{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Single Transmon - Floating \n",
    "\n",
    "We'll be creating a 2D design and adding a single transmon qcomponent.\n",
    "\n",
    " Create a standard pocket transmon qubit for a ground plane,\n",
    "        with two pads connected by a junction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# So, let us dive right in. For convenience, let's begin by enabling\n",
    "# automatic reloading of modules when they change.\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import qiskit_metal as metal\n",
    "from qiskit_metal import designs, draw\n",
    "from qiskit_metal import MetalGUI, Dict, open_docs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Each time you create a new quantum circuit design, \n",
    "# you start by instantiating a QDesign class. \n",
    "\n",
    "# The design class `DesignPlanar` is best for 2D circuit designs.\n",
    "\n",
    "design = designs.DesignPlanar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Launch Qiskit Metal GUI to interactively view, edit, and simulate QDesign: Metal GUI\n",
    "gui = MetalGUI(design)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# To force overwrite a QComponent with an existing name.  \n",
    "# This is useful when re-running cells in a notebook. \n",
    "design.overwrite_enabled = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A transmon qubit\n",
    "You can create a ready-made transmon qubit from the QComponent Library, `qiskit_metal.qlibrary.qubits`. \n",
    "`transmon_pocket.py` is the file containing our qubit so `transmon_pocket` is the module we import. \n",
    "The `TransmonPocket` class is our transmon qubit. Like all quantum components, `TransmonPocket` inherits from `QComponent`. \n",
    "\n",
    " Connector lines can be added using the `connection_pads` dictionary. \n",
    " Each connector pad has a name and a list of default properties."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'pos_x': '0um',\n",
       " 'pos_y': '0um',\n",
       " 'connection_pads': {},\n",
       " '_default_connection_pads': {'pad_gap': '15um',\n",
       "  'pad_width': '125um',\n",
       "  'pad_height': '30um',\n",
       "  'pad_cpw_shift': '5um',\n",
       "  'pad_cpw_extent': '25um',\n",
       "  'cpw_width': 'cpw_width',\n",
       "  'cpw_gap': 'cpw_gap',\n",
       "  'cpw_extend': '100um',\n",
       "  'pocket_extent': '5um',\n",
       "  'pocket_rise': '65um',\n",
       "  'loc_W': '+1',\n",
       "  'loc_H': '+1'},\n",
       " 'chip': 'main',\n",
       " 'pad_gap': '30um',\n",
       " 'inductor_width': '20um',\n",
       " 'pad_width': '455um',\n",
       " 'pad_height': '90um',\n",
       " 'pocket_width': '650um',\n",
       " 'pocket_height': '650um',\n",
       " 'orientation': '0',\n",
       " 'hfss_wire_bonds': False,\n",
       " 'q3d_wire_bonds': False,\n",
       " 'hfss_inductance': '10nH',\n",
       " 'hfss_capacitance': 0,\n",
       " 'hfss_resistance': 0,\n",
       " 'hfss_mesh_kw_jj': 7e-06,\n",
       " 'q3d_inductance': '10nH',\n",
       " 'q3d_capacitance': 0,\n",
       " 'q3d_resistance': 0,\n",
       " 'q3d_mesh_kw_jj': 7e-06,\n",
       " 'gds_cell_name': 'my_other_junction'}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit_metal.qlibrary.qubits.transmon_pocket import TransmonPocket\n",
    "\n",
    "# Be aware of the default_options that can be overridden by user.\n",
    "TransmonPocket.get_template_options(design)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "transmon_options = dict(\n",
    "    pos_x = '1mm',\n",
    "    pos_y = '2mm',\n",
    "    orientation = '90',\n",
    "    \n",
    "    connection_pads=dict(\n",
    "        a = dict(loc_W=+1, loc_H=-1, pad_width='70um', cpw_extend = '50um'), \n",
    "        b = dict(loc_W=-1, loc_H=-1, pad_width='125um', cpw_extend = '50um', pad_height='60um'),\n",
    "        c = dict(loc_W=+1, loc_H=+1, pad_width='110um', cpw_extend = '50um')\n",
    "    ),\n",
    "    \n",
    "    gds_cell_name='FakeJunction_01',\n",
    ")\n",
    "\n",
    "# Create a new Transmon Pocket object with name 'Q1' \n",
    "q1 = TransmonPocket(design, 'Q1', options=transmon_options)\n",
    "\n",
    "gui.rebuild()  # rebuild the design and plot \n",
    "gui.autoscale() # resize GUI to see QComponent \n",
    "gui.zoom_on_components(['Q1']) #Can also gui.zoom_on_components([q1.name]) \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see what the Q1 object looks like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[95m\u001b[1mname:    \u001b[94m\u001b[1mQ1\u001b[0m\n",
       "\u001b[95m\u001b[1mclass:   \u001b[94m\u001b[1mTransmonPocket        \u001b[0m\n",
       "\u001b[95m\u001b[1moptions: \u001b[0m\n",
       "  'pos_x'             : '1mm',                        \n",
       "  'pos_y'             : '2mm',                        \n",
       "  \u001b[1m'connection_pads'   \u001b[0m: {\n",
       "       \u001b[1m'a'                 \u001b[0m: {\n",
       "            'pad_gap'           : '15um',                       \n",
       "            'pad_width'         : '70um',                       \n",
