bugfix for interpolation with extra columns (#352)

RELEASE_NOTES.md

@@ -15,6 +15,7 @@ an IamDataFrame with `n/a` entries in columns other than `value` raises an error
 
 ## Individual Updates
 
+- [#352](https://github.com/IAMconsortium/pyam/pull/352) Bugfix when using `interpolate()` on data with extra columns
 - [#349](https://github.com/IAMconsortium/pyam/pull/349) Fixes an issue with checking that time columns are equal when appending IamDataFrames
 - [#348](https://github.com/IAMconsortium/pyam/pull/348) Extend pages for API docs, clean up docstrings, and harmonize formatting
 - [#347](https://github.com/IAMconsortium/pyam/pull/347) Enable contexts and custom UnitRegistry with unit conversion

pyam/core.py

@@ -355,7 +355,8 @@ def interpolate(self, time):
             raise ValueError(
                 'The `time` argument `{}` is not an integer'.format(time)
             )
-        df = self.pivot_table(index=IAMC_IDX, columns=[self.time_col],
+        index = [i for i in self._LONG_IDX if i not in [self.time_col]]
+        df = self.pivot_table(index=index, columns=[self.time_col],
                               values='value', aggfunc=np.sum)
         # drop time-rows where values are already defined
         if time in df.columns:

tests/test_core.py

@@ -10,6 +10,8 @@
 from pyam import IamDataFrame, validate, categorize, \
     require_variable, filter_by_meta, META_IDX, IAMC_IDX, sort_data, compare
 from pyam.core import _meta_idx, concat
+from pyam.utils import isstr
+from pyam.testing import assert_iamframe_equal
 
 from conftest import TEST_DTS
 
@@ -687,15 +689,40 @@ def test_category_top_level(test_df):
     pd.testing.assert_series_equal(obs, exp)
 
 
-def test_interpolate(test_df_year):
-    test_df_year.interpolate(2007)
-    obs = test_df_year.filter(year=2007).data['value'].reset_index(drop=True)
+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
-    test_df_year.interpolate(2007)
-    assert not test_df_year.filter().data.duplicated().any()
+    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_extra_cols():
+    # check hat interpolation with non-matching extra_cols has no effect (#351)
+    EXTRA_COL_DF = pd.DataFrame([
+        ['foo', 2005, 1],
+        ['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, interpolate
+    df2 = df.copy()
+    df2.interpolate(2007)
+
+    # assert that interpolation didn't change any data
+    assert_iamframe_equal(df, df2)
 
 
 def test_interpolate_datetimes(test_df):