def test_calc_data_missing_datapoint(westeros_solved):
s = westeros_solved
data = pd.read_excel(W_DATA_PATH, sheet_name=None, engine="openpyxl")
# skip first data point
data["gdp_calibrate"] = data["gdp_calibrate"][1:]
c = macro.Calculate(s, data)
pytest.raises(ValueError, c.read_data)
def test_calc_price_zero(westeros_solved):
s = westeros_solved
clone = s.clone(scenario="low_demand", keep_solution=False)
clone.check_out()
# Lowering demand in the first year
clone.add_par("demand", ["Westeros", "light", "useful", 700, "year"], 10,
"GWa")
# Making investment and var cost zero for delivering light
# TODO: these units are based on testing.make_westeros: needs improvement
clone.add_par("inv_cost", ["Westeros", "bulb", 700], 0, "USD/GWa")
for y in [690, 700]:
clone.add_par("var_cost",
["Westeros", "grid", y, 700, "standard", "year"], 0,
"USD/GWa")
clone.commit("demand reduced and zero cost for bulb")
clone.solve()
price = clone.var("PRICE_COMMODITY")
# Assert if there is no zero price (to make sure MACRO receives 0 price)
assert np.isclose(0, price["lvl"]).any()
c = macro.Calculate(clone, W_DATA_PATH)
c.read_data()
try:
c._price()
except RuntimeError as err:
# To make sure the right error message is raised in macro.py
assert "0-price found in MESSAGE variable PRICE_" in str(err)
else:
raise Exception("No error in macro.read_data() for zero price(s)")
def test_calc_data_missing_column(westeros_solved):
s = westeros_solved
data = pd.read_excel(W_DATA_PATH, sheet_name=None)
# skip first data point
data['gdp_calibrate'] = data['gdp_calibrate'].drop('year', axis=1)
c = macro.Calculate(s, data)
pytest.raises(ValueError, c.read_data)
def test_multiregion_derive_data():
s = MockScenario()
c = macro.Calculate(s, MR_DATA_PATH)
c.read_data()
c.derive_data()
nodes = ["R11_AFR", "R11_CPA"]
sectors = ["i_therm", "rc_spec"]
# make sure no extraneous data is there
check = c.data["demand"].reset_index()
assert (check["node"].unique() == nodes).all()
assert (check["sector"].unique() == sectors).all()
obs = c.data["aconst"]
exp = pd.Series(
[3.74767687, 0.00285472], name="value", index=pd.Index(nodes, name="node")
)
pd.testing.assert_series_equal(obs, exp)
obs = c.data["bconst"]
idx = pd.MultiIndex.from_product([nodes, sectors], names=["node", "sector"])
exp = pd.Series(
[1.071971e-08, 1.487598e-11, 9.637483e-09, 6.955715e-13],
name="value",
index=idx,
)
pd.testing.assert_series_equal(obs, exp)
def test_multiregion_derive_data():
s = MockScenario()
c = macro.Calculate(s, MR_DATA_PATH)
c.read_data()
c.derive_data()
nodes = ['R11_AFR', 'R11_CPA']
sectors = ['i_therm', 'rc_spec']
# make sure no extraneous data is there
check = c.data['demand'].reset_index()
assert (check['node'].unique() == nodes).all()
assert (check['sector'].unique() == sectors).all()
obs = c.data['aconst']
exp = pd.Series([3.74767687, 0.00285472],
name='value',
index=pd.Index(nodes, name='node'))
pd.testing.assert_series_equal(obs, exp)
obs = c.data['bconst']
idx = pd.MultiIndex.from_product([nodes, sectors],
names=['node', 'sector'])
exp = pd.Series([1.071971e-08, 1.487598e-11, 9.637483e-09, 6.955715e-13],
name='value',
index=idx)
pd.testing.assert_series_equal(obs, exp)
def test_calc(westeros_solved, method, test, expected):
calc = macro.Calculate(westeros_solved, W_DATA_PATH)
calc.read_data()
function = getattr(calc, method)
assertion = getattr(npt, f"assert_{test}")
assertion(function().values, expected)
def test_calc_bconst(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
c.read_data()
obs = c._bconst()
assert len(obs) == 1
obs = obs[0]
exp = 3.6846576e-05
assert np.isclose(obs, exp)
def test_calc_k0(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
c.read_data()
obs = c._k0()
assert len(obs) == 1
obs = obs[0]
exp = 1500
assert obs == exp
def test_calc_growth(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
c.read_data()
obs = c._growth()
assert len(obs) == 4
obs = obs.values
