def test_harmonize_linear_interpolation():
df = _df.copy()
hist = _hist.copy()
methods = _methods.copy()
h = harmonize.Harmonizer(df, hist)
methods['method'] = ['linear_interpolate_2060'] * nvals
res = h.harmonize(overrides=methods['method'])
# base year
obs = res['2015']
exp = _hist['2015']
npt.assert_array_almost_equal(obs, exp)
# future year
x1, x2, x = '2015', '2060', '2040'
y1, y2 = _hist[x1], _df[x2]
m = (y2 - y1) / (float(x2) - float(x1))
b = y1 - m * float(x1)
obs = res[x]
exp = m * float(x) + b
npt.assert_array_almost_equal(obs, exp)
# year after interp
obs = res['2060']
exp = _df['2060']
npt.assert_array_almost_equal(obs, exp)
def test_harmonize_reduce_ratio():
df = _df.copy()
hist = _hist.copy()
methods = _methods.copy()
h = harmonize.Harmonizer(df, hist)
# this is bad, there should be a test for each case
for tf in [2050, 2100, 2150]:
print(tf)
method = 'reduce_ratio_{}'.format(tf)
methods['method'] = [method] * nvals
res = h.harmonize(overrides=methods['method'])
# base year
obs = res['2015']
exp = _hist['2015']
npt.assert_array_almost_equal(obs, exp)
# future year
obs = res['2040']
ratio = _hist['2015'] / _df['2015']
exp = _df['2040'] * (ratio + _t_frac(tf) * (1 - ratio))
npt.assert_array_almost_equal(obs, exp)
# future year
if tf < 2060:
obs = res['2060']
exp = _df['2060']
npt.assert_array_almost_equal(obs, exp)
def test_harmonize_budget():
df = _df.copy()
hist = _hist.copy()
methods = _methods.copy()
h = harmonize.Harmonizer(df, hist)
methods['method'] = 'budget'
res = h.harmonize(overrides=methods['method'])
# base year
obs = res['2015']
exp = _hist['2015']
npt.assert_array_almost_equal(obs, exp)
# carbon budget conserved
def _carbon_budget(emissions):
# trapezoid rule
dyears = np.diff(emissions.columns.astype(int))
emissions = emissions.values
demissions = np.diff(emissions, axis=1)
budget = (dyears * (emissions[:, :-1] + demissions / 2)).sum(axis=1)
return budget
npt.assert_array_almost_equal(
_carbon_budget(res),
_carbon_budget(df) - _carbon_budget(hist.loc[:, '2010':'2015']),
)
def test_harmonize_constant_offset():
df = _df.copy()
hist = _hist.copy()
methods = _methods.copy()
h = harmonize.Harmonizer(df, hist)
res = h.harmonize(overrides=methods['method'])
# base year
obs = res['2015']
exp = _hist['2015']
npt.assert_array_almost_equal(obs, exp)
# future year
obs = res['2060']
exp = _df['2060'] + (_hist['2015'] - _df['2015'])
npt.assert_array_almost_equal(obs, exp)
def test_harmonize_mix():
df = _df.copy()
hist = _hist.copy()
methods = _methods.copy()
h = harmonize.Harmonizer(df, hist)
methods['method'] = ['constant_offset'] * nvals
res = h.harmonize(overrides=methods['method'])
# base year
obs = res['2015']
exp = _hist['2015']
npt.assert_array_almost_equal(obs, exp)
# future year
obs = res['2060'][:2]
exp = [_df['2060'][0] + (_hist['2015'][0] - _df['2015'][0]),
_df['2060'][1] * (_hist['2015'][1] / _df['2015'][1])]
npt.assert_array_almost_equal(obs, exp)