def test_fit_normal_dict():
fit_ = st.fit(NORMAL, "norm")
d = st.fit_results_to_dict(fit_, min_bound=-123, max_bound=123)
nt.assert_almost_equal(d["mu"], NORMAL_MU, 1)
nt.assert_almost_equal(d["sigma"], NORMAL_SIGMA, 1)
nt.assert_almost_equal(d["min"], -123, 1)
nt.assert_almost_equal(d["max"], 123, 1)
def test_fit_normal_dict():
fit_ = st.fit(NORMAL, 'norm')
d = st.fit_results_to_dict(fit_, min_bound=-123, max_bound=123)
nt.assert_almost_equal(d['mu'], NORMAL_MU, 1)
nt.assert_almost_equal(d['sigma'], NORMAL_SIGMA, 1)
nt.assert_almost_equal(d['min'], -123, 1)
nt.assert_almost_equal(d['max'], 123, 1)
def test_fit_normal_dict():
fit_ = st.fit(NORMAL, 'norm')
d = st.fit_results_to_dict(fit_, min_bound=-123, max_bound=123)
assert_almost_equal(d['mu'], NORMAL_MU, 1)
assert_almost_equal(d['sigma'], NORMAL_SIGMA, 1)
assert_almost_equal(d['min'], -123, 1)
assert_almost_equal(d['max'], 123, 1)
def test_fit_default_is_normal():
fit0_ = st.fit(NORMAL)
fit1_ = st.fit(NORMAL, 'norm')
nt.eq_(fit0_.params, fit1_.params)
nt.eq_(fit0_.errs, fit1_.errs)
def test_fit_normal_regression():
fit_ = st.fit(NORMAL, 'norm')
nt.assert_almost_equal(fit_.params[0], 10.019332055822, 12)
nt.assert_almost_equal(fit_.params[1], 0.978726207747, 12)
nt.assert_almost_equal(fit_.errs[0], 0.021479979161, 12)
nt.assert_almost_equal(fit_.errs[1], 0.745431659944, 12)
def test_fit_normal_params():
fit_ = st.fit(NORMAL, 'norm')
nt.assert_almost_equal(fit_.params[0], NORMAL_MU, 1)
nt.assert_almost_equal(fit_.params[1], NORMAL_SIGMA, 1)
def test_fit_default_is_normal():
fit0_ = st.fit(NORMAL)
fit1_ = st.fit(NORMAL, 'norm')
nt.assert_items_equal(fit0_.params, fit1_.params)
nt.assert_items_equal(fit0_.errs, fit1_.errs)
def test_fit_default_is_normal():
fit0_ = st.fit(NORMAL)
fit1_ = st.fit(NORMAL, 'norm')
assert fit0_.params == fit1_.params
assert fit0_.errs == fit1_.errs
def test_fit_normal_regression():
fit_ = st.fit(NORMAL, 'norm')
assert_almost_equal(fit_.params[0], 10.019332055822, 12)
assert_almost_equal(fit_.params[1], 0.978726207747, 12)
assert_almost_equal(fit_.errs[0], 0.021479979161, 12)
assert_almost_equal(fit_.errs[1], 0.7369569123250506, 12)
def test_fit_normal_params():
fit_ = st.fit(NORMAL, 'norm')
assert_almost_equal(fit_.params[0], NORMAL_MU, 1)
assert_almost_equal(fit_.params[1], NORMAL_SIGMA, 1)
def test_fit_default_is_normal():
fit0_ = st.fit(NORMAL)
fit1_ = st.fit(NORMAL, 'norm')
nt.eq_(fit0_.params, fit1_.params)
nt.eq_(fit0_.errs, fit1_.errs)
def test_fit_normal_regression():
fit_ = st.fit(NORMAL, 'norm')
nt.assert_almost_equal(fit_.params[0], 10.019332055822, 12)
nt.assert_almost_equal(fit_.params[1], 0.978726207747, 12)
nt.assert_almost_equal(fit_.errs[0], 0.021479979161, 12)
nt.assert_almost_equal(fit_.errs[1], 0.745431659944, 12)
def test_fit_default_is_normal():
fit0_ = st.fit(NORMAL)
fit1_ = st.fit(NORMAL, 'norm')
nt.assert_items_equal(fit0_.params, fit1_.params)
nt.assert_items_equal(fit0_.errs, fit1_.errs)
