# 1. 
x <- seq(-pi, pi, by = 0.01)
y <- x * sin(x)
plot(x, y, type = "l", col = "blue", lty = 2, lwd = 1.5, xlab = "x", ylab = "x * sin(x)", xlim = c(-3.5, 3.5), ylim = c(-0.5, 2))


# 2. 
load("reky.Rdata", verbose = TRUE)
str(reky)
barplot(reky, xlab = "reky", ylab = "delka rek", col = "green")
hist(reky, xlab = "delka reky", ylab = "relativni cetnost", freq = FALSE, col = "#FFCC00", main = "Histogram delek rek")
boxplot(reky, col = "#FFCC00", main = "Boxplot delek rek")
stripchart(reky, xlab = "delky rek", col = "red", pch = 2)
qqnorm(reky)
qqline(reky)

# 3. 
str(beaver1)
str(beaver2)
par(mfrow = c(1, 2))
plot(beaver1$temp, type = "l", col = "red", ylim = c(36, 38.5), xlab = "cas", ylab = "teplota", main = "bobr1")
plot(beaver2$temp, type = "l", col = "blue", ylim = c(36, 38.5), xlab = "cas", ylab = "teplota", main = "bobr2")
par(mfrow = c(1, 1))
# nebo presne podle dne a casu (format HHMM)
beaver1$h <- (beaver1$time %/% 100) + (beaver1$time %% 100) / 60 + (beaver1$day - min(beaver1$day)) * 24
beaver2$h <- (beaver2$time %/% 100) + (beaver2$time %% 100) / 60 + (beaver2$day - min(beaver2$day)) * 24
par(mfrow = c(1, 2))
plot(beaver1$h, beaver1$temp, type = "l", col = "red", ylim = c(36, 38.5), xlab = "cas [h]", ylab = "teplota", main = "bobr1")
plot(beaver2$h, beaver2$temp, type = "l", col = "blue", ylim = c(36, 38.5), xlab = "cas [h]", ylab = "teplota", main = "bobr2")
par(mfrow = c(1, 1))

# 4. 
str(volcano)
persp(volcano, theta = 45, phi = 15)

# 5. 
plot(0, 0, type = "n", xlim = c(-2, 7), ylim = c(-1, 9), xlab = "", ylab = "", asp = 1)
symbols(0, 7, circles = 1, inches = FALSE, add = TRUE, bg = "yellow", fg = "orange")
lines(c(2, 4, 6), c(3, 5, 3), col = "red", lwd = 2)
rect(2, 0, 6, 3, col = "gray", border = "black")

# 6. 
# Nejdrive ulozime XLS v nekterem z CSV formatu. Potom: 
X <- read.csv("petrklic.csv")
str(X)
vysky <- unlist(X[-1])
plot(rep(X$X, 3), vysky, type = "p", pch = 2, xlab = "druh", ylab = "vyska", col = 1:10, lwd = 2, xlim = c(0, 11))
legend(7, 0.7, legend = c(1:10), fill = 1:10, ncol = 5)

# 7. 
load("domacnosti.Rdata", verbose = TRUE)
str(domacnosti)
X <- rep(domacnosti$pocet.clenu, domacnosti$pocet.domacnosti)tab <- table(X)
barplot(tab, xlab = "pocet clenu domacnosti", ylab = "pocet domacnosti")
plot(ecdf(X), xlab = "pocet clenu domacnosti", ylab = "F(x)", main = "Empiricka distribucni funkce", col = "red", lwd = 2)

# 8. 
X <- read.csv2("mleko.csv", header = FALSE, row.names = )
roky <- X[1,-1]
mesice <- X[-1,1]
X <- X[-1,-1]
Y <- 0.45359237 * X
matplot(1:12, Y, type = "l", xlab = "mesic", ylab = "produkce mleka [kg]", ylim = c(250, 500), col = 1:13, lty = 1)
legend("topleft", legend = roky, ncol = 7, col = 1:13, lty = 1)
matplot(t(roky), t(Y), type = "l", xlab = "rok", ylab = "produkce mleka [kg]", ylim = c(250, 500), col = 1:12, lty = 1)
legend("topleft", legend = mesice, ncol = 6, col = 1:12, lty = 1:12)
index.1972 <- which(roky == 1972)
index.1973 <- which(roky == 1973)
mesice[Y[,index.1972] > Y[,index.1973]]
matplot(1:12, Y[,seq(1, ncol(Y), by = 2)], type = "l", xlab = "mesic", ylab = "produkce mleka [kg]", ylim = c(250, 500), col = 1:7, lty = 1)
legend("topleft", legend = roky[seq(1, ncol(Y), by = 2)], ncol = 7, col = 1:7, lty = 1)