vignettes/PC_IIC.R
In OscarGOGO/Makurhini: Makurhini: Analyzing landscape connectivity
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
## ----message=FALSE, warning=FALSE---------------------------------------------
library(Makurhini)
library(sf)
library(raster)
library(ggplot2)
## ----message=FALSE, warning=FALSE---------------------------------------------
#Habitat nodes
data("habitat_nodes", package = "Makurhini")
nrow(habitat_nodes)
#Study area
data("TMVS", package = "Makurhini")
#Resistance
data("resistance_matrix", package = "Makurhini")
## ----message=FALSE, warning=FALSE---------------------------------------------
raster_map <- as(resistance_matrix, "SpatialPixelsDataFrame")
raster_map <- as.data.frame(raster_map)
colnames(raster_map) <- c("value", "x", "y")
ggplot() +
geom_tile(data = raster_map, aes(x = x, y = y, fill = value), alpha = 0.8) +
geom_sf(data = TMVS, aes(color = "Study area"), fill = NA, color = "black") +
geom_sf(data = habitat_nodes, aes(color = "Habitat nodes"), fill = "forestgreen") +
scale_fill_gradientn(colors = c("#000004FF", "#1B0C42FF", "#4B0C6BFF", "#781C6DFF",
"#A52C60FF", "#CF4446FF", "#ED6925FF", "#FB9A06FF",
"#F7D03CFF", "#FCFFA4FF"))+
scale_color_manual(name = "", values = "black")+
theme_minimal() +
theme(axis.title.x = element_blank(),
axis.title.y = element_blank())
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# PC_example_1 <- MK_dPCIIC(nodes = habitat_nodes,
# attribute = NULL,
# distance = list(type = "centroid"),
# parallel = NULL,
# metric = "PC",
# probability = 0.5,
# distance_thresholds = c(250, 1500, 3000, 10000))
## ----eval=TRUE, message=FALSE, warning=FALSE, echo=FALSE----------------------
PC_example_1 <- readRDS("C:/Users/Usuario/Documents/R/TEST_Folder/PC_example_1.rds")
## ----eval=TRUE, message=FALSE, warning=FALSE----------------------------------
class(PC_example_1)
names(PC_example_1)
head(PC_example_1$d10000)
## ----eval=TRUE, message=FALSE, warning=FALSE, echo= FALSE---------------------
interv <- c(0.0000021, 0.0596058, 0.1612625, 0.2943665, 0.4937340, 0.8902072, 1.1303198, 1.7556675, 3.4064392, 80.7958156)
## ----eval=FALSE, message=FALSE, warning=FALSE, echo=TRUE----------------------
# #We can use some package to get intervals for example classInt R Packge:
# library(classInt)
# interv <- classIntervals(PC_example_1$d10000$dPC, 9, "jenks")[[2]] #9 intervalos
## ----eval=TRUE, message=FALSE, warning=FALSE, echo=TRUE-----------------------
ggplot()+
geom_sf(data = TMVS)+
geom_sf(data = PC_example_1$d10000, aes(fill = cut(dPC, breaks = interv)), color = NA)+
scale_fill_brewer(type = "qual",
palette = "RdYlGn",
name = "dPC",
na.translate = FALSE)+
theme_minimal() +
theme(
legend.position = "inside",
legend.position.inside = c(0.1,0.21),
legend.key.height = unit(0.2, "cm"),
legend.key.width = unit(0.3, "cm"),
legend.text = element_text(size = 5.5),
legend.title = element_text(size = 5.5)
) + labs(title="Euclidean distance")
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# PC_example_2 <- MK_dPCIIC(nodes = habitat_nodes,
# attribute = NULL,
# distance = list(type = "least-cost",
# resistance = resistance_matrix),
# parallel = NULL,
# metric = "PC",
# probability = 0.5,
# distance_thresholds = c(250, 1500, 3000, 10000))
## ----eval=TRUE, message=FALSE, warning=FALSE, echo=FALSE----------------------
PC_example_2 <- readRDS("C:/Users/Usuario/Documents/R/TEST_Folder/PC_example_2.rds")
## ----eval=TRUE, message=FALSE, warning=FALSE----------------------------------
class(PC_example_2)
names(PC_example_2)
head(PC_example_2$d10000)
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# write_sf(PC_example$d10000, “.../dPC_d0000.shp”)
## ----eval=TRUE, message=FALSE, warning=FALSE, echo = TRUE---------------------
#Keep the same range of values of PC_example_1 for comparison, only the highest range changes.
