Merge branch 'master' into feature/rnn-normalization

darts/models/forecasting/arima.py

@@ -13,6 +13,7 @@
 from typing import Optional, Tuple
 
 import numpy as np
+from statsmodels import __version_tuple__ as statsmodels_version
 from statsmodels.tsa.arima.model import ARIMA as staARIMA
 
 from darts.logging import get_logger
@@ -23,6 +24,9 @@
 
 logger = get_logger(__name__)
 
+# Check whether we are running statsmodels >= 0.13.5 or not:
+statsmodels_above_0135 = statsmodels_version > (0, 13, 5)
+
 
 class ARIMA(TransferableFutureCovariatesLocalForecastingModel):
     def __init__(
@@ -81,11 +85,15 @@ def __init__(
         self.seasonal_order = seasonal_order
         self.trend = trend
         self.model = None
-        self._random_state = (
-            random_state
-            if random_state is None
-            else np.random.RandomState(random_state)
-        )
+        if statsmodels_above_0135:
+            self._random_state = (
+                random_state
+                if random_state is None
+                else np.random.RandomState(random_state)
+            )
+        else:
+            self._random_state = None
+            np.random.seed(random_state if random_state is not None else 0)
 
     def _fit(self, series: TimeSeries, future_covariates: Optional[TimeSeries] = None):
         super()._fit(series, future_covariates)

requirements/core.txt

@@ -1,5 +1,5 @@
-catboost>=1.0.6
-holidays>=0.11.1
+catboost>=1.0.6,<1.2.0
+holidays>=0.11.1,<0.25.0
 joblib>=0.16.0
 lightgbm>=3.2.0
 matplotlib>=3.3.0
@@ -17,5 +17,6 @@ statsforecast>=1.4
 statsmodels>=0.13.0
 tbats>=1.1.0
 tqdm>=4.60.0
+typing-extensions
 xarray>=0.17.0
 xgboost>=1.6.0