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ignore zeros on mape calculation #89

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merged 8 commits into from
Jun 19, 2024
Merged

ignore zeros on mape calculation #89

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7195d68
ignore zeros on mape calculation
jmoralez Jun 18, 2024
9eedce7
disable multiproc in windows tests
jmoralez Jun 18, 2024
f64c65c
try without change
jmoralez Jun 18, 2024
59249ab
cap numba
jmoralez Jun 18, 2024
6a1d165
cap numpy
jmoralez Jun 18, 2024
386f74a
Revert "try without change"
jmoralez Jun 18, 2024
5d98990
cap numpy in polars req
jmoralez Jun 19, 2024
75ecc95
restore multiproc
jmoralez Jun 19, 2024
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3 changes: 1 addition & 2 deletions nbs/losses.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -652,7 +652,6 @@
" .sub(df[target_col], axis=0)\n",
" .abs()\n",
" .div(_zero_to_nan(df[target_col].abs()), axis=0)\n",
" .fillna(0)\n",
" .groupby(df[id_col], observed=True).mean()\n",
" )\n",
" res.index.name = id_col\n",
Expand All @@ -662,7 +661,7 @@
" abs_err = pl.col(target_col).sub(pl.col(model)).abs()\n",
" abs_target = _zero_to_nan(pl.col(target_col))\n",
" ratio = abs_err.truediv(abs_target).alias(model)\n",
" return ratio.fill_nan(0)\n",
" return ratio.fill_nan(None)\n",
"\n",
" res = _pl_agg_expr(df, models, id_col, gen_expr)\n",
" return res"
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2 changes: 1 addition & 1 deletion settings.ini
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Expand Up @@ -29,7 +29,7 @@ user = Nixtla
requirements = numpy packaging pandas>=1.1.1
plotting_requirements = pandas[plot] plotly plotly-resampler
scalers_requirements = numba scipy
polars_requirements = polars
polars_requirements = polars numpy<2
dev_requirements = datasetsforecast==0.0.8 nbdev pyarrow
readme_nb = index.ipynb
allowed_metadata_keys =
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3 changes: 1 addition & 2 deletions utilsforecast/losses.py
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Original file line number Diff line number Diff line change
Expand Up @@ -171,7 +171,6 @@ def mape(
.sub(df[target_col], axis=0)
.abs()
.div(_zero_to_nan(df[target_col].abs()), axis=0)
.fillna(0)
.groupby(df[id_col], observed=True)
.mean()
)
Expand All @@ -183,7 +182,7 @@ def gen_expr(model):
abs_err = pl.col(target_col).sub(pl.col(model)).abs()
abs_target = _zero_to_nan(pl.col(target_col))
ratio = abs_err.truediv(abs_target).alias(model)
return ratio.fill_nan(0)
return ratio.fill_nan(None)

res = _pl_agg_expr(df, models, id_col, gen_expr)
return res
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