{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b215e10e",
   "metadata": {},
   "source": [
    "# 2.11 Routing 101"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "367335f2",
   "metadata": {},
   "source": [
    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/qiskit-community/qiskit-metal/blob/main/tutorials/2%20From%20components%20to%20chip/B.%20Routing%20between%20QComponents/2.11%20Routing%20101.ipynb)\n",
    "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/qiskit-community/qiskit-metal/main?labpath=tutorials%2F2%20From%20components%20to%20chip%2FB.%20Routing%20between%20QComponents%2F2.11%20Routing%20101.ipynb)\n",
    "\n",
    "> 💡 **Running in Colab or Binder?** Skip the desktop GUI install — the cell below grabs the lite (no-Qt) wheel, and `qm.gui(design)` auto-picks an inline matplotlib viewer with the same API (`gui.rebuild()`, `gui.screenshot()`, `gui.edit_component(...)`) as the desktop `MetalGUI`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "00ab3c6b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:33.018989Z",
     "iopub.status.busy": "2026-08-08T04:39:33.018772Z",
     "iopub.status.idle": "2026-08-08T04:39:33.024050Z",
     "shell.execute_reply": "2026-08-08T04:39:33.023407Z"
    }
   },
   "outputs": [],
   "source": [
    "# In Colab / Binder, uncomment to install Quantum Metal (lite, no Qt).\n",
    "# Locally you should already have it via `pip install quantum-metal` or\n",
    "# `pip install 'quantum-metal[gui]'` for the desktop GUI.\n",
    "# !pip install -q quantum-metal"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b387cd8",
   "metadata": {},
   "source": [
    "> 💡 **Using this tutorial without the Qt GUI**\n",
    "> \n",
    "> This tutorial uses the desktop `MetalGUI`. To follow along on Colab, Binder, JupyterHub, or any environment where Qt isn't available, **replace any `gui.rebuild()` / `gui.screenshot()` call with `qm.view(design)`** — it renders the design to a matplotlib `Figure` you can display inline or save with `fig.savefig(...)`.\n",
    "> \n",
    "> See [1.1 Quick start](../1-Overview/1.1-Quick-start.ipynb) for a complete runnable walkthrough and [`docs/headless-usage.rst`](../../docs/headless-usage.rst) for the full reference."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9522117b",
   "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",
   "id": "b63665a2",
   "metadata": {},
   "source": [
    "![Transmission%20lines.jpg](attachment:Transmission%20lines.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b59ba155",
   "metadata": {},
   "source": [
    "### Prerequisite\n",
    "\n",
    "Initialize metal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9643e4ba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:33.026938Z",
     "iopub.status.busy": "2026-08-08T04:39:33.026764Z",
     "iopub.status.idle": "2026-08-08T04:39:35.095558Z",
     "shell.execute_reply": "2026-08-08T04:39:35.095105Z"
    }
   },
   "outputs": [],
   "source": [
    "import qiskit_metal as qm\n",
    "from qiskit_metal import designs\n",
    "from qiskit_metal import Dict\n",
    "\n",
    "design = designs.DesignPlanar()\n",
    "gui = qm.gui(design)\n",
    "\n",
    "design.variables[\"cpw_width\"] = \"10 um\"\n",
    "design.variables[\"cpw_gap\"] = \"6 um\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d7f06832",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:35.097175Z",
     "iopub.status.busy": "2026-08-08T04:39:35.097081Z",
     "iopub.status.idle": "2026-08-08T04:39:35.098894Z",
     "shell.execute_reply": "2026-08-08T04:39:35.098500Z"
    }
   },
   "outputs": [],
   "source": [
    "# enable rebuild of the same component\n",
    "design.overwrite_enabled = True"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "952dd278",
   "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,
   "id": "b19cc9a0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:35.099914Z",
     "iopub.status.busy": "2026-08-08T04:39:35.099856Z",
     "iopub.status.idle": "2026-08-08T04:39:35.102551Z",
     "shell.execute_reply": "2026-08-08T04:39:35.102172Z"
    }
   },
   "outputs": [],
   "source": [
    "# for pins:\n",
    "from qiskit_metal.qlibrary.terminations.open_to_ground import OpenToGround\n",
    "\n",
    "# for routing:\n",
    "from qiskit_metal.qlibrary.tlines.straight_path import RouteStraight\n",
    "from qiskit_metal.qlibrary.tlines.framed_path import RouteFramed\n",
    "\n",
    "# for jogs:\n",
    "from collections import OrderedDict"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc421ba9",
   "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,
   "id": "96288b44",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:35.103569Z",
     "iopub.status.busy": "2026-08-08T04:39:35.103511Z",
     "iopub.status.idle": "2026-08-08T04:39:35.105235Z",
     "shell.execute_reply": "2026-08-08T04:39:35.104898Z"
    }
   },
   "outputs": [],
   "source": [
    "pin_opt = Dict(\n",
    "    pin_inputs=Dict(\n",
    "        start_pin=Dict(component=\"open1i\", pin=\"open\"),\n",
