1. ev
  2. Soru-cevap
  3. Büyük daireler Bir ülke içinde harita içinde R

Büyük daireler Bir ülke içinde harita içinde R

2017-06-02 81 views
6

Banliyö seyahatlerinde çalışma Model (Origin - Destination) Flow Map in R. The Data i have adlı kişinin hareket tablosu (Date,Card,Entry_lat,Entry_Long,Exit_Lat,Exit_Long). Seyahat Yolu benzer olabilir (işe giderken).Büyük daireler Bir ülke içinde harita içinde R

Bu resmi map (great circles) numaralı belgede belirtmem gerekiyor. Kökeni & hedefi aynıysa - Bağlantı çizgilerinin yokluğu, orijini işaretlemelidir - hedefleme.

structure(list(business_date = structure(c(17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
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17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
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17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245, 
17245, 17245, 17245, 17245, 17245, 17245, 17245, 17245), class = "Date"), 
    token_id = c(1.12374e+19, 1.12374e+19, 1.81313e+19, 1.85075e+19, 
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"token_id", "Entry_Station_Lat", "Entry_Station_Long", "Exit_Station_Lat", 
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11029L, 11030L, 11032L, 11034L, 11035L, 11037L, 11038L, 11039L, 
11041L, 11042L, 11043L, 11044L, 11045L, 11047L, 11050L, 11051L, 
11054L, 11058L, 11062L, 11066L, 11067L, 11071L, 11074L, 11076L, 
11077L, 11080L, 11082L, 11084L, 11085L, 11089L, 11091L, 11093L, 
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11111L, 11112L, 11115L, 11119L, 11120L, 11121L, 11122L, 11123L, 
11125L, 11126L, 11127L, 11128L, 11129L, 11132L, 11134L, 11136L, 
11138L, 11140L, 11142L, 11146L, 11149L, 11151L, 11152L, 11155L, 
11158L, 11161L, 11164L, 11166L, 11167L, 11168L, 11169L, 11171L, 
11172L, 11174L, 11175L, 11179L, 11180L, 11192L, 11194L, 11195L, 
11198L, 11203L, 11206L, 11207L, 11208L, 11210L, 11213L, 11216L, 
11217L, 11219L, 11222L, 11225L, 11227L, 11228L, 11230L, 11233L, 
11234L, 11235L, 11240L, 11241L), class = "data.frame")

burada bana göre Flow map(Travel Path) Using Lat and Long in R

Ben GeoSpheres geçirdi ama görsel olarak çekici Seyahat deseni alamadım gelmiş sorulan benzer soru var.

Bu, Flow-MAp Graph sonucunu, kaynak ve hedef arasındaki toplam yolculukları hesaplayarak başarmak mümkün müdür. ya

enter image description here

veya

enter image description here

şimdiye kadar kullanılmış olan neyi: işte

require(ggplot2) 
require(ggmap) 
basemap <- get_map("Singapore", 
        source = "stamen", 
        maptype = "toner", 
        zoom = 11) 

g = ggplot(a) 
map = ggmap(basemap, base_layer = g) 
map = map + coord_cartesian() + 
     geom_curve(size = 1.3, 
       aes(x=as.numeric(Entry_Station_Long), 
        y=as.numeric(Entry_Station_Lat), 
        xend=as.numeric(as.character(Exit_Station_Long)), 
        yend=as.numeric(as.character(Exit_Station_Lat)) 
        )) 
map

kaynak

2017-06-02 RUser

+1

Büyük daire kavramının, bir küre üzerindeki en kısa mesafe olduğunu unutmayın (https://en.wikipedia.org/wiki/Great_circle). Birbirine çok yakın olan iki nokta arasındaki yolu düşünürseniz, dünyanın eğriliğinin optimal yol için dikkate değer bir etkisi yoktur. Yani, estetik görünümlü eğriler için arzu etmek büyük çemberler üzerinde çalışamaz, ancak düz çizgilerin bazı yapay bükülmelerini kullanmalıdır. – CMichael

