metadata:
  name: poly
  version: 1
  description: Poly suite incl. Poly-10.
  sources:
  - Poli 2003 lineage (via DSO aggregation)
  - formulas + ranges from dso-org/deep-symbolic-optimization benchmarks.csv (BSD-3;
    Petersen et al. 2021, Mundhenk et al. 2021)
  sampling_defaults:
    n_points: 20
    method: random
    noise: 0.0
  source_kind: set
  conventions:
    sampling: vars use the `fastsrb` distribution (sample_range/sample_type); DSO
      train_spec ranges; evenly-spaced (E) upstream grids are sampled uniformly here
      (noted per entry as meta.dso_spec).
    validity: 'accepted points follow the declared per-variable distribution CONDITIONED
      on the expression''s valid domain; meta.finite_fraction is the MC-estimated
      per-point valid fraction (n=20000); entries below 0.05 carry low_validity: true
      and need per-entry review.'
expressions:
  Poly-10:
    raw: x1*x2+x3*x4+x5*x6+x1*x7*x9+x3*x6*x10
    prepared: v1*v2+v3*v4+v5*v6+v1*v7*v9+v3*v6*v10
    n_variables: 10
    sources:
    - Poli 2003 lineage (via DSO aggregation)
    - formulas + ranges from dso-org/deep-symbolic-optimization benchmarks.csv (BSD-3;
      Petersen et al. 2021, Mundhenk et al. 2021)
    vars:
      v1:
        name: x1
        sample_range:
        - 0.0
        - 1.0
        sample_type:
        - uni
        - pos
      v2:
        name: x2
        sample_range:
        - 0.0
        - 1.0
        sample_type:
        - uni
        - pos
      v3:
        name: x3
        sample_range:
        - 0.0
        - 1.0
        sample_type:
        - uni
        - pos
      v4:
        name: x4
        sample_range:
        - 0.0
        - 1.0
        sample_type:
        - uni
        - pos
      v5:
        name: x5
        sample_range:
        - 0.0
        - 1.0
        sample_type:
        - uni
        - pos
      v6:
        name: x6
        sample_range:
        - 0.0
        - 1.0
        sample_type:
        - uni
        - pos
      v7:
        name: x7
        sample_range:
        - 0.0
        - 1.0
        sample_type:
        - uni
        - pos
      v8:
        name: x8
        sample_range:
        - 0.0
        - 1.0
        sample_type:
        - uni
        - pos
      v9:
        name: x9
        sample_range:
        - 0.0
        - 1.0
        sample_type:
        - uni
        - pos
      v10:
        name: x10
        sample_range:
        - 0.0
        - 1.0
        sample_type:
        - uni
        - pos
      v0:
        name: y
    meta:
      dso_spec:
        train:
          all:
            U:
            - 0
            - 1
            - 330
        test:
          all:
            U:
            - 0
            - 1
            - 170
        function_set: None
      finite_fraction: 1.0
  Poly-1:
    raw: x2/sqrt(pow(x1,2)+pow(x2,2)+pow(x3,2))
    prepared: v2/sqrt(((v1)**(2))+((v2)**(2))+((v3)**(2)))
    n_variables: 3
    sources:
    - Poli 2003 lineage (via DSO aggregation)
    - formulas + ranges from dso-org/deep-symbolic-optimization benchmarks.csv (BSD-3;
      Petersen et al. 2021, Mundhenk et al. 2021)
    vars:
      v1:
        name: x1
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v2:
        name: x2
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v3:
        name: x3
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v0:
        name: y
    meta:
      dso_spec:
        train:
          all:
            U:
            - 0.0
            - 3.0
            - 100
        test:
          all:
            U:
            - 0.0
            - 3.0
            - 30
        function_set: PKozaPlusSqrt
      finite_fraction: 1.0
  Poly-2:
    raw: pow(x1,3)+pow(x1,2)+x1+sin(x1)+sin(pow(x2,2))
    prepared: ((v1)**(3))+((v1)**(2))+v1+sin(v1)+sin(((v2)**(2)))
    n_variables: 2
    sources:
    - Poli 2003 lineage (via DSO aggregation)
    - formulas + ranges from dso-org/deep-symbolic-optimization benchmarks.csv (BSD-3;
      Petersen et al. 2021, Mundhenk et al. 2021)
    vars:
      v1:
        name: x1
        sample_range:
        - -1.0
        - 1.0
        sample_type:
        - uni
        - pos
      v2:
        name: x2
        sample_range:
        - -1.0
        - 1.0
        sample_type:
        - uni
        - pos
      v0:
        name: y
    meta:
      dso_spec:
        train:
          all:
            U:
            - -1
            - 1
            - 20
        test: null
        function_set: PKoza
      finite_fraction: 1.0
  Poly-3:
    raw: cos(x2)/(sqrt(12*x1*x2+1.3+x1-0.05*pow(x2,2))+x1)
    prepared: cos(v2)/(sqrt(12*v1*v2+1.3+v1-0.05*((v2)**(2)))+v1)
    n_variables: 2
    sources:
    - Poli 2003 lineage (via DSO aggregation)
    - formulas + ranges from dso-org/deep-symbolic-optimization benchmarks.csv (BSD-3;
      Petersen et al. 2021, Mundhenk et al. 2021)
    vars:
      v1:
        name: x1
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v2:
        name: x2
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v0:
        name: y
    meta:
      dso_spec:
        train:
          all:
            U:
            - 0.0
            - 3.0
            - 100
        test:
          all:
            U:
            - 0.0
            - 3.0
            - 30
        function_set: PKozaPlusSqrt
      finite_fraction: 1.0
  Poly-4:
    raw: sin(x4)/(sqrt(12*x1*x2+1.3-0.05*x3*x6*x10)*exp(x7))
    prepared: sin(v4)/(sqrt(12*v1*v2+1.3-0.05*v3*v6*v10)*exp(v7))
    n_variables: 10
    sources:
    - Poli 2003 lineage (via DSO aggregation)
    - formulas + ranges from dso-org/deep-symbolic-optimization benchmarks.csv (BSD-3;
      Petersen et al. 2021, Mundhenk et al. 2021)
    vars:
      v1:
        name: x1
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v2:
        name: x2
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v3:
        name: x3
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v4:
        name: x4
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v5:
        name: x5
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v6:
        name: x6
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v7:
        name: x7
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v8:
        name: x8
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v9:
        name: x9
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v10:
        name: x10
        sample_range:
        - 0.0
        - 3.0
        sample_type:
        - uni
        - pos
      v0:
        name: y
    meta:
      dso_spec:
        train:
          all:
            U:
            - 0.0
            - 3.0
            - 330
        test:
          all:
            U:
            - 0.0
            - 3.0
            - 170
        function_set: PKozaPlusSqrt
      finite_fraction: 1.0
  Poly-5:
    raw: sin(pow(x1,3)-x1-pi/6)
    prepared: sin(((v1)**(3))-v1-3.141592653589793/6)
    n_variables: 1
    sources:
    - Poli 2003 lineage (via DSO aggregation)
    - formulas + ranges from dso-org/deep-symbolic-optimization benchmarks.csv (BSD-3;
      Petersen et al. 2021, Mundhenk et al. 2021)
    vars:
      v1:
        name: x1
        sample_range:
        - -3.14
        - 3.14
        sample_type:
        - uni
        - pos
      v0:
        name: y
    meta:
      dso_spec:
        train:
          all:
            U:
            - -3.14
            - 3.14
            - 20
        test: null
        function_set: CPKoza
      finite_fraction: 1.0