Regression benchmarks

Gallery

ODE loader

ODE loader

import matplotlib.pyplot as plt
import numpy as np

from reg_bench.ode import all_loaders


shear_flow = all_loaders["shear_flow"]()

plt.plot(shear_flow.t, shear_flow.data)
plt.show()

Michaelis Menten Kinetics

Michaelis Menten Kinetics

import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import odeint

import reg_bench.ode


t = np.linspace(0, 10, 5 * 10 ** 2)
x0 = [1, 0]


noise = 0.01

x, dx = reg_bench.ode.generate_ode_data(
    reg_bench.ode.michaelis_menten, x0, t, noise_amplitude=noise, ode_params=dict(rho=1.3)
)

plt.plot(t, x)
plt.show()

Double pendulum

Double pendulum

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Out:

[0, 0, 1, 0]

import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import odeint

import reg_bench.ode


dblpdl = reg_bench.ode.double_pendulum()

dy = dblpdl()
y0 = dblpdl.initial_conditions()
t = np.linspace(0, 10, 5 * 10 ** 3)

print(y0)

s = odeint(dy, y0, t)
for j in range(4):
    plt.figure(j)
    plt.plot(t, s[:, j])

plt.show()

yeast

yeast

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import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import odeint

import reg_bench.ode


yeast = reg_bench.ode.yeast_glycolysis()

dy = yeast()


for i in range(3):
    y0 = yeast.initial_conditions(noise=True)
    t = np.linspace(0, 5, 5 * 10 ** 5)

    s = odeint(dy, y0, t)
    for j in range(3):
        plt.figure(j)
        plt.plot(t, s[:, j])

plt.show()

reg_bench package

Subpackages

reg_bench.maps package

Submodules

reg_bench.maps.maps module

reg_bench.maps.maps.henon(a=1.4, b=0.3)

reg_bench.maps.maps.chirikov(K=1)

reg_bench.maps.maps.logistic(r=3.18)

reg_bench.maps.maps.bogdanov(eps, k, mu)

reg_bench.maps.maps.duffing(a=2.75, b=0.15)

reg_bench.maps.maps.tinkerbell(a=0.9, b=-0.6013, c=2.0, d=0.5)

Module contents

reg_bench.maps.generate_map_data(problem, x0, t, params)

reg_bench.ode package

Submodules

reg_bench.ode.integrate module

reg_bench.ode.integrate.generate_ode_data(problem, x0, t, ode_params=None, noise_amplitude=0, noise_pdf=None, noise_params=None, noise_kind='additive', diff_params=None)

Generate a trajectory and estimate its derivate.

Noise will be added as measurement noise before estimating the derivatives.

Parameters

• problem – ode generator

• x0 – initial conditions

• t – timestamps of the output

• ode_params – kwargs for problem

• noise_kind – proportional or additive

• noise_amplitude – noise amplitude

• noise_pdf – function which generates noise

• noise_params – kwargs passed to noise_pdf

• derive_max_order – maximum order derivative

Returns

trajectory and derivative

Return type

x, dx

reg_bench.ode.integrate.add_measurement_noise(x, noise_amplitude=0, noise_pdf=None, noise_params=None, noise_kind='additive')

Add measurement noise to a trajectory.

reg_bench.ode.not_so_simple_ode module

class reg_bench.ode.not_so_simple_ode.ODE

Bases: object

ode(**params)

property params

class reg_bench.ode.not_so_simple_ode.yeast_glycolysis

Bases: reg_bench.ode.not_so_simple_ode.ODE

As of doi:10.1371/journal.pone.0119821.t002 Table 2

initial_conditions(noise=True, rng=<module 'random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/random.py'>)

property params

10.1371/journal.pone.0119821.t00 Table 1.

Type

As of doi

ode(j0, k1, k2, k3, k4, k5, k6, k, kappa, q, K1, psi, n, a)

Ruoff P, Christensen M, Wolf J, Heinrich R. Temperature dependency and temperature compensation in a model of yeast glycolytic oscillations. Biophys Chem 2003; 106: 179. doi: 10.1016/S0301-4622(03) 00191-1 PMID: 14556906

class reg_bench.ode.not_so_simple_ode.double_pendulum

Bases: reg_bench.ode.not_so_simple_ode.ODE

initial_conditions()

property params

ode(m, l, g)

static get_cartesian_coords(phi1, phi2, l)

reg_bench.ode.simple_ode module

reg_bench.ode.simple_ode.harmonic_oscillator(omega=1.0)

reg_bench.ode.simple_ode.anharmonic_oscillator(omega=1.0, c=1.0, l=1.0)

reg_bench.ode.simple_ode.lorenz(s=10.0, r=28.0, b=2.6666666666666665)

reg_bench.ode.simple_ode.van_der_pol(omega=1.0, a=0.1, b=0.01)

