library("openrouteservice", lib.loc="~/R/win-library/3.5")
coordinates <- list(c(8.34234, 48.23424), c(8.34423, 48.26424))
x <- ors_directions(coordinates)
library("data.table", lib.loc="~/R/win-library/3.5")
r
roma <- fread("C:/Users/hp5687/Downloads/taxi_february.tar/taxi_february/taxi_february.txt")
View(roma)
roma_filt <- roma[V1==156]
View(roma_filt)
View(roma_filt)
roma_taxi <- write.csv2(roma_filt, "C:\Users\hp5687\Downloads\taxi_february.tar\roma.csv")
roma_taxi <- write.csv2(roma_filt, "C:/Users/hp5687/Downloads/taxi_february.tar/roma.csv")
View(roma_filt)
roma_taxi <- write.csv2(roma_filt, "C:/Users/hp5687/Downloads/taxi_february.tar/roma.csv")
library(dplyr)
library(stplanr)
library(pct)
od_data_sample[1:3, 1:3]
od_data_sample[1:3, 1:3]
od_data_sample
samp <- od_data_sample
View(samp)
travel_network <- od2line(flow = od_data_sample, zones = cents_sf)
w <- flow$all / max(flow$all) *10
plot(travel_network, lwd = w)
routes <- route(
l = desire_lines,
route_fun = osrmRoute,
returnclass = "sf"
)
library("osrm", lib.loc="~/R/win-library/3.5")
routes <- route(
l = desire_lines,
route_fun = osrmRoute,
returnclass = "sf"
)
desire_lines <- travel_network[2:6, ]
routes <- route(
l = desire_lines,
route_fun = osrmRoute,
returnclass = "sf"
)
#> Data: (c) OpenStreetMap contributors, ODbL 1.0 - http://www.openstreetmap.org/copyright
#> Routing: OSRM - http://project-osrm.org/
trip <- route(
from = c(-0.11, 51.514),
to = c(-0.10, 51.506),
route_fun = osrmRoute,
returnclass = "sf"
)
#> Data: (c) OpenStreetMap contributors, ODbL 1.0 - http://www.openstreetmap.org/copyright
#> Routing: OSRM - http://project-osrm.org/
trip <- route(
from = c(-0.11, 51.514),
to = c(-0.10, 51.506),
route_fun = osrmRoute,
returnclass = "sf"
)
library(osrm)
#> Data: (c) OpenStreetMap contributors, ODbL 1.0 - http://www.openstreetmap.org/copyright
#> Routing: OSRM - http://project-osrm.org/
trip <- route(
from = c(-0.11, 51.514),
to = c(-0.10, 51.506),
route_fun = osrmRoute,
returnclass = "sf"
)
shiny::runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
library(dplyr)
library(ggmap)
library(rgdal)
install.packages("ggmap")
setwd("D:/Projekte/urbandatalab/data/export")
ka_00 <- readOGR(dsn = ".", layer = "ka_fr_00_link") %>%
spTransform("+proj=longlat +ellps=WGS84")
View(ka_00)
kaMap <- qmap("Karlsruhe", zoom = 10)
kaMap <- get_googlemap("Karlsruhe")
bboxka <- bbox(ka_00)
kamap <- get_openstreetmap(bbox=bboxka)
library(ggmap)
bboxka <- bbox(ka_00)
kamap <- get_openstreetmap(bbox=bboxka)
kamap <- OSM(bbox=bboxka)
kamap <- get_stamenmap(bbox=bboxka)
ggmap(kamap) + geom_polygon(data=ka_00, aes(x=lon, y=lat), col="red", fill=NA)
ggmap(kamap) + geom_polygon(data=ka_00), col="red", fill=NA)
ggmap(kamap) + geom_polygon(data=ka_00, col="red", fill=NA)
ggplot() +
geom_sf(data = ka_00, size = 3, color = "black") +
ggtitle("AOI Boundary Plot") +
