{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Routing 101"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this tutorial, we will show how to connect two points with a transmission line route.\n",
    "\n",
    "### Introduction\n",
    "\n",
    "Routes are strips of metal (or cuts in the bulk metal), that electrically connect two input-specified pins (pin = point on the perimeter of a QComponent, with orientation, indicating an allowed point for electrical contact).\n",
    "\n",
    "The core class `QRoute` is designed to support different route types, currently only single or double (CPW) wiring. We will use the CPW transmission line in the remainder of this notebook, and in the majority of the other tutorial notebooks.\n",
    "\n",
    "`QRoute` inherits the generic `QComponent`. QRoute also has two attributes of type `QRouteLead`, which enable close control of the start and end points in a route. We will describe in this notebook how to utilize the `QRouteLead`. `QRoutePoint` is a convenient exchange format for directed points.\n",
    "\n",
    "`QRoute` is an abstract class, without a `make()` method, thus cannot be instantiated as a design component. `QRoute` is inherited by classes that can be instantiated (have a `make()` method - blue highlights in the image below). By subclassing further, you can implement comprehensive routing algorithms, such as the `RouteMixed`.\n",
    "\n",
    "In this notebook we will only look at the simple `RouteStraight` and `RouteLead`."
   ]
  },
  {
   "attachments": {
    "Transmission%20lines.jpg": {
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    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Transmission%20lines.jpg](attachment:Transmission%20lines.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prerequisite\n",
    "\n",
    "Initialize metal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%reload_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit_metal import designs\n",
    "from qiskit_metal import MetalGUI, Dict\n",
    "\n",
    "design = designs.DesignPlanar()\n",
    "gui = MetalGUI(design)\n",
    "\n",
    "design.variables['cpw_width'] = '10 um'\n",
    "design.variables['cpw_gap'] = '6 um'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# enable rebuild of the same component\n",
    "design.overwrite_enabled = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use the following classes in the notebook. Let's import all of them at once."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for pins:\n",
    "from qiskit_metal.qlibrary.terminations.open_to_ground import OpenToGround\n",
    "# for routing:\n",
    "from qiskit_metal.qlibrary.tlines.straight_path import RouteStraight\n",
    "from qiskit_metal.qlibrary.tlines.framed_path import RouteFramed\n",
    "# for jogs:\n",
    "from collections import OrderedDict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To remove the complexity of large QComponents, we will only use the `OpenToGround` QComponent to establish pins. We want to initialize a dictionary of type `Dict` as follows (naming matching `Example 1`). We will later update this dictionary as needed using the simpler dot notation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "pin_opt = Dict(pin_inputs=Dict(start_pin=Dict(\n",
    "                                    component='open1i',\n",
    "                                    pin='open'),\n",
    "                                end_pin=Dict(\n",
    "                                    component='open1o',\n",
    "                                    pin='open')))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example 1: Straight routing between two pins\n",
    "First, we make sure our design contains two pins to connect to."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "design.delete_all_components()  #needed only for rebuilds. will get a warning\n",
    "\n",
    "otg11 = OpenToGround(design, 'open1i', options=dict(pos_x='0mm',  pos_y='1mm', orientation='180'))\n",
    "otg12 = OpenToGround(design, 'open1o', options=dict(pos_x='0.5mm',  pos_y='1mm', orientation='0'))\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we create the route in between them. Notice we are using the previously defined `pin_opt` to indicate which pins to connect to."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "route1 = RouteStraight(design, 'cpw_1', pin_opt)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()\n",
    "gui.highlight_components(['open1i','open1o'])\n",
    "#gui.screenshot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example 2: Any direction\n",
    "Let's add a few pins that we can use to connect in pairs. We here align them following a variety of orientations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "otg21 = OpenToGround(design, 'open2i', options=dict(pos_x='0mm',  pos_y='2mm', orientation='90'))\n",
    "otg22 = OpenToGround(design, 'open2o', options=dict(pos_x='0mm',  pos_y='1.5mm', orientation='-90'))\n",
    "otg31 = OpenToGround(design, 'open3i', options=dict(pos_x='0.35mm',  pos_y='1.55mm', orientation='45'))\n",
