breaking: allowmean and allowdrift True by default in AutoARIMA

.pre-commit-config.yaml

@@ -25,4 +25,4 @@ repos:
     hooks:
       - id: mypy
         args: [--ignore-missing-imports]
-        exclude: 'setup.py'
+        exclude: (experiments|setup.py)

experiments/m3/src/data.py

@@ -1,5 +1,4 @@
 import fire
-import pandas as pd
 from datasetsforecast.m3 import M3, M3Info
 
 dict_datasets = {

experiments/m3/src/evaluation.py

@@ -1,7 +1,6 @@
 from itertools import product
 
 import fire
-import numpy as np
 import pandas as pd
 from datasetsforecast.losses import mape, smape
 
@@ -50,11 +49,11 @@ def main(test: bool = False):
     time = evaluation.query('metric=="time"').T
     if test:
         expected_results = {
-            'AutoARIMA': 4.57,
+            'AutoARIMA': 4.46,
             'CES': 4.85, 
             'AutoETS': 4.35, 
             'DynamicOptimizedTheta': 4.54,
-            'StatisticalEnsemble': 4.23,
+            'StatisticalEnsemble': 4.3,
         }
         expected_results = pd.Series(expected_results)
         pd.testing.assert_series_equal(

experiments/m3/src/experiment.py

@@ -1,6 +1,5 @@
 import os
 import time
-from functools import partial
 from multiprocessing import cpu_count
 os.environ['NIXTLA_NUMBA_RELEASE_GIL'] = '1'
 os.environ['NIXTLA_NUMBA_CACHE'] = '1'
@@ -11,8 +10,7 @@
 from statsforecast import StatsForecast
 from statsforecast.models import (
         AutoTheta, AutoETS, AutoCES,AutoARIMA,
-        Theta, OptimizedTheta, 
-        DynamicTheta, DynamicOptimizedTheta
+        DynamicOptimizedTheta
 )
 from statsforecast.utils import AirPassengers as ap
 

nbs/src/core/models.ipynb

@@ -500,8 +500,8 @@
     "        test_kwargs: Optional[str] = None,\n",
     "        seasonal_test: str = 'seas',\n",
     "        seasonal_test_kwargs: Optional[Dict] = None,\n",
-    "        allowdrift: bool = False,\n",
-    "        allowmean: bool = False,\n",
+    "        allowdrift: bool = True,\n",
+    "        allowmean: bool = True,\n",
     "        blambda: Optional[float] = None,\n",
     "        biasadj: bool = False,\n",
     "        season_length: int = 1,\n",

python/statsforecast/models.py

@@ -289,8 +289,8 @@ def __init__(
         test_kwargs: Optional[str] = None,
         seasonal_test: str = "seas",
         seasonal_test_kwargs: Optional[Dict] = None,
-        allowdrift: bool = False,
-        allowmean: bool = False,
+        allowdrift: bool = True,
+        allowmean: bool = True,
         blambda: Optional[float] = None,
         biasadj: bool = False,
         season_length: int = 1,

settings.ini

@@ -21,7 +21,7 @@ ray_requirements = fugue[ray]>=0.8.1 protobuf>=3.15.3,<4.0.0 numpy<2 pandas<2.2
 dask_requirements = fugue[dask]>=0.8.1
 spark_requirements = fugue[spark]>=0.8.1
 plotly_requirements = plotly plotly-resampler
-dev_requirements = black datasetsforecast fire nbdev nbformat nbdev_plotly pandas[plot] pmdarima polars[numpy] pre-commit prophet pyarrow pybind11 pytest scikit-learn setuptools<70 supersmoother
+dev_requirements = black datasetsforecast fire nbdev==2.3.25 nbformat nbdev_plotly pandas[plot] pmdarima polars[numpy] pre-commit prophet pyarrow pybind11 pytest scikit-learn setuptools<70 supersmoother
 nbs_path = nbs
 doc_path = _docs
 recursive = True