def testTwo(self):
data = loglikelihood.llr(numpy.matrix([[1, 1], [1, 2]]))
expected = 0.372079209422
if int(data * 100000) != int(
expected * 100000): # Stupid float precision
print data
self.fail()
def testFour(self):
data = loglikelihood.llr(numpy.matrix([[10, 1], [1, 100000]]))
expected = 13.8131907646
if int(data*100000) != int(expected*100000): # Stupid float precision
self.fail()
def testThree(self):
data = loglikelihood.llr(numpy.matrix([[1, 1], [1, 10000]]))
expected = 3.85696813782
if int(data*100000) != int(expected*100000): # Stupid float precision
self.fail()
def testTwo(self):
data = loglikelihood.llr(numpy.matrix([[1, 1], [1, 2]]))
expected = 0.372079209422
if int(data*100000) != int(expected*100000): # Stupid float precision
print data
self.fail()
def testOne(self):
data = loglikelihood.llr(numpy.matrix([[13, 1000], [1000, 100000]]))
expected = 0.896523808514
if int(data*100000) != int(expected*100000): # Stupid float precision
self.fail()
def testFour(self):
data = loglikelihood.llr(numpy.matrix([[10, 1], [1, 100000]]))
expected = 13.8131907646
if int(data * 100000) != int(
expected * 100000): # Stupid float precision
self.fail()
def testThree(self):
data = loglikelihood.llr(numpy.matrix([[1, 1], [1, 10000]]))
expected = 3.85696813782
if int(data * 100000) != int(
expected * 100000): # Stupid float precision
self.fail()
def testOne(self):
data = loglikelihood.llr(numpy.matrix([[13, 1000], [1000, 100000]]))
expected = 0.896523808514
if int(data * 100000) != int(
expected * 100000): # Stupid float precision
self.fail()
