Clase 3
Carlos Rivera
16 de abril de 2019
a = 5; b = 3
h = 0; k = 0
curve((b/a)*sqrt(a^2-((x-h)^2)),
from = h-a, to = h+a, ylim=c(k-b,k+b))
curve(-(b/a)*sqrt(a^2-((x-h)^2)),
from = h-a, to = h+a, add = T)
A = pi*a*b; A## [1] 47.12389#####
set.seed(1964)
x = runif(100, 0, 1)
y = runif(100, 0, 1)
plot(y~x)
colores = ifelse(((x^2+y)/(x-y))<1,'red','blue')
par(mar = c(0,0,0,0), xpd = T)
plot(x,y, pch = 19, col = colores)
legend('topright', legend = c('sana','enferma'),
col = colores, title = 'Estado', text.font = 4,
bg = 'lightblue', inset = c(0,0), fill = colores)
#####
# Lote 1: 450 plantas, el viento tumbo 40
# Lote 2: 420 plantas, el viento tumbo 30
# Lote 3: 400 plantas, el viento tumbo 25
p.l1 = (40/450)*100
p.l2 = (30/400)*100
p.l3 = (25/120)*100
p.l1;p.l2;p.l3## [1] 8.888889## [1] 7.5## [1] 20.83333mean(c(p.l1,p.l2,p.l3))## [1] 12.40741(pm.t = ((40+30+25)/(450+400+120))*100)## [1] 9.793814###
# library(rspatial)
library(digest)
library(spatstat)## Loading required package: spatstat.data## Loading required package: nlme## Loading required package: rpart##
## spatstat 1.59-0 (nickname: 'J'ai omis les oeufs de caille')
## For an introduction to spatstat, type 'beginner'
nclust <- function(x0, y0, radius, n){
return(runifdisc(n, radius, centre=c(x0,y0)))
}
plot(rPoissonCluster(5,0.2, nclust, radius = 0.2, n=100))
plot(rPoissonCluster(5,0.2, nclust, radius = 0.5, n=100))
x3 = as.numeric(gl(10,1,100))
y3 = as.numeric(gl(10,10,100))
plot(x3,y3)
xy = expand.grid(x = seq(1,90,9), y = seq(1,70,7))
xy## x y
## 1 1 1
## 2 10 1
## 3 19 1
## 4 28 1
## 5 37 1
## 6 46 1
## 7 55 1
## 8 64 1
## 9 73 1
## 10 82 1
## 11 1 8
## 12 10 8
## 13 19 8
## 14 28 8
## 15 37 8
## 16 46 8
## 17 55 8
## 18 64 8
## 19 73 8
## 20 82 8
## 21 1 15
## 22 10 15
## 23 19 15
## 24 28 15
## 25 37 15
## 26 46 15
## 27 55 15
## 28 64 15
## 29 73 15
## 30 82 15
## 31 1 22
## 32 10 22
## 33 19 22
## 34 28 22
## 35 37 22
## 36 46 22
## 37 55 22
## 38 64 22
## 39 73 22
## 40 82 22
## 41 1 29
## 42 10 29
## 43 19 29
## 44 28 29
## 45 37 29
## 46 46 29
## 47 55 29
## 48 64 29
## 49 73 29
## 50 82 29
## 51 1 36
## 52 10 36
## 53 19 36
## 54 28 36
## 55 37 36
## 56 46 36
## 57 55 36
## 58 64 36
## 59 73 36
## 60 82 36
## 61 1 43
## 62 10 43
## 63 19 43
## 64 28 43
