Backports v0.13.5 (#3004)

* Raise warning in `QuantileForecast.mean` when mean is not there (#2843)

* [R] Bug fix for running R methods via ParallelizedPredictor (#2983)

* Fix Forecast plot method (#3006)

Latest matplotlib update had broken it since we were using internal API

* fixup to support py37

---------

Co-authored-by: Syama Sundar Rangapuram <[email protected]>

src/gluonts/ext/r_forecast/_univariate_predictor.py

@@ -121,6 +121,7 @@ def __init__(
             params["intervals"] = sorted(
                 set([level for level, _ in intervals_info])
             )
+            params.pop("quantiles")
 
         self.params.update(params)
 

src/gluonts/model/forecast.py

@@ -12,6 +12,7 @@
 # permissions and limitations under the License.
 
 import re
+import logging
 from dataclasses import field
 from typing import Callable, Dict, List, Optional, Union, Tuple
 
@@ -22,6 +23,8 @@
 from gluonts.core.component import validated
 from gluonts import maybe
 
+logger = logging.getLogger(__name__)
+
 
 def _linear_interpolation(
     xs: np.ndarray, ys: np.ndarray, x: float
@@ -313,7 +316,7 @@ def plot(
         # If no color is provided, we use matplotlib's internal color cycle.
         # Note: This is an internal API and might change in the future.
         color = maybe.unwrap_or_else(
-            color, lambda: next(ax._get_lines.prop_cycler)["color"]
+            color, lambda: ax._get_lines.get_next_color()
         )
 
         # Plot median forecast
@@ -656,7 +659,11 @@ def mean(self) -> np.ndarray:
         """
         if "mean" in self._forecast_dict:
             return self._forecast_dict["mean"]
-
+        logger.warning(
+            "The mean prediction is not stored in the forecast data; "
+            "the median is being returned instead. "
+            "This behaviour may change in the future."
+        )
         return self.quantile("p50")
 
     def dim(self) -> int: