def test_overlay_chain_distribution_integrates_to_1(self):
"""Overlays integrate to 1"""
m = ddm.Model(name="Overlay_test",
drift=ddm.DriftConstant(drift=2),
T_dur=5,
overlay=ddm.OverlayChain(overlays=[
ddm.OverlayPoissonMixture(pmixturecoef=.2, rate=2),
ddm.OverlayUniformMixture(umixturecoef=.2),
ddm.OverlayNonDecision(nondectime=.2)
]))
s = m.solve()
distsum = s.prob_correct() + s.prob_error()
assert .99 < distsum < 1.0001, "Distribution doesn't sum to 1"
dipparam=dipparam,
),
noise=NoiseDip(
noise=noise,
t1=t1,
t1slope=t1slope,
dipstart=dipstart,
dipstop=dipstop,
diptype=diptype,
),
IC=ICPoint(x0=x0),
bound=BoundDip(B=1,
dipstart=dipstart,
dipstop=dipstop,
diptype=diptype),
overlay=ddm.OverlayChain(overlays=[
ddm.OverlayNonDecision(nondectime=nondectime),
OverlayDipRatio(detect=detect, diptype=diptype),
ddm.OverlayPoissonMixture(pmixturecoef=pmixturecoef, rate=rate)
]),
dx=0.002,
dt=0.002,
T_dur=3.0)
# END demo
ddm.plot.model_gui(model=m,
conditions={
"coherence": [50, 53, 60, 70],
"presample": [0, 400, 800],
"highreward": [0, 1]
})