Examples

NLP Sampling

This creates the ‘IK’ problem, and shows how to call the default NLP sampler, as well as display and evaluate the samples.

import optsam as op
import numpy as np
import time

def generate_samples(nlp : op.NLP, n):
    solver = op.NLP_Sampler(nlp)
    #solver.setOptions() #access to many options - let's take default
    data = []
    while len(data)<n:
        ret = solver.sample()
        print(ret)
        if ret.feasible:
            data.append(ret.x)
    return np.stack(data)

def display_samples(nlp : op.NLP, data):
    komo = nlp.as_KOMO()
    assert komo is not None, 'this works only for komo problems'
    for x in data:
        phi, J = nlp.evaluate(x)
        err_eq = np.sum(phi[nlp.types==op.OT.eq])
        print('data:', x, '\nphi:', phi, '\nerr:', err_eq)
        komo.view(False, f'data {x}')
        time.sleep(1.)

def main():
    problems = op.get_NLP_Problem_names()
    print('== these are all problems:', problems)

    nlp = op.make_NLP_Problem('IK')
    print('== we pick "IK" as a problem:\n', nlp.report(1), '===')

    data = generate_samples(nlp, 10)
    display_samples(nlp, data)

if __name__ == "__main__":
    main()