flowreduct {cartograflow}R Documentation

Flow matrix reduction according to another matrix

Description

Reduces a flow dataset according to an external matrix, eg. a matrix of travelled distance.
Builds geographical movements, by weighting a flow dataset according to a distance criterion.

Usage

flowreduct(tab, tab.metric, metric, d.criteria, d)

Arguments

tab

is the input flowdata set

tab.metric

the distance dataset

metric

select "continuous" or "ordinal" metric. See Details

d.criteria

is for selecting "dmin" or "dmax" distance criteria for "continuous" metric. See Details.

d

is the value of the selected "dmin" or "dmax". see Details

Details

The involved metric can be continous or not.

(1) Metric is 'continous" for distance as euclidian, maximum, manhattan, etc.
See flowdist
- Metric is 'ordinal" for computing neighbourhood ordinal distance matrix. – Select ="dmin" for reducing flow dataset to flow values that are up or equal to the dmin distance parameter (Fij>=dmin);
– select ="dmax" for reducing flow dataset to values that are less or equal to the dmax distance parameter(Fij=<dmin).

- Metric is 'ordinal' for computing neighbourhood ordinal distance with k contiguity.
See flowcontig for computing ordinal distance matrix

Value

A flow dataset with distances computations and flow reduction

Examples

library(cartograflow)
library(sf)
library(dplyr)
data(flowdata)
map <- st_read(system.file("shape/MGP_TER.shp", package = "cartograflow"))

tab <- flowjointure(
  geom = "area", bkg = map, DF.flow = flows, origin = "i", destination = "j",
  id = "EPT_NUM", x = "X", y = "Y"
)

# Example for reducing a flow matrice with a distance matrice, in long format (i,j, distance)
## 1/2: Computes the matrice distances
tab.distance <- flowdist(tab, dist.method = "euclidian", result = "dist")
tab.distance <- tab.distance %>% select(i, j, distance)
## 2/2: Reduce the flow matrice
tab.flow <- flowreduct(flows, tab.distance,
  metric = "continous",
  d.criteria = "dmax", d = 8567
)

[Package cartograflow version 1.0.3 Index]