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## ----libraries, echo=T, eval= T, message=FALSE, warning= FALSE-----------
# R libraries
library(tangles);library(digest);library(raster);library(sp)
# DATA SETS
# POINT PATTERN
data("HV_subsoilpH")
# RASTER OBJECT
data("hunterCovariates_sub")
## ----vshifts, echo=T, eval= F, message=FALSE, warning= FALSE-------------
# ## Horizontal shift
# leap_X<- function(xyData=NULL){
# r.num<- sample(-999999:999999, 1)
# xyData[,1]<- xyData[,1] + r.num
# return(list(xyData, r.num))
# }
#
#
# ## Vertical shift
# leap_Y<- function(xyData=NULL){
# r.num<- sample(-999999:999999, 1)
# xyData[,2]<- xyData[,2] + r.num
# return(list(xyData, r.num))
# }
## ----rshifts, echo=T, eval= F, message=FALSE, warning= FALSE-------------
# ## Step 3 (data rotation)
# rotate_XY<- function(xyData=NULL){
#
# # pick a point at random from the dataset
# row.sample<- sample(1:nrow(xyData),1)
# origin.point<- xyData[row.sample,]
#
# ## Prep data for rotation
# x<- t(xyData[,1])
# y<- t(xyData[,2])
# v = rbind(x,y)
#
# x_center = origin.point[1]
# y_center = origin.point[2]
#
# #create a matrix which will be used later in caclculations
# center <- v
# center[1,]<- as.matrix(x_center)
# center[2,]<- as.matrix(y_center)
#
# if (rasterdata == TRUE){
# deg<- sample(c(90,180,270),1, replace = F)} else { # choose a random orientation
# deg<- sample(1:359,1, replace = F)} # choose a random orientation
#
# theta = (deg * pi)/180 # express in radians
#
# # rotation matrix
# R = matrix(c(cos(theta), -sin(theta), sin(theta), cos(theta)), nrow=2)
#
# # do the rotation...
# s = v - center # shift points in the plane so that the center of rotation is at the origin
# so = R%*%s # apply the rotation about the origin
# vo = so + center # shift again so the origin goes back to the desired center of rotation
#
# # pick out the vectors of rotated x- and y-data
# xyData<- cbind(vo[1,], vo[2,])
# return(list(xyData,origin.point,deg))
# }
#
## ----tangles, echo=T, eval= T, message=FALSE, warning= FALSE-------------
xyData<- as.matrix(HV_subsoilpH[,1:2])
tangles.out<- tangles(data = xyData, depth = 3, rasterdata = FALSE, raster_object = FALSE, saveTangles = TRUE, path = tempdir())
str(tangles.out)
## ----tangler, echo=T, eval= T, message=FALSE, warning= FALSE-------------
# First entangle the point pattern
xyData<- as.matrix(HV_subsoilpH[,1:2])
tangles.out<- tangles(data = xyData, depth = 5, rasterdata = TRUE, raster_object = FALSE, saveTangles = TRUE, path = tempdir())
# Now entangle the raster object
tangler.out<- tangler(data = hunterCovariates_sub, tanglerInfo = tangles.out[[2]], raster_object = TRUE, stub = "myname", saveTangles = TRUE, path = tempdir())
## ----t_plot, echo=T, eval= T, message=FALSE, warning= FALSE,fig.width=7, fig.height=5----
# Plotting
# original data
pHV_subsoilpH<- HV_subsoilpH
coordinates(pHV_subsoilpH)<- ~ X + Y
plot(hunterCovariates_sub[[1]], main="orginal data"); plot(pHV_subsoilpH, add=T)
# tangled data
tPP<- as.data.frame(tangles.out[[1]])
coordinates(tPP)<- ~ X + Y
plot(tangler.out[[1]], main="tangled data");plot(tPP, add=T)
## ----detangles, echo=T, eval= F, message=FALSE, warning= FALSE-----------
# # points
# xyData<- as.matrix(tangles.out[[1]])
# point_detang<- detangles(data=xyData, tanglerInfo=tangles.out[[2]], raster_object = FALSE, stub = "hv_fix", hash_key = "UNIQUE_HASH_KEY_HERE", saveTangles = TRUE, path = tempdir())
#
# #rasters
# raster_detang<- detangles(data=tangled.origi, tanglerInfo=tangles.out[[2]], raster_object = TRUE, stub = "hv_fix", hash_key = "UNIQUE_HASH_KEY_HERE", saveTangles = TRUE, path = tempdir())
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