Release of 0.4.0 (#78)

Release of 0.4.0
linkedin · Jul 15, 2022 · 5a6bcec · 5a6bcec
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diff --git a/AUTHORS.rst b/AUTHORS.rst
@@ -6,18 +6,18 @@ Development Leads
 -----------------
 
 * Reza Hosseini <rhosseini@linkedin.com> (Core Algorithms and Models)
-* Albert Chen <abchen@linkedin.com> (Modeling Framework, Templates, Auto-tuning)
+* Albert Chen <abchen@linkedin.com> (Modeling Framework, Templates, Auto-Tuning)
 
 Authors
 -------
 * Reza Hosseini
 * Albert Chen
 * Kaixu Yang
 * Sayan Patra
+* Yi Su
 * Rachit Arora
 
 Other Contributors
 ------------------
 * Saad Eddin Al Orjany
 * Rachit Kumar
-* Yi Su
diff --git a/HISTORY.rst b/HISTORY.rst
@@ -2,6 +2,38 @@
 History
 =======
 
+0.4.0 (2022-07-15)
+------------------
+
+* New features and methods
+    * @Reza Hosseini: Forecast interpretability. Forecasts can now be broken down to grouped components: trend, seasonality, events, autoregression, regressors, intercept, etc.
+    * @Sayan Patra: Enhanced components plot. Now supports autoregression, lagged regressors, residuals; adds support for centering.
+    * @Kaixu Yang: Auto model components. (1) seasonality inferrer (2) holiday inferrer (3) automatic growth.
+    * @Kaixu Yang: Lag-based estimator. Supports lag-based forecasts such as week-over-week.
+    * @Reza Hosseini: Fast simulation option. Provides a better accuracy and speed for mean prediction when simulation is used in autoregression.
+    * @Kaixu Yang: Quantile regression option for Silverkite `fit_algorithm`.
+
+* New model templates
+    * @Kaixu Yang: AUTO. Automatically chooses templates based on the data frequency, forecast horizon and evaluation configs.
+    * @Reza Hosseini, @Kaixu Yang: SILVERKITE_MONTHLY - a SimpleSilverkite template designed for monthly time series.
+    * @Kaixu Yang: SILVERKITE_WOW. Uses Silverkite to model seasonality, growth and holiday effects, and then uses week-over-week to fit the residuals. The final prediction is the total of the two models.
+
+* New datasets
+    * 4 hourly datasets: Solar Power, Wind Power, Electricity, San Francisco Bay Area Traffic.
+    * 1 daily dataset: Bitcoin Transactions.
+    * 2 monthly datasets: Sunspot, FRED House Supply.
+
+* Library enhancements and bug fixes
+    * The SILVERKITE template has been updated to include automatic autoregression and changepoint detection.
+    * Renamed `SilverkiteMultistageEstimator` to `MultistageForecastEstimator`.
+    * Renamed the normalization method "min_max" to "zero_to_one".
+    * @Reza Hosseini: Added normalization methods: "minus_half_to_half", "zero_at_origin".
+    * @Albert Chen: Updated tutorials.
+    * @Yi Su: Upgraded fbprophet 0.5 to prophet 1.0.
+    * @Yi Su: Upgraded holidays to 0.13.
+    * @Albert Chen @Kaixu Yang @Yi Su: Speed optimization for Silverkite algorithms.
+    * @Albert Chen @Reza Hosseini @Kaixu Yang @Sayan Patra @Yi Su: Other library enhancements and bug fixes.
+
 0.3.0 (2021-12-14)
 ------------------
 

diff --git a/docs/conf.py b/docs/conf.py
@@ -13,6 +13,7 @@
 sys.path.insert(0, os.path.abspath(os.path.join("..")))  # adds path to find greykite folder during doc build.
 
 from sphinx_gallery.sorting import FileNameSortKey
+
 from greykite.common.sphinx_plotly import plotly_sg_scraper
 
 # -- Path setup --------------------------------------------------------------
@@ -224,11 +225,13 @@
     'examples_dirs': [
         'nbpages/quickstart',
         'nbpages/tutorials',
+        'nbpages/templates'
     ],
     # where to save gallery generated output (added to gitignore)
     'gallery_dirs': [
         'gallery/quickstart',
         'gallery/tutorials',
+        'gallery/templates'
     ],
     'within_subsection_order': FileNameSortKey,  # alphanumeric order within a gallery
     'line_numbers': True,
@@ -243,6 +246,7 @@
     },
     'image_scrapers': image_scrapers,
     # 'default_thumb_file': default_thumb_file,
+    'capture_repr': ('_repr_html_', '__repr__'),
 }
 
 # Napoleon settings

diff --git a/docs/figures/multistage_forecast.png b/docs/figures/multistage_forecast.png
diff --git a/docs/index.rst b/docs/index.rst
@@ -26,6 +26,7 @@ Welcome to Greykite! View the contents to get started.
 
    gallery/quickstart/index
    gallery/tutorials/index
+   gallery/templates/index
 
 .. toctree::
    :maxdepth: 1

diff --git a/docs/nbpages/quickstart/0100_simple_forecast.py b/docs/nbpages/quickstart/0100_simple_forecast.py
@@ -54,17 +54,18 @@
 # %%
 # Create a forecast
 # -----------------
-# You can pick the ``PROPHET`` or ``SILVERKITE``
-# forecasting model template. (see :doc:`/pages/stepbystep/0100_choose_model`).
+# You can choose from many available
+# models (see :doc:`/pages/stepbystep/0100_choose_model`).
 #
-# In this example, we use ``SILVERKITE``.
-# You may also use ``PROPHET`` to see how a third-party library
-# is leveraged in the same framework.
+# In this example, we choose the "AUTO" model template,
+# which uses the Silverkite algorithm with automatic parameter configuration
+# given the input data frequency, forecast horizon and evaluation configs.
+# We recommend starting with the "AUTO" template for most use cases.
 forecaster = Forecaster()  # Creates forecasts and stores the result
 result = forecaster.run_forecast_config(  # result is also stored as `forecaster.forecast_result`.
     df=df,
     config=ForecastConfig(
-        model_template=ModelTemplateEnum.SILVERKITE.name,
+        model_template=ModelTemplateEnum.AUTO.name,
         forecast_horizon=365,  # forecasts 365 steps ahead
         coverage=0.95,         # 95% prediction intervals
         metadata_param=metadata
@@ -207,10 +208,10 @@
 #
 # See the following guides:
 #
-# * :doc:`/gallery/quickstart/0200_changepoint_detection`
-# * :doc:`/gallery/quickstart/0300_seasonality`
-# * :doc:`/gallery/quickstart/0400_model_summary`
-# * :doc:`/gallery/quickstart/0500_grid_search`
+# * :doc:`/gallery/quickstart/01_exploration/0100_changepoint_detection`
+# * :doc:`/gallery/quickstart/01_exploration/0300_seasonality_plots`
+# * :doc:`/gallery/quickstart/02_interpretability/0100_model_summary`
+# * :doc:`/gallery/quickstart/03_benchmark/0100_grid_search`
 #
 # For example, for this dataset, you could add changepoints to
 # handle the change in trend around 2014 and avoid the overprediction
@@ -228,5 +229,5 @@
 # For details about the model templates and how to set model
 # components, see the following guides:
 #
-# * :doc:`/gallery/tutorials/0200_templates`
+# * :doc:`/gallery/templates/0100_template_overview`
 # * :doc:`/pages/stepbystep/0000_stepbystep`