coord_sf()
library(sf)
ka00 <- st_read(dsn = ".", layer = "ka_fr_00_link")
ggplot() +
geom_sf(data = ka00, size = 3, color = "black") +
ggtitle("AOI Boundary Plot") +
coord_sf()
ggplot() +
geom_sf(data = ka00, size = 1, color = "black") +
ggtitle("AOI Boundary Plot") +
coord_sf()
ka_map <- get_stamenmap(bbox=bboxka, crop=TRUE)
ggmap(ka_map)
ka_map <- get_stamenmap(bbox=bboxka, zoo,=14)
ka_map <- get_stamenmap(bbox=bboxka, zoom=14)
ggmap(ka_map)
ka_map <- get_stamenmap(bbox=bboxka, zoom=12)
ggmap(ka_map)
ka_map <- get_stamenmap(bbox=bboxka, zoom=10)
ggmap(ka_map)
ggmap(ka_map)+
geom_sf(data = ka00, size = 1, color = "black") +
ggtitle("AOI Boundary Plot") +
coord_sf()
ggmap(ka_map)+
geom_sf(data = ka00, size = 1, color = "black", geom="polyline") +
ggtitle("AOI Boundary Plot") +
coord_sf()
shapefile_df <- fortify(ka_00)
map <- ggplot() +
geom_path(data = shapefile_df,
aes(x = long, y = lat, group = group),
color = 'gray', fill = 'white', size = .2)
m
map <- ggplot() +
geom_path(data = shapefile_df,
aes(x = long, y = lat, group = group),
color = 'gray', size = .2)
library(sf)
print(map)
qmap(location = "karlsruhe", zoom=14)
myMap <- get_map(location=ka_00@bbox,
source="google", maptype="roadmap", crop=FALSE,colour = class)
myMap
ggmap(myMap)
myMap <- get_map(location=ka_00@bbox)
ggmap(myMap)
map <- ggmap(myMap) +
geom_path(data = shapefile_df,
aes(x = long, y = lat, group = group),
color = 'red', size = 1)
ka_map <- get_map(location=ka_00@bbox)
map <- ggmap(ka_map) +
geom_path(data = shapefile_df,
aes(x = long, y = lat, group = group),
color = 'red', size = 1)
map
if(!require(dplyr)){install.packages("dplyr");library(dplyr)}
if(!require(ggmap)){install.packages("ggmap");library(ggmap)}
if(!require(rgdal)){install.packages("rgdal");library(rgdal)}
if(!require(sf)){install.packages("sf");library(sf)}
View(ka_00)
plot(ka_00)
plot all()
plot all(ka_00)
breaks_qt <- classIntervals(ka_00@data$MEDIANSP.3, n = 5, style = "equal"), pal=pal1)
breaks_qt <- classIntervals(ka_00@data$MEDIANSP.3, n = 5, style = "equal", pal=pal1)
library("classInt", lib.loc="~/R/win-library/3.5")
breaks_qt <- classIntervals(ka_00@data$MEDIANSP.3, n = 5, style = "equal", pal=pal1)
View(breaks_qt)
View(shapefile_df)
map <- ggmap(ka_map) +
geom_sf(data = ka_00,
aes(x = long, y = lat),
color = 'red', size = 1)
map <- ggmap(ka_map) +
geom_sf(data = ka_00@data,
aes(x = long, y = lat),
color = 'red', size = 1)
map <- ggmap(ka_map) +
geom_sf(data = ka_00,
aes(x = long, y = lat),
color = 'red', size = 1)
map <- ggmap(ka_map) +
geom_sf(data = ka_df,
aes(x = long, y = lat),
color = 'red', size = 1)
###shapefile has to be converted to a dataframe for use in ggplot2
ka_df <- fortify(ka_00)
map <- ggmap(ka_map) +
geom_sf(data = ka_df,
aes(x = long, y = lat),
color = 'red', size = 1)
map <- ggmap(ka_map) +
geom_sf(data = ka_df,
aes(x = long, y = lat),
