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Adjust for pandas-stubs 2.3.3.251201 #992

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Merged
khaeru merged 2 commits into from
Dec 2, 2025
Merged

Adjust for pandas-stubs 2.3.3.251201 #992

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41d5ec6
Adjust Scenario.add_par() per iiasa/ixmp#615
khaeru Dec 2, 2025
0ce4246
Ignore 3 mypy errors in add_year/__init__.py
khaeru Dec 2, 2025
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6 changes: 3 additions & 3 deletions message_ix/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -261,9 +261,9 @@ def add_par(
| dict
| pd.DataFrame
| None = None,
value: float | Iterable[float] | None = None,
unit: str | Iterable[str] | None = None,
comment: str | Iterable[str] | None = None,
value: float | Sequence[float] | None = None,
unit: str | Sequence[str] | None = None,
comment: str | Sequence[str] | None = None,
) -> None:
# ixmp.Scenario.add_par() is typed as accepting only str, but this method also
# accepts int for "year"-like dimensions. Proxy the call to avoid type check
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8 changes: 4 additions & 4 deletions message_ix/tools/add_year/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -829,7 +829,7 @@ def idx_check(df1: pd.DataFrame, df2: pd.DataFrame) -> pd.DataFrame:
d_n = slice_df(df_yrs, idx, year_ref, [yr_nn], yr)
d_n = d_n.loc[d_n.index.isin(d.index), :]
d = d.loc[d.index.isin(d_n.index), :]
d[d.isnull() & d_n.notnull()] = d_n
d[d.isnull() & d_n.notnull()] = d_n # type: ignore [call-overload]
df2.loc[df2.index.isin(d.index), :] = d

cond1 = df_dur.index <= yr_diff_new[0]
Expand Down Expand Up @@ -910,15 +910,15 @@ def idx_check(df1: pd.DataFrame, df2: pd.DataFrame) -> pd.DataFrame:
) # type: ignore
df_yr[np.isinf(df_pre)] = df_pre

# For those technolofies with one value for each year
# For those technologies with one value for each year
df_to_fill_nans: pd.DataFrame = intpol(
df_pre, df_pp.shift(+1, axis=1), year_pre, year_pp, yr
) # type: ignore
df_yr.loc[pd.isna(df_yr[yr])] = df_to_fill_nans.shift(+1, axis=1)
df_yr[pd.isna(df_yr)] = df_pre
df_yr[pd.isna(df_yr)] = df_pre # type: ignore [call-overload]

if extrapol_neg:
df_yr[(df_yr < 0) & (df_pre >= 0)] = df_pre * extrapol_neg
df_yr[(df_yr < 0) & (df_pre >= 0)] = df_pre * extrapol_neg # type: ignore [call-overload]
df_yr.loc[:, df_yr.columns < str(yr)] = np.nan

# c) Otherwise, do intrapolation
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