{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext line_profiler\n",
    "%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import set_matplotlib_formats\n",
    "import numpy as np\n",
    "import qcgpu\n",
    "from projectq import MainEngine\n",
    "import projectq.ops as ops\n",
    "from projectq.backends import Simulator\n",
    "import sys\n",
    "import time\n",
    "\n",
    "set_matplotlib_formats('png', 'pdf')\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_qcgpu_state(state):\n",
    "    labels = map(\n",
    "        lambda i: np.binary_repr(i, state.num_qubits), \n",
    "        range(0, 2**state.num_qubits)\n",
    "    )\n",
    "\n",
    "    y_pos = np.arange(len(labels))\n",
    "    performance = list(state.probabilities())\n",
    " \n",
    "    plt.bar(y_pos, performance, align='center')\n",
    "    plt.xticks(y_pos, labels)\n",
    "    plt.ylabel('Amplitude')\n",
    "    plt.title('Probability Amplitudes')\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bench_qcgpu(n, depth):\n",
    "    state = qcgpu.State(n)\n",
    "\n",
    "    h = qcgpu.gate.h()\n",
    "    x = qcgpu.gate.x()\n",
    "    sqrt_x = qcgpu.gate.sqrt_x()\n",
    "\n",
    "    print('started')\n",
    "    start = time.time()\n",
    "\n",
    "    for level in range(depth):\n",
    "        for q in range(n):\n",
    "    \n",
    "            state.apply_gate(h, q)\n",
    "            state.apply_gate(sqrt_x, q)\n",
    "\n",
    "            if q != 0:\n",
    "                state.apply_controlled_gate(x, q, 0)\n",
    "        \n",
    "    runtime = time.time() - start\n",
    "    print('ended: ', runtime)\n",
    "    return runtime\n",
    "    \n",
    "def bench_projectq(n, depth):\n",
    "    eng = MainEngine(backend=Simulator(gate_fusion=True), engine_list=[])\n",
    "    qbits = eng.allocate_qureg(n)\n",
    "\n",
    "    print('started')\n",
    "    start = time.time()\n",
    "\n",
    "    for level in range(depth):\n",
    "        for q in qbits:\n",
    "            ops.H | q\n",
    "            ops.SqrtX | q\n",
    "            if q != qbits[0]:\n",
    "                ops.CNOT | (q, qbits[0])\n",
    "\n",
    "    runtime = time.time() - start\n",
    "    print('ended: ', runtime)\n",
    "\n",
    "    for q in qbits:\n",
    "        ops.Measure | q\n",
    "    eng.flush()\n",
    "    return runtime\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# h = qcgpu.gate.h()\n",
    "# x = qcgpu.gate.x()\n",
    "# s = qcgpu.gate.s()\n",
    "# t = qcgpu.gate.t()\n",
    "# y = qcgpu.gate.y()\n",
    "# z = qcgpu.gate.z()\n",
    "\n",
    "# # Random Circuit\n",
    "# state = qcgpu.State(5)\n",
    "\n",
    "# state.apply_gate(h, 0)\n",
    "# state.apply_gate(t, 0)\n",
    "# state.apply_gate(y, 0)\n",
    "# state.apply_gate(z, 0)\n",
    "# state.apply_gate(h, 0)\n",
    "\n",
    "# state.num_qubits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "started\n",
      "('ended: ', 0.2988259792327881)\n"
     ]
    }
   ],
   "source": [
    "%lprun -f bench_qcgpu bench_qcgpu(26,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# bench_projectq(26,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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