Adapt docs to PennyLane theme (#64)

* redo docs

* fix doctree error

* Update README.rst

Co-authored-by: Theodor <theodor@xanadu.ai>

* Update README.rst

Co-authored-by: Theodor <theodor@xanadu.ai>

* update gitignore to not commit built folder

* temporarily whitelist code folder

* delete api files

* blacklist again

* clean pic

* Update doc/devices/numpy_wavefunction.rst

Co-authored-by: Theodor <theodor@xanadu.ai>

* Update doc/devices/qpu.rst

Co-authored-by: Theodor <theodor@xanadu.ai>

* Update doc/devices/qvm.rst

Co-authored-by: Theodor <theodor@xanadu.ai>

* Update doc/devices/qvm.rst

Co-authored-by: Theodor <theodor@xanadu.ai>

* Update README.rst

Co-authored-by: antalszava <antalszava@gmail.com>

* Update doc/devices/numpy_wavefunction.rst

Co-authored-by: antalszava <antalszava@gmail.com>

* Update doc/devices/numpy_wavefunction.rst

Co-authored-by: antalszava <antalszava@gmail.com>

* code review

* polish

* Update doc/devices/numpy_wavefunction.rst

Co-authored-by: antalszava <antalszava@gmail.com>

* Update doc/devices/numpy_wavefunction.rst

* add requirements file

* add pyquil as requirement

* change pennylane version in requirements

* make pygments a docs requirement

* Update README.rst

Co-authored-by: Nathan Killoran <co9olguy@users.noreply.github.com>

* undo deletion of importing gates

* don't import superfluous gates

* increase number of flaky tuns

Co-authored-by: Theodor <theodor@xanadu.ai>
Co-authored-by: antalszava <antalszava@gmail.com>
Co-authored-by: Josh Izaac <josh146@gmail.com>
Co-authored-by: Nathan Killoran <co9olguy@users.noreply.github.com>

.gitignore

@@ -1,7 +1,16 @@
+*~
 *.pyc
-.vscode/*
-.pytest_cache/*
-build/*
-dist/*
-*egg-info*
+doc/_build
+build
+dist
+PennyLane_Forest.egg-info
 .idea
+*.ipynb
+*.ipynb_checkpoints
+*.egg-info*
+.coverage
+coverage_html_report/*
+notebooks/*
+.pytest_cache/*
+.vscode/*
+doc/code/api/*

README.rst

@@ -27,21 +27,23 @@ PennyLane Forest Plugin
 
 .. header-start-inclusion-marker-do-not-remove
 
-Contains the PennyLane Forest plugin. This plugin allows three Rigetti devices to work with
+Contains the PennyLane Forest plugin. This plugin allows different Rigetti devices to work with
 PennyLane --- the wavefunction simulator, the Quantum Virtual Machine (QVM), and Quantum Processing
 Units (QPUs).
 
 `pyQuil <https://pyquil.readthedocs.io>`_ is a Python library for quantum programming using the
 quantum instruction language (Quil) --- resulting quantum programs can be executed using the
-`Rigetti Forest SDK <https://www.PennyLaneAI.com/forest>`_ and the `Rigetti QCS
-<https://www.PennyLaneAI.com/qcs>`_.
+`Rigetti Forest SDK <https://pyquil-docs.rigetti.com/en/stable/>`_ and the `Rigetti QCS
+<https://qcs.rigetti.com/>`_.
 
-`PennyLane <https://pennylane.ai>`_ is a machine learning library for optimization and automatic
-differentiation of hybrid quantum-classical computations.
+`PennyLane <https://pennylane.readthedocs.io>`__ is a cross-platform Python library for quantum machine
+learning, automatic differentiation, and optimization of hybrid quantum-classical computations.
 
 
 .. header-end-inclusion-marker-do-not-remove
 
+The plugin documentation can be found here: `<https://pennylane-forest.readthedocs.io/en/latest/>`__.
+
 Features
 ========
 
@@ -54,8 +56,8 @@ Features
 * All provided devices support all core qubit PennyLane operations and observables.
 
 
-* Provides custom PennyLane operations to cover additional pyQuil operations: ``T``, ``S``,
-  ``ISWAP``, ``CCNOT``, ``PSWAP``, and many more. Every custom operation supports analytic
+* Provides custom PennyLane operations to cover additional pyQuil operations:
+  ``ISWAP``, ``PSWAP``, and ``CPHASE``. Every custom operation supports analytic
   differentiation.
 
