Fix WhatsNew list and Moved Changelog to doc/whats_new

deephyper · Feb 23, 2020 · 9c81cd5 · 9c81cd5
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,199 +1,5 @@
 # Release history
-## Version 0.7.2
-
-## New features
-* Add expected_minimum_random_sampling
-* New plot examples
-* Add more parameter to plot_objective 
-* Return ordereddict in point_asdict
-* update_next() and get_results() added to Optimize
-
-## Bug fixes
-
-* Fix searchcv rank (issue #831)
-* Fix random forest regressor (issue #766)
-* Fix doc examples
-* Fix integer normalize by using round()
-* Fix random forest regressor (Add missing min_impurity_decrease)
-
-## Maintenance
-* Fix license detection in github
-* Add doctest to CI
-
-## Version 0.7.1
-
-### New features
-
-* Sphinx documentation
-* notebooks are replaced by sphinx-gallery
-* New StringEncoder, can be used in Categoricals
-* Remove string conversion in Identity
-* dtype can be set in Integer and Real
-
-### Bug fixes
-
-* Fix categorical space (issue #821)
-* int can be set as dtype to fix issue #790
-
-### Maintenance
-
-* Old pdoc scripts are removed and replaced by sphinx
-
-## Version 0.7
-
-### New features
-
-* Models queue has now a customizable size (model_queue_size).
-* Add log-uniform prior to Integer space
-* Support for plotting categorical dimensions
-
-### Bug fixes
-
-* Allow BayesSearchCV to work with sklearn 0.21 
-* Reduce the amount of deprecation warnings in unit tests
-
-### Maintenance
-
-* joblib instead of sklearn.externals.joblib 
-* Improve travis CI unit tests (Different sklearn version are checked)
-* Added `versioneer` support, to keep things simple and to fix pypi deploy
-
-## Version 0.6
-
-Highly composite six.
-
-### New features
-
-* `plot_regret` function for plotting the cumulative regret; 
-The purpose of such plot is to access how much an optimizer 
-is effective at picking good points.
-* `CheckpointSaver` that can be used to save a 
-checkpoint after each iteration with skopt.dump
-* `Space.from_yaml()`
- to allow for external file to define Space parameters
-
-### Bug fixes
-
-* Fixed numpy broadcasting issues in gaussian_ei, gaussian_pi 
-* Fixed build with newest scikit-learn 
-* Use native python types inside BayesSearchCV
-* Include fit_params in BayesSearchCV refit 
-
-### Maintenance
-
-* Added `versioneer` support, to reduce changes with new version of the `skopt`
-
-## Version 0.5.2
-
-### Bug fixes
-
-* Separated `n_points` from `n_jobs` in `BayesSearchCV`.
-* Dimensions now support boolean np.arrays.
-
-### Maintenance
-
-* `matplotlib` is now an optional requirement (install with `pip install 'scikit-optimize[plots]'`)
-
-## Version 0.5
-
-High five!
-
-### New features
-
-* Single element dimension definition, which can be used to
-fix the value of a dimension during optimization.
-* `total_iterations` property of `BayesSearchCV` that
-counts total iterations needed to explore all subspaces.
-* Add iteration event handler for `BayesSearchCV`, useful
-for early stopping inside `BayesSearchCV` search loop.
-* added `utils.use_named_args` decorator to help with unpacking named dimensions
-when calling an objective function.
-
-### Bug fixes
-
-* Removed redundant estimator fitting inside `BayesSearchCV`.
-* Fixed the log10 transform for Real dimensions that would lead to values being
-  out of bounds.
-
-## Version 0.4
-
-Go forth!
-
-### New features
-
-* Support early stopping of optimization loop.
-* Benchmarking scripts to evaluate performance of different surrogate models.
-* Support for parallel evaluations of the objective function via several
-  constant liar stategies.
-* BayesSearchCV as a drop in replacement for scikit-learn's GridSearchCV.
-* New acquisition functions "EIps" and "PIps" that takes into account
-  function compute time.
-
-### Bug fixes
-
-* Fixed inference of dimensions of type Real.
-
-### API changes
-
-* Change interface of GradientBoostingQuantileRegressor's predict method to
-  match return type of other regressors
-* Dimensions of type Real are now inclusive of upper bound.
-
-
-## Version 0.3
-
-Third time's a charm.
-
-### New features
-
-* Accuracy improvements of the optimization of the acquisition function
-by pre-selecting good candidates as starting points when
-using `acq_optimizer='lbfgs'`.
-* Support a ask-and-tell interface. Check out the `Optimizer` class if you need
-fine grained control over the iterations.
-* Parallelize L-BFGS minimization runs over the acquisition function.
-* Implement weighted hamming distance kernel for problems with only categorical dimensions.
-* New acquisition function `gp_hedge` that probabilistically chooses one of `EI`, `PI`
-or `LCB` at every iteration depending upon the cumulative gain.
-
-### Bug fixes
-* Warnings are now raised if a point is chosen as the candidate optimum multiple
-times.
-* Infinite gradients that were raised in the kernel gradient computation are
-now fixed.
-* Integer dimensions are now normalized to [0, 1] internally in `gp_minimize`.
-
-### API Changes.
-* The default `acq_optimizer` function has changed from `"auto"` to `"lbfgs"`
-in `gp_minimize`.
-
-
-## Version 0.2
-
-### New features
-
-* Speed improvements when using `gp_minimize` with `acq_optimizer='lbfgs'` and
-`acq_optimizer='auto'` when all the search-space dimensions are Real.
-* Persistence of minimization results using `skopt.dump` and `skopt.load`.
-* Support for using arbitrary estimators that implement a
-`return_std` argument in their `predict` method by means of `base_minimize` from `skopt.optimizer.`
-* Support for tuning noise in `gp_minimize` using the `noise` argument.
-* `TimerCallback` in `skopt.callbacks` to log the time between iterations of
-the minimization loop.
-
-
-## Version 0.1
-
-First light!
-
-### New features
-
-* Bayesian optimization via `gp_minimize`.
-* Tree-based sequential model-based optimization via `forest_minimize` and `gbrt_minimize`, with support for multi-threading.
-* Support of LCB, EI and PI as acquisition functions.
-* Plotting functions for inspecting convergence, evaluations and the objective function.
-* API for specifying and sampling from a parameter space.
-
+See https://scikit-optimize.github.io/dev/whats_new.html
 
