123 lines
3.8 KiB
R
123 lines
3.8 KiB
R
result <- dbSendQuery(conn, query_frames)
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data <- fetch(result)
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get_variance <- function(dataset = vector(), mean = 0) {
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sum <- 0
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for (item in dataset) {
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sum <- sum + ((item - mean) ^ 2)
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}
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variance <- sum / length(dataset)
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return(variance)
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}
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get_standard_deviation <- function(variance = 0) {
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return(round(sqrt(variance)))
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}
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dnorm_plot <- function(filename = "dnorm", dataset = vector(), title = "Title", xlab = "X Label") {
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mean <- round(mean(dataset))
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standard_deviation <- get_standard_deviation(get_variance(dataset, mean))
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possibility <- dnorm(dataset, mean, standard_deviation)
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png(file = filename)
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plot(dataset,
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possibility,
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xlab = xlab,
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ylab = "Probability Density",
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col = "blue",
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main = title)
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abline(v = c(mean, mean - standard_deviation, mean + standard_deviation),
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col = c("green", "red", "red"),
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lty = c(2, 2, 2))
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legend("topright",
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legend = c(round(mean, 2), standard_deviation),
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col = c("green", "red"),
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lty = 2,
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lwd = 1,
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box.lty = 1)
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}
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pnorm_less <- function(dataset = vector(), value = 0, word = "") {
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mean <- mean(dataset)
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standard_deviation <- get_standard_deviation(get_variance(dataset, mean))
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probability_text <- "The probability of getting less than"
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probability_text <- paste(probability_text, value)
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probability_text <- paste(probability_text, word)
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probability_text <- paste(probability_text, "is")
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probability_text <- paste(probability_text, round(pnorm(value, mean, standard_deviation) * 100, 2))
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probability_text <- paste(probability_text, "%", sep = "")
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print(probability_text)
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}
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pnorm_more <- function(dataset = vector(), value = 0, word = "") {
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mean <- mean(dataset)
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standard_deviation <- get_standard_deviation(get_variance(dataset, mean))
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probability_text <- "The probability of getting more than"
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probability_text <- paste(probability_text, value)
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probability_text <- paste(probability_text, word)
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probability_text <- paste(probability_text, "is")
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probability_text <- paste(probability_text, round(pnorm(value, mean, standard_deviation, lower.tail = FALSE) * 100, 2))
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probability_text <- paste(probability_text, "%", sep = "")
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print(probability_text)
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}
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pnorm_between <- function(dataset = vector(), min = 0, max = 0, word = "") {
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mean <- mean(dataset)
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standard_deviation <- get_standard_deviation(get_variance(dataset, mean))
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probability_text <- "The probability of getting between"
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probability_text <- paste(probability_text, min)
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probability_text <- paste(probability_text, "and")
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probability_text <- paste(probability_text, max)
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probability_text <- paste(probability_text, "coins is")
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probability_text <- paste(probability_text, round((pnorm(max, mean, standard_deviation) - pnorm(min, mean, standard_deviation)) * 100, 2))
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probability_text <- paste(probability_text, "%", sep = "")
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print(probability_text)
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}
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dnorm_plot("out/dnorm_coins.png", sort(data[, 1]), "Coins Normal Distribution", xlab = "Coins")
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dnorm_plot("out/dnorm_time.png", sort(data[, 2]), "Time Normal Distribution", xlab = "Time (s)")
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min <- 0
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max <- 13
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while (T) {
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cat("Minimum number of coins: ")
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input <- readLines("stdin", n = 1)
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input <- as.numeric(input)
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if (!is.na(input) && input >= min && input < max) {
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min <- input
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break
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}
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}
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while (T) {
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cat("Maximum number of coins: ")
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input <- readLines("stdin", n = 1)
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input <- as.numeric(input)
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if (!is.na(input) && input > min && input <= max) {
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max <- input
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break
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}
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}
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pnorm_less(sort(data[, 1]), min, "coins")
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pnorm_more(sort(data[, 1]), min, "coins")
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pnorm_less(sort(data[, 1]), max, "coins")
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pnorm_more(sort(data[, 1]), max, "coins")
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pnorm_between(sort(data[, 1]), min, max, "coins")
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