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import numpy as np | ||
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from psdr import PolynomialApproximation, PolynomialFunction, LegendreTensorBasis | ||
from checkder import * | ||
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def test_poly_der(dimension = 3, degree = 5): | ||
coef = np.random.randn(len(LegendreTensorBasis(dimension, degree))) | ||
pf = PolynomialFunction(dimension, degree, coef) | ||
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x = np.random.randn(dimension) | ||
print x | ||
print pf.eval(x) | ||
print pf.grad(x) | ||
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assert check_derivative(x, pf.eval, lambda x: pf.grad(x).flatten() ) < 1e-7 | ||
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def test_poly_hess(dimension = 3, degree = 5): | ||
coef = np.random.randn(len(LegendreTensorBasis(dimension, degree))) | ||
pf = PolynomialFunction(dimension, degree, coef) | ||
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x = np.random.randn(dimension) | ||
print x | ||
print pf.eval(x) | ||
print pf.hessian(x) | ||
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assert check_hessian(x, pf.eval, lambda x: pf.hessian(x).reshape(dimension, dimension) ) < 1e-5 |