color = 'red', size = 1)
plot(map)
map
map <- ggmap(ka_map) +
geom_sf(data = ka_df,
aes(x = long, y = lat),
color = 'red', size = 1)
View(map)
print(map)
#####Exercise 1: Reading shp-files in R and displaying with ggmap/ggplot#####
setwd("D:/Projekte/urbandatalab/data/export")
ka_00 <- readOGR(dsn = ".", layer = "ka_fr_00_link") %>%
spTransform("+proj=longlat +ellps=WGS84")
ka_map <- get_map(location=ka_00@bbox)
###shapefile has to be converted to a dataframe for use in ggplot2
ka_df <- fortify(ka_00)
map <- ggmap(ka_map) +
geom_sf(data = ka_df,
aes(x = long, y = lat),
color = 'red', size = 1)
map
if(!require(dplyr)){install.packages("dplyr");library(dplyr)}
if(!require(ggmap)){install.packages("ggmap");library(ggmap)}
if(!require(rgdal)){install.packages("rgdal");library(rgdal)}
if(!require(sf)){install.packages("sf");library(sf)}
#####Exercise 1: Reading shp-files in R and displaying with ggmap/ggplot#####
setwd("D:/Projekte/urbandatalab/data/export")
ka_00 <- readOGR(dsn = ".", layer = "ka_fr_00_link") %>%
spTransform("+proj=longlat +ellps=WGS84")
ka_map <- get_map(location=ka_00@bbox)
###shapefile has to be converted to a dataframe for use in ggplot2
ka_df <- fortify(ka_00)
map <- ggmap(ka_map) +
geom_sf(data = ka_df,
aes(x = long, y = lat),
color = 'red', size = 1)
map
plot(map)
plot(ka_map)
map <- ggmap(ka_map) +
geom_sf(data = ka_df,
aes(x = long, y = lat),
color = 'red', size = 1)
plot(map)
map <- ggmap(ka_map) +
geom_path(data = ka_df,
aes(x = long, y = lat),
color = 'red', size = 1)
plot(map)
map <- ggmap(ka_map) +
geom_path(data = ka_df,
aes(x = long, y = lat, group=ka),
color = 'red', size = 1)
plot(map)
map <- ggmap(ka_map) +
geom_path(data = ka_df,
aes(x = long, y = lat, group=group),
color = 'red', size = 1)
plot(map)
map
#####Exercise 2:
breaks_eq <- classIntervals(ka_00@data$MEDIANSP.3, n = 5, style = "equal")
ka_00@data$speed_cat<- cut(ka_00@data$MEDIANSP.3, breaks_eq$brks)
ka_sf <- st_read(dsn = ".", "ka_fr_00_link")
View(ka_sf)
ggplot(ka_map) +
geom_sf(ka_sf,
aes(x = long, y = lat))
ggplot(ka_map) +
geom_sf(data=ka_sf,
aes(x = long, y = lat))
ka_sf <- st_read(dsn = ".", "ka_fr_00_link")%>%
spTransform("+proj=longlat +ellps=WGS84")
ggplot(ka_map) +
geom_sf(data=ka_sf,
aes(x = long, y = lat))
View(ka_sf)
ka_sf %>% ggplot() + geom_sf(aes(color=red))
ka_sf %>% ggplot() + geom_sf(aes(color="red"))
ka_sf %>% ggplot(ka_map) + geom_sf(aes(color="red"))
ka_sf %>% ggplot(ka_map) + geom_sf(data=ka_sf,aes(color="red"))
ggplot(ka_map) + geom_sf(data=ka_sf,aes(color="red"))
ggplot() + geom_sf(data=ka_sf,aes(color="red"))
ggplot(ka_map) + geom_sf(data=ka_sf,aes(color="red"))
ggplot(ka_map) + geom_sf() + geom_line(data=ka_sf,aes(color="red"))
ggplot(ka_map) + geom_sf() + geom_line(data=ka_sf,aes(color="red"))
rlang::last_error()
if(!require(tmap)){install.packages("tmap");library(tmap)}
