  geom_step(
    aes(
      minutes_work,
      capacity_numeric,
      group = ID,
      colour = new_battery
    ),
    alpha = 0.75,
    show.legend = FALSE,
    linewidth = 0.5
  ) +
  scale_color_manual(values = c("#C3362E", "#797979")) +
  scale_y_continuous(
    breaks = seq(0, 100, 10),
    labels = paste0(seq(0, 100, 10), "%"),
    expand = c(0.01, 0)
  ) +
  scale_x_continuous(breaks = seq(0, 420, 60), expand = c(0.01, 0)) +
  labs(
    title =
      glue::glue(
        "**Время работы моего ноутбука Xiaomi Air 12.5 <br><b style='color:#797979;'>**до**</b> и <b style='color:#C3362E;'>**после**</b> замены аккумулятора**"
      ),
    subtitle = glue::glue(
      "На основе данных поминутного мониторинга оставшегося <br><span style='color:#000000;'>% заряда аккумулятора</span> для {length(unique(battery_log$ID))} цикла разряда"
    ),
    x = "Время работы, минут",
    # y = "Емкость аккумулятора, %",
    caption = "Источник данных: BatteryInfoView v.1.25\nВизуализация: Юрий Тукачев, август 2023 @weekly_charts"
  ) +
  theme(
    text = element_text(family = "PT Sans", size = 18),
    plot.title.position = "plot",
    plot.caption.position = "plot",
    plot.margin = margin(25, 25, 10, 25),
    plot.title = element_markdown(),
    plot.subtitle = element_markdown(color = "gray60",
                                     margin = margin(15, 0, 10, 0)),
    plot.caption = element_text(
      color = "gray60",
      size = 12,
      margin = margin(t = 15)
    ),
    axis.title.y = element_blank(),
    panel.background = element_rect(fill = "white",
                                    colour = "white"),
    panel.grid.major = element_line(colour = "white"),
    panel.grid.minor = element_line(colour = "white")
  ) +
  coord_cartesian(clip = "off")

ggsave(
  "battery_log.png",
  scale = 1.5,
  dpi = 300,
  width = 5,
  height = 5
)

# check
battery_summary <- battery_log %>% group_by(ID) %>%
  summarise(
    max_cap = max(capacity_numeric),
    min_cap = min(capacity_numeric),
    mins_max = max(mins),
    max_cap_value = max(capacity_value),
    n = n()
  )