Backports for v0.11.1 (#2401)

* Fix dominick dataset bug. (#2364) * Remove strange quoting marks from docstrings (#2368) * Change 'confidence interval' to 'prediction interval' (#2373) * Proposed fix to zero seed bug. (#2379) Co-authored-by: Sigrid Passano Hellan <[email protected]> Co-authored-by: Bhaskar Dhariyal <[email protected]> Co-authored-by: Nils Kiele <[email protected]> Co-authored-by: Sigrid Passano Hellan <[email protected]> Co-authored-by: Sigrid Passano Hellan <[email protected]>
awslabs · Oct 28, 2022 · ca6e4f2 · ca6e4f2
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diff --git a/docs/getting_started/background.md b/docs/getting_started/background.md
@@ -104,7 +104,7 @@ that there is probably a demand of say 50 dishes, but unlikely more than 60.
 ```{figure} ../_static/forecast-distributions.png
 ---
 ---
-Predicting 24 hours, showing `p50`, `p90`, `p95`, `p98` confidence intervals.
+Predicting 24 hours, showing `p50`, `p90`, `p95`, `p98` prediction intervals.
 ```
 
 ```{note}

diff --git a/src/gluonts/dataset/repository/_tsf_datasets.py b/src/gluonts/dataset/repository/_tsf_datasets.py
@@ -238,7 +238,7 @@ def default_prediction_length_from_frequency(freq: str) -> int:
         "T": 60,
         "H": 48,
         "D": 30,
-        "W": 8,
+        "W-SUN": 8,
         "M": 12,
         "Y": 4,
     }

diff --git a/src/gluonts/evaluation/_base.py b/src/gluonts/evaluation/_base.py
@@ -117,7 +117,7 @@ class Evaluator:
         for the given series frequency as returned by `get_seasonality`
     alpha
         Parameter of the MSIS metric from the M4 competition that
-        defines the confidence interval.
+        defines the prediction interval.
         For alpha=0.05 (default) the 95% considered is considered in the
         metric, see
         https://www.m4.unic.ac.cy/wp-content/uploads/2018/03/M4-Competitors-Guide.pdf

diff --git a/src/gluonts/model/forecast.py b/src/gluonts/model/forecast.py
@@ -341,14 +341,14 @@ def plot(
         **kwargs,
     ):
         """
-        Plots the median of the forecast as well as confidence bounds.
+        Plots the median of the forecast as well as prediction interval bounds
         (requires matplotlib and pandas).
 
         Parameters
         ----------
         prediction_intervals : float or list of floats in [0, 100]
-            Confidence interval size(s). If a list, it will stack the error
-            plots for each confidence interval. Only relevant for error styles
+            Prediction interval size(s). If a list, it will stack the error
+            plots for each prediction interval. Only relevant for error styles
             with "ci" in the name.
         show_mean : boolean
             Whether to also show the mean of the forecast.

diff --git a/src/gluonts/model/naive_2/_predictor.py b/src/gluonts/model/naive_2/_predictor.py
@@ -34,7 +34,7 @@ def seasonality_test(past_ts_data: np.array, season_length: int) -> bool:
     Code based on:
     https://github.com/Mcompetitions/M4-methods/blob/master/Benchmarks%20and%20Evaluation.R
     """
-    critical_z_score = 1.645  # corresponds to 90% confidence interval
+    critical_z_score = 1.645  # corresponds to 90% prediction interval
     if len(past_ts_data) < 3 * season_length:
         return False
     else:

diff --git a/src/gluonts/mx/model/n_beats/_ensemble.py b/src/gluonts/mx/model/n_beats/_ensemble.py
@@ -43,7 +43,7 @@
 
 class NBEATSEnsemblePredictor(Predictor):
     """
-    " An ensemble predictor for N-BEATS. Calling '.predict' will result in::
+    An ensemble predictor for N-BEATS. Calling '.predict' will result in::
 
         |predictors|x|dataset|
 

diff --git a/src/gluonts/mx/model/n_beats/_network.py b/src/gluonts/mx/model/n_beats/_network.py
@@ -304,7 +304,7 @@ def initialize_basis(self, F):
 
 class NBEATSTrendBlock(NBEATSBlock):
     """
-    " The NBEATS Block as described in the paper:
+    The NBEATS Block as described in the paper:
     https://arxiv.org/abs/1905.10437. This is the Trend block variant.
 
     Parameters

diff --git a/src/gluonts/mx/model/seq2seq/_mq_dnn_estimator.py b/src/gluonts/mx/model/seq2seq/_mq_dnn_estimator.py
@@ -87,7 +87,7 @@ class MQCNNEstimator(ForkingSeq2SeqEstimator):
         It makes sense to disable this, if you don't have ``feat_dynamic_real``
         for the prediction range.
     seed
-        Will set the specified int seed for numpy anc MXNet if specified.
+        Will set the specified int seed for numpy and MXNet if specified.
         (default: None)
     decoder_mlp_dim_seq
         The dimensionalities of the Multi Layer Perceptron layers of the
@@ -217,7 +217,7 @@ def __init__(
             f"{len(self.dilation_seq)} vs. {len(self.kernel_size_seq)}"
         )
 
-        if seed:
+        if seed is not None:
             np.random.seed(seed)
             mx.random.seed(seed, trainer.ctx)
 

diff --git a/src/gluonts/transform/field.py b/src/gluonts/transform/field.py
@@ -49,7 +49,7 @@ def transform(self, data: DataEntry):
 
 class RemoveFields(SimpleTransformation):
     """
-    " Remove field names if present.
+    Remove field names if present.
 
     Parameters
     ----------