Working on benchmarking and documentation

Author: adamisntdead

benchmarking.py

@@ -23,6 +23,7 @@ def bench_qcgpu(n, depth):
 
             if q != 0:
                 state.apply_controlled_gate(x, q, 0)
+
     return time.time() - start
 
 # Qiskit Implementation
@@ -34,18 +35,19 @@ def bench_qiskit(n, depth):
     c = ClassicalRegister(n)
     qc = QuantumCircuit(q, c)
 
+    start = time.time()
+
     for level in range(depth):
         for i in range(n):
             qc.h(q[i])
             qc.t(q[i])
 
             if i != 0:
                 qc.cx(q[i], q[0])
-    qc.measure(q, c)
 
-    start = time.time()
-    
     job_sim = execute(qc, "local_statevector_simulator")
+
+    job_sim.result()
 
     return time.time() - start
 
@@ -68,28 +70,26 @@ def bench_projectq(n, depth):
             if q != qbits[0]:
                 ops.CNOT | (q, qbits[0])
 
-    runtime = time.time() - start
-
     for q in qbits:
         ops.Measure | q
-    eng.flush()
-    return runtime
+    return time.time() - start
 
 # Reporting
 
-functions = bench_qcgpu, bench_qiskit, bench_projectq
+functions = bench_qcgpu, bench_qiskit#, bench_projectq
+# functions = bench_qiskit,
 
 times = {f.__name__: [] for f in functions}
 
 names = []
 means = []
 
-samples = 10
+samples = 100
 for i in range(samples):  # adjust accordingly so whole thing takes a few sec
     progress = i / samples
     print("\rProgress: [{0:50s}] {1:.1f}%".format('#' * int(progress * 50), progress*100), end="", flush=True)
     func = random.choice(functions)
-    t = func(5,1)
+    t = func(20,10)
     times[func.__name__].append(t)
 
 print('')

docs/conf.py

@@ -44,6 +44,7 @@
     'sphinx.ext.mathjax',
     'sphinx.ext.ifconfig',
     'sphinx.ext.githubpages',
+    'sphinx.ext.napoleon'
 ]
 
 # Add any paths that contain templates here, relative to this directory.
@@ -79,7 +80,7 @@
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
 #
-html_theme = 'sphinx_rtd_theme'
+html_theme = 'press'
 
 # Theme options are theme-specific and customize the look and feel of a theme
 # further.  For a list of options available for each theme, see the

docs/index.rst

@@ -1,14 +1,42 @@
-.. include:: ../README.rst
+QCGPU
+=====
+
+.. image:: https://img.shields.io/travis/QCGPU/qcgpu.svg?style=for-the-badge   
+   :alt: Travis (.org)   
+   :target: https://travis-ci.org/QCGPU/qcgpu
+.. image:: https://img.shields.io/pypi/v/qcgpu.svg?style=for-the-badge
+   :target: https://pypi.python.org/pypi/qcgpu
+   :alt: PyPi Version
+.. image:: https://img.shields.io/pypi/l/qcgpu.svg?style=for-the-badge
+   :target: https://pypi.python.org/pypi/qcgpu/
+   :alt: License
+.. image:: https://img.shields.io/github/stars/qcgpu/qcgpu.svg?style=for-the-badge&label=Stars
+   :alt: GitHub stars
+   :target: https://github.com/QCGPU/qcgpu
+
+QCGPU is an open source, high performance library for simulating
+quantum circuits. 
+It takes advantage of hardware acceleration with
+OpenCL.
+Read the `research paper`_.
+
+.. _`research paper`: https://arxiv.org/abs/1805.00988
+
+
+
+Table of Contents
+==================
 
 .. toctree::
    :maxdepth: 2
-   :caption: Contents:
 
-   installing
-
-Indices and tables
-==================
+   install
+   Getting started <quickstart>
+   Software reference <_autodoc/qcgpu>
 
-* :ref:`genindex`
-* :ref:`modindex`
-* :ref:`search`
+.. Python Modules
+    ==============
+    .. autosummary::
+        :nosignatures:
+        qcgpu
+    :ref:`modindex`

docs/install.rst

@@ -0,0 +1,46 @@
+============
+Installation
+============
+
+Prerequisites
+-------------
+
+To use QCGPU you will need to be using `Python 2.7 or later <https://www.python.org/downloads/>`_.
+You will also need to ensure that you have an `OpenCL <https://www.khronos.org/opencl/>`_ implementation installed. 
+This is done by default on MacOS, but you shuld check that ``clinfo`` or some other diagnostic command will run.
+
+You can also use `Anaconda 3 <https://www.continuum.io/downloads>`_, which will have many of the required dependencies already installed.
+
+Installing from PyPI
+--------------------
+
+This library is distributed on `PyPI <https://pypi.python.org/pypi/qcgpu>`_ and can be installed using pip:
+
+.. code:: sh
+
+   $ pip install qcgpu
+
+If you run into any issues, you should try installing from source.
+
+Installing from Source
+----------------------
+
+You can install QCGPU from the source. First, clone the repository off
+GitHub:
+
+.. code:: sh
+
+   $ git clone https://github.com/qcgpu/qcgpu
+
+Then you will need to ``cd`` into the directory, and install the
+requirements.
+
+.. code:: sh
+
+   $ pip install -r requirements.txt
+
+And finally you can install:
+
+.. code:: sh
+
+   $ python setup.py install

docs/installing.rst

@@ -0,0 +1,38 @@
+Getting Started
+===============
+
+When using this library, you will most likely be using the :class:`~qiskit.State` class.
+This class represents the state of a quantum register. 
+Using this class you can apply gates to the register, measure, get the state vector and things like that.
+
+To run a simple quantum circuit, you can use something like this,
+
+.. code-block:: python
+
+    # Import QCGPU
+    import qcgpu
+
+    # Create a new quantum register with 2 qubits
+    register = qcgpu.State(2)
+
+    # Apply a hadamard (H) gate to the first qubit.
+    # You should note that the qubits are zero indexed
+    register.h(0)
+
+    # Add a controlled not (CNOT/CX) gate, with the control as
+    # the first qubit and target as the second.
+    # The register will now be in the bell state.
+    register.cx(0, 1)
+
+    # Perform a measurement with 1000 samples
+    results = register.measure(samples=1000)
+
+    # Show the results
+    print(results)
+
+The output of a measurement gives a dictionary of measurement outcomes,
+along with how often they occurred.
+
+.. code-block:: python
+
+    {'00': 486, '11': 514}