library(dplyr)
library(tidyr)

setwd("C:/Users/PAULA/Desktop/Datos doctorado/inercia")

data <- read.csv("./Archivos para paper/temp_sensors.csv")  

data$Time <- as.POSIXct(data$Time, format = "%d/%m/%Y %H:%M")


long_data <- data %>%
  pivot_longer(cols = c(M1, M5, M12, N1, N5, N12),
               names_to = "Sensor",
               values_to = "Temperature")


summary_stats <- long_data %>%
  group_by(Sensor) %>%
  summarise(
    Tmin = min(Temperature, na.rm = TRUE),
    Tmean = mean(Temperature, na.rm = TRUE),
    Tmax = max(Temperature, na.rm = TRUE)
  )


print(summary_stats)


write.csv(summary_stats, "./Estmeteo/summary_temperature_sensors.csv", row.names = FALSE)




data_sensors <- data %>% select(Time, M1, N1, M5, N5, M12, N12)


t_M1_N1 <- t.test(data_sensors$M1, data_sensors$N1, alternative = "two.sided")
t_M5_N5 <- t.test(data_sensors$M5, data_sensors$N5, alternative = "two.sided")
t_M12_N12 <- t.test(data_sensors$M12, data_sensors$N12, alternative = "two.sided")


t_M1_N1
t_M5_N5
t_M12_N12

results <- data.frame(
  Pair = c("M1-N1", "M5-N5", "M12-N12"),
  Mean_M = c(mean(data_sensors$M1, na.rm = TRUE),
             mean(data_sensors$M5, na.rm = TRUE),
             mean(data_sensors$M12, na.rm = TRUE)),
  Mean_N = c(mean(data_sensors$N1, na.rm = TRUE),
             mean(data_sensors$N5, na.rm = TRUE),
             mean(data_sensors$N12, na.rm = TRUE)),
  p_value = c(t_M1_N1$p.value, t_M5_N5$p.value, t_M12_N12$p.value)
)

write.csv(results, "./Estmeteo/t_test_results.csv", row.names = FALSE)