 * Combine Forest and the Rigetti Cloud Services with PennyLane's automatic differentiation and
@@ -67,36 +69,73 @@ Features
 Installation
 ============
 
-PennyLane-Forest requires both PennyLane and pyQuil. It can be installed via ``pip``:
+PennyLane-Forest, as well as all required Python packages mentioned above, can be installed via ``pip``:
+::
 
-.. code-block:: bash
+   	$ python -m pip install pennylane-forest
 
-    $ python -m pip install pennylane-forest
 
+Make sure you are using the Python 3 version of pip.
 
-.. installation-end-inclusion-marker-do-not-remove
+Alternatively, you can install PennyLane-Forest from the source code by navigating to the top-level directory and running
+::
+
+	$ python setup.py install
+
+Dependencies
+~~~~~~~~~~~~
+
+.. highlight:: bash
+
+PennyLane-Forest requires the following libraries be installed:
+
+* `Python <http://python.org/>`_ >=3.6
+
+as well as the following Python packages:
+
+* `PennyLane <http://pennylane.readthedocs.io/>`_
+* `pyQuil <https://pyquil-docs.rigetti.com/en/stable/>`_
+
+If you currently do not have Python 3 installed, we recommend
+`Anaconda for Python 3 <https://www.anaconda.com/download/>`_, a distributed version
+of Python packaged for scientific computation.
+
+Additionally, if you would like to compile the quantum instruction language (Quil) and run it
+locally using a quantum virtual machine (QVM) server, you will need to download and install the
+Forest software development kit (SDK):
 
-Getting started
-===============
+* `Forest SDK <https://pyquil-docs.rigetti.com/en/stable/>`_
 
-Once the PennyLane-Forest plugin is installed, the three provided pyQuil devices can be accessed straight away in PennyLane.
+Alternatively, you may sign up for Rigetti's Quantum Cloud Services (QCS) to acquire a Quantum Machine
+Image (QMI) which will allow you to compile your quantum code and run on real quantum processing units (QPUs),
+or on a preinstalled QVM. Note that this requires a valid QCS account.
 
-You can instantiate these devices for PennyLane as follows:
+* `Quantum Cloud Services <https://docs.rigetti.com/en/>`_
 
-.. code-block:: python
+Tests
+~~~~~
 
-    import pennylane as qml
-    dev_numpy = qml.device('forest.numpy_wavefunction', wires=2)
-    dev_simulator = qml.device('forest.wavefunction', wires=2)
-    dev_pyqvm = qml.device('forest.qvm', device='2q-pyqvm', shots=1000)
-    dev_qvm = qml.device('forest.qvm', device='2q-qvm', shots=1000)
-    dev_qpu = qml.device('forest.qpu', device='Aspen-8', shots=1000)
+To test that the PennyLane-Forest plugin is working correctly you can run
+
+.. code-block:: bash
+
+    $ make test
+
+in the source folder.
+
+Documentation
+~~~~~~~~~~~~~
+
+To build the HTML documentation, go to the top-level directory and run:
+
+.. code-block:: bash
+
+  $ make docs
 
-These devices can then be used just like other devices for the definition and evaluation of QNodes
-within PennyLane. For more details, see the `plugin usage guide
-<https://pennylane-forest.readthedocs.io/en/latest/usage.html>`_ and refer to the PennyLane
-documentation.
 
+The documentation can then be found in the ``doc/_build/html/`` directory.
+
+.. installation-end-inclusion-marker-do-not-remove
 
 Contributing
 ============
@@ -121,7 +160,7 @@ If you are doing research using PennyLane and PennyLane-Forest, please cite `our
     Zeyue Niu, Antal Száva, and Nathan Killoran.
     *PennyLane: Automatic differentiation of hybrid quantum-classical computations.* 2018. arXiv:1811.04968
 
-
+.. support-start-inclusion-marker-do-not-remove
 
 Support
 =======
@@ -143,4 +182,4 @@ License
 PennyLane-Forest is **free** and **open source**, released under the BSD 3-Clause `license
 <https://github.com/PennyLaneAI/pennylane-forest/blob/master/LICENSE>`_.
 
-.. license-end-inclusion-marker-do-not-remove
+.. license-end-inclusion-marker-do-not-remove

doc/Makefile

@@ -4,7 +4,7 @@
 # You can set these variables from the command line.
 SPHINXOPTS    =
 SPHINXBUILD   = python3 -msphinx
-SPHINXPROJ    = PennyLane
+SPHINXPROJ    = PennyLane-Forest
 SOURCEDIR     = .
 BUILDDIR      = _build