 # Contributors
 

diff --git a/README.rst b/README.rst
@@ -139,7 +139,7 @@ create a new issue and work through the following checklist:
 * update the version tag in ``__init__.py``
 * update the version tag mentioned in the README
 * check if the dependencies in ``setup.py`` are valid or need unpinning
-* check that the ``CHANGELOG.md`` is up to date
+* check that the ``doc/whats_new/v0.X.rst`` is up to date
 * did the last build of master succeed?
 * create a `new release <https://github.com/scikit-optimize/scikit-optimize/releases>`__
 * ping `conda-forge <https://github.com/conda-forge/scikit-optimize-feedstock>`__

diff --git a/build_tools/circle/build_test_pypy.sh b/build_tools/circle/build_test_pypy.sh
diff --git a/doc/contents.rst b/doc/contents.rst
@@ -14,6 +14,7 @@ Table Of Contents
 .. toctree::
     :maxdepth: 2
 
+    preface
     getting_started
     user_guide
     auto_examples/index

diff --git a/doc/preface.rst b/doc/preface.rst
@@ -0,0 +1,25 @@
+.. This helps define the TOC ordering for "about us" sections. Particularly
+   useful for PDF output as this section is not linked from elsewhere.
+
+.. Places global toc into the sidebar
+
+:globalsidebartoc: True
+
+.. _preface_menu:
+
+.. include:: includes/big_toc_css.rst
+.. include:: tune_toc.rst
+
+==========================
+Welcome to scikit-optimize
+==========================
+
+|
+
+.. toctree::
+    :maxdepth: 2
+
+    install
+    whats_new
+
+|
diff --git a/doc/templates/index.html b/doc/templates/index.html
@@ -106,7 +106,7 @@ <h4 class="sk-landing-subheader text-dark font-italic mb-3">Sequential model-bas
         <h4 class="sk-landing-call-header">News</h4>
         <ul class="sk-landing-call-list list-unstyled">
         <li><strong>On-going development:</strong>
-        <a href="whats_new.html"><strong>What's new</strong> (Changelog)</a>
+        <a href="https://scikit-optimize.github.io/dev/whats_new.html"><strong>What's new</strong> (Changelog)</a>
         </li>
         <li><strong>Feb 2020.</strong> scikit-optimize 0.7.2  (<a href="whats_new/v0.7.2.html">Changelog</a>).
         <li><strong>Feb 2020.</strong> scikit-optimize 0.7.1  (<a href="whats_new/v0.7.1.html">Changelog</a>).

diff --git a/doc/whats_new.rst b/doc/whats_new.rst
@@ -7,10 +7,8 @@ Release notes for all scikit-optimize releases are linked in this this page.
 
 .. toctree::
     :maxdepth: 1
+
     Version 0.8 <whats_new/v0.8.rst>
-    Version 0.7.3 <whats_new/v0.7.3.rst>
-    Version 0.7.2 <whats_new/v0.7.2.rst>
-    Version 0.7.1 <whats_new/v0.7.1.rst>
     Version 0.7 <whats_new/v0.7.rst>
     Version 0.6 <whats_new/v0.6.rst>
     Version 0.5 <whats_new/v0.5.rst>

diff --git a/doc/whats_new/_contributors.rst b/doc/whats_new/_contributors.rst
@@ -0,0 +1,12 @@
+.. role:: raw-html(raw)
+   :format: html
+
+.. role:: raw-latex(raw)
+   :format: latex
+
+.. |MajorFeature| replace:: :raw-html:`<span class="badge badge-success">Major Feature</span>` :raw-latex:`{\small\sc [Major Feature]}`
+.. |Feature| replace:: :raw-html:`<span class="badge badge-success">Feature</span>` :raw-latex:`{\small\sc [Feature]}`
+.. |Efficiency| replace:: :raw-html:`<span class="badge badge-info">Efficiency</span>` :raw-latex:`{\small\sc [Efficiency]}`
+.. |Enhancement| replace:: :raw-html:`<span class="badge badge-info">Enhancement</span>` :raw-latex:`{\small\sc [Enhancement]}`
+.. |Fix| replace:: :raw-html:`<span class="badge badge-danger">Fix</span>` :raw-latex:`{\small\sc [Fix]}`
+.. |API| replace:: :raw-html:`<span class="badge badge-warning">API Change</span>` :raw-latex:`{\small\sc [API Change]}`
diff --git a/doc/whats_new/v0.7.1.rst b/doc/whats_new/v0.7.1.rst
diff --git a/doc/whats_new/v0.7.2.rst b/doc/whats_new/v0.7.2.rst
diff --git a/doc/whats_new/v0.7.3.rst b/doc/whats_new/v0.7.3.rst