nmos_v1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5cc68934-84d2-4efa-8bd3-714b4478b4d0",
   "metadata": {},
   "source": [
    "**Script name:** nmos_v0\\\n",
    "**Purpose:** This is version 0 of nmos layout design with the phidl package.\\\n",
    "**Author:** Yanbing Chen\\\n",
    "**Created date:** 09-23-2024\\\n",
    "**Copyright:** Hacker Fab @ Carnegie Mellon University\\\n",
    "**Contact info:** *yanbing2@andrew.cmu.edu*\\\n",
    "**Notes:** This Python macro should be loaded into KLayout as either \".py\" file or \".lym\" file with the interpreter set to \"Python\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "719f307b-fa18-4035-bb56-6f3848d3af8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from phidl import Device\n",
    "from phidl import quickplot as qp # Rename \"quickplot()\" to the easier \"qp()\"\n",
    "import phidl.geometry as pg\n",
    "import phidl.routing as pr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ab210ae-3066-40dd-82c2-7623f3a2f810",
   "metadata": {},
   "source": [
    "## Create some shape devices to be used as references"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "9d08a12e-aa9d-4640-957a-492471ed8465",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a blank device to store gate reference\n",
    "G = Device('gate')\n",
    "# Define points and add a polygon enclosed by the points \n",
    "xpts = [0,5,5,3.5,3.5,1.5,1.5,0]\n",
    "ypts = [0,0,5,5,  15, 15, 5,  5]\n",
    "G_poly = G.add_polygon([xpts,ypts],layer = 0)\n",
    "\n",
    "# Create a blank device \n",
    "AR = pg.rectangle(size=(15,8), layer = 1)\n",
    "\n",
    "\n",
    "# Create a blank device to store gate via reference\n",
    "VIA = pg.rectangle(size=(2,2), layer = 2)\n",
    "\n",
    "AL = pg.rectangle(size=(4,4), layer = 3)\n",
    "\n",
    "#qp(G)\n",
    "#qp(AR)\n",
    "#qp(GV)\n",
    "#qp(ARLV)\n",
    "#qp(ARRV)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fc2c30e-7f14-4cc9-8571-fd469ad7e9b4",
   "metadata": {},
   "source": [
    "## Reuse polygon (as reference)- *add_ref* or *<<*\n",
    "We want to reuse this polygon repeatedly but do not want to make multiple copies of it. To do so, we need to make a second blank Device, this time called D. In this new Device we’ll reference our Device P which contains our polygon.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "6d286cfd-7afc-4509-8a22-735a407910dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "N1 = Device('nmos_N1')             # Create a new blank Device\n",
    "# Add shapes to N1 as references\n",
    "G_N1 = N1 <<G # or G_N1 = N1.add_ref(G)  \n",
    "AR_N1 = N1 << AR.move([-5,6])\n",
    "GV_N1 = N1 << VIA\n",
    "ARLV_N1 = N1 << VIA\n",
    "ARRV_N1 = N1 << VIA\n",
    "ALGV_N1 = N1 << AL\n",
    "ALLV_N1 = N1 << AL\n",
    "ALRV_N1 = N1 << AL\n",
    "\n",
    "GV_N1.move([1.5,1.5])\n",
    "ARLV_N1.move([-3,9])\n",
    "ARRV_N1.move([6,9])\n",
    "ALGV_N1.move([0.5,0.5])\n",
    "ALLV_N1.move([-4,8])\n",
    "ALRV_N1.move([5,8])\n",
    "\n",
    "qp(N1) # Quickplot the reference-containing device \"N1\"\n",
    "\n",
    "#AR_N1.move([-5,6]) # Translate by dx = -5, dy = 7.5\n",
    "#GV_N1.move([1.5,1.5])\n",
    "#qp(N1) # Quickplot the reference-containing device \"N1\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "44075eb5-aa93-49fc-85da-c8f0958ec08b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Nn = Device()\n",
    "# Reference the Device \"D\" that 3 references in it\n",
    "d_ref1 = Nn.add_array(N1, columns = 6, rows = 3, spacing = [9,20])\n",
    "\n",
    "qp(Nn)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}