reg_bench.ode.simple_ode.michaelis_menten(vmax=0.25, Km=0.1, rho=1.0)

reg_bench.ode.simple_ode.rössler(a=0.15, b=0.2, c=10.0)

reg_bench.ode.simple_ode.brusselator(a=1.0, b=3.0)

reg_bench.ode.simple_ode.magnets(K=0.25)

reg_bench.ode.simple_ode.predator_prey(a=0.5, b=0.5)

reg_bench.ode.simple_ode.bacterial_respiration(a=0.1, b=0.2, q=1.0)

reg_bench.ode.simple_ode.glider(d=1.0)

reg_bench.ode.simple_ode.shear_flow(a=0.3)

reg_bench.ode.simple_ode.make_bunch(data_config)

reg_bench.ode.simple_ode.make_load(ode, t=array([0.000e+00, 1.000e-02, 2.000e-02, ..., 9.998e+01, 9.999e+01, 1.000e+02]), x0=1)

reg_bench.ode.simple_ode.load_anharmonic_oscillator()

reg_bench.ode.simple_ode.load_bacterial_respiration()

reg_bench.ode.simple_ode.load_brusselator()

reg_bench.ode.simple_ode.load_glider()

reg_bench.ode.simple_ode.load_harmonic_oscillator()

reg_bench.ode.simple_ode.load_lorenz()

reg_bench.ode.simple_ode.load_magnets()

reg_bench.ode.simple_ode.load_michaelis_menten()

reg_bench.ode.simple_ode.load_predator_prey()

reg_bench.ode.simple_ode.load_rössler()

reg_bench.ode.simple_ode.load_shear_flow()

reg_bench.ode.simple_ode.load_van_der_pol()

Module contents

reg_bench.symbolic_regression package

Submodules

reg_bench.symbolic_regression.keijzer module

reg_bench.symbolic_regression.keijzer.keijzer_func4(x)

reg_bench.symbolic_regression.keijzer.keijzer_func5(x)

reg_bench.symbolic_regression.keijzer.keijzer_func6(x, y, z)

reg_bench.symbolic_regression.keijzer.keijzer_func7(x)

reg_bench.symbolic_regression.keijzer.keijzer_func8(x)

reg_bench.symbolic_regression.keijzer.keijzer_func9(x)

reg_bench.symbolic_regression.keijzer.keijzer_func10(x)

reg_bench.symbolic_regression.keijzer.keijzer_func11(x, y)

reg_bench.symbolic_regression.keijzer.keijzer_func12(x, y)

reg_bench.symbolic_regression.keijzer.keijzer_func13(x, y)

reg_bench.symbolic_regression.keijzer.keijzer_func14(x, y)

reg_bench.symbolic_regression.keijzer.keijzer_func15(x, y)

reg_bench.symbolic_regression.keijzer.keijzer_func16(x, y)

reg_bench.symbolic_regression.keijzer._keijzer1_3_helper(step, ranges)

reg_bench.symbolic_regression.keijzer.generate_keijzer1()

reg_bench.symbolic_regression.keijzer.generate_keijzer2()

reg_bench.symbolic_regression.keijzer.generate_keijzer3()

reg_bench.symbolic_regression.keijzer.generate_keijzer4()

reg_bench.symbolic_regression.keijzer.generate_keijzer5(rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.keijzer.generate_keijzer6()

reg_bench.symbolic_regression.keijzer.generate_keijzer7()

reg_bench.symbolic_regression.keijzer.generate_keijzer8()

reg_bench.symbolic_regression.keijzer.generate_keijzer9()

reg_bench.symbolic_regression.keijzer.generate_keijzer10(rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.keijzer._keijzer11_15_helper(func, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.keijzer.generate_keijzer11(*, func=<function keijzer_func12>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.keijzer.generate_keijzer12(*, func=<function keijzer_func13>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.keijzer.generate_keijzer13(*, func=<function keijzer_func14>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.keijzer.generate_keijzer14(*, func=<function keijzer_func15>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns module

reg_bench.symbolic_regression.korns.korns_func1(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func2(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func3(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func4(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func5(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func6(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func7(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func8(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func9(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func10(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func11(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func12(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func13(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func14(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns.korns_func15(x0, x1, x2, x3, x4)

reg_bench.symbolic_regression.korns._korns_helper(func, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns1(*, func=<function korns_func1>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns10(*, func=<function korns_func10>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns11(*, func=<function korns_func11>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns12(*, func=<function korns_func12>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns13(*, func=<function korns_func13>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns14(*, func=<function korns_func14>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns15(*, func=<function korns_func15>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns2(*, func=<function korns_func2>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns3(*, func=<function korns_func3>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns4(*, func=<function korns_func4>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns5(*, func=<function korns_func5>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns6(*, func=<function korns_func6>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns7(*, func=<function korns_func7>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns8(*, func=<function korns_func8>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.korns.generate_korns9(*, func=<function korns_func9>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.koza module