interv[length(interv)] <- max(PC_example_2$d10000$dPC)
ggplot()+
geom_sf(data = TMVS)+
geom_sf(data = PC_example_2$d10000, aes(fill = cut(dPC, breaks = interv)), color = NA)+
scale_fill_brewer(type = "qual",
palette = "RdYlGn",
name = "dPC",
na.translate = FALSE)+
theme_minimal() +
theme(
legend.position = "inside",
legend.position.inside = c(0.1, 0.21),
legend.key.height = unit(0.2, "cm"),
legend.key.width = unit(0.3, "cm"),
legend.text = element_text(size = 5.5),
legend.title = element_text(size = 5.5)
)+ labs(title="Least-cost distance")
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# PC_example <- MK_dPCIIC(nodes = patches, attribute = NULL, area_unit = "ha",
# distance = list(type = "least-cost",
# resistance = resistance_matrix,
# least_cost.java = TRUE,
# cores.java = 4),
# metric = "PC", overall = TRUE, probability = 0.5,
# distance_thresholds = c(250, 1500, 3000, 10000),
# intern = FALSE)
# #155.59 sec elapsed
## ----eval=TRUE, message=FALSE, warning=FALSE, echo=FALSE----------------------
PC_example_3 <- MK_dPCIIC(nodes = habitat_nodes,
attribute = NULL,
area_unit = "ha",
distance = list(type = "centroid"),
parallel = NULL,
metric = "PC",
probability = 0.5,
distance_thresholds = c(250, 1500, 3000, 10000),
overall = TRUE, intern = FALSE)
## ----eval=FALSE, message=FALSE, warning=FALSE, echo=TRUE----------------------
# PC_example_3 <- MK_dPCIIC(nodes = habitat_nodes,
# attribute = NULL,
# area_unit = "ha",
# distance = list(type = "centroid"),
# parallel = NULL,
# metric = "PC",
# probability = 0.5,
# distance_thresholds = c(250, 1500, 3000, 10000),
# overall = TRUE)
#
## -----------------------------------------------------------------------------
class(PC_example_3)
class(PC_example_3$d10000$node_importances_d10000)
class(PC_example_3$d10000$overall_d10000)
PC_example_3$d10000$overall_d10000
## -----------------------------------------------------------------------------
PC_example_3$d10000$node_importances_d10000
## -----------------------------------------------------------------------------
PC_example_3$d10000$overall_d10000
## ----eval=TRUE, message=FALSE, warning=FALSE, echo=FALSE----------------------
#Maximum landcape attribute or LA = total area of the estudy area
Area <- unit_convert( st_area(TMVS), "m2", "ha") #hectares
PC_example_3 <- MK_dPCIIC(nodes = habitat_nodes,
attribute = NULL,
area_unit = "ha",
distance = list(type = "centroid"),
parallel = NULL,
metric = "PC",
probability = 0.5,
distance_thresholds = c(250, 1500, 3000, 10000),
LA = Area,
onlyoverall = TRUE, intern = FALSE)
## ----eval=FALSE, message=FALSE, warning=FALSE, echo=TRUE----------------------
# #Maximum landcape attribute or LA = total area of the estudy area
# Area <- unit_convert( st_area(TMVS), "m2", "ha") #hectares
# PC_example_3 <- MK_dPCIIC(nodes = habitat_nodes,
# attribute = NULL,
# area_unit = "ha",
# distance = list(type = "centroid"),
# parallel = NULL,
# metric = "PC",
# probability = 0.5,
# distance_thresholds = c(250, 1500, 3000, 10000),
# LA = Area,
# onlyoverall = TRUE)
## ----eval=TRUE----------------------------------------------------------------
class(PC_example_3)
class(PC_example_3$d10000)
PC_example_3$d10000
## ----eval=TRUE, echo=FALSE, message=FALSE, warning=FALSE----------------------
IIC_example_4 <- MK_dPCIIC(nodes = habitat_nodes,
attribute = NULL,
area_unit = "ha",
distance = list(type = "centroid"),
parallel = NULL,
metric = "IIC",
probability = NULL,
distance_thresholds = c(250, 1500, 3000, 10000),
LA = Area,
overall = TRUE, intern = FALSE)
## ----eval=FALSE---------------------------------------------------------------
# IIC_example_4 <- MK_dPCIIC(nodes = habitat_nodes,
# attribute = NULL,
# area_unit = "ha",
# distance = list(type = "centroid"),
# parallel = NULL,
# metric = "IIC",
# probability = NULL,
# distance_thresholds = c(250, 1500, 3000, 10000),
# LA = Area,
# overall = TRUE)
## ----eval=TRUE----------------------------------------------------------------
class(IIC_example_4)
class(IIC_example_4$d10000$node_importances_d10000)
class(IIC_example_4$d10000$overall_d10000)
