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')