def integrated_autocorr4r(x):
r.require('coda')
# r.assign('x', x)
# print(r('spectrum0(x, max.freq=0.1)'))
# print(r('spectrum0(x, max.freq=0.5)'))
# print(r('spectrum0(x, max.freq=0.5)'))
value = r['spectrum0'](x)[0][0] / np.var(x, ddof=1)
return value
def test_1():
x = generate_AR1(0.95, 1, 50**2+25, random_state=0)
val = integrated_autocorr5(x, size='sqrt')[0]
r.require('batchmeans')
r.assign('x', x)
ref = r('(bm(x)$se)^2 * length(x) / var(x)')[0]
np.testing.assert_almost_equal(val, ref)
def test_1():
y = generate_AR1(0.95, 1, 10000)
tau = integrated_autocorr3(y)
r.require('mcmc')
r.assign('x', y)
r('popvar = (var(x)*(nrow(x)-1)/nrow(x))')
r('init = initseq(x)')
tau_ref = r('initseq(x)$var.pos / popvar')[0]
print(tau, tau_ref)
np.testing.assert_array_almost_equal(tau, tau_ref)
def plot(self, hardcopy=None):
if hardcopy:
R.png(hardcopy, width=1024, height=768, type="cairo")
R.require('qvalue')
# build a qobj
R.assign("pval", self.mPValues)
R.assign("pi0", self.mPi0)
R.assign("qval", self.mQValues)
R.assign("lambda", self.mLambda)
R("""qobj <-list( pi0=pi0, qvalues=qval, pvalues=pval, lambda=lambda)""")
R(""" class(qobj) <- "qvalue" """)
R("""qplot(qobj)""")
if hardcopy:
R.dev_off()
def plot(self, hardcopy=None):
if hardcopy:
R.png(hardcopy, width=1024, height=768, type="cairo")
R.require('qvalue')
# build a qobj
R.assign("pval", self.mPValues)
R.assign("pi0", self.mPi0)
R.assign("qval", self.mQValues)
R.assign("lambda", self.mLambda)
R("""qobj <-list( pi0=pi0, qvalues=qval, pvalues=pval, lambda=lambda)""")
R(""" class(qobj) <- "qvalue" """)
R("""qplot(qobj)""")
if hardcopy:
R.dev_off()
def install_package(package, upgrade=False, force=False):
if not upgrade:
exists = r.suppressPackageStartupMessages(r.require(package))[0]
if exists:
print("SKIPPING ", package)
return
utils = rpackages.importr('utils')
utils.chooseCRANmirror(ind=1)
print("INSTALLING ", package, "; force=", force)
utils.install_packages(package, force=force)
def setup():
r("install.packages('batchmeans', repos='http://cran.us.r-project.org')")
r.require('batchmeans')
def setup():
r("install.packages('mcmc', repos='http://cran.us.r-project.org')")
r.require('mcmc')