    "otg32 = OpenToGround(design, 'open3o', options=dict(pos_x='0mm',  pos_y='1.2mm', orientation='-135'))\n",
    "otg41 = OpenToGround(design, 'open4i', options=dict(pos_x='0mm',  pos_y='0.8mm', orientation='135'))\n",
    "otg42 = OpenToGround(design, 'open4o', options=dict(pos_x='0.35mm',  pos_y='0.45mm', orientation='-45'))\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we connect pair of pins using a straight route. Notice how we update the `pin_opt` component names to the new pair, for each new `RouteStraight`. Indeed, we can only use a pin for one single connection, and we will get an error if we try to connect a second route to the same pin."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "pin_opt.pin_inputs.start_pin.component = 'open2i'\n",
    "pin_opt.pin_inputs.end_pin.component = 'open2o'\n",
    "route2 = RouteStraight(design, 'cpw_2', pin_opt)\n",
    "pin_opt.pin_inputs.start_pin.component = 'open3i'\n",
    "pin_opt.pin_inputs.end_pin.component = 'open3o'\n",
    "route3 = RouteStraight(design, 'cpw_3', pin_opt)\n",
    "pin_opt.pin_inputs.start_pin.component = 'open4i'\n",
    "pin_opt.pin_inputs.end_pin.component = 'open4o'\n",
    "route4 = RouteStraight(design, 'cpw_4', pin_opt)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example 3: Angles and leads\n",
    "If the two pins to connect are not facing each other, the router will create the necessary jogs. Here is a simple example that shows 45° jogs.\n",
    "\n",
    "The `RouteStraight` will use a single straight line in any orientation to connect the two pins. Feel free to try using other algorithms, by replacing the class to any other `QRoute` subclass (image at the start of this notebook)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "otg51 = OpenToGround(design, 'open5i', options=dict(pos_x='0.7mm',  pos_y='1.9mm', orientation='180'))\n",
    "otg52 = OpenToGround(design, 'open5o', options=dict(pos_x='0.8mm',  pos_y='2.0mm', orientation='90'))\n",
    "\n",
    "pin_opt.pin_inputs.start_pin.component = 'open5i'\n",
    "pin_opt.pin_inputs.end_pin.component = 'open5o'\n",
    "route5 = RouteStraight(design, 'cpw_5', pin_opt)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.zoom_on_components(['cpw_5'])\n",
    "#gui.screenshot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's make another connection. This time, we add a lead extension to both pins. An extension is a route segment that begins from the pin coordinates and extends straight in the pin direction by the given length."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "otg61 = OpenToGround(design, 'open6i', options=dict(pos_x='0.7mm',  pos_y='1.7mm', orientation='180'))\n",
    "otg62 = OpenToGround(design, 'open6o', options=dict(pos_x='0.8mm',  pos_y='1.8mm', orientation='90'))\n",
    "\n",
    "pin_opt.pin_inputs.start_pin.component = 'open6i'\n",
    "pin_opt.pin_inputs.end_pin.component = 'open6o'\n",
    "\n",
    "pin_opt.lead.start_straight = '0.04mm'\n",
    "pin_opt.lead.end_straight = '0.06mm'\n",
    "route6 = RouteStraight(design, 'cpw_6', pin_opt)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.zoom_on_components(['cpw_6'])\n",
    "#gui.screenshot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example 4: 90° angles\n",
    "In most applications, you might want to limit the jogs to 90° angles. In the following example we use the same `pin_opts` of the previous example, but we replace `RouteStraight` with `RouteFramed`. You will notice that our route now has only one 90° jog."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "otg71 = OpenToGround(design, 'open7i', options=dict(pos_x='0.7mm',  pos_y='1.5mm', orientation='180'))\n",
    "otg72 = OpenToGround(design, 'open7o', options=dict(pos_x='0.8mm',  pos_y='1.6mm', orientation='90'))\n",
    "\n",
    "pin_opt.pin_inputs.start_pin.component = 'open7i'\n",
    "pin_opt.pin_inputs.end_pin.component = 'open7o'\n",
    "\n",
    "route7 = RouteFramed(design, 'cpw_7', pin_opt)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.zoom_on_components(['cpw_7'])\n",
    "#gui.screenshot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The route resulting from the cell above, had no trace of the lead segments. That is because the length of the lead segments was less than the edge of the corner. By extending the `start_straight` for example, we can see the effect of the lead again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "otg81 = OpenToGround(design, 'open8i', options=dict(pos_x='0.7mm',  pos_y='1.3mm', orientation='180'))\n",
    "otg82 = OpenToGround(design, 'open8o', options=dict(pos_x='0.8mm',  pos_y='1.4mm', orientation='90'))\n",
    "\n",
    "pin_opt.pin_inputs.start_pin.component = 'open8i'\n",
    "pin_opt.pin_inputs.end_pin.component = 'open8o'\n",
    "\n",
    "pin_opt.lead.start_straight = '0.15mm'\n",
    "pin_opt.lead.end_straight = '0.05mm'\n",
    "route8 = RouteFramed(design, 'cpw_8', pin_opt)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.zoom_on_components(['cpw_8'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice how the `RouteFramed` executed in the previous cell needs to create 2 jogs to complete the routing, as opposed to the previous single 90° job example.\n",
