example2: Example of using 'deduplication' package - the long way

In bogdanoancea/deduplication: R package for computing the duplicity probility for each mobile device.

Description

This is just an example on how to compute duplicity probabilities using simulated data. All the files used in this example are supposed to be produced using the simulation software. The "simulation.xml" file is an exception and it is an input file for the simulation software. The files used in this example are provided with the deduplication package.

Usage

example2()

Details

This is detailed example on how to compute duplicity probabilities using simulated data. All the files used in this example are supposed to be produced using the simulation software. The "simulation.xml" file is an exception and it is an input file for the simulation software. The files used in this example are provided with the deduplication package. This example shows step by step all intermediate computations performed before calling one the functions that computes the duplicity probabilities. All three methods are used in this example: "1-to-1", "pairs" and "trajectory".

References

https://github.com/MobilePhoneESSnetBigData

Examples

# set the folder where the necessary input files are stored

path_root      <- 'extdata'

# 0. Read simulation params

simParams <-readSimulationParams(system.file(path_root, 'simulation.xml', 
package = 'deduplication'))

 # 1. Read grid parameters
 
gridParams <-readGridParams(system.file(path_root, 'grid.csv', 
package = 'deduplication'))

 # 2.Read network events
 
events <- readEvents(system.file(path_root, 'AntennaInfo_MNO_MNO1.csv', 
package = 'deduplication'))

 # 3. Get a list of detected devices
 
devices <- getDeviceIDs(events)

#4. Get connections for each device

connections <- getConnections(events)

#5. Emission probabilities are computed from the signal strength/quality file

emissionProbs <- getEmissionProbs(gridParams$nrow, gridParams$ncol, 
system.file(path_root, 'SignalMeasure_MNO1.csv', package = 'deduplication'), 
simParams$conn_threshold)

#6. Build joint emission probabilities

jointEmissionProbs <- getEmissionProbsJointModel(emissionProbs)

#7. Build the generic model

model <- getGenericModel(gridParams$nrow, gridParams$ncol, emissionProbs)

#8. Fit models

ll <- fitModels(length(devices), model,connections)

#9. Build the joint model

modelJ <- getJointModel(gridParams$nrow, gridParams$ncol, jointEmissionProbs)

#10. Read antenna cells and build a matrix of neighboring antennas

coverarea <- readCells(system.file(path_root, 'AntennaCells_MNO1.csv', 
package = 'deduplication'))

antennaNeigh <- antennaNeighbours(coverarea)

#11. Apriori probability of duplicity

P1 <- aprioriDuplicityProb(simParams$prob_sec_mobile_phone, length(devices))

#12. Build a matrix of pairs of devices to compute duplicity probability

pairs4dupP<-computePairs(connections, length(devices), oneToOne = FALSE, P1=P1, 
limit = 0.05, antennaNeighbors = antennaNeigh)

#13. Compute duplicity probabilities using the "pairs" method (faster)

out1 <- computeDuplicityBayesian("pairs", devices, pairs4dupP, modelJ, ll, P1)

#14. Apriori probability of 2-to-1 

Pii <- aprioriOneDeviceProb(simParams$prob_sec_mobile_phone, length(devices))

#15. Build a matrix of pairs of devices to compute duplicity probability

pairs4dupO<-computePairs(connections, length(devices), oneToOne = TRUE)

#16. Compute duplicity probabilities using "1to1" method

out2 <- computeDuplicityBayesian("1to1", devices, pairs4dupO, modelJ, ll, 
P1 = NULL, Pii=Pii)

#17. Compute duplicity probabilities using "trajectory method"

T<-sort(unique(events[,1][[1]]))

out3 <-computeDuplicityTrajectory(path=system.file(path_root, package = 'deduplication'), 
"postLocDevice", devices, gridParams, pairs4dupP, P1 = P1, T, gamma = 0.5)

bogdanoancea/deduplication documentation built on Dec. 2, 2020, 11:22 p.m.