#####Exercise 2: Reading shp-files with sf and displaying with tmap#####
ka_sf <- st_read(dsn = ".", layer = "ka_fr_00_link")
tm_shape()
tm_shape(ka_sf)
View(ka_sf)
View(ka_sf)
tm_shape(ka_sf)+tm_lines(MEDIANSP.3, lwd = 1)
tm_shape(ka_sf)+tm_lines(col="MEDIANSP.3", lwd = 1)
tm_shape(ka_sf)+tm_lines(col="MEDIANSP.3", style = "equal")
tm_shape(ka_sf)+tm_lines(col="MEDIANSP.3", style = "equal", lwd="scalerank", scale=2)
tm_shape(ka_sf)+tm_lines(col="MEDIANSP.3", style = "equal", lwd="MEDIANSP.3", scale=2)
tm_shape(ka_sf)+tm_lines(col="MEDIANSP.3", style = "equal", lwd="MEDIANSP.3", scale=5)
tm_shape(ka_sf)+tm_lines(col="MEDIANSP.3", style = "equal", lwd="MEDIANSP.3", scale=5, legend.lwd.show = FALSE)
tmap_mode("view")
tmap_last()
tm_shape(ka_sf)+tm_lines(col="MEDIANSP.3", style = "equal", lwd="FRC", scale=5, legend.lwd.show = FALSE)
###Change between plot and view mode
tmap_mode("view")
tmap_last()
tm_shape(ka_sf)+tm_lines(col="MEDIANSP.3", style = "equal", lwd="MEDIANSP.3", scale=5, legend.lwd.show = FALSE)
tmap_last()
tm_shape(ka_sf)+tm_lines(col="MEDIANSP.3", style = "equal", lwd="FRC", scale=10, legend.lwd.show = FALSE)
###Change between plot and view mode
tmap_mode("plot")
tmap_last()
shp_files <- list.files(dsn=".", pattern = "\\.shp$")
shp_files <- list.files(".", pattern = "\\.shp$")
print(shp_files)
wd <- "D:/Projekte/urbandatalab/data/export"
shp_files <- list.files(wd, pattern = "\\.shp$")
print(shp_files)
wd <- "/D:/Projekte/urbandatalab/data/export"
shp_files <- list.files(wd, pattern = "\\.shp$")
print(shp_files)
dir <- "D:/Projekte/urbandatalab/data/export"
shp_files <- list.files(dir, pattern = "\\.shp$", full.names = TRUE)
print(shp_files)
shp_files <- list.files(dir, pattern = "*.shp", full.names = TRUE)
print(shp_files)
shp_files <- list.files(pattern = "*.shp", full.names = TRUE)
print(shp_files)
ggplot(data = ka_map) +
geom_sf() +
geom_sf(data = ka_sf, color = gray(.5))
if(!require(leaflet)){install.packages("leaflet");library(leaflet)}
leaflet(ka_sf)
leaflet(ka_sf) %>%
addPolylines()
ka_sf <- st_read(dsn = ".", layer = "ka_fr_00_link") %>%
st_transform(ka_sf, 4326)
tm_shape(ka_sf)+tm_lines(col="MEDIANSP.3", style = "equal", lwd="MEDIANSP.3", scale=5, legend.lwd.show = FALSE)
leaflet(ka_sf) %>%
addPolylines()
leaflet() %>%
addPolylines(ka_sf)
int_map <- leaflet %>%
addTiles()
int_map
int_map <- leaflet() %>%
addTiles()
int_map
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(ka_sf)
int_map
int_map <- leaflet(ka_sf) %>%
addTiles() %>%
addPolylines()
int_map
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sf)
st_crs(ka_sf, 4326)
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sf)
st_transform(ka_sf, 4326)
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sf)
ka_sf <- st_transform(ka_sf, "+init=epsg:4326")
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sf)
int_map
ka_sf <- st_transform(ka_sf, 4326)
