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    "# 1.4 Saving Your Chip Design\n",
    "\n",
    "By the end of this tutorial you will know how to:\n",
    "\n",
    "1. **Export a design to a Python script** with ``to_python_script()`` — for reproducibility, version control, and CI replay.\n",
    "2. **Export to GDS** for fabrication, and visually inspect the result.\n",
    "\n",
    "We start from the full 2-qubit chip built in [tutorial 1.2](./1.1-Quick-start.ipynb). The block below is exactly what ``design.to_python_script()`` produces — a self-contained Python definition you can version-control, share, and replay."
   ]
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    "[![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/1%20Overview/1.4%20Saving%20Your%20Chip%20Design.ipynb)\n",
    "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/qiskit-community/qiskit-metal/main?labpath=tutorials%2F1%20Overview%2F1.4%20Saving%20Your%20Chip%20Design.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`."
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   "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"
   ]
  },
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    "execution": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Design ready: 15 components\n"
     ]
    }
   ],
   "source": [
    "# === Design reproduced from tutorial 1.2 via design.to_python_script() ===\n",
    "from qiskit_metal import designs, Dict\n",
    "from qiskit_metal.qlibrary.qubits.transmon_pocket_cl import TransmonPocketCL\n",
    "from qiskit_metal.qlibrary.tlines.pathfinder import RoutePathfinder\n",
    "from qiskit_metal.qlibrary.tlines.meandered import RouteMeander\n",
    "from qiskit_metal.qlibrary.lumped.cap_3_interdigital import Cap3Interdigital\n",
    "from qiskit_metal.qlibrary.terminations.launchpad_wb import LaunchpadWirebond\n",
    "\n",
    "design = designs.DesignPlanar()\n",
    "design.overwrite_enabled = True\n",
    "\n",
    "Q1 = TransmonPocketCL(\n",
    "    design,\n",
    "    \"Q1\",\n",
    "    options=dict(\n",
    "        pos_x=\"0.7mm\",\n",
    "        pos_y=\"0mm\",\n",
    "        orientation=\"0\",\n",
    "        pad_gap=\"30um\",\n",
    "        inductor_width=\"20um\",\n",
    "        pad_width=\"425 um\",\n",
    "        pad_height=\"90um\",\n",
    "        pocket_width=\"650um\",\n",
    "        pocket_height=\"650um\",\n",
    "        gds_cell_name=\"FakeJunction_01\",\n",
    "        make_CL=True,\n",
    "        cl_gap=\"6um\",\n",
    "        cl_width=\"10um\",\n",
    "        cl_length=\"20um\",\n",
    "        cl_ground_gap=\"6um\",\n",
    "        cl_pocket_edge=\"180\",\n",
    "        cl_off_center=\"50um\",\n",
    "        connection_pads=dict(\n",
    "            readout=dict(\n",
    "                loc_W=1,\n",
    "                loc_H=1,\n",
    "                pad_gap=\"15um\",\n",
    "                pad_width=\"125um\",\n",
    "                pad_height=\"30um\",\n",
    "                cpw_extend=\"100um\",\n",
    "                pocket_extent=\"5um\",\n",
    "                pocket_rise=\"65um\",\n",
    "            ),\n",
    "            bus=dict(\n",
    "                loc_W=-1,\n",
    "                loc_H=-1,\n",
    "                pad_gap=\"15um\",\n",
    "                pad_width=\"125um\",\n",
    "                pad_height=\"30um\",\n",
    "                cpw_extend=\"100um\",\n",
    "                pocket_extent=\"5um\",\n",
    "                pocket_rise=\"65um\",\n",
    "            ),\n",
    "        ),\n",
    "    ),\n",
    "    make=True,\n",
    ")\n",
    "\n",
    "Q2 = TransmonPocketCL(\n",
    "    design,\n",
    "    \"Q2\",\n",
    "    options=dict(\n",
    "        pos_x=\"-0.7mm\",\n",
    "        pos_y=\"0mm\",\n",
    "        orientation=\"180\",\n",
    "        pad_gap=\"30um\",\n",
    "        inductor_width=\"20um\",\n",
    "        pad_width=\"425 um\",\n",
    "        pad_height=\"90um\",\n",
    "        pocket_width=\"650um\",\n",
    "        pocket_height=\"650um\",\n",
    "        gds_cell_name=\"FakeJunction_01\",\n",
    "        make_CL=True,\n",
    "        cl_gap=\"6um\",\n",
    "        cl_width=\"10um\",\n",
    "        cl_length=\"20um\",\n",
    "        cl_ground_gap=\"6um\",\n",
    "        cl_pocket_edge=\"180\",\n",
    "        cl_off_center=\"50um\",\n",
    "        connection_pads=dict(\n",
    "            readout=dict(\n",
    "                loc_W=1,\n",
    "                loc_H=1,\n",
    "                pad_gap=\"15um\",\n",