exp = np.array([0.0265836, 0.041380, 0.041380, 0.029186])
assert np.isclose(obs, exp).all()
def test_calc_aconst(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
c.read_data()
obs = c._aconst()
assert len(obs) == 1
obs = obs[0]
exp = 26.027323
assert np.isclose(obs, exp)
def test_calc_demand(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
c.read_data()
obs = c._demand()
# 4 values, 3 in model period, one in history
assert len(obs) == 4
obs = obs.values
exp = np.array([90, 100, 150, 190])
assert np.isclose(obs, exp).all()
def test_calc_price(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
c.read_data()
obs = c._price()
# 4 values, 3 in model period, one in history
assert len(obs) == 4
obs = obs.values
exp = np.array([195, 182.852229, 162.039539, 161.002627])
assert np.isclose(obs, exp).all()
def test_calc_total_cost(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
c.read_data()
obs = c._total_cost()
# 4 values, 3 in model period, one in history
assert len(obs) == 4
obs = obs.values
exp = np.array([15, 17.477751, 22.143634, 28.114812]) / 1e3
assert np.isclose(obs, exp).all()
def test_config(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
c.nodes = set(list(c.nodes) + ["foo"])
c.sectors = set(list(c.sectors) + ["bar"])
assert c.nodes == set(["Westeros", "foo"])
assert c.sectors == set(["light", "bar"])
c.read_data()
assert c.nodes == set(["Westeros"])
assert c.sectors == set(["light"])
def test_config(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
c.nodes = set(list(c.nodes) + ['foo'])
c.sectors = set(list(c.sectors) + ['bar'])
assert c.nodes == set(['Westeros', 'foo'])
assert c.sectors == set(['light', 'bar'])
c.read_data()
assert c.nodes == set(['Westeros'])
assert c.sectors == set(['light'])
def test_calc_valid_years(westeros_solved):
s = westeros_solved
data = pd.read_excel(W_DATA_PATH, sheet_name=None, engine="openpyxl")
# Adding an arbitrary year
arbitrary_yr = 2021
gdp_extra_yr = data["gdp_calibrate"].iloc[0, :].copy()
gdp_extra_yr["year"] = arbitrary_yr
data["gdp_calibrate"] = data["gdp_calibrate"].append(gdp_extra_yr)
# Check the arbitrary year is not in config
assert arbitrary_yr not in data["config"]["year"]
# But it is in gdp_calibrate
assert arbitrary_yr in set(data["gdp_calibrate"]["year"])
# And macro does calibration without error
c = macro.Calculate(s, data)
c.read_data()
def test_config(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
assert "config" in c.data
assert "sector" in c.data["config"]
# Removing a column from config and testing
data = c.data.copy()
data["config"] = c.data["config"][["node", "sector"]]
try:
macro.Calculate(s, data)
except KeyError as error:
assert 'Missing config data for "level"' in str(error)
# Removing config completely and testing
data.pop("config")
try:
macro.Calculate(s, data)
except KeyError as error:
assert "Missing config in input data" in str(error)
c.read_data()
assert c.nodes == set(["Westeros"])
assert c.sectors == set(["light"])
def test_calc_data_missing_par(westeros_solved):
s = westeros_solved
data = pd.read_excel(W_DATA_PATH, sheet_name=None, engine="openpyxl")
data.pop("gdp_calibrate")
c = macro.Calculate(s, data)
pytest.raises(ValueError, c.read_data)
def test_multiregion_valid_data():
s = MockScenario()
c = macro.Calculate(s, MR_DATA_PATH)
c.read_data()
def test_calc_invalid_data(westeros_solved):
with pytest.raises(TypeError, match="neither a dict nor a valid path"):
macro.Calculate(westeros_solved, list())
with pytest.raises(ValueError, match="not an Excel data file"):
macro.Calculate(westeros_solved, Path(__file__).joinpath("other.zip"))
def test_calc_valid_data_dict(westeros_solved):
s = westeros_solved
data = pd.read_excel(W_DATA_PATH, sheet_name=None, engine="openpyxl")
c = macro.Calculate(s, data)
c.read_data()
def test_calc_valid_data_file(westeros_solved):
s = westeros_solved
c = macro.Calculate(s, W_DATA_PATH)
c.read_data()