reg_bench.symbolic_regression.koza.koza_func1(x, *, i=4)

reg_bench.symbolic_regression.koza.koza_func2(x)

reg_bench.symbolic_regression.koza.koza_func3(x)

reg_bench.symbolic_regression.koza._koza_helper(func, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.koza.generate_koza1(*, func=functools.partial(<function poly>, i=4), rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.koza.generate_koza2(*, func=<function koza_func2>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.koza.generate_koza3(*, func=<function koza_func3>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen module

reg_bench.symbolic_regression.nguyen.nguyen_func1(x, *, i=3)

reg_bench.symbolic_regression.nguyen.nguyen_func3(x, *, i=5)

reg_bench.symbolic_regression.nguyen.nguyen_func4(x, *, i=6)

reg_bench.symbolic_regression.nguyen.nguyen_func5(x)

reg_bench.symbolic_regression.nguyen.nguyen_func6(x)

reg_bench.symbolic_regression.nguyen.nguyen_func7(x)

reg_bench.symbolic_regression.nguyen.nguyen_func8(x)

reg_bench.symbolic_regression.nguyen.nguyen_func9(x, y)

reg_bench.symbolic_regression.nguyen.nguyen_func10(x, y)

reg_bench.symbolic_regression.nguyen._nguyen1_6_helper(func, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen.generate_nguyen7(rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen.generate_nguyen8(rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen._nguyen9_10_helper(func, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen.generate_nguyen1(*, func=functools.partial(<function poly>, i=3), rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen.generate_nguyen10(*, func=<function nguyen_func10>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen.generate_nguyen3(*, func=functools.partial(<function poly>, i=5), rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen.generate_nguyen4(*, func=functools.partial(<function poly>, i=6), rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen.generate_nguyen5(*, func=<function nguyen_func5>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen.generate_nguyen6(*, func=<function nguyen_func6>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.nguyen.generate_nguyen9(*, func=<function nguyen_func9>, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.pagie module

reg_bench.symbolic_regression.pagie.pagie_func1(x, y)

reg_bench.symbolic_regression.pagie.generate_pagie1()

reg_bench.symbolic_regression.util module

reg_bench.symbolic_regression.util.poly(x, i)

reg_bench.symbolic_regression.util.test_data

alias of reg_bench.symbolic_regression.util.TestData

reg_bench.symbolic_regression.util.generate_data_set(testfunction, num_points, dist, params)

reg_bench.symbolic_regression.util.nd_dist_factory(dist)

reg_bench.symbolic_regression.util.generate_uniform_data_set(testfunction, num_points, ranges, rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.util.isiterable(x)

reg_bench.symbolic_regression.util.generate_evenly_spaced_data_set(testfunction, step_sizes, ranges)

reg_bench.symbolic_regression.util.generator_from_helper(helper, shift=0, i=())

reg_bench.symbolic_regression.vladislavleva module

reg_bench.symbolic_regression.vladislavleva.vladislavleva_func1(x, y)

reg_bench.symbolic_regression.vladislavleva.vladislavleva_func2(x)

reg_bench.symbolic_regression.vladislavleva.vladislavleva_func3(x, y)

reg_bench.symbolic_regression.vladislavleva.vladislavleva_func4(x, y, z, w, v)

reg_bench.symbolic_regression.vladislavleva.vladislavleva_func5(x, y, z)

reg_bench.symbolic_regression.vladislavleva.vladislavleva_func6(x, y)

reg_bench.symbolic_regression.vladislavleva.vladislavleva_func7(x, y)

reg_bench.symbolic_regression.vladislavleva.vladislavleva_func8(x, y)

reg_bench.symbolic_regression.vladislavleva.generate_vladislavleva1(rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.vladislavleva.generate_vladislavleva2()

reg_bench.symbolic_regression.vladislavleva.generate_vladislavleva3()

reg_bench.symbolic_regression.vladislavleva.generate_vladislavleva4(rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.vladislavleva.generate_vladislavleva5(rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.vladislavleva.generate_vladislavleva6(rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.vladislavleva.generate_vladislavleva7(rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

reg_bench.symbolic_regression.vladislavleva.generate_vladislavleva8(rng=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/regression-benchmarks/envs/latest/lib/python3.7/site-packages/numpy/random/__init__.py'>)

Module contents

This module implements all 53 benchmark problems of “GP Needs Better Benchmarks” by McDermott et. al. DOI: 10.1145/2330163.2330273

Submodules

reg_bench.__version__ module

reg_bench.utils module

reg_bench.utils.make_register(dct)

Module contents