## 65 37 43
## 66 46 43
## 67 55 43
## 68 64 43
## 69 73 43
## 70 82 43
## 71 1 50
## 72 10 50
## 73 19 50
## 74 28 50
## 75 37 50
## 76 46 50
## 77 55 50
## 78 64 50
## 79 73 50
## 80 82 50
## 81 1 57
## 82 10 57
## 83 19 57
## 84 28 57
## 85 37 57
## 86 46 57
## 87 55 57
## 88 64 57
## 89 73 57
## 90 82 57
## 91 1 64
## 92 10 64
## 93 19 64
## 94 28 64
## 95 37 64
## 96 46 64
## 97 55 64
## 98 64 64
## 99 73 64
## 100 82 64plot(xy, cex = 0.5, pch = 16)
###
set.seed(1964)
x4 = runif(20)
y4 = runif(20)
plot(x4, y4, cex = 0.5, pch = 16)
cont.conv = chull(x4,y4)
set.seed(1964)
dat <- matrix(rnorm(200), ncol = 2)
(ch <- chull(dat))## [1] 79 44 81 52 83 96 56 99 55coords <- dat[c(ch, ch[1]),]; coords## [,1] [,2]
## [1,] 2.8181775 -0.6573410
## [2,] 0.6885724 -1.9870463
## [3,] -0.3649199 -2.1106867
## [4,] -1.8953622 -1.9202198
## [5,] -2.2157494 -1.2504596
## [6,] -2.9116270 0.3833158
## [7,] -3.2962041 2.7097300
## [8,] 1.8287782 2.0858646
## [9,] 2.6259778 0.5570128
## [10,] 2.8181775 -0.6573410plot(dat, pch=19, cex = 0.5)
lines(coords, col="red")
#####
library(spatstat)
# demo(spatstat)
data("swedishpines")
(x = swedishpines)## Planar point pattern: 71 points
## window: rectangle = [0, 96] x [0, 100] units (one unit = 0.1 metres)windows(7,7)
plot(x)
class(x)## [1] "ppp"#####
library(spatstat)
set.seed(1964)
x5 = runif(40)
y5 = runif(40)
plot(x5,y5, col='darkblue',pch=19)
grid(22,col = 'gray60')
dataxy = ppp(x5,y5)
(q = t(quadratcount(dataxy, nx = 22, ny = 22)))## y
## x [0.955,1] [0.909,0.955) [0.864,0.909) [0.818,0.864)
## [0,0.0455) 0 0 0 0
## [0.0455,0.0909) 0 0 0 0
## [0.0909,0.136) 0 0 0 0
## [0.136,0.182) 0 0 0 0
## [0.182,0.227) 1 0 0 0
## [0.227,0.273) 0 0 0 0
## [0.273,0.318) 0 0 1 0
## [0.318,0.364) 0 0 0 0
## [0.364,0.409) 0 0 0 0
## [0.409,0.455) 0 0 0 0
## [0.455,0.5) 0 0 0 0
## [0.5,0.545) 0 1 0 0
## [0.545,0.591) 0 0 0 0
## [0.591,0.636) 0 0 0 0
## [0.636,0.682) 0 0 0 0
## [0.682,0.727) 0 0 0 0
## [0.727,0.773) 0 0 0 1
## [0.773,0.818) 0 0 0 0
## [0.818,0.864) 0 0 0 0
## [0.864,0.909) 0 0 0 0
## [0.909,0.955) 0 0 0 1
## [0.955,1] 0 0 0 1
## y
## x [0.773,0.818) [0.727,0.773) [0.682,0.727) [0.636,0.682)
## [0,0.0455) 0 0 0 0
## [0.0455,0.0909) 0 0 0 0
## [0.0909,0.136) 0 1 0 0
## [0.136,0.182) 1 0 0 1
