Final_b12208017

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library(sf)
library(dplyr)
library(tmap)

taipei_li <- st_read("C:/Users/user/OneDrive/文件/空間/Taipei_Vill.shp")

Reading layer `Taipei_Vill' from data source 
  `C:\Users\user\OneDrive\文件\空間\Taipei_Vill.shp' using driver `ESRI Shapefile'
Simple feature collection with 456 features and 8 fields
Geometry type: POLYGON
Dimension:     XY
Bounding box:  xmin: 296094.4 ymin: 2761518 xmax: 317198.9 ymax: 2789180
Projected CRS: TWD97 / TM2 zone 121

fastfood <- st_read("C:/Users/user/OneDrive/文件/空間/Tpe_Fastfood.shp")

Reading layer `Tpe_Fastfood' from data source 
  `C:\Users\user\OneDrive\文件\空間\Tpe_Fastfood.shp' using driver `ESRI Shapefile'
Simple feature collection with 98 features and 8 fields
Geometry type: POINT
Dimension:     XY
Bounding box:  xmin: 297198.9 ymin: 2763885 xmax: 312205.7 ymax: 2781148
Projected CRS: TWD97 / TM2 zone 121

schools <- st_read("C:/Users/user/OneDrive/文件/空間/SCHOOL.shp")

Reading layer `SCHOOL' from data source 
  `C:\Users\user\OneDrive\文件\空間\SCHOOL.shp' using driver `ESRI Shapefile'
Simple feature collection with 148 features and 4 fields
Geometry type: POINT
Dimension:     XY
Bounding box:  xmin: 297078.6 ymin: 2763290 xmax: 312516.7 ymax: 2784542
Projected CRS: TWD97 / TM2 zone 121

schools <- st_transform(schools, st_crs(fastfood))
taipei_li <- st_transform(taipei_li, st_crs(fastfood))

A_districts <- c("文山區", "大安區", "中正區")
B_districts <- c("信義區", "南港區", "松山區")

A_li <- taipei_li %>% filter(TOWN %in% A_districts)
B_li <- taipei_li %>% filter(TOWN %in% B_districts)

fastfood_A <- fastfood[A_li, ]
fastfood_B <- fastfood[B_li, ]

buffer_A <- st_buffer(fastfood_A, dist = 15000)
buffer_B <- st_buffer(fastfood_B, dist = 15000)

count_A <- lengths(st_intersects(buffer_A, schools))
count_B <- lengths(st_intersects(buffer_B, schools))
length(count_A)

[1] 0

length(count_B)

[1] 0

t.test(count_A, count_B, var.equal = FALSE)

錯誤發生在 t.test.default(count_A, count_B, var.equal = FALSE)： 
  'x' 觀察值數量不夠

library(spdep)
library(stars)
library(spatialreg)
library(spdep)

bbox <- st_bbox(taipei_li)
grid <- st_make_grid(taipei_li, cellsize = 500, square = TRUE) %>%
  st_sf() %>%
  st_filter(taipei_li)

grid$fastfood_count <- lengths(st_intersects(grid, fastfood))

nb <- poly2nb(grid, queen = TRUE)
lw <- nb2listw(nb, style = "W")

nb <- poly2nb(grid, queen = TRUE)           
lw <- nb2listw(nb, style = "W")           

mcorr <- sp.correlogram(nb, grid$fastfood_count,
                        order = 10, method = "I", style = "W")

plot(mcorr)

library(spdep)
library(sf)
library(dplyr)

grid$school_count <- lengths(st_intersects(grid, schools))

Gi_fastfood <- localG(grid$fastfood_count, lw)
Gi_school <- localG(grid$school_count, lw)

grid$Gi_fastfood <- as.numeric(Gi_fastfood)
grid$Gi_school <- as.numeric(Gi_school)

grid$p_fastfood <- 2 * pnorm(-abs(grid$Gi_fastfood))
grid$p_school <- 2 * pnorm(-abs(grid$Gi_school))

grid$p_fastfood_adj <- p.adjust(grid$p_fastfood, method = "BH")
grid$p_school_adj <- p.adjust(grid$p_school, method = "BH")

grid$hotspot_fastfood <- grid$p_fastfood_adj < 0.05 & grid$Gi_fastfood > 0
grid$hotspot_school <- grid$p_school_adj < 0.05 & grid$Gi_school > 0

tm_shape(grid) +
  tm_fill("hotspot_fastfood", palette = c("white", "red"), title = "速食店熱區") +
  tm_borders()

── tmap v3 code detected ─────────────────────────────────────────────────────────────
[v3->v4] `tm_tm_fill()`: migrate the argument(s) related to the scale of the visual
variable `fill` namely 'palette' (rename to 'values') to fill.scale =
tm_scale(<HERE>).[v3->v4] `tm_fill()`: migrate the argument(s) related to the legend of the visual
variable `fill` namely 'title' to 'fill.legend = tm_legend(<HERE>)'

tm_shape(grid) +
  tm_fill("hotspot_school", palette = c("white", "blue"), title = "學校熱區") +
  tm_borders()

── tmap v3 code detected ─────────────────────────────────────────────────────────────
[v3->v4] `tm_tm_fill()`: migrate the argument(s) related to the scale of the visual
variable `fill` namely 'palette' (rename to 'values') to fill.scale =
tm_scale(<HERE>).[v3->v4] `tm_fill()`: migrate the argument(s) related to the legend of the visual
variable `fill` namely 'title' to 'fill.legend = tm_legend(<HERE>)'

library(sf)
library(dplyr)
library(spatstat.geom)

taipei_li <- st_read("C:/Users/user/OneDrive/文件/空間/Taipei_Vill.shp")

Reading layer `Taipei_Vill' from data source 
  `C:\Users\user\OneDrive\文件\空間\Taipei_Vill.shp' using driver `ESRI Shapefile'
Simple feature collection with 456 features and 8 fields
Geometry type: POLYGON
Dimension:     XY
Bounding box:  xmin: 296094.4 ymin: 2761518 xmax: 317198.9 ymax: 2789180
Projected CRS: TWD97 / TM2 zone 121

fastfood <- st_read("C:/Users/user/OneDrive/文件/空間/Tpe_Fastfood.shp")

Reading layer `Tpe_Fastfood' from data source 
  `C:\Users\user\OneDrive\文件\空間\Tpe_Fastfood.shp' using driver `ESRI Shapefile'
Simple feature collection with 98 features and 8 fields
Geometry type: POINT
Dimension:     XY
Bounding box:  xmin: 297198.9 ymin: 2763885 xmax: 312205.7 ymax: 2781148
Projected CRS: TWD97 / TM2 zone 121

study_districts <- c("文山區", "大安區", "信義區")
study_area <- taipei_li %>% filter(TOWN %in% study_districts)

bbox <- st_bbox(study_area)

win <- owin(
  xrange = c(as.numeric(bbox["xmin"]), as.numeric(bbox["xmax"])),
  yrange = c(as.numeric(bbox["ymin"]), as.numeric(bbox["ymax"]))
)

錯誤發生在 if (!is.vector(xrange) || length(xrange) != 2 || xrange[2L] < ： 
  需要 TRUE/FALSE 值的地方有缺值

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