Extended documentation

docs/source/api/models.rst

@@ -9,3 +9,6 @@ Calibration methods
 .. automodule:: pycalib.models
     :members:
 
+.. automodule:: pycalib.models.calibrators
+    :members:
+

docs/source/usage/installation.rst

@@ -5,8 +5,21 @@
 Installation
 ============
 
-In order to install PyCalib 
+There are multiple ways to install PyCalib. The simplest way is to use the
+packaged version available in the Python Package Index PyPI. Further details of
+the packaged version can be found at https://pypi.org/project/pycalib/
 
-```
-pip install pycalib
-```
+In order to install PyCalib from PyPI just run the following command
+
+.. code-block:: bash
+
+    pip install pycalib
+
+This will install the library into your current Python environment. You can
+check that the library is available in your environment by running
+
+.. code-block:: bash
+
+    python -c "import pycalib; print(pycalib.__version__)"
+
+which if successful should print the installed version in the standard output.

docs/source/usage/quickstart.rst

@@ -10,25 +10,27 @@ following:
 
 First choose the calibration method you want to use
 
-```
-from pycalib.models import IsotonicCalibration
-cal = IsotonicCalibration()
-```
+.. code-block:: python
+
+    from pycalib.models import IsotonicCalibration
+    cal = IsotonicCalibration()
 
 Now we can put together a probabilistic classifier with the chosen calibration
 method
 
-```
-from pycalib.models import CalibratedModel
+.. code-block:: python
+
+    from pycalib.models import CalibratedModel
 
-cal_clf = CalibratedModel(base_estimator=clf, method=cal)
-```
+    cal_clf = CalibratedModel(base_estimator=clf, calibrator=cal)
 
 Now you can train both classifier and calibrator all together.
 
-```
-from sklearn.datasets import load_iris
+.. code-block:: python
+
+    from sklearn.datasets import load_iris
+
+    dataset = load_iris()
+    cal_clf.fit(dataset.data, dataset.target)
 
-dataset = load_iris()
-cal_clf.fit(dataset.data, dataset.target)
-```
+For a full example check the Section Examples quick start.