## [0.182,0.227) 0 0 0 0
## [0.227,0.273) 0 0 0 0
## [0.273,0.318) 0 0 0 0
## [0.318,0.364) 0 0 0 0
## [0.364,0.409) 0 0 0 0
## [0.409,0.455) 0 0 0 0
## [0.455,0.5) 0 0 0 0
## [0.5,0.545) 0 1 1 0
## [0.545,0.591) 0 0 0 0
## [0.591,0.636) 0 0 0 0
## [0.636,0.682) 0 0 0 0
## [0.682,0.727) 0 0 0 0
## [0.727,0.773) 0 0 0 0
## [0.773,0.818) 0 0 0 1
## [0.818,0.864) 0 0 0 0
## [0.864,0.909) 0 0 0 0
## [0.909,0.955) 0 1 1 0
## [0.955,1] 0 1 0 0
## y
## x [0.591,0.636) [0.545,0.591) [0.5,0.545) [0.455,0.5)
## [0,0.0455) 0 0 0 0
## [0.0455,0.0909) 0 0 0 0
## [0.0909,0.136) 0 0 1 0
## [0.136,0.182) 0 0 0 0
## [0.182,0.227) 0 0 0 0
## [0.227,0.273) 0 0 0 0
## [0.273,0.318) 1 0 0 0
## [0.318,0.364) 0 0 0 0
## [0.364,0.409) 0 0 0 0
## [0.409,0.455) 0 0 0 0
## [0.455,0.5) 0 0 0 0
## [0.5,0.545) 0 0 0 0
## [0.545,0.591) 0 0 0 0
## [0.591,0.636) 0 0 1 0
## [0.636,0.682) 0 1 0 0
## [0.682,0.727) 0 0 0 0
## [0.727,0.773) 0 0 0 0
## [0.773,0.818) 0 0 0 0
## [0.818,0.864) 0 0 0 0
## [0.864,0.909) 0 0 0 0
## [0.909,0.955) 0 0 0 0
## [0.955,1] 0 0 1 0
## y
## x [0.409,0.455) [0.364,0.409) [0.318,0.364) [0.273,0.318)
## [0,0.0455) 0 0 0 0
## [0.0455,0.0909) 0 0 0 0
## [0.0909,0.136) 0 0 0 0
## [0.136,0.182) 0 0 1 0
## [0.182,0.227) 0 0 0 0
## [0.227,0.273) 0 0 0 0
## [0.273,0.318) 0 1 0 0
## [0.318,0.364) 0 0 0 0
## [0.364,0.409) 0 1 0 0
## [0.409,0.455) 0 1 0 0
## [0.455,0.5) 0 0 0 0
## [0.5,0.545) 0 1 0 0
## [0.545,0.591) 0 0 0 0
## [0.591,0.636) 0 0 0 0
## [0.636,0.682) 0 0 0 0
## [0.682,0.727) 0 0 0 0
## [0.727,0.773) 0 0 0 0
## [0.773,0.818) 0 0 0 0
## [0.818,0.864) 1 0 0 0
## [0.864,0.909) 0 0 0 0
## [0.909,0.955) 0 0 0 0
## [0.955,1] 0 0 0 0
## y
## x [0.227,0.273) [0.182,0.227) [0.136,0.182) [0.0909,0.136)
## [0,0.0455) 0 0 0 0
## [0.0455,0.0909) 1 0 0 0
## [0.0909,0.136) 0 0 0 0
## [0.136,0.182) 0 0 0 1
## [0.182,0.227) 0 1 0 0
## [0.227,0.273) 0 1 0 0
## [0.273,0.318) 1 0 0 0
## [0.318,0.364) 0 0 0 0
## [0.364,0.409) 0 0 0 0
## [0.409,0.455) 0 1 0 0
## [0.455,0.5) 0 0 0 0
## [0.5,0.545) 0 0 1 0
## [0.545,0.591) 0 0 0 0
## [0.591,0.636) 0 0 0 0
## [0.636,0.682) 0 0 0 0
## [0.682,0.727) 0 0 0 0
## [0.727,0.773) 0 0 0 0
## [0.773,0.818) 0 0 0 0
## [0.818,0.864) 0 0 0 1
## [0.864,0.909) 0 0 0 0
## [0.909,0.955) 0 0 1 0
## [0.955,1] 0 0 