## -----------------------------------------------------------------------------
IIC_example_4$d10000$node_importances_d10000
## -----------------------------------------------------------------------------
IIC_example_4$d10000$overall_d10000
OscarGOGO/Makurhini documentation built on Jan. 9, 2025, 1:20 p.m.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
## ----message=FALSE, warning=FALSE---------------------------------------------
library(Makurhini)
library(sf)
library(raster)
library(ggplot2)
## ----message=FALSE, warning=FALSE---------------------------------------------
#Habitat nodes
data("habitat_nodes", package = "Makurhini")
nrow(habitat_nodes)
#Study area
data("TMVS", package = "Makurhini")
#Resistance
data("resistance_matrix", package = "Makurhini")
## ----message=FALSE, warning=FALSE---------------------------------------------
raster_map <- as(resistance_matrix, "SpatialPixelsDataFrame")
raster_map <- as.data.frame(raster_map)
colnames(raster_map) <- c("value", "x", "y")
ggplot() +
geom_tile(data = raster_map, aes(x = x, y = y, fill = value), alpha = 0.8) +
geom_sf(data = TMVS, aes(color = "Study area"), fill = NA, color = "black") +
geom_sf(data = habitat_nodes, aes(color = "Habitat nodes"), fill = "forestgreen") +
scale_fill_gradientn(colors = c("#000004FF", "#1B0C42FF", "#4B0C6BFF", "#781C6DFF",
"#A52C60FF", "#CF4446FF", "#ED6925FF", "#FB9A06FF",
"#F7D03CFF", "#FCFFA4FF"))+
scale_color_manual(name = "", values = "black")+
theme_minimal() +
theme(axis.title.x = element_blank(),
axis.title.y = element_blank())
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# PC_example_1 <- MK_dPCIIC(nodes = habitat_nodes,
# attribute = NULL,
# distance = list(type = "centroid"),
# parallel = NULL,
# metric = "PC",
# probability = 0.5,
# distance_thresholds = c(250, 1500, 3000, 10000))
## ----eval=TRUE, message=FALSE, warning=FALSE, echo=FALSE----------------------
PC_example_1 <- readRDS("C:/Users/Usuario/Documents/R/TEST_Folder/PC_example_1.rds")
## ----eval=TRUE, message=FALSE, warning=FALSE----------------------------------
class(PC_example_1)
names(PC_example_1)
head(PC_example_1$d10000)
## ----eval=TRUE, message=FALSE, warning=FALSE, echo= FALSE---------------------
interv <- c(0.0000021, 0.0596058, 0.1612625, 0.2943665, 0.4937340, 0.8902072, 1.1303198, 1.7556675, 3.4064392, 80.7958156)
## ----eval=FALSE, message=FALSE, warning=FALSE, echo=TRUE----------------------
# #We can use some package to get intervals for example classInt R Packge:
# library(classInt)
# interv <- classIntervals(PC_example_1$d10000$dPC, 9, "jenks")[[2]] #9 intervalos
## ----eval=TRUE, message=FALSE, warning=FALSE, echo=TRUE-----------------------
ggplot()+
geom_sf(data = TMVS)+
geom_sf(data = PC_example_1$d10000, aes(fill = cut(dPC, breaks = interv)), color = NA)+
scale_fill_brewer(type = "qual",
palette = "RdYlGn",
name = "dPC",
na.translate = FALSE)+
theme_minimal() +
theme(
legend.position = "inside",
legend.position.inside = c(0.1,0.21),
legend.key.height = unit(0.2, "cm"),
legend.key.width = unit(0.3, "cm"),
legend.text = element_text(size = 5.5),
legend.title = element_text(size = 5.5)
) + labs(title="Euclidean distance")
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# PC_example_2 <- MK_dPCIIC(nodes = habitat_nodes,
# attribute = NULL,
# distance = list(type = "least-cost",
# resistance = resistance_matrix),
# parallel = NULL,
# metric = "PC",
# probability = 0.5,
# distance_thresholds = c(250, 1500, 3000, 10000))
## ----eval=TRUE, message=FALSE, warning=FALSE, echo=FALSE----------------------
PC_example_2 <- readRDS("C:/Users/Usuario/Documents/R/TEST_Folder/PC_example_2.rds")
## ----eval=TRUE, message=FALSE, warning=FALSE----------------------------------
class(PC_example_2)
names(PC_example_2)
head(PC_example_2$d10000)
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# write_sf(PC_example$d10000, “.../dPC_d0000.shp”)
## ----eval=TRUE, message=FALSE, warning=FALSE, echo = TRUE---------------------
#Keep the same range of values of PC_example_1 for comparison, only the highest range changes.