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sf)
int_map
ka_sx <- st_read(dsn = ".", layer = "ka_fr_00_link")
ka_sx <- st_transform(ka_sf, 4326)
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sx)
int_map
ka_map+ggplot()+geom_sf(ka_sf)
ka_map+geom_sf(ka_sf)
ka_map+geom_sf(ka_sf(aes))
ka_map+geom_sf(ka_sf,aes())
colours <- seq(1, floor(max(ka_sf$MEDIANSP.3)))
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sf, col = brewer.pal(6, "Set1"), breaks=breaks_eq$brks)
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sf, col = brewer.pal(6, "Set1"))
binpal <- colorBin("Red", ka_sf$MEDIANSP.3, 6, pretty = FALSE)
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sf, color = ~binpal(MEDIANSP.3))
int_map
binpal <- colorBin("inferno", ka_sf$MEDIANSP.3, 6, pretty = FALSE)
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sf, color = ~binpal(MEDIANSP.3))
int_map
int_map <- leaflet() %>%
addTiles(opacity=0.35) %>%
addPolylines(data=ka_sf, color = ~binpal(MEDIANSP.3))
int_map <- leaflet() %>%
addTiles(options = providerTileOptions(opacity = 0.35)) %>%
addPolylines(data=ka_sf, color = ~binpal(MEDIANSP.3))
int_map
#####Exercise 3: Displaying maps with leaflet#####
binpal <- colorBin("plasma", ka_sf$MEDIANSP.3, 5, pretty = FALSE)
int_map <- leaflet() %>%
addTiles() %>%
addPolylines(data=ka_sf, color = ~binpal(MEDIANSP.3))
int_map
runApp('D:/Google Drive/IfV/Projekte/rcodes/stuttgart')
dir <- "D:/Projekte/urbandatalab/data/export"
shp_files <- list.files(wd, pattern = "\\.shp$")
shp_files <- list.files(dir, pattern = "\\.shp$")
shp_files <- list.files(dir, pattern = "*.shp")
dir <- "D:\Projekte\urbandatalab\data\export"
dir <- "/D:/Projekte/urbandatalab/data/export"
list.files(dir)
list.files()
list.files(, pattern = "*.shp")
list.files(, pattern = "*.SHP")
shps <- list.files(, pattern = "*.SHP")
shps <- list.files("",pattern = "*.SHP")
rgdal_batch_shp <- function(shp_list) {
layer_name <- as.character(gsub(".shp","",shp_list))
shp_spdf <-readOGR(dsn = wd, stringsAsFactors = FALSE, verbose = TRUE,
useC = TRUE, dropNULLGeometries = TRUE, addCommentsToPolygons = TRUE,
layer = layer_name, require_geomType = NULL,
p4s = NULL, encoding = 'ESRI Shapefile')
}
batch_shp_list <- lapply(shps, rgdal_batch_shp)
rgdal_batch_shp <- function(shp_list) {
layer_name <- as.character(gsub(".shp","",shp_list))
shp_spdf <-readOGR(dsn = ".", stringsAsFactors = FALSE, verbose = TRUE,
useC = TRUE, dropNULLGeometries = TRUE, addCommentsToPolygons = TRUE,
layer = layer_name, require_geomType = NULL,
p4s = NULL, encoding = 'ESRI Shapefile')
}
batch_shp_list <- lapply(shps, rgdal_batch_shp)
layer_name <- as.character(gsub(".SHP","",shp_list))
rgdal_batch_shp <- function(shp_list) {
layer_name <- as.character(gsub(".SHP","",shp_list))
shp_spdf <-readOGR(dsn = ".", stringsAsFactors = FALSE, verbose = TRUE,
