def test_grid_centers():
x = numpy.linspace(-1, 1, 100)
dx = x[1] - x[0]
nx, rng = sampling.grid_npix(rng=[x[0], x[-1]], dx=dx)
centers, _dx = sampling.grid_centers(rng, nx)
assert dx == _dx, 'Bad linear step size'
assert numpy.allclose(centers, x), 'Bad linear borders'
x = numpy.logspace(-1, 1, 100)
dx = numpy.log10(x[1]) - numpy.log10(x[0])
nx, rng = sampling.grid_npix(rng=[x[0], x[-1]], dx=dx, log=True)
centers, _dx = sampling.grid_centers(rng, nx, log=True)
assert dx == _dx, 'Bad logarithmic step size'
assert numpy.allclose(centers, x), 'Bad geometric borders'
def test_grid_npix():
for s in numpy.random.randint(2, high=1000, size=100):
x = numpy.linspace(-1., 1., s)
nx, rng = sampling.grid_npix(rng=[x[0], x[-1]], dx=x[1] - x[0])
assert nx == s, 'Bad number of linear grid points'
assert numpy.allclose(rng, [-1., 1.]), 'Bad linear grid range'
x = numpy.logspace(-1., 1., s)
nx, rng = sampling.grid_npix(rng=[x[0], x[-1]],
dx=numpy.log10(x[1]) - numpy.log10(x[0]),
log=True)
assert nx == s, 'Bad number of logarithmic grid points'
assert numpy.allclose(rng, numpy.power(
10., [-1., 1.])), 'Bad logarithmic grid range'