def test_n():
sph = Sphere(par(.5), 1.6, (5,5,5))
sch = ImageSchema(shape=[100, 100], spacing=[0.1, 0.1],
optics=Optics(wavelen=0.66,
index=1.33,
polarization=[1, 0],
divergence=0.0),
origin=[0.0, 0.0, 0.0])
model = Model(sph, Mie.calc_holo, alpha=1)
holo = Mie.calc_holo(model.scatterer.guess, sch)
coster = CostComputer(holo, model, use_random_fraction=.1)
assert_allclose(coster.flattened_difference({'n' : .5}), 0)
def test_n():
sph = Sphere(par(.5), 1.6, (5,5,5))
sch = ImageSchema(shape=[100, 100], spacing=[0.1, 0.1],
optics=Optics(wavelen=0.66,
index=1.33,
polarization=[1, 0],
divergence=0.0),
origin=[0.0, 0.0, 0.0])
model = Model(sph, Mie.calc_holo, alpha=1)
holo = Mie.calc_holo(model.scatterer.guess, sch)
coster = CostComputer(holo, model, random_subset=.1)
assert_allclose(coster.flattened_difference({'n' : .5}), 0)
def test_constraint():
sch = ImageSchema(100)
with warnings.catch_warnings():
# TODO: we should really only supress overlap warnings here,
# but I am too lazy to figure it out right now, and I don't
# think we are likely to hit warnings here that won't get
# caught elsewhere -tgd 2013-12-01
warnings.simplefilter("ignore")
spheres = Spheres([Sphere(r=.5, center=(0,0,0)),
Sphere(r=.5, center=(0,0,par(.2)))])
model = Model(spheres, Multisphere.calc_holo, constraints=limit_overlaps())
coster = CostComputer(sch, model)
cost = coster._calc({'1:Sphere.center[2]' : .2})
assert_equal(cost, np.ones_like(sch)*np.inf)
def test_constraint():
sch = ImageSchema(100)
with warnings.catch_warnings():
# TODO: we should really only supress overlap warnings here,
# but I am too lazy to figure it out right now, and I don't
# think we are likely to hit warnings here that won't get
# caught elsewhere -tgd 2013-12-01
warnings.simplefilter("ignore")
spheres = Spheres([Sphere(r=.5, center=(0,0,0)),
Sphere(r=.5, center=(0,0,par(.2)))])
model = Model(spheres, Multisphere.calc_holo, constraints=limit_overlaps())
coster = CostComputer(sch, model)
cost = coster._calc({'1:Sphere.center[2]' : .2})
assert_equal(cost, np.ones_like(sch)*np.inf)