    "                pad_width=\"125um\",\n",
    "                pad_height=\"30um\",\n",
    "                cpw_extend=\"100um\",\n",
    "                pocket_extent=\"5um\",\n",
    "                pocket_rise=\"65um\",\n",
    "            ),\n",
    "            bus=dict(\n",
    "                loc_W=-1,\n",
    "                loc_H=-1,\n",
    "                pad_gap=\"15um\",\n",
    "                pad_width=\"125um\",\n",
    "                pad_height=\"30um\",\n",
    "                cpw_extend=\"100um\",\n",
    "                pocket_extent=\"5um\",\n",
    "                pocket_rise=\"65um\",\n",
    "            ),\n",
    "        ),\n",
    "    ),\n",
    "    make=True,\n",
    ")\n",
    "\n",
    "Bus_Q1_Q2 = RoutePathfinder(\n",
    "    design,\n",
    "    \"Bus_Q1_Q2\",\n",
    "    options=dict(\n",
    "        pin_inputs=dict(\n",
    "            start_pin=dict(component=\"Q1\", pin=\"bus\"),\n",
    "            end_pin=dict(component=\"Q2\", pin=\"bus\"),\n",
    "        ),\n",
    "        fillet=\"99um\",\n",
    "        total_length=\"7mm\",\n",
    "        layer=\"1\",\n",
    "        lead=dict(start_straight=\"0mm\", end_straight=\"250um\"),\n",
    "        advanced=dict(avoid_collision=\"true\"),\n",
    "        step_size=\"0.25mm\",\n",
    "    ),\n",
    ")\n",
    "\n",
    "Cap_Q1 = Cap3Interdigital(\n",
    "    design,\n",
    "    \"Cap_Q1\",\n",
    "    options=dict(\n",
    "        layer=\"1\",\n",
    "        pos_x=\"2.5mm\",\n",
    "        pos_y=\"0.25mm\",\n",
    "        orientation=\"90\",\n",
    "        trace_width=\"10um\",\n",
    "        finger_length=\"40um\",\n",
    "    ),\n",
    ")\n",
    "Cap_Q2 = Cap3Interdigital(\n",
    "    design,\n",
    "    \"Cap_Q2\",\n",
    "    options=dict(\n",
    "        layer=\"1\",\n",
    "        pos_x=\"-2.5mm\",\n",
    "        pos_y=\"-0.25mm\",\n",
    "        orientation=\"-90\",\n",
    "        trace_width=\"10um\",\n",
    "        finger_length=\"40um\",\n",
    "    ),\n",
    ")\n",
    "\n",
    "Readout_Q1 = RouteMeander(\n",
    "    design,\n",
    "    \"Readout_Q1\",\n",
    "    options=dict(\n",
    "        pin_inputs=dict(\n",
    "            start_pin=dict(component=\"Q1\", pin=\"readout\"),\n",
    "            end_pin=dict(component=\"Cap_Q1\", pin=\"a\"),\n",
    "        ),\n",
    "        fillet=\"99um\",\n",
    "        total_length=\"5mm\",\n",
    "        layer=\"1\",\n",
    "        lead=dict(start_straight=\"0.325mm\", end_straight=\"125um\"),\n",
    "        meander=dict(spacing=\"200um\", asymmetry=\"-50um\"),\n",
    "    ),\n",
    ")\n",
    "Readout_Q2 = RouteMeander(\n",
    "    design,\n",
    "    \"Readout_Q2\",\n",
    "    options=dict(\n",
    "        pin_inputs=dict(\n",
    "            start_pin=dict(component=\"Q2\", pin=\"readout\"),\n",
    "            end_pin=dict(component=\"Cap_Q2\", pin=\"a\"),\n",
    "        ),\n",
    "        fillet=\"99um\",\n",
    "        total_length=\"6mm\",\n",
    "        layer=\"1\",\n",
    "        lead=dict(start_straight=\"0.325mm\", end_straight=\"125um\"),\n",
    "        meander=dict(spacing=\"200um\", asymmetry=\"-50um\"),\n",
    "    ),\n",
    ")\n",
    "\n",
    "for name, px, py, ori in [\n",
    "    (\"Launch_Q1_Read\", \"3.5mm\", \"0um\", \"180\"),\n",
    "    (\"Launch_Q2_Read\", \"-3.5mm\", \"0um\", \"0\"),\n",
    "    (\"Launch_Q1_CL\", \"1.35mm\", \"-2.5mm\", \"90\"),\n",
    "    (\"Launch_Q2_CL\", \"-1.35mm\", \"2.5mm\", \"-90\"),\n",
    "]:\n",
    "    LaunchpadWirebond(\n",
    "        design,\n",
    "        name,\n",
    "        options=dict(\n",
    "            layer=\"1\",\n",
    "            pos_x=px,\n",
    "            pos_y=py,\n",
    "            orientation=ori,\n",
    "            trace_width=\"cpw_width\",\n",
    "            trace_gap=\"cpw_gap\",\n",
    "            lead_length=\"25um\",\n",
    "        ),\n",
    "    )\n",
    "\n",
    "for name, src_comp, src_pin, dst_comp, dst_pin, length in [\n",
    "    (\"TL_Q1\", \"Launch_Q1_Read\", \"tie\", \"Cap_Q1\", \"b\", \"7mm\"),\n",
    "    (\"TL_Q2\", \"Launch_Q2_Read\", \"tie\", \"Cap_Q2\", \"b\", \"7mm\"),\n",
    "    (\"TL_Q1_CL\", \"Launch_Q1_CL\", \"tie\", \"Q1\", \"Charge_Line\", \"7mm\"),\n",
    "    (\"TL_Q2_CL\", \"Launch_Q2_CL\", \"tie\", \"Q2\", \"Charge_Line\", \"7mm\"),\n",
    "]:\n",
    "    RoutePathfinder(\n",
    "        design,\n",
    "        name,\n",
    "        options=dict(\n",
    "            pin_inputs=dict(\n",