+0

İlk çizim raporlaması, her istasyon çifti için toplam seyahat yoğunluğunu mu? Yani bireysel yolculuklardan uzaklaşmak, ancak seyahat yoğunluğunu göstermek mi istiyorsunuz? – CMichael

+0

Eğer bireysel yoğunlukla gidersem, çavuş güzel görünüyor. Daha ziyade istasyon çifti için seyahat yoğunluğu ile deneyeceğim. – RUser

cevap

1

OP güncellenmiş istek (SO gelen atfen) Başka bir deneyin geçerli:

#load packages and map 
require(tidyverse) 
require(ggmap) 
basemap <- get_map("Singapore", 
        source = "stamen", 
        maptype = "toner", 
        zoom = 11) 

#oversample data (because of too few rides) and summarize for station pairs 
a %>% 
    sample_n(size=5000,replace=T) %>% 
    mutate(Entry_Station_Lat = as.numeric(as.character(Entry_Station_Lat)), 
     Exit_Station_Lat = as.numeric(as.character(Exit_Station_Lat)), 
     Entry_Station_Long = as.numeric(as.character(Entry_Station_Long)), 
     Exit_Station_Long = as.numeric(as.character(Exit_Station_Long))) %>% 
    group_by(Entry_Station_Lat,Entry_Station_Long,Exit_Station_Lat,Exit_Station_Long) %>% 
    summarize(count=n()) -> plotData 

#extract entry Stations 
a %>% 
    mutate(Entry_Station_Lat = as.numeric(as.character(Entry_Station_Lat)), 
     Exit_Station_Lat = as.numeric(as.character(Exit_Station_Lat)), 
     Entry_Station_Long = as.numeric(as.character(Entry_Station_Long)), 
     Exit_Station_Long = as.numeric(as.character(Exit_Station_Long))) %>% 
    select(Entry_Station_Lat,Entry_Station_Long) %>% 
    group_by(Entry_Station_Lat,Entry_Station_Long) %>% 
    summarize(freq=n()) -> entryStations 

#extract exit stations  
a %>% 
    mutate(Entry_Station_Lat = as.numeric(as.character(Entry_Station_Lat)), 
     Exit_Station_Lat = as.numeric(as.character(Exit_Station_Lat)), 
     Entry_Station_Long = as.numeric(as.character(Entry_Station_Long)), 
     Exit_Station_Long = as.numeric(as.character(Exit_Station_Long))) %>% 
    select(Exit_Station_Lat,Exit_Station_Long) %>% 
    group_by(Exit_Station_Lat,Exit_Station_Long) %>% 
    summarize(freq=n()) -> exitStations 

#plot map, curves with size proportional to frequency, points for entry and exit stations 
g = ggplot(plotData) 
map = ggmap(basemap, base_layer = g) 
map = map + coord_cartesian() + 
    geom_curve(color="red",alpha=0.5,curvature=0.2, 
      aes(x=Entry_Station_Long,size = count, 
       y=Entry_Station_Lat, 
       xend=Exit_Station_Long, 
       yend=Exit_Station_Lat)) + 
    geom_point(data=exitStations,alpha=0.5,size=4, 
      aes(x=Exit_Station_Long, 
       y=Exit_Station_Lat)) + 
    geom_point(data=entryStations,alpha=0.5,size=4, 
      aes(x=Entry_Station_Long, 
       y=Entry_Station_Lat)) 
map

enter image description here

kaynak

2017-06-02 14:29:36 CMichael

+0

"mutate_at": mutate_at (vars (-business_date, -token_id), funs (as.numeric (as.character (.)))) ' – GGamba

+0

işaretçisinin @GGamba - için teşekkürler Daha önce asla mutasyona geçmedim ama gerçekten çok güçlü görünüyor. Başlangıçta, bu tür dönüşümün tamamen ortadan kaldırılması için tür dönüşümünün gerçekleşeceği, ancak hiç geçmediği orijinal yayına bir düzenleme önerdim. – CMichael

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