All numeric parameters for a map are computed from the raw segment data of other maps using leave-one-map-out cross-validation. First the actual values of the relevant properties (e.g., length, depth, angle) are computed, and then parameter values are computed by a function of the mean and standard deviation of these values. //////////////numeric parameters definitions begin////////////////// DoorLength = the mean of the length of all Door segments. DoorDepth = the mean of the depth of all Door segments. WallLength = the mean of the length of all Wall segments. WallDepth = the mean of the depth of all Wall segments. MaxDoorDepth = mu + 1.5*sigma, where miu is the mean of the depth of all Door segments, and sigma is the standard deviation MinWallDepth = mu - 1.5*sigma, where miu is the mean of the depth, (which is typically around 0) of all Wall segments, and sigma is the standard deviation MinDoorLength = mu - 1.5*sigma, where miu is the mean of the length of all Door segments, and sigma is the standard deviation MaxDoorLength = mu + 1.5*sigma, where miu and sigma is similar as above MinWallLength is the lower bound of the length of Wall segments MaxAngle is computed by mu + 1.5*sigma, where miu is the mean of the angle values of all Wall segments, and sigma is the standard deviation //////////numeric parameters definitions end/////////// ////////parameter settings for learning (VP + HMWS) begin///////// number of learning iterations: 100 global learning rate: 1.0 //HMWS settings are same as HMWS inference setting //////////parameter settings for learning (VP + HMWS) end///////// //////////parameter settings for HMCS begin////////////////////// num of HWS steps for each HSS step: 100000 probability of random move for HWS: 0.5 probability of simulated annealing for HSS: 0.4 simulated annealing temperature: 0.5 number of steps of HSS after reaching a solution: 100 number of burn-in steps: 1000 ///////////parameter settings for HMCS end//////////////////////// /////////////parameter settings for MCS begin///////////////////// num of WS steps for each SS step: 100000 probability of random move for WS: 0.5 probability of simulated annealing for SS: 0.5 simulated annealing temperature: 0.5 number of steps of SS after reaching a solution: 100 number of burn-in steps: 1000 /////////////parameter settings for MCS end/////////////////////// //////////parameter settings for SMTP begin//////////////// SMTP number of runs: 3 SMTP number of swapping chains: 10 SMTP chain weight: log distributed, i.e., w, w/k, w/k^2, ..., w/(k^n-1). k is the (n-1)th root of the largest weight initilization for each chain: by MWS for hard clauses number of burn in steps: 1000 ////////////parameter settings for SMTP end/////////////// /////////////parameter settings for Gibbs begin/////////// Gibbs number of chains: 10 initilization for each chain: by MWS for hard clauses Gibbs samples per test: 100 (actually it doesn't matter because the inference never converges during experiments) number of burn-in steps: 1000 /////////////parameter settings for Gibbs end//////////// ///////////parameter settings for HMWS begin//////////// probability of random move: 0.06 max number of flips: 100000 max number of retries: 10 standard deviation for random move of numeric variables: depends on data ///////////parameter settings for HMWS end///////////// ///////////parameter settings for MWS begin//////////// probability of random move: 0.5 max number of flips: 100000 max number of retries: 10 ///////////parameter settings for MWS end///////////// ////////////parameter settings for SA begin/////////// initial temperature: 10 temperature reduction rate: 0.96 number of steps for every temperature reduction: 100 standard deviation of numeric variables for SA proposal distribution: depends on data ////////////parameter settings for SA end////////////