def test_init_df_datetime_error(test_pd_df):
tdf = ScmDataFrame(test_pd_df).data
tdf["time"] = 2010
error_msg = r"^All time values must be convertible to datetime\. The following values are not:(.|\s)*$"
with pytest.raises(ValueError, match=error_msg):
ScmDataFrame(tdf)
def test_write_read_datafile(test_pd_df, tmp_path):
tfile = str(tmp_path / "testfile.csv")
tdf = ScmDataFrame(test_pd_df)
tdf.to_csv(tfile)
ScmDataFrame(tfile)
def combo_df(request):
combination = deepcopy(request.param)
vals = combination._asdict()
source = combination.source
# For average timeseries we drop the last time value so that the data and times are same length
if combination.timeseries_type == ParameterType.AVERAGE_TIMESERIES:
assert source[-1] - source[-2] == source[-2] - source[-3]
source = source[:-1]
vals["target"] = combination.target.copy()[:-1]
assert len(vals["target"]) == len(combination.target_values)
assert len(source) == len(combination.source_values)
df = ScmDataFrame(
combination.source_values,
columns={
"scenario": ["a_scenario"],
"model": ["a_model"],
"region": ["World"],
"variable": ["Emissions|BC"],
"unit": ["Mg /yr"],
"parameter_type":
[("point" if combination.timeseries_type
== ParameterType.POINT_TIMESERIES else "average")],
},
index=source,
)
return Combination(**vals), df
def combo_df(request):
combo = deepcopy(request.param)
vals = combo._asdict()
df_dts = [convert_openscm_time_to_datetime(d) for d in combo.source]
# For average timeseries we drop the last time value so that the data and times are same length
if combo.timeseries_type == ParameterType.AVERAGE_TIMESERIES:
assert df_dts[-1] - df_dts[-2] == df_dts[-2] - df_dts[-3]
df_dts = df_dts[:-1]
vals["target"] = combo.target.copy()[:-1]
assert len(vals["target"]) == len(combo.target_values)
assert len(df_dts) == len(combo.source_values)
df = ScmDataFrame(
combo.source_values,
columns={
"scenario": ["a_scenario"],
"model": ["a_model"],
"region": ["World"],
"variable": ["Emissions|BC"],
"unit": ["Mg /yr"],
"parameter_type": [
(
"point"
if combo.timeseries_type == ParameterType.POINT_TIMESERIES
else "average"
)
],
},
index=df_dts,
)
return Combination(**vals), df
def test_write_read_datafile(test_pd_df, tmp_path):
tfile = str(tmp_path / "testfile.csv")
tdf = ScmDataFrame(test_pd_df)
tdf.to_csv(tfile)
rdf = ScmDataFrame(tfile)
pd.testing.assert_frame_equal(tdf.timeseries(), rdf.timeseries())
def test_scm_datetime_df():
tdf = TEST_DF.copy()
tdf.rename(
{
2005: datetime(2005, 6, 17, 12),
2010: datetime(2010, 1, 3, 0),
2015: datetime(2015, 1, 4, 0),
},
axis="columns",
inplace=True,
)
yield ScmDataFrame(tdf)
def test_processing_scm_df():
yield ScmDataFrame(
data=np.array([[1, 6.0, 7], [0.5, 3, 2], [2, 7, 0], [-1, -2, 3]]).T,
columns={
"model": ["a_iam"],
"climate_model": ["a_model"],
"scenario": ["a_scenario", "a_scenario", "a_scenario2", "a_scenario3"],
"region": ["World"],
"variable": [
"Primary Energy",
"Primary Energy|Coal",
"Primary Energy",
"Primary Energy",
],
"unit": ["EJ/yr"],
},
index=[datetime(2005, 1, 1), datetime(2010, 1, 1), datetime(2015, 6, 12)],
)
def rcp26():
fname = join(TEST_DATA, "rcp26_emissions.csv")
return ScmDataFrame(fname)
def test_scm_df(request):
if IamDataFrame is None:
pytest.skip("pyam is not installed")
yield ScmDataFrame(**request.param)
append_scm_df_pairs_vars = [
"Primary Energy",
"Primary Energy|Coal",
"Primary Energy",
"Primary Energy",
]
append_scm_df_pairs_times = [
datetime(2005, 1, 1),
datetime(2010, 1, 1),
datetime(2015, 6, 12),
]
append_scm_df_base = ScmDataFrame(
data=np.array([[1, 6.0, 7], [0.5, 3, 2], [2, 7, 0], [-1, -2, 3]]).T,
index=append_scm_df_pairs_times,
columns={
"scenario": append_scm_df_pairs_scens,
"variable": append_scm_df_pairs_vars,
**append_scm_df_pairs_cols,
},
)
append_scm_df_pairs = [
{
"base":
append_scm_df_base,
"other":
ScmDataFrame(
data=np.array([[-1, 0, 1]]).T,
index=append_scm_df_pairs_times,
columns={
"scenario": ["a_scenario"],
"variable": ["Primary Energy"],
def test_init_df_long_timespan(test_pd_df):
df = ScmDataFrame(test_pd_df)
pd.testing.assert_frame_equal(
df.timeseries().reset_index(), test_pd_df, check_like=True
)