flowanalysis: Computation of a global concentration criterion of flows...
In fbahoken/cartogRaflow: Filtering Matrix for Flow Mapping

Description Usage Arguments Details References Examples

Computation of a global selection criterion for filtering flows values or flow features.
To be use after flowgini and before flowmap.

1	flowanalysis(tab, fij = NULL, critflow, critlink, result)

`tab`	input flow dataset from flowgini
`fij`	flow value between origin and destination places
`critflow`	desired level of information significativity. See Details.
`critlink`	desired level of features density. See Details.
`result`	resulting filtering criterion value. See Details.

-critflow = desired level of flow's information significativity (e.g. 80 -critlink = desired level of flow's features density (e.g. 20 of the flow features that represents the more significant information.

-result="density" returns the desired level of features density as a -result = "significativity" returns the level of flow significativity as a

Bahoken Françoise, 2016,« La cartographie d’une sélection globale de flux, entre ‘significativité’ et ‘densité’ », Netcom Online, 30-3/4 | 2016, Online since 23 March 2017, connection on 05 May 2019. URL : http://journals.openedition.org/netcom/2565 ; DOI : 10.4000/netcom.2565

library(cartograflow)
data(flowdata)

# 1/4: Computes Gini's coefficent
tabgini <- flowgini(ODpts = flows, origin = "i", destination = "j", 
                     valflow = "Fij", lorenz.plot = FALSE)
### [1] Gini's coefficent = 73.16 %

# 2/4: Plot Lorenz curve
flowgini(tab_gini,
  format = "L", origin = "i", dest = "j", valflow = "ydata",
  bkg, code = "EPT_NUM", lorenz.plot = TRUE
)

# 3/4: Compute critflow filtering parameter
# critflow = 0.8 #selected criterion
flowanalysis(tabgini, critflow = 0.8, result = "signif")
### [1] "threshold =  11238  ---  flows =  80 % ---  links =  22.94 %"

# 4/4: Plot the flowmap

flowmap(
  tab = tabflow, fij = "Fij", origin.f = "i", destination.f = "j",
  bkg = map, code = "EPT_NUM", nodes.X = "X", nodes.Y = "Y",
  filter = TRUE,
  threshold = 11238,
  taille = 8,
  a.head = 1,
  a.length = 0.11,
  a.angle = 30,
  a.col = "#3f4247"
)