targets

[temospena]

set up an automation for the whole process, that in the end only adjusts the filter conditions for selection.

use targets

[temospena]

Set as variables:

• [x] CITY = "Lisboa"
• [x] cellsize = c(200, 200)
• [x] square = TRUE # FALSE for hexagons
• [x] degree_min = summary(centrality_grid$degree)[[4]] # mean
• [x] betweenness_min = quantile(centrality_grid$betweenness, 0.40, na.rm = TRUE) # Change to 0.25 ?
• [x] betweenness_max = quantile(centrality_grid$betweenness, 0.60, na.rm = TRUE) # Change to 0.75 ?
• [x] closeness_min = 0.25 # Change to P25 ?
• [x] closeness_max = 0.75 # Change to P75 ?
• [x] population_min = mean(density_grid$population) # Change to median?

[temospena]

if not provided, use defaults!

[temospena]

for now, we can set defaults in _targets.R file

# Set defaults HERE ######################
CITY_input = "Almada"

#########################################

[temospena]

Not sure if we should use the quartile in closeness, or just the value. @valenca13 ?

degree_min = mean # mean or median? default: mean
betweeness_range = 0.4 # percentile to exclude (upper and lower) default: 0.25
closeness_range = 0.25 # value to exclude (upper and lower) default: 0.25

In the paper we used the value, but it can make no sense... depending on the area