-------------DATE OF CREATION:------------- 2019-06-11 16:18:22.771859 -------------COMMON CONFIGURATIONS:------------- path : /home/isarlab/Documenti/Ebrake/e-brake/Data/Dataset betaspace : 35 npointslip : 1000 startslip : 0.0 stopslip : 1.0 subsampling : None windows : 50 focusmin : None focusmax : None noise : 0.005 ncurvvalid : 5 ncurvhid : 5 -------------CUSTOM CONFIGURATIONS:-------------- BETAS(Min,Max) b1:(0.19, 2) b2:(94.93, 6.0) b3:(0.06, 0.7) Generation of Beta Method-> burchkardt_three_sets_linspace: starting from 3 tuples corresponding to the values (min, max) assumed by b1, b2, b3 and from the number of desired points, will be generated three vectors containing the values included between the minimum and the maximum of beta. These 3 vectors are partitioned in other 3 sets of beta for the generation of 3 different scenarios: 'used,validation,hidden'. --------------ROAD SCENARIOS------------- --> USED: N° scenarios:1 Coeff. Model: Burckhardt Annotation: BUR_DIAG_USED # Curves: 25 --> VALIDATION: N° scenarios:1 Coeff. Model: Burckhardt Annotation: BUR_DIAG_VALID # Curves: 5 --> HIDDEN: N° scenarios:1 Coeff. Model: Burckhardt Annotation: BUR_DIAG_HIDD # Curves: 5 ----CSV BUILD CONFIGURATIONS:---- Builder type-> SlidingWindowBestSlip: Starting from a list of road models (curve families) iteratively for each model, each curve is sampled through a sliding window of fixed size (size passed as function argument). The elements present in the window at each step are shuffled. Each step corresponds to one line of the csv, and the size of the window determines the number of features: Len(win)+bestSlip(curve sampled at step n-th): from each the model, from each curve is extracted the value of best slip and linked to the values in the window at step n. Csv: c50e1006_used--> Rows: 23775 Columns: 101 Csv: c50e1006_val--> Rows: 4755 Columns: 101 Csv: c50e1006_hid--> Rows: 4755 Columns: 101