    "        end_pin=Dict(component=\"open1o\", pin=\"open\"),\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b210a629",
   "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,
   "id": "4fe36bb7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:35.106159Z",
     "iopub.status.busy": "2026-08-08T04:39:35.106093Z",
     "iopub.status.idle": "2026-08-08T04:39:35.167460Z",
     "shell.execute_reply": "2026-08-08T04:39:35.166569Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "design.delete_all_components()  # needed only for rebuilds. will get a warning\n",
    "\n",
    "otg11 = OpenToGround(\n",
    "    design, \"open1i\", options=dict(pos_x=\"0mm\", pos_y=\"1mm\", orientation=\"180\")\n",
    ")\n",
    "otg12 = OpenToGround(\n",
    "    design, \"open1o\", options=dict(pos_x=\"0.5mm\", pos_y=\"1mm\", orientation=\"0\")\n",
    ")\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "620d4d8a",
   "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,
   "id": "643d661a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:35.170137Z",
     "iopub.status.busy": "2026-08-08T04:39:35.169971Z",
     "iopub.status.idle": "2026-08-08T04:39:35.375983Z",
     "shell.execute_reply": "2026-08-08T04:39:35.375177Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "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",
   "id": "44ac4e08",
   "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,
   "id": "320d8a12",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:35.378826Z",
     "iopub.status.busy": "2026-08-08T04:39:35.378618Z",
     "iopub.status.idle": "2026-08-08T04:39:35.480965Z",
     "shell.execute_reply": "2026-08-08T04:39:35.480594Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "otg21 = OpenToGround(\n",
    "    design, \"open2i\", options=dict(pos_x=\"0mm\", pos_y=\"2mm\", orientation=\"90\")\n",
    ")\n",
    "otg22 = OpenToGround(\n",
    "    design, \"open2o\", options=dict(pos_x=\"0mm\", pos_y=\"1.5mm\", orientation=\"-90\")\n",
    ")\n",
    "otg31 = OpenToGround(\n",
    "    design, \"open3i\", options=dict(pos_x=\"0.35mm\", pos_y=\"1.55mm\", orientation=\"45\")\n",
    ")\n",
    "otg32 = OpenToGround(\n",
    "    design, \"open3o\", options=dict(pos_x=\"0mm\", pos_y=\"1.2mm\", orientation=\"-135\")\n",
    ")\n",
    "otg41 = OpenToGround(\n",
    "    design, \"open4i\", options=dict(pos_x=\"0mm\", pos_y=\"0.8mm\", orientation=\"135\")\n",
    ")\n",
    "otg42 = OpenToGround(\n",
    "    design, \"open4o\", options=dict(pos_x=\"0.35mm\", pos_y=\"0.45mm\", orientation=\"-45\")\n",
    ")\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "522d3acf",
   "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,
   "id": "af173fe5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:35.482174Z",
     "iopub.status.busy": "2026-08-08T04:39:35.482103Z",
     "iopub.status.idle": "2026-08-08T04:39:35.590508Z",
     "shell.execute_reply": "2026-08-08T04:39:35.590101Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "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": "code",
   "execution_count": 10,
   "id": "16c0cbbd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:35.591635Z",
     "iopub.status.busy": "2026-08-08T04:39:35.591566Z",
     "iopub.status.idle": "2026-08-08T04:39:35.651194Z",
     "shell.execute_reply": "2026-08-08T04:39:35.650795Z"
    },
    "nbsphinx-thumbnail": {}
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gui.screenshot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51cdbec3",
   "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": 11,
   "id": "db9bb06e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:35.652316Z",
     "iopub.status.busy": "2026-08-08T04:39:35.652241Z",
     "iopub.status.idle": "2026-08-08T04:39:35.767006Z",
     "shell.execute_reply": "2026-08-08T04:39:35.766683Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "otg51 = OpenToGround(\n",
    "    design, \"open5i\", options=dict(pos_x=\"0.7mm\", pos_y=\"1.9mm\", orientation=\"180\")\n",
    ")\n",
    "otg52 = OpenToGround(\n",
    "    design, \"open5o\", options=dict(pos_x=\"0.8mm\", pos_y=\"2.0mm\", orientation=\"90\")\n",
    ")\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",
   "id": "d02cb667",
   "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": 12,
   "id": "d99fdf19",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:35.768244Z",
     "iopub.status.busy": "2026-08-08T04:39:35.768172Z",
     "iopub.status.idle": "2026-08-08T04:39:36.079463Z",
     "shell.execute_reply": "2026-08-08T04:39:36.079100Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Ignoring fixed x limits to fulfill fixed data aspect with adjustable data limits.\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "otg61 = OpenToGround(\n",
    "    design, \"open6i\", options=dict(pos_x=\"0.7mm\", pos_y=\"1.7mm\", orientation=\"180\")\n",
    ")\n",
    "otg62 = OpenToGround(\n",
    "    design, \"open6o\", options=dict(pos_x=\"0.8mm\", pos_y=\"1.8mm\", orientation=\"90\")\n",
