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()