sp-var-dec-heur categorical {0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19}[0]    # Originally, 3,4,9,10 not used following Domagoj's advice. 20 requires modular arithmetic input format
sp-learned-clause-sort-heur categorical {0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19}[0]   # All values make sense here. 20 requires modular arithmetic input format
sp-orig-clause-sort-heur categorical {0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19}[0]   # All values make sense here. 20 requires modular arithmetic input format
sp-res-order-heur categorical {0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19}[0]     # All values make sense here. 20 requires modular arithmetic input format 
sp-clause-del-heur categorical {0,1,2}[2]                         # All values make sense here.
sp-phase-dec-heur categorical {0,1,2,3,4,5,6}[5]                  # All values make sense here. 
sp-resolution categorical {0,1,2}[1]                              # 0 renders a whole bunch of conditionals irrelevant.
sp-variable-decay real [1, 2] [1.4] log                   # Should be bigger than 1 (o/w increase not decay).  Was:  in 1.1,1.4,2.0, def 1.4
sp-clause-decay real [1, 2] [1.4] log                     # Same thing.
sp-restart-inc real [1.1, 1.9] [1.5]                      # Uniform because multiplicative. Was: in 1.1,1.3,1.5,1.7,1.9, def 1.5
sp-learned-size-factor real [0.1, 1.6] [0.4] log          # Uniform on logarithmic scale (starting value). Was: in 0.1,0.2,0.4,0.8,1.6, def 0.4
sp-learned-clauses-inc real [1.1, 1.5] [1.3]              # 1.2 and 1.4 were introduced later. Uniform because multiplicative Was: in1.1,1.2,1.3,1.4,1.5, def 1.3
sp-clause-activity-inc real [0.5, 1.5] [1]                # Was: in 0.5,1,1.5, def 1
sp-var-activity-inc real [0.5, 1.5] [1]                   # Was: in 0.5,1,1.5, def 1
sp-rand-phase-dec-freq ordinal {0, 0.0001, 0.001, 0.005, 0.01, 0.05}[0.001] # Used discretized version to preserve 0. Never picked 0.05 in previous experiments, always zero.
sp-rand-var-dec-freq ordinal {0, 0.0001, 0.001, 0.005, 0.01, 0.05}[0.001]  # Used discretized version to preserve 0. Never picked 0.05 in previous experiments, always zero.
sp-rand-var-dec-scaling real [0.3, 1.1] [1]               # Domagoj said the previous values were too coarse, so finer discretization now.
sp-rand-phase-scaling real [0.3, 1.1] [1]                 # Same thing. Was: in 0.3,0.6,0.9,1,1.1, def 1
sp-max-res-lit-inc real [0.25, 4][1] log                  # 0.5 and 2 were introduced later. Was: in 0.25,0.5,1,2,4, def 1
sp-first-restart integer [25, 3200] [100] log                 # Uniform on logarithmic scale (starting value). Was: in 25,50,100,200,400,800,1600,3200, def 100
sp-res-cutoff-cls integer [2, 20] [8] log                     # Only up to 20 allowed, would've used 32 otherwise.
sp-res-cutoff-lits integer [100, 1600] [400] log              # Was: in 100,200,400,800,1600, def 400
sp-max-res-runs integer [1, 32] [4] log                       # Was: in 1,2,4,8,16,32, def 4
sp-update-dec-queue categorical {0,1}[1]                          # Enable by default.
sp-use-pure-literal-rule categorical {0,1}[1]                     # Enable by default. 
sp-clause-inversion categorical {0,1}[1]                          # Enable by default. Enable reversion of learned clauses if fixed order (sp-learned-clause-sort-heur=19) 

Conditionals:
sp-rand-phase-dec-freq|sp-phase-dec-heur in {0,1,3,4,5,6} # when heuristic is random, then additional random steps don't change anything
sp-rand-var-dec-scaling|sp-rand-var-dec-freq in {0.0001, 0.001, 0.005, 0.01, 0.05}  # not 0
sp-rand-phase-scaling|sp-rand-phase-dec-freq in {0.0001, 0.001, 0.005, 0.01, 0.05}  # not 0
sp-clause-inversion|sp-learned-clause-sort-heur in {19}

sp-res-order-heur|sp-resolution in {1,2}
sp-max-res-lit-inc|sp-resolution in {1,2}
sp-res-cutoff-cls|sp-resolution in {1,2}
sp-res-cutoff-lits|sp-resolution in {1,2}
sp-max-res-runs|sp-resolution in {1,2}