interv[length(interv)] <- max(PC_example_2$d10000$dPC)
ggplot()+
geom_sf(data = TMVS)+
geom_sf(data = PC_example_2$d10000, aes(fill = cut(dPC, breaks = interv)), color = NA)+
scale_fill_brewer(type = "qual",
palette = "RdYlGn",
name = "dPC",
na.translate = FALSE)+
theme_minimal() +
theme(
legend.position = "inside",
legend.position.inside = c(0.1, 0.21),
legend.key.height = unit(0.2, "cm"),
legend.key.width = unit(0.3, "cm"),
legend.text = element_text(size = 5.5),
legend.title = element_text(size = 5.5)
)+ labs(title="Least-cost distance")
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# PC_example <- MK_dPCIIC(nodes = patches, attribute = NULL, area_unit = "ha",
# distance = list(type = "least-cost",
# resistance = resistance_matrix,
# least_cost.java = TRUE,
# cores.java = 4),
# metric = "PC", overall = TRUE, probability = 0.5,
# distance_thresholds = c(250, 1500, 3000, 10000),
# intern = FALSE)
# #155.59 sec elapsed
## ----eval=TRUE, message=FALSE, warning=FALSE, echo=FALSE----------------------
PC_example_3 <- MK_dPCIIC(nodes = habitat_nodes,
attribute = NULL,
area_unit = "ha",
distance = list(type = "centroid"),
parallel = NULL,
metric = "PC",
probability = 0.5,
distance_thresholds = c(250, 1500, 3000, 10000),
overall = TRUE, intern = FALSE)
## ----eval=FALSE, message=FALSE, warning=FALSE, echo=TRUE----------------------
# PC_example_3 <- MK_dPCIIC(nodes = habitat_nodes,
# attribute = NULL,
# area_unit = "ha",
# distance = list(type = "centroid"),
# parallel = NULL,
# metric = "PC",
# probability = 0.5,
# distance_thresholds = c(250, 1500, 3000, 10000),
# overall = TRUE)
#
## -----------------------------------------------------------------------------
class(PC_example_3)
class(PC_example_3$d10000$node_importances_d10000)
class(PC_example_3$d10000$overall_d10000)
PC_example_3$d10000$overall_d10000
## -----------------------------------------------------------------------------
PC_example_3$d10000$node_importances_d10000
## -----------------------------------------------------------------------------
PC_example_3$d10000$overall_d10000
## ----eval=TRUE, message=FALSE, warning=FALSE, echo=FALSE----------------------
#Maximum landcape attribute or LA = total area of the estudy area
Area <- unit_convert( st_area(TMVS), "m2", "ha") #hectares
PC_example_3 <- MK_dPCIIC(nodes = habitat_nodes,
attribute = NULL,
area_unit = "ha",
distance = list(type = "centroid"),
parallel = NULL,
metric = "PC",
probability = 0.5,
distance_thresholds = c(250, 1500, 3000, 10000),
LA = Area,
onlyoverall = TRUE, intern = FALSE)
## ----eval=FALSE, message=FALSE, warning=FALSE, echo=TRUE----------------------
# #Maximum landcape attribute or LA = total area of the estudy area
# Area <- unit_convert( st_area(TMVS), "m2", "ha") #hectares
# PC_example_3 <- MK_dPCIIC(nodes = habitat_nodes,
# attribute = NULL,
# area_unit = "ha",
# distance = list(type = "centroid"),
# parallel = NULL,
# metric = "PC",
# probability = 0.5,
# distance_thresholds = c(250, 1500, 3000, 10000),
# LA = Area,
# onlyoverall = TRUE)
## ----eval=TRUE----------------------------------------------------------------
class(PC_example_3)
class(PC_example_3$d10000)
PC_example_3$d10000
## ----eval=TRUE, echo=FALSE, message=FALSE, warning=FALSE----------------------
IIC_example_4 <- MK_dPCIIC(nodes = habitat_nodes,
attribute = NULL,
area_unit = "ha",
distance = list(type = "centroid"),
parallel = NULL,
metric = "IIC",
probability = NULL,
distance_thresholds = c(250, 1500, 3000, 10000),
LA = Area,
overall = TRUE, intern = FALSE)
## ----eval=FALSE---------------------------------------------------------------
# IIC_example_4 <- MK_dPCIIC(nodes = habitat_nodes,
# attribute = NULL,
# area_unit = "ha",
# distance = list(type = "centroid"),
# parallel = NULL,
# metric = "IIC",
# probability = NULL,
# distance_thresholds = c(250, 1500, 3000, 10000),
# LA = Area,
# overall = TRUE)
## ----eval=TRUE----------------------------------------------------------------
class(IIC_example_4)
class(IIC_example_4$d10000$node_importances_d10000)
class(IIC_example_4$d10000$overall_d10000)
## -----------------------------------------------------------------------------
IIC_example_4$d10000$node_importances_d10000
## -----------------------------------------------------------------------------
IIC_example_4$d10000$overall_d10000
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