def test_interpolate(test_pd_df):
_df = test_pd_df.copy()
_df["foo"] = ["bar", "baz", 2] # add extra_col (check for #351)
df = IamDataFrame(_df)
obs = df.interpolate(2007, inplace=False).filter(year=2007)._data.values
npt.assert_allclose(obs, [3, 1.5, 4])
# redo the interpolation and check that no duplicates are added
df.interpolate(2007, inplace=False)
assert not df._data.index.duplicated().any()
# assert that extra_col does not have nan's (check for #351)
assert all([True if isstr(i) else ~np.isnan(i) for i in df.foo])
def test_interpolate(test_pd_df):
_df = test_pd_df.copy()
_df['foo'] = ['bar', 'baz', 2] # add extra_col (check for #351)
df = IamDataFrame(_df)
df.interpolate(2007)
obs = df.filter(year=2007).data['value'].reset_index(drop=True)
exp = pd.Series([3, 1.5, 4], name='value')
pd.testing.assert_series_equal(obs, exp)
# redo the interpolation and check that no duplicates are added
df.interpolate(2007)
assert not df.filter().data.duplicated().any()
# assert that extra_col does not have nan's (check for #351)
assert all([True if isstr(i) else ~np.isnan(i) for i in df.data.foo])
def test_interpolate_full_example():
cols = ['model_a', 'scen_a', 'World']
df = IamDataFrame(
pd.DataFrame(
[
cols + ['all', 'EJ/yr', 0, 1, 6., 10],
cols + ['last', 'EJ/yr', 0, 0.5, 3, np.nan],
cols + ['first', 'EJ/yr', 0, np.nan, 2, 7],
cols + ['middle', 'EJ/yr', 0, 1, np.nan, 7],
cols + ['first two', 'EJ/yr', 0, np.nan, np.nan, 7],
cols + ['last two', 'EJ/yr', 0, 1, np.nan, np.nan],
],
columns=IAMC_IDX + [2000, 2005, 2010, 2017],
))
exp = IamDataFrame(
pd.DataFrame(
[
cols + ['all', 'EJ/yr', 0, 1, 6., 7.142857, 10],
cols + ['last', 'EJ/yr', 0, 0.5, 3, np.nan, np.nan],
cols + ['first', 'EJ/yr', 0, 1., 2, 3.428571, 7],
cols + ['middle', 'EJ/yr', 0, 1, np.nan, 4.5, 7],
cols +
['first two', 'EJ/yr', 0, 2.058824, np.nan, 4.941176, 7],
cols + ['last two', 'EJ/yr', 0, 1, np.nan, np.nan, np.nan],
],
columns=IAMC_IDX + [2000, 2005, 2010, 2012, 2017],
))
obs = df.interpolate([2005, 2012], inplace=False)
assert_iamframe_equal(obs, exp)
def test_interpolate_full_example():
cols = ["model_a", "scen_a", "World"]
df = IamDataFrame(
pd.DataFrame(
[
cols + ["all", "EJ/yr", 0, 1, 6.0, 10],
cols + ["last", "EJ/yr", 0, 0.5, 3, np.nan],
cols + ["first", "EJ/yr", 0, np.nan, 2, 7],
cols + ["middle", "EJ/yr", 0, 1, np.nan, 7],
cols + ["first two", "EJ/yr", 0, np.nan, np.nan, 7],
cols + ["last two", "EJ/yr", 0, 1, np.nan, np.nan],
],
columns=IAMC_IDX + [2000, 2005, 2010, 2017],
))
exp = IamDataFrame(
pd.DataFrame(
[
cols + ["all", "EJ/yr", 0, 1, 6.0, 7.142857, 10],
cols + ["last", "EJ/yr", 0, 0.5, 3, np.nan, np.nan],
cols + ["first", "EJ/yr", 0, 1.0, 2, 3.428571, 7],
cols + ["middle", "EJ/yr", 0, 1, np.nan, 4.5, 7],
cols +
["first two", "EJ/yr", 0, 2.058824, np.nan, 4.941176, 7],
cols + ["last two", "EJ/yr", 0, 1, np.nan, np.nan, np.nan],
],
columns=IAMC_IDX + [2000, 2005, 2010, 2012, 2017],
))
obs = df.interpolate([2005, 2012], inplace=False)
assert_iamframe_equal(obs, exp)
def test_interpolate_extra_cols():
# check that interpolation with non-matching extra_cols has no effect
# (#351)
EXTRA_COL_DF = pd.DataFrame(
[
["foo", 2005, 1],
["foo", 2010, 2],
["bar", 2005, 2],
["bar", 2010, 3],
],
columns=["extra_col", "year", "value"],
)
df = IamDataFrame(
EXTRA_COL_DF,
model="model_a",
scenario="scen_a",
region="World",
variable="Primary Energy",
unit="EJ/yr",
)
# create a copy from interpolation
df2 = df.interpolate(2007, inplace=False)
# interpolate should work as if extra_cols is in the _data index
assert_iamframe_equal(df, df2.filter(year=2007, keep=False))
obs = df2.filter(year=2007)._data.values
npt.assert_allclose(obs, [2.4, 1.4])
