{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "%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",
    "\n",
    "set_matplotlib_formats('png', 'pdf')\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_qubits = 2\n",
    "\n",
    "state = qcgpu.State(num_qubits)\n",
    "h = qcgpu.gate.h()\n",
    "x = qcgpu.gate.x()\n",
    "y = qcgpu.gate.y()\n",
    "z = qcgpu.gate.z()\n",
    "\n",
    "state.apply_gate(h, 0)\n",
    "state.apply_gate(y, 0)\n",
    "state.apply_gate(z, 1)\n",
    "state.apply_gate(y, 0)\n",
    "state.apply_controlled_gate(x, 0, 1)\n",
    "state.apply_gate(x, 1)\n",
    "state.apply_gate(y, 0)\n",
    "state.apply_gate(z, 1)\n",
    "state.apply_gate(y, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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\n",
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "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()\n",
    "\n"
   ]
  }
 ],
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