    "                start_pin=dict(component=src_comp, pin=src_pin),\n",
    "                end_pin=dict(component=dst_comp, pin=dst_pin),\n",
    "            ),\n",
    "            fillet=\"99um\",\n",
    "            total_length=length,\n",
    "            layer=\"1\",\n",
    "            lead=dict(start_straight=\"0mm\", end_straight=\"150um\"),\n",
    "            advanced=dict(avoid_collision=\"true\"),\n",
    "            step_size=\"0.25mm\",\n",
    "        ),\n",
    "    )\n",
    "\n",
    "print(f\"Design ready: {len(design.components)} components\")"
   ]
  },
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    {
     "data": {
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",
      "text/plain": [
       "<Figure size 900x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1300x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import qiskit_metal as qm\n",
    "\n",
    "fig_full = qm.view(design, figsize=(9, 9), title=\"Full 2-qubit chip\")\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(13, 6))\n",
    "qm.view(design, components=[\"Q1\"], title=\"Q1 — FakeJunction_01\", ax=axes[0])\n",
    "qm.view(design, components=[\"Q2\"], title=\"Q2 — FakeJunction_01\", ax=axes[1])\n",
    "plt.tight_layout()\n",
    "plt.close(fig)\n",
    "\n",
    "display(fig_full)\n",
    "display(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "760009da",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-31T23:57:28.386220Z",
     "iopub.status.busy": "2026-05-31T23:57:28.386124Z",
     "iopub.status.idle": "2026-05-31T23:57:28.399976Z",
     "shell.execute_reply": "2026-05-31T23:57:28.399506Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"\\nfrom qiskit_metal.qlibrary.tlines.meandered import RouteMeander\\n\\nfrom qiskit_metal.qlibrary.tlines.pathfinder import RoutePathfinder\\n\\nfrom qiskit_metal.qlibrary.qubits.transmon_pocket_cl import TransmonPocketCL\\n\\nfrom qiskit_metal.qlibrary.terminations.launchpad_wb import LaunchpadWirebond\\n\\nfrom qiskit_metal.qlibrary.lumped.cap_3_interdigital import Cap3Interdigital\\n\\nfrom qiskit_metal import designs, MetalGUI\\n\\ndesign = designs.DesignPlanar()\\n\\ngui = MetalGUI(design)\\n\\n\\n\\n            # WARNING\\n#options_connection_pads failed to have a value\\nQ1 = TransmonPocketCL(\\ndesign,\\nname='Q1',\\noptions={'cl_pocket_edge': '180',\\n 'connection_pads': {'bus': {'cpw_extend': '100um',\\n                             'cpw_gap': 'cpw_gap',\\n                             'cpw_width': 'cpw_width',\\n                             'loc_H': -1,\\n                             'loc_W': -1,\\n                             'pad_cpw_extent': '25um',\\n                             'pad_cpw_shift': '5um',\\n                             'pad_gap': '15um',\\n                             'pad_height': '30um',\\n                             'pad_width': '125um',\\n                             'pocket_extent': '5um',\\n                             'pocket_rise': '65um'},\\n                     'readout': {'cpw_extend': '100um',\\n                                 'cpw_gap': 'cpw_gap',\\n                                 'cpw_width': 'cpw_width',\\n                                 'loc_H': 1,\\n                                 'loc_W': 1,\\n                                 'pad_cpw_extent': '25um',\\n                                 'pad_cpw_shift': '5um',\\n                                 'pad_gap': '15um',\\n                                 'pad_height': '30um',\\n                                 'pad_width': '125um',\\n                                 'pocket_extent': '5um',\\n                                 'pocket_rise': '65um'}},\\n 'gds_cell_name': 'FakeJunction_01',\\n 'orientation': '0',\\n 'pad_width': '425 um',\\n 'pos_x': '0.7mm',\\n 'pos_y': '0mm'}\\n)\\n\\n\\n\\n\\n\\n            # WARNING\\n#options_connection_pads failed to have a value\\nQ2 = TransmonPocketCL(\\ndesign,\\nname='Q2',\\noptions={'cl_pocket_edge': '180',\\n 'connection_pads': {'bus': {'cpw_extend': '100um',\\n                             'cpw_gap': 'cpw_gap',\\n                             'cpw_width': 'cpw_width',\\n                             'loc_H': -1,\\n                             'loc_W': -1,\\n                             'pad_cpw_extent': '25um',\\n                             'pad_cpw_shift': '5um',\\n                             'pad_gap': '15um',\\n                             'pad_height': '30um',\\n                             'pad_width': '125um',\\n                             'pocket_extent': '5um',\\n                             'pocket_rise': '65um'},\\n                     