def testEvaluateDKappa(self):
"Test vonMisesSufficient.evaluate_derivative_kappa degenerate case"
for i in xrange(100):
randno = [uniform(-4 * pi, 4 * pi), uniform(-pi, pi), uniform(0.1, 100)]
fn = vonMises(*randno)
fn2 = vonMisesSufficient(randno[0], 1, 1, randno[1], randno[2])
self.assertAlmostEqual(fn.evaluate_derivative_kappa(), fn2.evaluate_derivative_kappa(), delta=0.001)
def testDensity(self):
"Test vonMisesSufficient.density degenerate case"
for i in xrange(100):
randno = [uniform(-4 * pi, 4 * pi), uniform(-pi, pi), uniform(0.1, 100)]
fn = vonMises(*randno)
fn2 = vonMisesSufficient(randno[0], 1, 1, randno[1], randno[2])
self.assertAlmostEqual(fn.density(), fn2.density(), delta=0.001)
def testEvaluate(self):
"tests vonMisesSufficient.evaluate"
for i in xrange(100):
randno = [uniform(-4 * pi, 4 * pi), uniform(-pi, pi), uniform(0.1, 100)]
fn = vonMises(*randno)
fn2 = vonMisesSufficient(randno[0], 1, 1, randno[1], randno[2])
self.assertAlmostEqual(fn.evaluate(), fn2.evaluate(), delta=0.001)
def testEvaluateDMu(self):
"tests vonMises.evaluate_derivative_mu"
for i in xrange(100):
randno = [uniform(-4*pi,4*pi), uniform(-pi,pi),
uniform(0.1,100)]
fn=vonMises(*randno)
self.assertAlmostEqual(fn.evaluate_derivative_mu(),
-randno[2]*sin(randno[0]-randno[1]),
delta=0.001)
def testDensity(self):
"Test vonMisesSufficient.density degenerate case"
for i in xrange(100):
randno = [
uniform(-4 * pi, 4 * pi),
uniform(-pi, pi),
uniform(0.1, 100)
]
fn = vonMises(*randno)
fn2 = vonMisesSufficient(randno[0], 1, 1, randno[1], randno[2])
self.assertAlmostEqual(fn.density(), fn2.density(), delta=0.001)
def testEvaluateDMu(self):
"tests vonMises.evaluate_derivative_mu"
for i in xrange(100):
randno = [
uniform(-4 * pi, 4 * pi),
uniform(-pi, pi),
uniform(0.1, 100)
]
fn = vonMises(*randno)
self.assertAlmostEqual(fn.evaluate_derivative_mu(),
-randno[2] * sin(randno[0] - randno[1]),
delta=0.001)
def testEvaluateDKappa(self):
"Test vonMisesSufficient.evaluate_derivative_kappa degenerate case"
for i in xrange(100):
randno = [
uniform(-4 * pi, 4 * pi),
uniform(-pi, pi),
uniform(0.1, 100)
]
fn = vonMises(*randno)
fn2 = vonMisesSufficient(randno[0], 1, 1, randno[1], randno[2])
self.assertAlmostEqual(fn.evaluate_derivative_kappa(),
fn2.evaluate_derivative_kappa(),
delta=0.001)
def testDensity(self):
"tests vonMises.density"
try:
from scipy.special import i0,i1
except ImportError:
self.skipTest("this test requires the scipy Python module")
for i in xrange(100):
randno = [uniform(-4*pi,4*pi), uniform(-pi,pi),
uniform(0.1,100)]
fn=vonMises(*randno)
self.assertAlmostEqual(fn.density(),
exp(randno[2]*cos(randno[0]-randno[1]))/(2*pi*i0(randno[2])),
delta=0.001)
def testEvaluateDKappa(self):
"tests vonMises.evaluate_derivative_kappa"
try:
from scipy.special import i0,i1
except ImportError:
self.skipTest("this test requires the scipy Python module")
for i in xrange(100):
randno = [uniform(-4*pi,4*pi), uniform(-pi,pi),
uniform(0.1,100)]
fn=vonMises(*randno)
self.assertAlmostEqual(fn.evaluate_derivative_kappa(),
i1(randno[2])/i0(randno[2]) - cos(randno[0]-randno[1]),
delta=0.001)
def testEvaluateDKappa(self):
"tests vonMises.evaluate_derivative_kappa"
try:
from scipy.special import i0, i1
except ImportError:
self.skipTest("this test requires the scipy Python module")
for i in xrange(100):
randno = [
uniform(-4 * pi, 4 * pi),
uniform(-pi, pi),
uniform(0.1, 100)
]
fn = vonMises(*randno)
self.assertAlmostEqual(fn.evaluate_derivative_kappa(),
i1(randno[2]) / i0(randno[2]) -
cos(randno[0] - randno[1]),
delta=0.001)
def testEvaluate(self):
"tests vonMises.evaluate"
try:
from scipy.special import i0, i1
except ImportError:
self.skipTest("this test requires the scipy Python module")
for i in range(100):
randno = [
uniform(-4 * pi, 4 * pi),
uniform(-pi, pi),
uniform(0.1, 100)
]
fn = vonMises(*randno)
self.assertAlmostEqual(fn.evaluate(),
log(2 * pi * i0(randno[2])) -
randno[2] * cos(randno[0] - randno[1]),
delta=0.001)