0 0
## y
## x [0.0455,0.0909) [0,0.0455)
## [0,0.0455) 0 0
## [0.0455,0.0909) 0 0
## [0.0909,0.136) 0 0
## [0.136,0.182) 0 1
## [0.182,0.227) 0 0
## [0.227,0.273) 0 0
## [0.273,0.318) 0 0
## [0.318,0.364) 0 0
## [0.364,0.409) 0 0
## [0.409,0.455) 1 1
## [0.455,0.5) 0 0
## [0.5,0.545) 0 1
## [0.545,0.591) 0 0
## [0.591,0.636) 0 0
## [0.636,0.682) 0 1
## [0.682,0.727) 0 0
## [0.727,0.773) 0 0
## [0.773,0.818) 0 0
## [0.818,0.864) 0 0
## [0.864,0.909) 0 0
## [0.909,0.955) 0 0
## [0.955,1] 0 0(q2 = t(quadratcount(dataxy, nx = 20, ny = 20)))## y
## x [0.95,1] [0.9,0.95) [0.85,0.9) [0.8,0.85) [0.75,0.8)
## [0,0.05) 0 0 0 0 0
## [0.05,0.1) 0 0 0 0 0
## [0.1,0.15) 0 0 0 0 1
## [0.15,0.2) 0 0 0 0 0
## [0.2,0.25) 1 0 0 0 0
## [0.25,0.3) 0 0 1 0 0
## [0.3,0.35) 0 0 0 0 0
## [0.35,0.4) 0 0 0 0 0
## [0.4,0.45) 0 0 0 0 0
## [0.45,0.5) 0 0 0 0 0
## [0.5,0.55) 0 1 0 0 0
## [0.55,0.6) 0 0 0 0 0
## [0.6,0.65) 0 0 0 0 0
## [0.65,0.7) 0 0 0 0 0
## [0.7,0.75) 0 0 0 1 0
## [0.75,0.8) 0 0 0 0 0
## [0.8,0.85) 0 0 0 0 0
## [0.85,0.9) 0 0 0 0 0
## [0.9,0.95) 0 0 0 1 0
## [0.95,1] 0 0 0 1 1
## y
## x [0.7,0.75) [0.65,0.7) [0.6,0.65) [0.55,0.6) [0.5,0.55)
## [0,0.05) 0 0 0 0 0
## [0.05,0.1) 0 0 0 0 0
## [0.1,0.15) 1 0 0 0 1
## [0.15,0.2) 0 1 0 0 0
## [0.2,0.25) 0 0 0 0 0
## [0.25,0.3) 0 0 0 0 0
## [0.3,0.35) 0 0 1 0 0
## [0.35,0.4) 0 0 0 0 0
## [0.4,0.45) 0 0 0 0 0
## [0.45,0.5) 0 0 0 0 0
## [0.5,0.55) 2 0 0 0 0
## [0.55,0.6) 0 0 0 0 1
## [0.6,0.65) 0 0 0 1 0
## [0.65,0.7) 0 0 0 0 0
## [0.7,0.75) 0 0 0 0 0
## [0.75,0.8) 0 1 0 0 0
## [0.8,0.85) 0 0 0 0 0
## [0.85,0.9) 0 0 0 0 0
## [0.9,0.95) 1 1 0 0 0
## [0.95,1] 0 0 0 0 1
## y
## x [0.45,0.5) [0.4,0.45) [0.35,0.4) [0.3,0.35) [0.25,0.3)
## [0,0.05) 0 0 0 0 0
## [0.05,0.1) 0 0 0 0 0
## [0.1,0.15) 0 0 0 1 0
## [0.15,0.2) 0 0 0 0 0
## [0.2,0.25) 0 0 0 0 0
## [0.25,0.3) 0 1 0 0 0
## [0.3,0.35) 0 0 0 0 0
## [0.35,0.4) 0 1 0 0 0
## [0.4,0.45) 0 1 0 0 0
## [0.45,0.5) 0 0 0 0 0
## [0.5,0.55) 0 0 1 0 0
## [0.55,0.6) 0 0 0 0 0
## [0.6,0.65) 0 0 0 0 0
## [0.65,0.7) 0 0 0 0 0
## [0.7,0.75) 0 0 0 0 0
## [0.75,0.8) 0 0 0 0 0
## [0.8,0.85) 0 1 0 0 0
## [0.85,0.9) 0 0 0 0 0
## [0.9,0.95) 0 0 0 0 0
## [0.95,1] 0 0 0 0 0
## y
## x [0.2,0.25) [0.15,0.2) [0.1,0.15) [0.05,0.1) [0,0.05)
## [0,0.05) 1 0 0 0 0
## [0.05,0.1) 