def test_hlog_inv(self):
expected = _xall
result = trans.hlog_inv(trans.hlog(_xall))
d = (result - expected) / expected
assert_almost_equal(d, np.zeros(len(d)), decimal=2)
result = trans.hlog_inv(trans.hlog(_xall, b=10), b=10)
d = (result - expected) / expected
assert_almost_equal(d, np.zeros(len(d)), decimal=2)
def test_hlog_inv(self):
expected = _xall
result = trans.hlog_inv(trans.hlog(_xall))
d = (result - expected) / expected
assert_almost_equal(d, np.zeros(len(d)), decimal=2)
result = trans.hlog_inv(trans.hlog(_xall, b=10), b=10)
d = (result - expected) / expected
assert_almost_equal(d, np.zeros(len(d)), decimal=2)
def test_hlog(self):
hlpos = trans.hlog(_xpos)
hlneg = trans.hlog(_xneg)
assert_almost_equal((hlpos[-1] - _ymax) / _ymax, 0, decimal=2)
assert_almost_equal(hlpos, -hlneg[::-1]) # check symmetry
# test that values get larger as b decreases
hlpos10 = trans.hlog(_xpos, b=10)
self.assertTrue(np.all(hlpos10 >= hlpos))
# check that converges to tlog for large values
tlpos = trans.tlog(_xpos)
i = np.where(_xpos > 1e4)[0]
tlpos_large = tlpos[i]
hlpos_large = hlpos10[i]
d = (hlpos_large - tlpos_large) / hlpos_large
assert_almost_equal(d, np.zeros(len(d)), decimal=2)
# test spline option
result1 = trans.hlog(_xall, use_spln=True)
result2 = trans.hlog(_xall, use_spln=False)
d = (result1 - result2) / result1
assert_almost_equal(d, np.zeros(len(d)), decimal=2)
def test_hlog(self):
hlpos = trans.hlog(_xpos)
hlneg = trans.hlog(_xneg)
assert_almost_equal((hlpos[-1] - _ymax) / _ymax, 0, decimal=2)
assert_almost_equal(hlpos, -hlneg[::-1]) # check symmetry
# test that values get larger as b decreases
hlpos10 = trans.hlog(_xpos, b=10)
self.assertTrue(np.all(hlpos10 >= hlpos))
# check that converges to tlog for large values
tlpos = trans.tlog(_xpos)
i = np.where(_xpos > 1e4)[0]
tlpos_large = tlpos[i]
hlpos_large = hlpos10[i]
d = (hlpos_large - tlpos_large) / hlpos_large
assert_almost_equal(d, np.zeros(len(d)), decimal=2)
# test spline option
transformation = Transformation(transform='hlog', direction='forward')
result1 = transformation(_xall, use_spln=True)
result2 = transformation(_xall, use_spln=False)
d = (result1 - result2) / result1
assert_almost_equal(d, np.zeros(len(d)), decimal=2)
