setup_wing_weight_benchmark

pyapprox.benchmarks.setup_wing_weight_benchmark()[source]

Setup the wing weight model benchmark.

The model is given by

\[f(x) = 0.036\; S_w^{0.758}W_{fw}^{0.0035}\left(\frac{A}{\cos^2(\Lambda)}\right)^{0.6}q^{0.006}\lambda^{0.04}\left(\frac{100t_c}{\cos(\Lambda)}\right)^{-0.3}(N_zW_{dg})^{0.49}+S_wW_p,\]
Returns:
benchmarkBenchmark

Object containing the benchmark attributes documented below

funcallable

The wing weight model with signature

fun(z) -> np.ndarray

where z is a 2D np.ndarray with shape (nvars,nsamples) and the output is a 2D np.ndarray with shape (nsamples,1)

jaccallable

The jacobian of fun with signature

jac(z) -> np.ndarray

where z is a 2D np.ndarray with shape (nvars,nsamples) and the output is a 2D np.ndarray with shape (nvars,1)

variableIndependentMarginalsVariable

Object containing information of the joint density of the inputs z which is the tensor product of independent and identically distributed uniform variables`.

References