https://www.w3schools.com/r/default.asp
https://cran.r-project.org/doc/manuals/r-release/R-intro.html
https://www.jdoodle.com/execute-r-online/

ls() - listowanie nazw zmiennych    rm(x,y) # remove
Ctrl+L - czysci konsole (nie czysci zmiennych)

mtcars

x=c(1:100)   x<-1:20   #komentarz   toString(44)   i<-2; while(i<7){print(i);i<-i+1}  
x <- seq(-3,3,len=31)   x<-seq(-3,3,by=0.1)    rep(x, times=5)
x <- 1:20; Data <-data.frame(x=x,y=rnorm(x))
m=matrix(c(1,2,3,4,5,6), nrow = 3, ncol = 2)   m[1, 2]  m[,2]  m[2,]  m[c(1,2),]
arrays can have more than two dimensions
f = data.frame (k1 = c("A", "B", "C"), k2 = c(100, 150, 120),  k3 = c(60, 30, 45))
summary(f)   f[1]   

hist(x) sort(x)  order()  boxplot(x)   sample(0:6, 1) - rzut kostką   ecdf(x) - emp. kumul.   
y=scale(x)  y=(x-mean(x))/sd(x)    ifelse(1<2,5,6)   =5
x=rnorm(100); r=0.9; y=r*x+(1-r^2)*rnorm(100); plot(x,y); 
f=data.frame(y,x); reg=lm(f); summary(reg)
y1=x*summary(reg)$coefficients[2,1]+summary(reg)$coefficients[1,1]    (pod ,2] mamy błędy, pod 4 p-value)
plot(x,y,ylim=c(-3,3)); par(new = TRUE); plot(x,y1,col='red',ylim=c(-3,3))
plot(1:10, type="l", col="blue", lwd=2) gruba linia   
plot(line1, type = "l", col = "blue"); lines(line2, type="l", col = "red") lub points(x2, y2, col="blue", cex=2)

for (k in 1:12){         12 osobnych wykresow po 4 obrazki kazdy, na kazdym kilka linii
dev.new(width=15, height=5); par(mfcol=c(1,4))
for (i in 0:3){ plot(x); lines(t,x,col="red"); 
for (n in 1:4){lines(c(-3,10),c(pp[n],pp[n]),col="green")}}}

x <- c(10,20,30,40); pie(x)
x <- c("A", "B", "C", "D"); y <- c(2, 4, 6, 8); barplot(y, names.arg = x)


y=c(); for (i in 1:70){if (x[i]>0) {y= append(y,x[i])} else {y= append(y,0)}}}

i<-2; while(i<7){print(i);i<-i+1}

p = read.table("E:\\Różne\\Prokop\\data.txt", header = FALSE)
write.csv(SPI,file="E:\\Różne\\Prokop\\SPI.txt")

save(x,file="C:\\Users\\Laurem\\Desktop\\zajecia\\x.RData")
load("C:\\Users\\Laurem\\Desktop\\zajecia\\x.RData")	

> install.packages("smatr")
> library(smatr)

?sin   help.search("fourier")

toString(44)         rep(x, times=5)

x <- seq(-3,3,len=31)   x<-seq(-3,3,by=0.1)  -3.0 -2.8 -2.6 ... 2.8 3.0

i<-2; while(i<66){y <- as.numeric(c(Ar[1:365,i])); z <- supsmu(x, y, span = "cv", periodic = FALSE, bass = 0)
write.table(z[2],file=paste("D:/Ludzie/Idalia/zebrane_dane",toString(i),".txt",sep=""))
i<-i+1}


for (rows in 1:nrow(thismatrix)) {
  for (columns in 1:ncol(thismatrix)) {
    print(thismatrix[rows, columns])
  }
}

r=0.9; y=r*x+(1-r^2)*rnorm(100); plot(x,y)   ***  R E G R E S J A ***
f=data.frame(y,x); reg=lm(f); summary(reg)
****
x<-rnorm(30); e<-rnorm(30)/10; y<-x^2+x*0.1+e; plot(x,y)
Reg<-lm(formula = y~x+I(x^2)); summary(Reg)


x=rnorm(1000); y=rnorm(1000)         *** P C A  ***
x1=x+y; x2=x-y; x3=x+0.1*y; x4=0.1*x+y; x5=x+0.2*rnorm(1000); x6=rnorm(1000)
f=data.frame(x1,x2,x3,x4,x5,x6)
pca=prcomp(f)
plot(pca$sdev)    plot(pca$x[,1],pca$x[,2])    cor(pca$x[,1],pca$x[,2])