'readout': {'cpw_extend': '100um',\\n                                 'cpw_gap': 'cpw_gap',\\n                                 'cpw_width': 'cpw_width',\\n                                 'loc_H': 1,\\n                                 'loc_W': 1,\\n                                 'pad_cpw_extent': '25um',\\n                                 'pad_cpw_shift': '5um',\\n                                 'pad_gap': '15um',\\n                                 'pad_height': '30um',\\n                                 'pad_width': '125um',\\n                                 'pocket_extent': '5um',\\n                                 'pocket_rise': '65um'}},\\n 'gds_cell_name': 'FakeJunction_01',\\n 'orientation': '180',\\n 'pad_width': '425 um',\\n 'pos_x': '-0.7mm',\\n 'pos_y': '0mm'}\\n)\\n\\n\\n\\n\\nBus_Q1_Q2 = RoutePathfinder(\\ndesign,\\nname='Bus_Q1_Q2',\\noptions={'_actual_length': '0.8550176727053895 '\\n                   'mm',\\n 'fillet': '99um',\\n 'lead': {'end_jogged_extension': '',\\n          'end_straight': '250um',\\n          'start_jogged_extension': '',\\n          'start_straight': '0mm'},\\n 'pin_inputs': {'end_pin': {'component': 'Q2',\\n                            'pin': 'bus'},\\n                'start_pin': {'component': 'Q1',\\n                              'pin': 'bus'}},\\n 'trace_gap': 'cpw_gap'},\\n\\ntype='CPW',\\n)\\n\\n\\n\\n\\nCap_Q1 = Cap3Interdigital(\\ndesign,\\nname='Cap_Q1',\\noptions={'finger_length': '40um',\\n 'orientation': '90',\\n 'pos_x': '2.5mm',\\n 'pos_y': '0.25mm'},\\n\\ncomponent_template=None,\\n)\\n\\n\\n\\n\\nCap_Q2 = Cap3Interdigital(\\ndesign,\\nname='Cap_Q2',\\noptions={'finger_length': '40um',\\n 'orientation': '-90',\\n 'pos_x': '-2.5mm',\\n 'pos_y': '-0.25mm'},\\n\\ncomponent_template=None,\\n)\\n\\n\\n\\n\\nReadout_Q1 = RouteMeander(\\ndesign,\\nname='Readout_Q1',\\noptions={'_actual_length': '5.000000000000001 '\\n                   'mm',\\n 'fillet': '99um',\\n 'lead': {'end_jogged_extension': '',\\n          'end_straight': '125um',\\n          'start_jogged_extension': '',\\n          'start_straight': '0.325mm'},\\n 'meander': {'asymmetry': '-50um',\\n             'spacing': '200um'},\\n 'pin_inputs': {'end_pin': {'component': 'Cap_Q1',\\n                            'pin': 'a'},\\n                'start_pin': {'component': 'Q1',\\n                              'pin': 'readout'}},\\n 'total_length': '5mm',\\n 'trace_gap': 'cpw_gap'},\\n\\ntype='CPW',\\n)\\n\\n\\n\\n\\nReadout_Q2 = RouteMeander(\\ndesign,\\nname='Readout_Q2',\\noptions={'_actual_length': '5.999999999999999 '\\n                   'mm',\\n 'fillet': '99um',\\n 'lead': {'end_jogged_extension': '',\\n          'end_straight': '125um',\\n          'start_jogged_extension': '',\\n          'start_straight': '0.325mm'},\\n 'meander': {'asymmetry': '-50um',\\n             'spacing': '200um'},\\n 'pin_inputs': {'end_pin': {'component': 'Cap_Q2',\\n                            'pin': 'a'},\\n                'start_pin': {'component': 'Q2',\\n                              'pin': 'readout'}},\\n 'total_length': '6mm',\\n 'trace_gap': 'cpw_gap'},\\n\\ntype='CPW',\\n)\\n\\n\\n\\n\\nLaunch_Q1_Read = LaunchpadWirebond(\\ndesign,\\nname='Launch_Q1_Read',\\noptions={'orientation': '180',\\n 'pos_x': '3.5mm',\\n 'pos_y': '0um'},\\n\\ncomponent_template=None,\\n)\\n\\n\\n\\n\\nLaunch_Q2_Read = LaunchpadWirebond(\\ndesign,\\nname='Launch_Q2_Read',\\noptions={'orientation': '0',\\n 'pos_x': '-3.5mm',\\n 'pos_y': '0um'},\\n\\ncomponent_template=None,\\n)\\n\\n\\n\\n\\nLaunch_Q1_CL = LaunchpadWirebond(\\ndesign,\\nname='Launch_Q1_CL',\\noptions={'orientation': '90',\\n 'pos_x': '1.35mm',\\n 'pos_y': '-2.5mm'},\\n\\ncomponent_template=None,\\n)\\n\\n\\n\\n\\nLaunch_Q2_CL = LaunchpadWirebond(\\ndesign,\\nname='Launch_Q2_CL',\\noptions={'orientation': '-90',\\n 'pos_x': '-1.35mm',\\n 'pos_y': '2.5mm'},\\n\\ncomponent_template=None,\\n)\\n\\n\\n\\n\\nTL_Q1 = RoutePathfinder(\\ndesign,\\nname='TL_Q1',\\noptions={'_actual_length': '1.0750176727053897 '\\n                   'mm',\\n 'fillet': '99um',\\n 'lead': {'end_jogged_extension': '',\\n          'end_straight': '150um',\\n          'start_jogged_extension': '',\\n          'start_straight': '0mm'},\\n 'pin_inputs': {'end_pin': {'component': 'Cap_Q1',\\n                            'pin': 'b'},\\n                'start_pin': {'component': 'Launch_Q1_Read',\\n                              'pin': 'tie'}},\\n 'trace_gap': 'cpw_gap'},\\n\\ntype='CPW',\\n)\\n\\n\\n\\n\\nTL_Q2 = RoutePathfinder(\\ndesign,\\nname='TL_Q2',\\noptions={'_actual_length': '1.0750176727053897 '\\n                   'mm',\\n 'fillet': '99um',\\n 'lead': {'end_jogged_extension': '',\\n          'end_straight': '150um',\\n          'start_jogged_extension': '',\\n          'start_straight': '0mm'},\\n 'pin_inputs': {'end_pin': {'component': 'Cap_Q2',\\n                            'pin': 'b'},\\n                'start_pin': {'component': 'Launch_Q2_Read',\\n                              'pin': 'tie'}},\\n 'trace_gap': 'cpw_gap'},\\n\\ntype='CPW',\\n)\\n\\n\\n\\n\\nTL_Q1_CL = RoutePathfinder(\\ndesign,\\nname='TL_Q1_CL',\\noptions={'_actual_length': '2.610508836352695 '\\n                   'mm',\\n 'fillet': '99um',\\n 'lead': {'end_jogged_extension': '',\\n          'end_straight': '150um',\\n          'start_jogged_extension': '',\\n          'start_straight': '0mm'},\\n 'pin_inputs': {'end_pin': {'component': 'Q1',\\n                            'pin': 'Charge_Line'},\\n                'start_pin': {'component': 'Launch_Q1_CL',\\n                              'pin': 'tie'}},\\n 'trace_gap': 'cpw_gap'},\\n\\ntype='CPW',\\n)\\n\\n\\n\\n\\nTL_Q2_CL = RoutePathfinder(\\ndesign,\\nname='TL_Q2_CL',\\noptions={'_actual_length': '2.610508836352695 '\\n                   'mm',\\n 'fillet': '99um',\\n 'lead': {'end_jogged_extension': '',\\n          'end_straight': '150um',\\n          'start_jogged_extension': '',\\n          'start_straight': '0mm'},\\n 'pin_inputs': {'end_pin': {'component': 'Q2',\\n                            'pin': 'Charge_Line'},\\n                'start_pin': {'component': 'Launch_Q2_CL',\\n                              'pin': 'tie'}},\\n 'trace_gap': 'cpw_gap'},\\n\\ntype='CPW',\\n)\\n\\n\\n\\ngui.rebuild()\\ngui.autoscale()\\n        \""
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "design.to_python_script()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a005811d",
   "metadata": {},
   "source": [
    "## Saving with `to_python_script()`\n",
    "\n",
    "`design.to_python_script()` serialises the entire design state — every component, every option, every route — into a self-contained Python script. Running that script recreates the design identically, with no dependency on the original notebook session.\n",
    "\n",
    "**When to use it:**\n",
    "- **Version control** — commit the `.py` file alongside your notebook; diffs are readable\n",
    "- **Sharing** — send the script to a collaborator who can reproduce the exact design\n",
    "- **Headless / batch** — run the script in CI or a parameter sweep without launching the GUI\n",
    "- **Long-term archiving** — the script is plain Python, readable years later without notebook tooling\n",
    "\n",
    "The output prints to the cell below. Copy it into the cell underneath and run it to verify it reproduces your design cleanly."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e614c57e",
   "metadata": {},
   "source": [
    "### Replay the saved script\n",
    "\n",
    "Copy the output from the cell above into a fresh code cell (or a `.py` file) and run it. It should rebuild the full design without any of the intermediate cells above.\n",
    "\n",
    "You can also save it directly to a file:\n",
    "\n",
    "```python\n",
    "import pathlib\n",
    "\n",
    "script = design.to_python_script()          # returns the script as a string\n",
    "pathlib.Path(\"my_chip_design.py\").write_text(script)\n",
    "print(\"Saved to my_chip_design.py\")\n",
    "```\n",
    "\n",
    "Then replay from the command line:\n",
    "\n",
    "```bash\n",
    "python my_chip_design.py\n",
    "```\n",
    "\n",
    "> **Tip:** the script is deterministic — running it twice produces the same geometry. This makes it safe to use as a fixture in automated tests or as input to a parameter sweep."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30460f25",
   "metadata": {},
   "source": [
    "## Exporting to GDS\n",
    "\n",
    "`to_python_script()` captures your design intent; GDS export produces the fabrication mask. The GDS renderer handles junction placement, ground-plane cheesing, and layer assignment.\n",
    "\n",
    "```python\n",
    "gds = design.renderers.gds\n",
    "\n",
    "# Point to a GDS file containing your Josephson junction cells.\n",
    "# The file can use any unit (µm, nm, mm) — the renderer auto-scales.\n",
    "gds.options.path_filename = \"../resources/Fake_Junctions.GDS\"\n",
    "\n",
    "# Control whether cheese/no-cheese geometry appears in the output.\n",
    "# {1: False} = process layer 1 but suppress cheese holes from the file.\n",
    "# Using Dict(main={}) omits the layer entirely and triggers a warning.\n",
