{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "059560e8",
   "metadata": {},
   "source": [
    "# SIwave DC-IR Analysis\n",
    "\n",
    "This example demonstrates the use of EDB to interact with a PCB\n",
    "layout and run DC-IR analysis in SIwave."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3672343",
   "metadata": {},
   "source": [
    "## Perform imports\n",
    "\n",
    "Perform required imports."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "68ca155d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import tempfile\n",
    "import time\n",
    "\n",
    "import pyedb\n",
    "from pyedb.misc.downloads import download_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7eb9e74c",
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_dir = tempfile.TemporaryDirectory(suffix=\".ansys\")\n",
    "targetfile = download_file(\"edb/ANSYS-HSD_V1.aedb\", destination=temp_dir.name)\n",
    "\n",
    "siwave_file = os.path.join(os.path.dirname(targetfile), \"ANSYS-HSD_V1.siw\")\n",
    "print(targetfile)\n",
    "aedt_file = targetfile[:-4] + \"aedt\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adea2693",
   "metadata": {},
   "source": [
    "## Launch Ansys Electronics Database (EDB)\n",
    "\n",
    "Instantiate an instance of the `pyedb.Edb` class using SI units."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bebe4a05",
   "metadata": {},
   "outputs": [],
   "source": [
    "if os.path.exists(aedt_file):\n",
    "    os.remove(aedt_file)\n",
    "\n",
    "# Select EDB version (change it manually if needed, e.g. \"2025.1\")\n",
    "edb_version = \"2025.1\"\n",
    "print(f\"EDB version: {edb_version}\")\n",
    "\n",
    "edb = pyedb.Edb(edbpath=targetfile, edbversion=edb_version)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4773b48f",
   "metadata": {},
   "source": [
    "## Identify nets and components\n",
    "\n",
    "The ``Edb.nets.netlist`` and ``Edb.components.instances`` properties contain information\n",
    "about all of the nets and components. The following cell uses this information to print the\n",
    "number of nets and components."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53978b87",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Nets {}\".format(len(edb.nets.netlist)))\n",
    "start = time.time()\n",
    "print(\"Components {}\".format(len(edb.components.instances.keys())))\n",
    "print(\"elapsed time = \", time.time() - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d9b84d2",
   "metadata": {},
   "source": [
    "## Identify pin positions\n",
    "\n",
    "This code shows how to obtain all pins for a specific component and\n",
    "print the ``[x, y]`` position of each pin."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a970641f",
   "metadata": {},
   "outputs": [],
   "source": [
    "pins = edb.components[\"U2\"].pins\n",
    "count = 0\n",
    "for pin in edb.components[\"U2\"].pins.values():\n",
    "    if count < 10:  # Only print the first 10 pin coordinates.\n",
    "        print(pin.position)\n",
    "    elif count == 10:\n",
    "        print(\"...and many more.\")\n",
    "    else:\n",
    "        pass\n",
    "    count += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e383c791",
   "metadata": {},
   "source": [
    "Get all nets connected to a specific component. Print\n",
    "the pin and the name of the net that it is connected to."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd960749",
   "metadata": {},
   "outputs": [],
   "source": [
    "connections = edb.components.get_component_net_connection_info(\"U2\")\n",
    "n_print = 0  # Counter to limit the number of printed lines.\n",
    "print_max = 15\n",
    "for m in range(len(connections[\"pin_name\"])):\n",
    "    ref_des = connections[\"refdes\"][m]\n",
    "    pin_name = connections[\"pin_name\"][m]\n",
    "    net_name = connections[\"net_name\"][m]\n",
    "    if net_name != \"\" and (n_print < print_max):\n",
    "        print('{}, pin {} -> net \"{}\"'.format(ref_des, pin_name, net_name))\n",
    "        n_print += 1\n",
    "    elif n_print == print_max:\n",
    "        print(\"...and many more.\")\n",
    "        n_print += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d09bb0d",
   "metadata": {},
   "source": [
    "Compute rats."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7ab5d4ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "rats = edb.components.get_rats()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fde631fd",
   "metadata": {},
   "source": [
    "## Identify connected nets\n",
    "\n",
    "The ``get_dcconnected_net_list()`` method retrieves a list of\n",
    "all DC-connected power nets. Each group of connected nets is returned\n",
    "as a [set](https://docs.python.org/3/tutorial/datastructures.html#sets).\n",
    "The first argument to the method is the list of ground nets, which are\n",
    "not considered in the search for connected nets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "78983bd3",
   "metadata": {},
   "outputs": [],
   "source": [
    "GROUND_NETS = [\"GND\", \"GND_DP\"]\n",
    "dc_connected_net_list = edb.nets.get_dcconnected_net_list(GROUND_NETS)\n",
    "for pnets in dc_connected_net_list:\n",
    "    print(pnets)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c23b9661",
   "metadata": {},
   "source": [
    "## Power Tree\n",
    "\n",
    "The power tree provides connectivity through all components from the VRM to\n",
    "the device."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "953ae113",
   "metadata": {},
   "outputs": [],
   "source": [
    "VRM = \"U1\"\n",
    "OUTPUT_NET = \"AVCC_1V3\"\n",
    "powertree_df, component_list_columns, net_group = edb.nets.get_powertree(OUTPUT_NET, GROUND_NETS)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f525402",
   "metadata": {},
   "source": [