    "\n",
    "This algorithm helps also connecting pins not facing each other, like in the next cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "otg91 = OpenToGround(design, 'open9i', options=dict(pos_x='0.7mm',  pos_y='1.05mm', orientation='180'))\n",
    "otg92 = OpenToGround(design, 'open9o', options=dict(pos_x='0.8mm',  pos_y='1.15mm', orientation='270'))\n",
    "\n",
    "pin_opt.pin_inputs.start_pin.component = 'open9i'\n",
    "pin_opt.pin_inputs.end_pin.component = 'open9o'\n",
    "\n",
    "route9 = RouteFramed(design, 'cpw_9', pin_opt)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.zoom_on_components(['cpw_9'])\n",
    "#gui.screenshot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `RouteFramed` can create up to 3 segments. Observe the following case of opposing pins."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "otg101 = OpenToGround(design, 'open10i', options=dict(pos_x='0.7mm',  pos_y='0.8mm', orientation='90'))\n",
    "otg102 = OpenToGround(design, 'open10o', options=dict(pos_x='0.8mm',  pos_y='0.9mm', orientation='270'))\n",
    "\n",
    "pin_opt.pin_inputs.start_pin.component = 'open10i'\n",
    "pin_opt.pin_inputs.end_pin.component = 'open10o'\n",
    "\n",
    "pin_opt.lead.start_straight = '0.03mm'\n",
    "pin_opt.lead.end_straight = '0.03mm'\n",
    "route10 = RouteFramed(design, 'cpw_10', pin_opt)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.zoom_on_components(['cpw_10'])\n",
    "#gui.screenshot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example 5: Tight control on leads and angles\n",
    "`QRouteLeads` are a \"stack\" of points that describe in detail the \"last-mile\" to the pins where the route terminates. These stacks are seeded with the pin coordinates and direction and build incrementally.\n",
    "\n",
    "In the previous examples we controlled the QRouteLead points by utilizing the `lead` options inside the `pin_opt` construct. Specifically, we utilized `start_straight` and `end_straight`, which add one point to the respective leads, at the specified distance in the direction specified by the pins (outwards from the QComponent that has the pin).\n",
    "\n",
    "We are however not limited to a single aligned extension point. Utilizing the `start_jogged_extension` and `end_jogged_extension`, we can specify any number of points to add to the lead stacks. The points are computed by providing a OrderedDict() of **steps**, expressed as `[angle,distance]` pairs.\n",
    "* `distance` is the string describing how long the step needs to be\n",
    "* `angle` describe the direction in which to take the step\n",
    "\n",
    "The `angle` can be described in several ways, to accommodate different coding styles. For example, all of the options above will lead to the same 90° left turn:\n",
    "> \"L\", \"L90\", \"R-90\", 90, \"90\", \"A,90\", \"left\", \"left90\", \"right-90\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "otg111 = OpenToGround(design, 'open11i', options=dict(pos_x='0.7mm',  pos_y='0.5mm', orientation='180'))\n",
    "otg112 = OpenToGround(design, 'open11o', options=dict(pos_x='0.8mm',  pos_y='0.6mm', orientation='270'))\n",
    "\n",
    "pin_opt.pin_inputs.start_pin.component = 'open11i'\n",
    "pin_opt.pin_inputs.end_pin.component = 'open11o'\n",
    "\n",
    "# the first step is always stright, let's define by how much (minimum is half the route width):\n",
    "pin_opt.lead.start_straight = '0.03mm'\n",
    "pin_opt.lead.end_straight = '0.04mm'\n",
    "\n",
    "# any subsequent step of the lead_start\n",
    "jogsS = OrderedDict()\n",
    "jogsS[0] = [\"L\", '20um']\n",
    "jogsS[1] = [\"R\", '50um']\n",
    "jogsS[2] = [90, '30um']\n",
    "jogsS[3] = [-90, '60um']\n",
    "jogsS[4] = [\"90\", '40um']\n",
    "jogsS[5] = [\"-90\", '70um']\n",
    "jogsS[6] = [\"L30\", '30um']\n",
    "jogsS[7] = [\"A,30\", '30um']\n",
    "jogsS[8] = [\"left30\", '50um']\n",
    "\n",
    "# single jog on the lead_end, just for kicks\n",
    "jogsE = OrderedDict()\n",
    "jogsE[0] = [\"L\", '30um']\n",
    "\n",
    "pin_opt.lead.start_jogged_extension = jogsS\n",
    "pin_opt.lead.end_jogged_extension = jogsE\n",
    "route10 = RouteFramed(design, 'cpw_11', pin_opt)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.zoom_on_components(['cpw_11'])\n",
    "#gui.screenshot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook explains the basics of `QRoute`, illustrating **custom** methods to route. In this same tutorial folder you will find other notebooks describing the use of more automated routing options:\n",
    "* `RouteMeader` to obtain a routing of an exact length\n",
    "* `RoutePathfinder` to circumvent existing layout obstacles\n",
    "* `RouteAnchors` to guarantee routing through a given set of non-oriented points\n",
    "* `RouteMixed` to be able to specify what other auto-route algorithm to use in between each pair of anchors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "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": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# gui.main_window.close()"
   ]
  }
 ],
 "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
}