0 0 0 0 0
## [0.1,0.15) 0 0 0 0 0
## [0.15,0.2) 0 0 0 1 1
## [0.2,0.25) 1 1 0 0 0
## [0.25,0.3) 1 0 0 0 0
## [0.3,0.35) 0 0 0 0 0
## [0.35,0.4) 0 0 0 0 0
## [0.4,0.45) 0 1 0 1 1
## [0.45,0.5) 0 0 0 0 0
## [0.5,0.55) 0 1 0 0 1
## [0.55,0.6) 0 0 0 0 0
## [0.6,0.65) 0 0 0 0 0
## [0.65,0.7) 0 0 0 0 1
## [0.7,0.75) 0 0 0 0 0
## [0.75,0.8) 0 0 0 0 0
## [0.8,0.85) 0 0 0 0 0
## [0.85,0.9) 0 0 1 0 0
## [0.9,0.95) 0 0 0 0 0
## [0.95,1] 0 0 1 0 0vc = data.frame(q)
colores = c(ifelse(vc$Freq==0,'darkred','darkblue'))
plot(t(q),col=colores,cex = 0.8,
main = 'Discretizacion de conteo de cuadrantes')
plot(t(q2),col=colores,cex = 0.8,
main = 'Discretizacion de conteo de cuadrantes')
###
set.seed(1964)
x6 = rnorm(50)
y6 = runif(50)
plot(x6,y6)
dxy2 = ppp(x6,y6)## Warning: 30 points were rejected as lying outside the specified window(q = t(quadratcount(dataxy, nx = 10, ny = 10)))## y
## x [0.9,1] [0.8,0.9) [0.7,0.8) [0.6,0.7) [0.5,0.6) [0.4,0.5)
## [0,0.1) 0 0 0 0 0 0
## [0.1,0.2) 0 0 2 1 1 0
## [0.2,0.3) 1 1 0 0 0 1
## [0.3,0.4) 0 0 0 1 0 1
## [0.4,0.5) 0 0 0 0 0 1
## [0.5,0.6) 1 0 2 0 1 0
## [0.6,0.7) 0 0 0 0 1 0
## [0.7,0.8) 0 1 0 1 0 0
## [0.8,0.9) 0 0 0 0 0 1
## [0.9,1] 0 2 2 1 1 0
## y
## x [0.3,0.4) [0.2,0.3) [0.1,0.2) [0,0.1)
## [0,0.1) 0 1 0 0
## [0.1,0.2) 1 0 0 2
## [0.2,0.3) 0 2 1 0
## [0.3,0.4) 0 0 0 0
## [0.4,0.5) 0 0 1 2
## [0.5,0.6) 1 0 1 1
## [0.6,0.7) 0 0 0 1
## [0.7,0.8) 0 0 0 0
## [0.8,0.9) 0 0 1 0
## [0.9,1] 0 0 1 0vc = data.frame(q)
colores = c(ifelse(vc$Freq==0,'darkred',ifelse(vc$Freq>1,'darkgreen','darkblue')))
plot(t(q),col=colores,cex = 1)
cua = 1
set.seed(1964)
x6 = rnorm(50)
y6 = runif(50)
dxy2 = ppp(x6,y6)## Warning: 30 points were rejected as lying outside the specified window(q = t(quadratcount(dxy2, nx = cua, ny = cua)))## A
## [1,] 20vc = data.frame(q)
while (sum(vc$Freq>1)!=0) {
q = t(quadratcount(dxy2, nx = cua, ny = cua))
vc = data.frame(q)
colores = c(ifelse(vc$Freq==0,'darkred',
ifelse(vc$Freq>1,'darkgreen','darkblue')))
plot(t(q),col=colores,cex = 1, main = paste('tamano: ',cua-1))
print(cua)
cua = cua + 1
}
## [1] 1
## [1] 2
## [1] 3
## [1] 4
## [1] 5
## [1] 6
## [1] 7
## [1] 8
## [1] 9
## [1] 10
## [1] 11
## [1] 12
## [1] 13
## [1] 14
## [1] 15cua-1## [1] 15####
m.x = clickppp(10)
plot(m.x)