gistfile1.txt

import numpy as np

import openmdao.api as om
from openmdao.components.interp_util.interp_semi import InterpNDSemi

grid = np.array([
    [1.0, 5.0, 8.0],
    [1.0, 5.0, 9.0],
    [1.0, 5.0, 10.0],
    [1.0, 5.0, 20.0],
    [1.0, 5.3, 8.0],
    [1.0, 5.3, 9.0],
    [1.0, 5.3, 10.0],
    [1.0, 5.3, 20.0],
    [1.0, 5.6, 8.0],
    [1.0, 5.6, 9.0],
    [1.0, 5.6, 10.0],
    [1.0, 5.6, 20.0],
    [1.0, 6.0, 8.0],
    [1.0, 6.0, 9.0],
    [1.0, 6.0, 10.0],
    [1.0, 6.0, 20.0],
    [2.0, 7.0, 13.0],
    [2.0, 7.0, 14.0],
    [2.0, 7.0, 15.0],
    [2.0, 7.0, 16.0],
    [2.0, 8.0, 13.0],
    [2.0, 8.0, 14.0],
    [2.0, 8.0, 15.0],
    [2.0, 8.0, 16.0],
    [2.0, 8.5, 13.0],
    [2.0, 8.5, 14.0],
    [2.0, 8.5, 15.0],
    [2.0, 8.5, 16.0],
    [2.0, 9.0, 13.0],
    [2.0, 9.0, 14.0],
    [2.0, 9.0, 15.0],
    [2.0, 9.0, 16.0],
])

values = 15.0 + 2 * np.random.random(32)

prob = om.Problem()
model = prob.model

interp = om.MetaModelSemiStructuredComp(vec_size=3, training_data_gradients=True)
interp.add_input('x')
interp.add_input('y')
interp.add_input('z')
interp.add_output('f', grid_points=grid, training_data=values)

model.add_subsystem('interp', interp)

prob.setup(force_alloc_complex=True)

prob.set_val('interp.x', np.array([1.1, 1.5, 1.9]))
prob.set_val('interp.y', np.array([5.1, 6.5, 8.75]))
prob.set_val('interp.z', np.array([18.5, 11.0, 15.1]))

prob.run_model()

print(prob.get_val('interp.f'))
print('done')