d = read.table("D://AGH//zajecia21//R//doPCA.txt", header = TRUE)
d = read.table("D://AGH//zajecia21//R//plodnosc_pca.txt", header = TRUE)
pca = prcomp(d)
p1=pca$x[,1]


x=rnorm(128); t=c(0:127); rep(0,128)    *** F F T ***
s=sin(2*pi/32*t); x0=x; x=x+s
y=fft(x); y[2]; y[128]
z=exp(2i*pi/32*t)
ym=Mod(y); ym=ym[1:65]
f=c(0:64)
plot(f,ym,type='b',col='blue',axes=FALSE); axis(side=1, at=c(0:64))
plot(t,x,type='l')
plot(x); par(new = TRUE); plot(x1) - dwa na jednym
Arg(y[2])
length(x)
x=rep(0,1000); for(i in 1:j){f=i*2-1; x=x+1/f}; plot(x)    - cztery wykresy.



					ARRAY   and    MAHALONOBIS

x<-c(0,0.1,0.2); y<-c(0,1,2); z<-outer(x,y,FUN="+"); x; y; z

cov <- array(c(1, 0.9, 0.9, 1), c(2,2))
w1<-c(0,1); w2<-c(1,0)
(w2-w1) %*% cov %*% (w2-w1)   # quadratic form
w<-c(1,1); w %*% cov %*% w

					OBRoT
p1<-c(1,0)
alpha<-1/100
rot<-array(c(cos(alpha),-sin(alpha),sin(alpha),cos(alpha)), c(2,2))
p1%*%rot

a<-array(c(3,8,12,8,5,9,12,9,14),c(3,3)); x<-det(a)

x1<-rnorm(1000); x2<-rnorm(1000)
x<-rnorm(5000)
dim(x)<-c(1000,5)
x[1,]    =  [1] 1.664114 1.161365 1.568821 1.203283 1.134660
x[,1]    =  tysiąc
x[,2]<-x2; x[,1]<-x1+0.5*x2; x[,2]<-x2-0.5*x1; x[,3]<-x[,3]+0.5*x1; x[,4]<-x[,4]+2*x2
cx<-cor(x)
evcx<-eigen(cx)
evcx[[2]][3,4]
i=
					GRAFIKA

x<-c(1,1,2,2);   plot(x);  abline(h=1);  abline(v=1.7); abline(a=1,b=0.3) #intercept, slope

x<-c(1,2,3,4,1.5);  barplot(height=x)

x<-seq(-3,3,by=0.1)
G2<-function(x,y) f<-exp(-0.5*(x^2-2*0.9*x*y+y^2)); z<-outer(x,x,FUN=G2)
image(x, x, z,col=gray((100:0)/100))

G2<-function(x,y) f<-exp(-0.5*(x^2-2*0.0*x*y+y^2)); z1<-outer(x,x,FUN=G2)
G2<-function(x,y) f<-exp(-0.5*(x^2-2*0.9*x*y+y^2)); z2<-outer(x,x,FUN=G2)
G2<-function(x,y) f<-exp(-0.5*(x^2-2*0.3*x*y+y^2)); z3<-outer(x,x,FUN=G2)
G2<-function(x,y) f<-exp(-0.5*(x^2+2*0.5*x*y+y^2)); z4<-outer(x,x,FUN=G2)
contour(x,x,z1, col = rgb(0,0,0), add = FALSE, nlevels=20, drawlabels = FALSE)
contour(x,x,z2, col = rgb(1,0,0), add = TRUE, nlevels=20, drawlabels = FALSE)
contour(x,x,z3, col = rgb(0.7,0,0), add = TRUE, nlevels=20, drawlabels = FALSE)
contour(x,x,z4, col = rgb(0,0.7,0), add = TRUE, nlevels=20, drawlabels = FALSE)

x<-seq(-3,3,by=0.1)
image(x, x, outer(x,x,FUN=G2<-function(x,y) f<-exp(-0.5*(x^2-2*0.75*x*y+y^2))),col=gray((100:20)/100))
points(1,1,col="red")




x<-rep(0,times=100)
x<-c(x,x+1,x)
y<-convolve(x,x,type="o")

x<-seq(-5,5,by=0.1)
y<-dnorm(x,0,1)
z<-convolve(y,y,type="o")
plot(x,y,type="l")
x1<-seq(-10,10,by=0.1)
lines(x1,z*0.1414)

				NN

library(nnet)
iris3
ir <- rbind(iris3[,,1],iris3[,,2],iris3[,,3])
ir
cor(ir)
targets <- class.ind( c(rep("s",50), rep("c",50), rep("v",50)))
targets
ir1 <- nnet(ir,targets,size=2,rang=0.1,maxit=200)
summary(ir1)
predict(ir1,c(5,3,5,2))