def test_timeseries_edit(mp):
scen = TimeSeries(mp, *test_args)
df = {'region': ['World'] * 2, 'variable': ['Testing'] * 2,
'unit': ['???', '???'], 'year': [2010, 2020], 'value': [23.7, 23.8]}
exp = pd.DataFrame.from_dict(df)
obs = scen.timeseries()
npt.assert_array_equal(exp[IDX_COLS], obs[IDX_COLS])
npt.assert_array_almost_equal(exp['value'], obs['value'])
scen.check_out(timeseries_only=True)
df = {'region': ['World'] * 2,
'variable': ['Testing'] * 2,
'unit': ['???', '???'], 'year': [2010, 2020],
'value': [23.7, 23.8]}
df = pd.DataFrame.from_dict(df)
scen.add_timeseries(df)
scen.commit('testing of editing timeseries (same years)')
scen.check_out(timeseries_only=True)
df = {'region': ['World'] * 3,
'variable': ['Testing', 'Testing', 'Testing2'],
'unit': ['???', '???', '???'], 'year': [2020, 2030, 2030],
'value': [24.8, 24.9, 25.1]}
df = pd.DataFrame.from_dict(df)
scen.add_timeseries(df)
scen.commit('testing of editing timeseries (other years)')
mp.close_db()
mp.open_db()
scen = TimeSeries(mp, *test_args)
obs = scen.timeseries().sort_values(by=['year'])
df = df.append(exp.loc[0]).sort_values(by=['year'])
npt.assert_array_equal(df[IDX_COLS], obs[IDX_COLS])
npt.assert_array_almost_equal(df['value'], obs['value'])
def test_timeseries_edit(mp):
scen = TimeSeries(mp, *test_args)
df = {
"region": ["World"] * 2,
"variable": ["Testing"] * 2,
"unit": ["???", "???"],
"year": [2010, 2020],
"value": [23.7, 23.8],
}
exp = pd.DataFrame.from_dict(df)
obs = scen.timeseries()
npt.assert_array_equal(exp[IDX_COLS], obs[IDX_COLS])
npt.assert_array_almost_equal(exp["value"], obs["value"])
scen.check_out(timeseries_only=True)
df = {
"region": ["World"] * 2,
"variable": ["Testing"] * 2,
"unit": ["???", "???"],
"year": [2010, 2020],
"value": [23.7, 23.8],
}
df = pd.DataFrame.from_dict(df)
scen.add_timeseries(df)
scen.commit("testing of editing timeseries (same years)")
scen.check_out(timeseries_only=True)
df = {
"region": ["World"] * 3,
"variable": ["Testing", "Testing", "Testing2"],
"unit": ["???", "???", "???"],
"year": [2020, 2030, 2030],
"value": [24.8, 24.9, 25.1],
}
df = pd.DataFrame.from_dict(df)
scen.add_timeseries(df)
scen.commit("testing of editing timeseries (other years)")
mp.close_db()
mp.open_db()
scen = TimeSeries(mp, *test_args)
obs = scen.timeseries().sort_values(by=["year"])
df = df.append(exp.loc[0]).sort_values(by=["year"])
npt.assert_array_equal(df[IDX_COLS], obs[IDX_COLS])
npt.assert_array_almost_equal(df["value"], obs["value"])
def test_get_timeseries_iamc(mp):
scen = TimeSeries(mp, *test_args)
obs = scen.timeseries(region='World', variable='Testing', iamc=True)
exp = DATA['timeseries'].pivot_table(index=['region', 'variable', 'unit'],
columns='year')['value'].reset_index()
exp['model'] = 'Douglas Adams'
exp['scenario'] = 'Hitchhiker'
npt.assert_array_equal(exp[IAMC_IDX], obs[IAMC_IDX])
npt.assert_array_almost_equal(exp[2010], obs[2010])
def test_get_timeseries_iamc(mp):
scen = TimeSeries(mp, *test_args)
obs = scen.timeseries(region="World", variable="Testing", iamc=True)
exp = (DATA["timeseries"].pivot_table(
index=["region", "variable",
"unit"], columns="year")["value"].reset_index())
exp["model"] = "Douglas Adams"
exp["scenario"] = "Hitchhiker"
npt.assert_array_equal(exp[IAMC_IDX], obs[IAMC_IDX])
npt.assert_array_almost_equal(exp[2010], obs[2010])
