def test_store_ts(request, caplog, test_mp):
# Computer and target scenario
c = Computer()
# Target scenario
model_name = __name__
scenario_name = "test scenario"
scen = Scenario(test_mp, model_name, scenario_name, version="new")
scen.commit("Empty scenario")
c.add("target", scen)
# Add test data to the Computer: a pd.DataFrame
input_1 = test_data[0].assign(variable="Foo")
c.add("input 1", input_1)
# A pyam.IamDataFrame
input_2 = test_data[2050].assign(variable="Bar")
c.add("input 2", pyam.IamDataFrame(input_2))
# Expected results: same as input, but with the `model` and `scenario` columns
# filled automatically.
expected_1 = input_1.assign(model=model_name, scenario=scenario_name)
expected_2 = input_2.assign(model=model_name, scenario=scenario_name)
# Task to update the scenario with the data
c.add("test 1", store_ts, "target", "input 1", "input 2")
# Scenario starts empty of time series data
assert 0 == len(scen.timeseries())
# The computation runs successfully
c.get("test 1")
# All rows from both inputs are present
assert len(input_1) + len(input_2) == len(scen.timeseries())
# Input is stored exactly
assert_frame_equal(expected_1, scen.timeseries(variable="Foo"))
assert_frame_equal(expected_2, scen.timeseries(variable="Bar"))
def test_timeseries_remove_all_data(mp):
args_all = ('Douglas Adams', 'test_remove_all')
scen = Scenario(mp, *args_all, version='new', annotation='fo')
scen.add_timeseries(DATA['timeseries'].pivot_table(values='value',
index=IDX_COLS))
scen.commit('importing a testing timeseries')
scen = Scenario(mp, *args_all)
assert_timeseries(scen, DATA['timeseries'])
exp = DATA['timeseries'].copy()
exp['variable'] = 'Testing2'
scen.check_out()
scen.add_timeseries(exp)
scen.remove_timeseries(DATA['timeseries'])
scen.commit('testing for removing a full timeseries row')
assert scen.timeseries(region='World', variable='Testing').empty
assert_timeseries(scen, exp)
def test_timeseries_remove_all_data(mp):
args_all = ("Douglas Adams", "test_remove_all")
scen = Scenario(mp, *args_all, version="new", annotation="fo")
scen.add_timeseries(DATA["timeseries"].pivot_table(values="value",
index=IDX_COLS))
scen.commit("importing a testing timeseries")
scen = Scenario(mp, *args_all)
assert_timeseries(scen, DATA["timeseries"])
exp = DATA["timeseries"].copy()
exp["variable"] = "Testing2"
scen.check_out()
scen.add_timeseries(exp)
scen.remove_timeseries(DATA["timeseries"])
scen.commit("testing for removing a full timeseries row")
assert scen.timeseries(region="World", variable="Testing").empty
assert_timeseries(scen, exp)