MATSim Code

do not regenerate primary ties when calibrating secondary threshold

HashMap -> LinkedHashMap

remove the Tie class

there are actually only the map-based methods of SocialNetwork which are
really useful, and the Tie list took a huge amount of memory leading to
filling the heap with dense networks.

use object pool for coords

make thresholds match the returned network at the end of iteration

express "secondary threshold" in terms of "reduction"

(theta in the paper). This is better for the calibration process, as
this allows the secondary threshold to follow the evolutions of the
primary threshold.

dump evolution of thresholds in a file

create a class to iterate the model to calibrate "thresholds"

this corresponds to the "manual calibration" of the paper. Instead that
I do not want to manually calibrate anything.

use log( dist + 1 ) instead of log( dist ) in utility

otherwise, utility of being friend with somebody living in the same
building is infinite. Distance usually being expressed in meter, this
should not change much to the results for friends living farther than
one meter away... This should be tested, though.

much faster secondary tie search