def setUp(self):
xs, ys, wxs, wys = pearson()
exs = wxs**-0.5
eys = wys**-0.5
self.reg = ReedYorkRegressor(xs=xs, ys=ys, xserr=exs, yserr=eys)
self.reg.calculate()
def setUp(self):
xs, ys, wxs, wys = pearson()
exs = wxs ** -0.5
eys = wys ** -0.5
self.reg = ReedYorkRegressor(xs=xs, ys=ys,
xserr=exs,
yserr=eys)
self.reg.calculate()
def test_chi_squared(self):
x, y, wx, wy = pearson()
b = -0.4807
a = 5.4806
ex = 1 / wx ** 0.5
ey = 1 / wy ** 0.5
v = 1.4833
m = calculate_mswd2(x, y, ex, ey, a, b, correlated_errors=True)
self.assertAlmostEqual(m, v, 4)
v = 2.2045
m = calculate_mswd2(x, y, ex, ey, a, b)
self.assertAlmostEqual(m, v, 4)
def test_chi_squared(self):
x, y, wx, wy = pearson()
b = -0.4807
a = 5.4806
ex = 1 / wx**0.5
ey = 1 / wy**0.5
v = 1.4833
m = calculate_mswd2(x, y, ex, ey, a, b, correlated_errors=True)
self.assertAlmostEqual(m, v, 4)
v = 2.2045
m = calculate_mswd2(x, y, ex, ey, a, b)
self.assertAlmostEqual(m, v, 4)
def test_mswd(self):
expected = pearson('reed')
self.assertAlmostEqual(self.reg.mswd, expected['mswd'], 4)
def test_y_intercept(self):
expected = pearson('reed')
self.assertAlmostEqual(self.reg.intercept, expected['intercept'], 4)
def test_slope(self):
exp = pearson('reed')
self.assertAlmostEqual(self.reg.slope, exp['slope'], 4)
def test_mswd(self):
expected = pearson('reed')
self.assertAlmostEqual(self.reg.mswd, expected['mswd'], 4)
def test_y_intercept(self):
expected = pearson('reed')
self.assertAlmostEqual(self.reg.intercept, expected['intercept'], 4)
def test_slope(self):
exp = pearson('reed')
self.assertAlmostEqual(self.reg.slope, exp['slope'], 4)
