update docs

Author: josesho

docs/source/api.rst

@@ -10,23 +10,27 @@ Loading Data
 
 .. autofunction:: load
 
+
+Computing Effect Sizes
+----------------------
+
+.. autoclass:: dabest._classes.Dabest
+  :members: mean_diff, median_diff, cohens_d, hedges_g, cliffs_delta
+  :member-order: bysource
+
+.. .. autoclass:: dabest._classes.TwoGroupsEffectSize
+
+
 Plotting Data
 -------------
 
-.. autofunction:: dabest._classes.EffectSizeDataFrame.plot
-.. .. autoclass:: dabest._classes.EffectSizeDataFrame
-..    :members: plot
+.. autoclass:: dabest._classes.EffectSizeDataFrame
+  :members: plot, lqrt
+  :member-order: bysource
 
 
-Computing Effect Sizes
-----------------------
 
-.. autoclass:: dabest._classes.TwoGroupsEffectSize
-..
-.. .. autofunction:: dabest._stats_tools.effsize.func_difference
-..
-.. .. autofunction:: dabest._stats_tools.effsize.cohens_d
-..
-.. .. autofunction:: dabest._stats_tools.effsize.hedges_g
-..
-.. .. autofunction:: dabest._stats_tools.effsize.cliffs_delta
+Permutation Tests
+-----------------
+
+.. autoclass:: dabest._classes.PermutationTest

docs/source/conf.py

@@ -46,7 +46,7 @@
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.
 extensions = ['sphinx.ext.autodoc', 'sphinx.ext.napoleon',
-              'sphinx.ext.githubpages', 'sphinx.ext.intersphinx']
+              'sphinx.ext.mathjax', 'sphinx.ext.githubpages', 'sphinx.ext.intersphinx']
 
 # Add mappings
 intersphinx_mapping = {
@@ -67,7 +67,7 @@
 
 # General information about the project.
 project = 'dabest'
-copyright = '2019, Joses W. Ho'
+copyright = '2017-2020, Joses W. Ho'
 author = 'Joses W. Ho'
 
 # The version info for the project you're documenting, acts as replacement for

docs/source/index.rst

@@ -23,7 +23,7 @@ December 2019:
 
 October 2019:
   - v0.2.7 released. A minor bugfix in the handling of wide datasets with unequal Ns in each group. 
-  - v0.2.6 released. This release has one new feature (plotting of estimation plot inside any :py:mod:`matplotlib` :py:class:`Axes`; see the section on :ref:`inset_plot` in the :doc:`tutorial`). There are also two bug patches for the handling of bootstrap plotting, and of dependency installation. 
+  - v0.2.6 released. This release has one new feature (plotting of estimation plot inside any :py:mod:`matplotlib` :py:class:`Axes`; see the section on :ref:`inset plot` in the :doc:`tutorial`). There are also two bug patches for the handling of bootstrap plotting, and of dependency installation. 
 
 September 2019:
   - v0.2.5 released. This release addresses two feature requests, and also patches two bugs: one affecting the paired difference CIs, and one involving NaNs in unused/irrelevant columns.
@@ -44,12 +44,12 @@ Contents
 --------
 
 .. toctree::
-   :maxdepth: 2
-
-   robust-beautiful
-   bootstraps
-   getting-started
-   tutorial
-   release-notes
-   api
-   about
+  :maxdepth: 2
+
+  robust-beautiful
+  bootstraps
+  getting-started
+  tutorial
+  release-notes
+  api
+  about

docs/source/release-notes.rst

@@ -4,10 +4,21 @@
 Release Notes
 =============
 
+
+v0.3.0
+------
+This is a new major release that refactors the statistical test output. All users are strongly encouraged to update to this release.
+
+Main Changes:
+  - the Lq-Likelihood Ratio-Type test results are now computed only when the user calls the `lqrt` property of the `dabest_object.effect_size` :py:class:`EffectSizeDataFrame` object. This refactor was done to mitigate the lengthy computation time the test took. See Issues `#94 <https://github.com/ACCLAB/DABEST-python/issues/94>`_ and `#91 <https://github.com/ACCLAB/DABEST-python/issues/91>`_.
+  - The default hypothesis test reported by calling the `dabest_object.effect_size` :py:class:`EffectSizeDataFrame` object is now the `non-parametric two-sided permutation t-test <https://en.wikipedia.org/wiki/Resampling_(statistics)#Permutation_tests>`_. Conceptually, this hypothesis test mirrors the usage of the bootstrap (to obtain the 95% confidence intervals). Read more at :doc:`tutorial`. See Issue `#92 <https://github.com/ACCLAB/DABEST-python/issues/92>`_ and PR `#93 <https://github.com/ACCLAB/DABEST-python/issues/93>`_.
+  - The minimum version of :py:mod:`numpy` is now v0.17, which has an updated method of generating random samples. The resampling code used in :py:mod:`dabest` has thus been updated as well.
+
+
 v0.2.8
 ------
 
-This release fixes minor bugs, and implements a new statistical test. There are no known breaking changes to the API; hence **all users are strongly encouraged to upgrade to the latest version**.
+This release fixes minor bugs, and implements a new statistical test.
 
 Feature Additions:
   -  Implement `Lq-Likelihood-Ratio-Type Test <https://github.com/alyakin314/lqrt>`_ in statistical output with `PR #85 <https://github.com/ACCLAB/DABEST-python/pull/85>`_; thanks to Adam Li (`@adam2392 <https://github.com/adam2392>`_).
@@ -28,7 +39,7 @@ v0.2.6
 ------
 
 Feature additions:
-  - It is now possible to specify a pre-determined :py:mod:`matplotlib` :py:class:`Axes` to create the estimation plot in. See the new section in the tutorial for more information. (`Pull request #73 <https://github.com/ACCLAB/DABEST-python/pull/73>`_; thanks to Adam Nekimken (`@anekimken <https://github.com/anekimken>`_).
+  - It is now possible to specify a pre-determined :py:mod:`matplotlib` :py:class:`Axes` to create the estimation plot in. See :ref:`inset plot` in the :doc:`tutorial` (`Pull request #73 <https://github.com/ACCLAB/DABEST-python/pull/73>`_; thanks to Adam Nekimken (`@anekimken <https://github.com/anekimken>`_).
   -