    "Print some information about the power tree."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e3aa9011",
   "metadata": {},
   "outputs": [],
   "source": [
    "print_columns = [\"refdes\", \"pin_name\", \"component_partname\"]\n",
    "ncol = [component_list_columns.index(c) for c in print_columns]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3245862",
   "metadata": {},
   "source": [
    "This prints the header. Replace \"pin_name\" with \"pin\" to\n",
    "make the header align with the values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "58f53ae6",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"\\t\".join(print_columns).replace(\"pin_name\", \"pin\"))\n",
    "\n",
    "for el in powertree_df:\n",
    "    s = \"\"\n",
    "    count = 0\n",
    "    for e in el:\n",
    "        if count in ncol:\n",
    "            s += \"{}\\t\".format(e)\n",
    "        count += 1\n",
    "    s.rstrip()\n",
    "    print(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7854ee37",
   "metadata": {},
   "source": [
    "## Remove unused components\n",
    "\n",
    "Delete all RLC components that are connected with only one pin.\n",
    "The ``Edb.components.delete_single_pin_rlc()`` method\n",
    "provides a useful way to\n",
    "remove components that are not needed for the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "359d25a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "edb.components.delete_single_pin_rlc()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ccd8d42",
   "metadata": {},
   "source": [
    "You can also remove unused components explicitly by name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dcde2f94",
   "metadata": {},
   "outputs": [],
   "source": [
    "edb.components.delete(\"C380\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf1cb1d7",
   "metadata": {},
   "source": [
    "Nets can also be removed explicitly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c2f403c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "edb.nets.delete(\"PDEN\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c458a600",
   "metadata": {},
   "source": [
    "Print the top and bottom elevation of the stackup obtained using\n",
    "the ``Edb.stackup.limits()`` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fd5f875f",
   "metadata": {},
   "outputs": [],
   "source": [
    "s = 'Top layer name: \"{top}\", Elevation: {top_el:.2f} '\n",
    "s += 'mm\\nBottom layer name: \"{bot}\", Elevation: {bot_el:2f} mm'\n",
    "top, top_el, bot, bot_el = edb.stackup.limits()\n",
    "print(s.format(top=top, top_el=top_el * 1e3, bot=bot, bot_el=bot_el * 1e3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f36d8a66",
   "metadata": {},
   "source": [
    "## Set up for SIwave DCIR analysis\n",
    "\n",
    "Create a voltage source and then set up a DCIR analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d02fb4ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "edb.siwave.create_voltage_source_on_net(\"U1\", \"AVCC_1V3\", \"U1\", \"GND\", 1.3, 0, \"V1\")\n",
    "edb.siwave.create_current_source_on_net(\"IC2\", \"NetD3_2\", \"IC2\", \"GND\", 1.0, 0, \"I1\")\n",
    "setup = edb.siwave.add_siwave_dc_analysis(\"myDCIR_4\")\n",
    "setup.use_dc_custom_settings = True\n",
    "setup.set_dc_slider = 0\n",
    "setup.add_source_terminal_to_ground(\"V1\", 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38c75f38",
   "metadata": {},
   "source": [
    "## Solve\n",
    "\n",
    "Save the modifications and run the analysis in SIwave."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4b43c019",
   "metadata": {},
   "outputs": [],
   "source": [
    "edb.save_edb()\n",
    "edb.nets.plot(None, \"1_Top\", plot_components_on_top=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e3cb699f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "aba863e8",
   "metadata": {},
   "source": [
    "## Export results\n",
    "\n",
    "Export all quantities calculated from the DC-IR analysis.\n",
    "The following method runs SIwave in batch mode from the command line.\n",
    "Results are written to the edb folder.\n",
    "Un-commment following lines to analyze with SIwave and export results."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6544a00",
   "metadata": {},
   "source": [
    "siw_file = edb.solve_siwave()\n",
    "outputs = edb.export_siwave_dc_results(\n",
    "    siw_file,\n",
    "    setup.name,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70ad1d81",
   "metadata": {},
   "source": [
    "Close EDB. After EDB is closed, it can be opened by AEDT."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "38aed08b",
   "metadata": {},
   "outputs": [],
   "source": [
    "edb.close_edb()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29d2fb5c",
   "metadata": {},
   "source": [
    "## View Layout in SIwave\n",
    "\n",
    "The SIwave user interface can be visualized and manipulated\n",
    "using the SIwave user interface. This command works on Window OS only."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "62d9c399",
   "metadata": {},
   "outputs": [],
   "source": [
    "# siwave = pyedb.Siwave(\"2025.1\")\n",
    "# siwave.open_project(siwave_file)\n",
    "# report_file = os.path.join(temp_folder,'Ansys.htm')\n",
    "\n",
    "# siwave.export_siwave_report(\"myDCIR_4\", report_file)\n",
    "# siwave.close_project()\n",
    "# siwave.quit_application()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53f25e4d",
   "metadata": {},
   "source": [
    "Clean up the temporary files and directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1310241f",
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_dir.cleanup()"
   ]
  }
 ],
 "metadata": {
  "jupytext": {
   "cell_metadata_filter": "-all",
   "main_language": "python",
   "notebook_metadata_filter": "-all"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}