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e72949b69b* [chore] Stricter ruff rules * [chore] Furture lint rules and removal of flake8 * [ci] Bump github action versions * [chore] Add additional test coverage * Revert RNG switch to np.random.default_rng() Restore use of the global np.random state in pseudo_Obs (misc.py) and the prior id generation (fits.py), keeping seed behavior unchanged. The switch to a module-local generator is out of scope for this lint-focused PR. * Silence NPY002 on intentional legacy np.random calls The RNG migration was reverted to keep np.random.seed() behavior, so add per-line noqa: NPY002 on the three legacy np.random calls instead of the Generator API. * [Fix] Fix exception messages
72 lines
2.3 KiB
Python
72 lines
2.3 KiB
Python
import numpy as np
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import autograd.numpy as anp
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import pyerrors as pe
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def test_integration():
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def f(p, x):
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return p[0] * x + p[1] * x**2 - p[2] / x
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def F(p, x):
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return p[0] * x**2 / 2. + p[1] * x**3 / 3. - anp.log(x) * p[2]
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def check_ana_vs_int(p, l, u, **kwargs):
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numint_full = pe.integrate.quad(f, p, l, u, **kwargs)
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numint = numint_full[0]
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anaint = F(p, u) - F(p, l)
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diff = (numint - anaint)
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if isinstance(numint, pe.Obs):
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numint.gm()
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anaint.gm()
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assert(diff.is_zero())
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else:
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assert(np.isclose(0, diff))
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pobs = np.array([pe.cov_Obs(1., .1**2, '0'), pe.cov_Obs(2., .2**2, '1'), pe.cov_Obs(2.2, .17**2, '2')])
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lobs = pe.cov_Obs(.123, .012**2, 'l')
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uobs = pe.cov_Obs(1., .05**2, 'u')
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check_ana_vs_int(pobs, lobs, uobs)
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check_ana_vs_int(pobs, lobs.value, uobs)
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check_ana_vs_int(pobs, lobs, uobs.value)
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check_ana_vs_int(pobs, lobs.value, uobs.value)
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for i in range(len(pobs)):
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p = [pi for pi in pobs]
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p[i] = pobs[i].value
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check_ana_vs_int(p, lobs, uobs)
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check_ana_vs_int([pi.value for pi in pobs], lobs, uobs)
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check_ana_vs_int([pi.value for pi in pobs], lobs.value, uobs.value)
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check_ana_vs_int(pobs, lobs, uobs, epsabs=1.e-9, epsrel=1.236e-10, limit=100)
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assert(len(pe.integrate.quad(f, pobs, lobs, uobs, full_output=True)) > 2)
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r1, _ = pe.integrate.quad(F, pobs, 1, 0.1)
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r2, _ = pe.integrate.quad(F, pobs, 0.1, 1)
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assert r1 == -r2
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iamzero, _ = pe.integrate.quad(F, pobs, 1, 1)
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assert iamzero == 0
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def test_integrate_per_parameter_derivatives():
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# \int_0^1 p0*x + p1*x^2 dx = p0/2 + p1/3
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# If the lambda closure in integrate.quad failed to bind `i` per-iteration,
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# all per-parameter derivatives would collapse to a single value.
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def f(p, x):
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return p[0] * x + p[1] * x ** 2
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p = [pe.cov_Obs(1.0, 0.1 ** 2, "p0"), pe.cov_Obs(2.0, 0.2 ** 2, "p1")]
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res, _ = pe.integrate.quad(f, p, 0.0, 1.0)
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res.gm()
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ana_val = p[0].value / 2 + p[1].value / 3
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assert np.isclose(res.value, ana_val)
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grad0 = res.covobs["p0"].grad.item()
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grad1 = res.covobs["p1"].grad.item()
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assert np.isclose(grad0, 0.5)
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assert np.isclose(grad1, 1.0 / 3.0)
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assert not np.isclose(grad0, grad1)
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