       "            'pad_height'        : '30um',                       \n",
       "            'pad_cpw_shift'     : '5um',                        \n",
       "            'pad_cpw_extent'    : '25um',                       \n",
       "            'cpw_width'         : 'cpw_width',                  \n",
       "            'cpw_gap'           : 'cpw_gap',                    \n",
       "            'cpw_extend'        : '50um',                       \n",
       "            'pocket_extent'     : '5um',                        \n",
       "            'pocket_rise'       : '65um',                       \n",
       "            'loc_W'             : 1,                            \n",
       "            'loc_H'             : -1,                           \n",
       "                             },\n",
       "       \u001b[1m'b'                 \u001b[0m: {\n",
       "            'pad_gap'           : '15um',                       \n",
       "            'pad_width'         : '125um',                      \n",
       "            'pad_height'        : '60um',                       \n",
       "            'pad_cpw_shift'     : '5um',                        \n",
       "            'pad_cpw_extent'    : '25um',                       \n",
       "            'cpw_width'         : 'cpw_width',                  \n",
       "            'cpw_gap'           : 'cpw_gap',                    \n",
       "            'cpw_extend'        : '50um',                       \n",
       "            'pocket_extent'     : '5um',                        \n",
       "            'pocket_rise'       : '65um',                       \n",
       "            'loc_W'             : -1,                           \n",
       "            'loc_H'             : -1,                           \n",
       "                             },\n",
       "       \u001b[1m'c'                 \u001b[0m: {\n",
       "            'pad_gap'           : '15um',                       \n",
       "            'pad_width'         : '110um',                      \n",
       "            'pad_height'        : '30um',                       \n",
       "            'pad_cpw_shift'     : '5um',                        \n",
       "            'pad_cpw_extent'    : '25um',                       \n",
       "            'cpw_width'         : 'cpw_width',                  \n",
       "            'cpw_gap'           : 'cpw_gap',                    \n",
       "            'cpw_extend'        : '50um',                       \n",
       "            'pocket_extent'     : '5um',                        \n",
       "            'pocket_rise'       : '65um',                       \n",
       "            'loc_W'             : 1,                            \n",
       "            'loc_H'             : 1,                            \n",
       "                             },\n",
       "                        },\n",
       "  'chip'              : 'main',                       \n",
       "  'pad_gap'           : '30um',                       \n",
       "  'inductor_width'    : '20um',                       \n",
       "  'pad_width'         : '455um',                      \n",
       "  'pad_height'        : '90um',                       \n",
       "  'pocket_width'      : '650um',                      \n",
       "  'pocket_height'     : '650um',                      \n",
       "  'orientation'       : '90',                         \n",
       "  'hfss_wire_bonds'   : False,                        \n",
       "  'q3d_wire_bonds'    : False,                        \n",
       "  'hfss_inductance'   : '10nH',                       \n",
       "  'hfss_capacitance'  : 0,                            \n",
       "  'hfss_resistance'   : 0,                            \n",
       "  'hfss_mesh_kw_jj'   : 7e-06,                        \n",
       "  'q3d_inductance'    : '10nH',                       \n",
       "  'q3d_capacitance'   : 0,                            \n",
       "  'q3d_resistance'    : 0,                            \n",
       "  'q3d_mesh_kw_jj'    : 7e-06,                        \n",
       "  'gds_cell_name'     : 'FakeJunction_01',            \n",
       "\u001b[95m\u001b[1mmodule:  \u001b[94m\u001b[1mqiskit_metal.qlibrary.qubits.transmon_pocket\u001b[0m\n",
       "\u001b[95m\u001b[1mid:      \u001b[94m\u001b[1m1\u001b[0m"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1 #print Q1 information"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save screenshot as a .png formatted file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gui.screenshot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Screenshot the canvas only as a .png formatted file.\n",
    "gui.figure.savefig('shot.png')\n",
    "\n",
    "from IPython.display import Image, display\n",
    "_disp_ops = dict(width=500)\n",
    "display(Image('shot.png', **_disp_ops))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Closing the Qiskit Metal GUI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gui.main_window.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Tags",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}