def test_category_top_level(meta_df):
dct = {'model': ['a_model', 'a_model'],
'scenario': ['a_scenario', 'a_scenario2'],
'category': ['Testing', 'uncategorized']}
exp = pd.DataFrame(dct).set_index(['model', 'scenario'])['category']
categorize(meta_df, 'category', 'Testing',
criteria={'Primary Energy': {'up': 6, 'year': 2010}},
variable='Primary Energy')
obs = meta_df['category']
pd.testing.assert_series_equal(obs, exp)
def test_category_top_level(test_df):
dct = {'model': ['model_a', 'model_a'],
'scenario': ['scen_a', 'scen_b'],
'category': ['foo', None]}
exp = pd.DataFrame(dct).set_index(['model', 'scenario'])['category']
categorize(test_df, 'category', 'foo',
criteria={'Primary Energy': {'up': 6, 'year': 2010}},
variable='Primary Energy')
obs = test_df['category']
pd.testing.assert_series_equal(obs, exp)
def test_category_top_level(test_df):
dct = {
"model": ["model_a", "model_a"],
"scenario": ["scen_a", "scen_b"],
"category": ["foo", None],
}
exp = pd.DataFrame(dct).set_index(["model", "scenario"])["category"]
categorize(
test_df,
"category",
"foo",
criteria={"Primary Energy": {
"up": 6,
"year": 2010
}},
variable="Primary Energy",
)
obs = test_df["category"]
pd.testing.assert_series_equal(obs, exp)
return 'AR5 climate diagnostics|Temperature|Exceedance Probability|{} °C|MAGICC6'.format(
x)
expected_warming = 'AR5 climate diagnostics|Temperature|Global Mean|MAGICC6|Expected value'
median_warming = 'AR5 climate diagnostics|Temperature|Global Mean|MAGICC6|MED'
#%%
sr1p5.set_meta(meta=sr1p5['category'], name='subcategory')
#%%
pyam.categorize(sr1p5,
exclude=False,
subcategory='uncategorized',
value='Below 1.5C (I)',
name='subcategory',
criteria={warming_exccedance_prob(1.5): {
'up': 0.34
}},
color='xkcd:baby blue')
#%%
pyam.categorize(sr1p5,
exclude=False,
subcategory='uncategorized',
value='Below 1.5C (II)',
name='subcategory',
criteria={warming_exccedance_prob(1.5): {
'up': 0.50
}},
color='xkcd:baby blue')