def testCar1Defaults(self):
cppSample = carmcmc.run_mcmc_car1(self.nSample, self.nBurnin,
self.xdata, self.ydata, self.dydata)
cppSample = carmcmc.run_mcmc_car1(self.nSample, self.nBurnin,
self.xdata, self.ydata, self.dydata,
self.nThin)
guess = cppSample.getSamples()[0]
cppSample = carmcmc.run_mcmc_car1(self.nSample, self.nBurnin,
self.xdata, self.ydata, self.dydata,
self.nThin, guess)
def doit(args):
pModel = int(args[0])
x, y, dy = args[1]
nSample = 10000
nBurnin = 1000
nThin = 1
nWalkers = 10
# Should not have to do this...
xv = carmcmc.vecD()
xv.extend(x)
yv = carmcmc.vecD()
yv.extend(y)
dyv = carmcmc.vecD()
dyv.extend(dy)
if pModel == 1:
sampler = carmcmc.run_mcmc_car1(nSample, nBurnin, xv, yv, dyv, nWalkers, nThin)
samplep = carmcmc.CarSample1(x, y, dy, sampler)
else:
sampler = carmcmc.run_mcmc_carma(nSample, nBurnin, xv, yv, dyv, pModel, 0, nWalkers, False, nThin)
samplep = carmcmc.CarmaSample(x, y, dy, sampler)
dic = samplep.DIC()
print "DIC", pModel, dic
return samplep
def testCar1(self):
cppSample = carmcmc.run_mcmc_car1(self.nSample, self.nBurnin, self.xdata, self.ydata, self.dydata, self.nThin)
psampler = carmcmc.Car1Sample(self.x, self.y, self.dy, cppSample)
self.assertEqual(psampler.p, 1)
psamples = np.array(cppSample.getSamples())
ploglikes = np.array(cppSample.GetLogLikes())
sample0 = carmcmc.vecD()
sample0.extend(psamples[0])
logprior0 = cppSample.getLogPrior(sample0)
loglike0 = cppSample.getLogDensity(sample0)
self.assertAlmostEqual(ploglikes[0], loglike0)
def testCar1(self):
cppSample = carmcmc.run_mcmc_car1(self.nSample, self.nBurnin,
self.xdata, self.ydata, self.dydata,
self.nThin)
psampler = carmcmc.Car1Sample(self.x, self.y, self.dy, cppSample)
self.assertEqual(psampler.p, 1)
psamples = np.array(cppSample.getSamples())
ploglikes = np.array(cppSample.GetLogLikes())
sample0 = carmcmc.vecD()
sample0.extend(psamples[0])
logprior0 = cppSample.getLogPrior(sample0)
loglike0 = cppSample.getLogDensity(sample0)
self.assertAlmostEqual(ploglikes[0], loglike0)
def testCar1Defaults(self):
cppSample = carmcmc.run_mcmc_car1(self.nSample, self.nBurnin, self.xdata, self.ydata, self.dydata)
cppSample = carmcmc.run_mcmc_car1(self.nSample, self.nBurnin, self.xdata, self.ydata, self.dydata, self.nThin)
guess = cppSample.getSamples()[0]
cppSample = carmcmc.run_mcmc_car1(self.nSample, self.nBurnin, self.xdata, self.ydata, self.dydata, self.nThin, guess)