    "gds.options.cheese.view_in_file    = Dict(main={1: False})\n",
    "gds.options.no_cheese.view_in_file = Dict(main={1: False})\n",
    "\n",
    "gds.export_to_gds(\"my_chip.gds\")\n",
    "```\n",
    "\n",
    "After export, inspect the result:\n",
    "\n",
    "```python\n",
    "import gdstk\n",
    "\n",
    "lib = gdstk.read_gds(\"my_chip.gds\")\n",
    "\n",
    "# show=True embeds an SVG preview directly in this cell output.\n",
    "# Increase scale for a larger chip; increase width to fill the cell.\n",
    "gds.debug_summarize_gds_library(lib, show=True, scale=100, width=900)\n",
    "```\n",
    "\n",
    "### Junction units\n",
    "\n",
    "The qubit components in this design use `gds_cell_name` to name the junction placeholder:\n",
    "\n",
    "| Qubit | `gds_cell_name` |\n",
    "|-------|----------------|\n",
    "| Q1 | `FakeJunction_01` |\n",
    "| Q2 | `FakeJunction_02` |\n",
    "\n",
    "These names must match cells inside the GDS file pointed to by `path_filename`. The renderer reads the file's `unit` field and rescales all junction geometry automatically — a junction file in nm, µm, or any other unit will land at the correct physical size. See **1.1 Quick start → Render to GDS** for a full walkthrough including layer options and the debug summary tool.\n",
    "\n",
    "### What's next\n",
    "\n",
    "- **1.1 Quick start** — run and visualise this design without the Qt GUI\n",
    "- **2 From components to chip** — multi-qubit designs, CPW routing, and design variables\n",
    "- **3 Renderers** — HFSS, Q3D, GDS, and gmsh/Elmer in depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3c244cef-b426-4784-911d-d36b4e20eb9a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-31T23:57:28.401387Z",
     "iopub.status.busy": "2026-05-31T23:57:28.401299Z",
     "iopub.status.idle": "2026-05-31T23:57:28.434510Z",
     "shell.execute_reply": "2026-05-31T23:57:28.434076Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "04:57PM 28s WARNING [import_junction_gds_file]: Not able to find file:\"../resources/Fake_Junctions.GDS\".  Not used to replace junction. Checked directory:\"/Users/zlatkominev/CODE_REPOS/quantum_hardware/qiskit-metal/docs/tut/resources\".\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit_metal import Dict, open_docs\n",
    "\n",
    "gds = design.renderers.gds\n",
    "\n",
    "# Point to a GDS file containing your Josephson junction cells.\n",
    "# The file can use any unit (µm, nm, mm) — the renderer auto-scales.\n",
    "gds.options.path_filename = \"../resources/Fake_Junctions.GDS\"\n",
    "\n",
    "# Control whether cheese/no-cheese geometry appears in the output.\n",
    "# {1: False} = process layer 1 but suppress cheese holes from the file.\n",
    "# Using Dict(main={}) omits the layer entirely and triggers a warning.\n",
    "gds.options.cheese.view_in_file = Dict(main={1: False})\n",
    "gds.options.no_cheese.view_in_file = Dict(main={1: False})\n",
    "\n",
    "gds.export_to_gds(\"my_chip.gds\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "47d96d2e-6fea-4ede-aeb9-ffca207e6915",
   "metadata": {
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     "iopub.execute_input": "2026-05-31T23:57:28.435780Z",
     "iopub.status.busy": "2026-05-31T23:57:28.435710Z",
     "iopub.status.idle": "2026-05-31T23:57:28.444612Z",
     "shell.execute_reply": "2026-05-31T23:57:28.443860Z"
    }
   },
   "outputs": [
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       "</g>\n",
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       "</defs>\n",
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       "</g>\n",
       "</svg></div><table style=\"font-size:12px;font-family:monospace;border-collapse:collapse;margin-top:8px\"><thead><tr style=\"border-bottom:1px solid #ccc;text-align:left\"><th></th><th style=\"padding:1px 10px\">Layer</th><th style=\"padding:1px 10px\">DType</th><th style=\"padding:1px 10px\">Description</th><th style=\"padding:1px 10px\">Polygons</th><th style=\"padding:1px 10px\">Paths</th></tr></thead><tbody><tr><td><div style=\"width:18px;height:12px;background:#4C9BE8;border:1px solid #888;border-radius:2px;margin:2px 0\"></div></td><td style=\"padding:1px 10px\">1</td><td style=\"padding:1px 10px\">0</td><td style=\"padding:1px 10px;color:#555\">metal (boolean result)</td><td style=\"padding:1px 10px;text-align:right\">39 poly</td><td style=\"padding:1px 10px;text-align:right\">0 paths</td></tr><tr><td><div style=\"width:18px;height:12px;background:#F5A623;border:1px solid #888;border-radius:2px;margin:2px 0\"></div></td><td style=\"padding:1px 10px\">1</td><td style=\"padding:1px 10px\">10</td><td style=\"padding:1px 10px;color:#555\">component polygon input</td><td style=\"padding:1px 10px;text-align:right\">28 poly</td><td style=\"padding:1px 10px;text-align:right\">0 paths</td></tr><tr><td><div style=\"width:18px;height:12px;background:#7ED321;border:1px solid #888;border-radius:2px;margin:2px 0\"></div></td><td style=\"padding:1px 10px\">1</td><td style=\"padding:1px 10px\">11</td><td style=\"padding:1px 10px;color:#555\">CPW FlexPath trace</td><td style=\"padding:1px 10px;text-align:right\">42 poly</td><td style=\"padding:1px 10px;text-align:right\">0 paths</td></tr></tbody></table>"
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       "<IPython.core.display.HTML object>"
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "=== GDS LIBRARY SUMMARY ===\n",
      "name:      library\n",
      "unit:      0.001\n",
      "precision: 1e-09\n",
      "cells:     4\n",
      "\n",
      "CELLS:\n",
      "  - TOP                            geom=True bbox=((-4.5, -3.0), (4.5, 3.0))\n",
      "  - TOP_main                       geom=True bbox=((-4.5, -3.0), (4.5, 3.0))\n",
      "  - TOP_main_1                     geom=True bbox=((-4.5, -3.0), (4.5, 3.0))\n",
      "  - ground_main_1                  geom=True bbox=((-4.5, -3.0), (4.5, 3.0))\n",
      "\n",
      "LAYER / DATATYPE USAGE:\n",
      "  layer  dtype   polys   paths\n",
      "  -----  -----   -----   -----\n",
      "      1      0      39       0\n",
      "      1     10      28       0\n",
      "      1     11      42       0\n",
      "\n",
      "=== END SUMMARY ===\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import gdstk\n",
    "\n",
    "lib = gdstk.read_gds(\"my_chip.gds\")\n",
    "\n",
    "# show=True embeds an SVG preview directly in this cell output.\n",
    "# Increase scale for a larger chip; increase width to fill the cell.\n",
    "gds.debug_summarize_gds_library(lib, show=True, scale=100, width=900)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0348dfe6",
   "metadata": {},
   "source": [
    "### GDS layer legend\n",
    "\n",
    "The renderer writes geometry across several **layer / datatype** pairs.\n",
    "The layer number matches the `layer` option on each component (default `1`).\n",
    "The datatype encodes how the geometry was produced:\n",
    "\n",
    "| Layer | Datatype | Content |\n",
    "|-------|----------|---------|\n",
    "| 1 | 0 | **Final metal pattern** — post-boolean result (chip outline, ground plane, qubit pockets merged into a single mask) |\n",
    "| 1 | 10 | **Component polygons** — individual pad, pocket, and junction-extension-pad outlines before the boolean merge |\n",
    "| 1 | 11 | **CPW traces** — `FlexPath` geometry for routes, transmission lines, and connectors |\n",
    "| 53 | 0 | **Junction primary layer** — polygons from the imported junction GDS file (`FakeJunction_01/02`) |\n",
    "| 54 | 0 | **Junction secondary layer** — second contact layer from the same junction GDS file |\n",
    "\n",
    "> **Layers 53 and 54 are whatever layers your junction file uses.** If you supply\n",
    "> your own junction GDS, its layer numbers will appear here instead. Use KLayout's\n",
    "> layer panel (right-hand side) to toggle each layer on/off and identify them.\n",
    "\n",
    "The `plot_gds_zoom` panels below colour each `(layer, datatype)` pair distinctly,\n",
    "making it easy to see where the junction sits relative to the qubit pads.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c97fcee",
   "metadata": {},
   "source": [
    "### Zooming into junction pads in GDS\n",
    "\n",
    "``debug_summarize_gds_library`` gives a chip-level overview. To inspect individual junctions at fabrication scale, ``gds.plot_gds_zoom`` clips a small window out of the flattened GDS and renders it with matplotlib — no KLayout required.\n",
    "\n",
    "It works by calling ``top.get_polygons(depth=None)`` to flatten the full cell hierarchy, filtering to a bounding box around your target, then drawing each polygon coloured by ``(layer, datatype)``.\n",
    "\n",
    "> **Matplotlib backend note:** when ``qm.gui(design)`` returns the desktop ``MetalGUI`` (Qt path), matplotlib's backend is ``Qt6Agg`` — ``plt.subplots()`` then opens a Qt window instead of rendering inline. The ``%matplotlib inline`` cell below resets to the static ``Agg`` backend. With the headless viewer this isn't needed; the inline backend is already active."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e635be1c-547d-47f9-a2af-bd536837c6da",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-31T23:57:28.445937Z",
