[doc] Update install instructions

+ Minor doc fix in model.py

README.md

@@ -42,7 +42,7 @@ The [documentation](https://best.readthedocs.io) describes the API in detail.
 
 ## Installation ##
 
-Ensure your Python version is sufficiently up-to-date:
+Ensure your Python version is sufficiently up-to-date (at least 3.5.4):
 
 ```bash
 $ python --version
@@ -51,7 +51,7 @@ Python 3.5.6
 
 Then install with Pip:
 ```bash
-$ pip install https://github.com/treszkai/best/archive/master.tar.gz
+$ pip install best
 ```
 
 ## Developer notes ##

best/model.py

@@ -43,10 +43,10 @@ def model(self) -> pm.Model:
         pass
 
     @abstractmethod
-    def observed_data(self, group_id):
+    def observed_data(self, group_id: int):
         """Return the observed data as a NumPy array
 
-        (This property is accessible primarily for internal purposes.)
+        (This method is accessible primarily for internal purposes.)
         """
         pass
 
@@ -123,7 +123,7 @@ def version(self):
     def model(self):
         return self._model
 
-    def observed_data(self, group_id):
+    def observed_data(self, group_id: int):
         if group_id == 1:
             return self.y
         else:
@@ -200,7 +200,7 @@ def version(self):
     def model(self):
         return self._model
 
-    def observed_data(self, group_id):
+    def observed_data(self, group_id: int):
         if group_id == 1:
             return self.y1
         elif group_id == 2:
@@ -241,28 +241,32 @@ def trace(self) -> MultiTrace:
         """
         return self._trace
 
-    def observed_data(self, group_id):
+    def observed_data(self, group_id: int):
+        """Return the observed data as a NumPy array
+
+        (This method is accessible primarily for internal purposes.)
+        """
         return self.model.observed_data(group_id)
 
     def summary(self, alpha=None, credible_mass: float = 0.95):
         """Return summary statistics of the results
 
         Parameters
         ----------
+        credible_mass : float
+            The highest posterior density intervals in the summary will cover
+            credible_mass * 100% of the probability mass.
+            For example, credible_mass=0.95 results in 95% credible intervals.
+            Default: 0.95.
         alpha : float, optional
             Deprecated argument to specify the width of the HDIs.
             ``alpha=0.05`` is equivalent to ``credible_mass=0.95``.
             If specified, the ``credible_mass`` argument is ignored.
-            Default: ``None``, use the credible_mass argument.)
+            Default: ``None``, use the ``credible_mass`` argument instead.)
 
             *Deprecated since version 2.1.0:*
             Use of this argument is deprecated since version 2.1.0,
             and will be removed in version 3.0.0.
-        credible_mass : float
-            The highest posterior density intervals in the summary will cover
-            credible_mass * 100% of the probability mass.
-            For example, credible_mass=0.95 results in 95% credible intervals.
-            Default: 0.95.
         """
 
         return pm.summary(self.trace, alpha=alpha or (1 - credible_mass))

docs/index.rst

@@ -78,7 +78,7 @@ and can be installed with *pip*:
 
 .. code-block:: bash
 
-   pip install https://github.com/treszkai/best/archive/master.zip
+   pip install best
 
 This command installs the following dependencies:
 
@@ -89,10 +89,12 @@ This command installs the following dependencies:
 Get in touch
 ------------
 
-If you have trouble installing or using `best`, or understanding the results, or you found an error,
+If you find the documentation lacking or you have found an error,
 please `open an issue <https://github.com/treszkai/best/issues>`_  at the project's GitHub page,
 or open a `pull request <https://github.com/treszkai/best/pulls>`_ if you have a proposed solution.
 
+Your feedback and contribution is welcome!
+
 Further documentation
 ---------------------
 

setup.py

@@ -1,22 +1,23 @@
 from setuptools import setup
 
 
-with open("README.md", "r") as fh:
+with open('README.md', 'r') as fh:
     long_description = fh.read()
 
 setup(name='best',
       description='Bayesian estimation supersedes the t-test',
       author='Andrew Straw and Laszlo Treszkai',
       author_email='laszlo.treszkai@gmail.com',
       long_description=long_description,
-      long_description_content_type="text/markdown",
+      long_description_content_type='text/markdown',
       url='https://github.com/treszkai/best',
       version='2.1.0',
       packages=['best'],
       classifiers=[
-              "Programming Language :: Python :: 3",
-              "License :: OSI Approved :: MIT License",
-              "Operating System :: OS Independent",
+              'Programming Language :: Python :: 3',
+              'License :: OSI Approved :: MIT License',
+              'Operating System :: OS Independent',
       ],
       license='MIT',
-      )
+      python_requires='>=3.5',
+)