useC = TRUE, dropNULLGeometries = TRUE, addCommentsToPolygons = TRUE,
layer = layer_name, require_geomType = NULL,
p4s = NULL, encoding = 'ESRI Shapefile')
}
batch_shp_list <- lapply(shps, rgdal_batch_shp)
shps <- list.files(,pattern = "*.SHP")
rgdal_batch_shp <- function(shp_list) {
layer_name <- as.character(gsub(".SHP","",shp_list))
shp_spdf <-readOGR(dsn = ".", stringsAsFactors = FALSE, verbose = TRUE,
useC = TRUE, dropNULLGeometries = TRUE, addCommentsToPolygons = TRUE,
layer = layer_name, require_geomType = NULL,
p4s = NULL, encoding = 'ESRI Shapefile')
}
batch_shp_list <- lapply(shps, rgdal_batch_shp)
for (i in seq(batch_shp_list))
assign(paste("", i, sep = ""), batch_shp_list[[i]])
for (i in seq(batch_shp_list))
assign(paste("ka", i, sep = ""), batch_shp_list[[i]])
###extract files
batch_shp_list <- lapply(shps, rgdal_batch_shp)
for (i in seq(batch_shp_list))
assign(paste("ka", i-1, sep = ""), batch_shp_list[[i]])
shps <- list.files(,pattern = "*.SHP")
###shp load function
rgdal_batch_shp <- function(shp_list) {
layer_name <- as.character(gsub(".SHP","",shp_list))
shp_spdf <-readOGR(dsn = ".", stringsAsFactors = FALSE, verbose = TRUE,
useC = TRUE, dropNULLGeometries = TRUE, addCommentsToPolygons = TRUE,
layer = layer_name, require_geomType = NULL,
p4s = NULL, encoding = 'ESRI Shapefile')
}
###extract files
batch_shp_list <- lapply(shps, rgdal_batch_shp)
for (i in seq(batch_shp_list))
assign(paste("ka", i-1, sep = ""), batch_shp_list[[i]])
runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
shps <- list.files(,pattern = "*.SHP")
###shp load function
rgdal_batch_shp <- function(shp_list) {
layer_name <- as.character(gsub(".SHP","",shp_list))
shp_spdf <-readOGR(dsn = ".", stringsAsFactors = FALSE, verbose = TRUE,
useC = TRUE, dropNULLGeometries = TRUE, addCommentsToPolygons = TRUE,
layer = layer_name, require_geomType = NULL,
p4s = NULL, encoding = 'ESRI Shapefile')
shp_spdf <- spTransform(shp_sdf, CRS("+proj=longlat +datum=WGS84 +no_defs"))
}
###extract files
batch_shp_list <- lapply(shps, rgdal_batch_shp)
###shp load function
rgdal_batch_shp <- function(shp_list) {
layer_name <- as.character(gsub(".SHP","",shp_list))
shp_spdf <-readOGR(dsn = ".", stringsAsFactors = FALSE, verbose = TRUE,
useC = TRUE, dropNULLGeometries = TRUE, addCommentsToPolygons = TRUE,
layer = layer_name, require_geomType = NULL,
p4s = NULL, encoding = 'ESRI Shapefile')
shp_spdf <- spTransform(shp_spdf, CRS("+proj=longlat +datum=WGS84 +no_defs"))
}
###extract files
batch_shp_list <- lapply(shps, rgdal_batch_shp)
for (i in seq(batch_shp_list))
assign(paste("ka", i-1, sep = ""), batch_shp_list[[i]])
runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
paste0("ka", input$std)
paste0("ka", 10)
plot(paste0("ka", 10))
plot(paste0("ka", "10"))
runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
runApp('D:/Projekte/urbandatalab/shiny/UDS_Tag4')