    ")\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",
   "id": "b3722048",
   "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": 13,
   "id": "3e8c58f1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:36.080619Z",
     "iopub.status.busy": "2026-08-08T04:39:36.080551Z",
     "iopub.status.idle": "2026-08-08T04:39:36.379129Z",
     "shell.execute_reply": "2026-08-08T04:39:36.378738Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Ignoring fixed x limits to fulfill fixed data aspect with adjustable data limits.\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "otg71 = OpenToGround(\n",
    "    design, \"open7i\", options=dict(pos_x=\"0.7mm\", pos_y=\"1.5mm\", orientation=\"180\")\n",
    ")\n",
    "otg72 = OpenToGround(\n",
    "    design, \"open7o\", options=dict(pos_x=\"0.8mm\", pos_y=\"1.6mm\", orientation=\"90\")\n",
    ")\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",
   "id": "4846549b",
   "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": 14,
   "id": "2dcd0b5b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:36.380268Z",
     "iopub.status.busy": "2026-08-08T04:39:36.380187Z",
     "iopub.status.idle": "2026-08-08T04:39:36.621765Z",
     "shell.execute_reply": "2026-08-08T04:39:36.621331Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "otg81 = OpenToGround(\n",
    "    design, \"open8i\", options=dict(pos_x=\"0.7mm\", pos_y=\"1.3mm\", orientation=\"180\")\n",
    ")\n",
    "otg82 = OpenToGround(\n",
    "    design, \"open8o\", options=dict(pos_x=\"0.8mm\", pos_y=\"1.4mm\", orientation=\"90\")\n",
    ")\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",
   "id": "e208a21b",
   "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": 15,
   "id": "70e76c01",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:36.622974Z",
     "iopub.status.busy": "2026-08-08T04:39:36.622905Z",
     "iopub.status.idle": "2026-08-08T04:39:36.890445Z",
     "shell.execute_reply": "2026-08-08T04:39:36.890105Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Ignoring fixed x limits to fulfill fixed data aspect with adjustable data limits.\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "otg91 = OpenToGround(\n",
    "    design, \"open9i\", options=dict(pos_x=\"0.7mm\", pos_y=\"1.05mm\", orientation=\"180\")\n",
    ")\n",
    "otg92 = OpenToGround(\n",
    "    design, \"open9o\", options=dict(pos_x=\"0.8mm\", pos_y=\"1.15mm\", orientation=\"270\")\n",
    ")\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",
   "id": "35f30b9a",
   "metadata": {},
   "source": [
    "The `RouteFramed` can create up to 3 segments. Observe the following case of opposing pins."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c38b5638",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:36.891609Z",
     "iopub.status.busy": "2026-08-08T04:39:36.891524Z",
     "iopub.status.idle": "2026-08-08T04:39:37.172933Z",
     "shell.execute_reply": "2026-08-08T04:39:37.172572Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Ignoring fixed x limits to fulfill fixed data aspect with adjustable data limits.\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "otg101 = OpenToGround(\n",
    "    design, \"open10i\", options=dict(pos_x=\"0.7mm\", pos_y=\"0.8mm\", orientation=\"90\")\n",
    ")\n",
    "otg102 = OpenToGround(\n",
    "    design, \"open10o\", options=dict(pos_x=\"0.8mm\", pos_y=\"0.9mm\", orientation=\"270\")\n",
    ")\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",
   "id": "cd2f5a3e",
   "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": 17,
   "id": "37605687",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:37.174138Z",
     "iopub.status.busy": "2026-08-08T04:39:37.174050Z",
     "iopub.status.idle": "2026-08-08T04:39:37.395860Z",
     "shell.execute_reply": "2026-08-08T04:39:37.395516Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "otg111 = OpenToGround(\n",
    "    design, \"open11i\", options=dict(pos_x=\"0.7mm\", pos_y=\"0.5mm\", orientation=\"180\")\n",
    ")\n",
    "otg112 = OpenToGround(\n",
    "    design, \"open11o\", options=dict(pos_x=\"0.8mm\", pos_y=\"0.6mm\", orientation=\"270\")\n",
    ")\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",
   "id": "19acfa23",
   "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": 18,
   "id": "114d099c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:37.397087Z",
     "iopub.status.busy": "2026-08-08T04:39:37.397015Z",
     "iopub.status.idle": "2026-08-08T04:39:37.417940Z",
     "shell.execute_reply": "2026-08-08T04:39:37.417665Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "19822c65",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-08T04:39:37.419137Z",
     "iopub.status.busy": "2026-08-08T04:39:37.419074Z",
     "iopub.status.idle": "2026-08-08T04:39:37.420914Z",
     "shell.execute_reply": "2026-08-08T04:39:37.420597Z"
    }
   },
   "outputs": [],
   "source": [
    "# gui.main_window.close()"
   ]
  }
 ],
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   "language": "python",
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