     "iopub.status.busy": "2026-05-31T23:57:28.445864Z",
     "iopub.status.idle": "2026-05-31T23:57:28.448507Z",
     "shell.execute_reply": "2026-05-31T23:57:28.447678Z"
    }
   },
   "outputs": [],
   "source": [
    "# Reset to the static Agg backend so plots render inline.\n",
    "# Needed because MetalGUI (used above) initialises PySide6 which can\n",
    "# switch matplotlib to Qt6Agg. See the note in the markdown cell above.\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "81267beb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-31T23:57:28.449636Z",
     "iopub.status.busy": "2026-05-31T23:57:28.449566Z",
     "iopub.status.idle": "2026-05-31T23:57:28.574984Z",
     "shell.execute_reply": "2026-05-31T23:57:28.574600Z"
    },
    "nbsphinx-thumbnail": {}
   },
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1300x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Zoom into each qubit — 200 µm window centred on the junction.\n",
    "# Q1 sits at (0.70,  0) mm (orientation   0°) → junction cell rotated  90° → vertical\n",
    "# Q2 sits at (−0.70, 0) mm (orientation 180°) → junction cell rotated −90° → vertical\n",
    "fig, axes = plt.subplots(1, 2, figsize=(13, 6))\n",
    "fig.suptitle(\"GDS junction pad zoom — 200 µm window\", fontsize=13)\n",
    "\n",
    "gds.plot_gds_zoom(\n",
    "    lib,\n",
    "    center_mm=(0.70, 0.0),\n",
    "    span_mm=0.10,\n",
    "    title=\"Q1 — FakeJunction_01 at (0.7, 0) mm\",\n",
    "    ax=axes[0],\n",
    ")\n",
    "gds.plot_gds_zoom(\n",
    "    lib,\n",
    "    center_mm=(-0.70, 0.0),\n",
    "    span_mm=0.10,\n",
    "    title=\"Q2 — FakeJunction_02 at (−0.7, 0) mm\",\n",
    "    ax=axes[1],\n",
    ")\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.close(fig)\n",
    "# fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7e4c9d2-viewer",
   "metadata": {},
   "source": [
    "## Viewing your GDS file\n",
    "\n",
    "Once you have a `.gds` file, you'll want to inspect it visually — zoom into junction pads, verify layer colours, check that routes don't collide. Several free tools can do this on every platform.\n",
    "\n",
    "---\n",
    "\n",
    "### KLayout (recommended)\n",
    "\n",
    "[KLayout](https://www.klayout.de) is the industry-standard open-source GDS/OASIS viewer and editor. It handles multi-layer designs, has a Python scripting console, and runs on **Windows, macOS, and Linux**.\n",
    "\n",
    "**Install:**\n",
    "\n",
    "| Platform | Method |\n",
    "|----------|---------|\n",
    "| **macOS** | `brew install --cask klayout` — or download the `.dmg` from [klayout.de/build.html](https://www.klayout.de/build.html) |\n",
    "| **Windows** | Download the `.exe` installer from [klayout.de/build.html](https://www.klayout.de/build.html) |\n",
    "| **Linux** | `.rpm` / `.deb` packages available, or `conda install -c conda-forge klayout` |\n",
    "\n",
    "**Open your file:**\n",
    "\n",
    "```bash\n",
    "# From the terminal — opens KLayout with the file loaded\n",
    "klayout my_chip.gds\n",
    "```\n",
    "\n",
    "Or launch KLayout and use **File → Open**.\n",
    "\n",
    "**Key things to check:**\n",
    "- **Layer panel** (right side) — toggle layers on/off to isolate metal, junctions, cheese holes\n",
    "- **Ruler tool** (`R`) — measure distances in design units\n",
    "- **Zoom to fit** (`F`) — see the full chip at once\n",
    "- **Zoom into junction pads** — verify physical size matches your design (30 µm × 3 µm for the fake junctions here)\n",
    "\n",
    "---\n",
    "\n",
    "### Quick in-notebook preview (no install needed)\n",
    "\n",
    "You already have `gdstk` and the `debug_summarize_gds_library` tool. For a fast sanity check without leaving Jupyter:\n",
    "\n",
    "```python\n",
    "import gdstk\n",
    "lib = gdstk.read_gds(\"my_chip.gds\")\n",
    "gds.debug_summarize_gds_library(lib, show=True, scale=100, width=900)\n",
    "```\n",
    "\n",
    "This embeds an SVG overview directly in the cell output and saves with the notebook. Good for a quick geometry and layer check; use KLayout for detailed inspection.\n",
    "\n",
    "---\n",
    "\n",
    "### Other free viewers\n",
    "\n",
    "| Tool | Platform | Notes |\n",
    "|------|----------|-------|\n",
    "| [gdstk](https://heitzmann.github.io/gdstk/) | Python (all platforms) | Programmatic; `cell.write_svg()` for per-cell previews |\n",
    "| [Magic VLSI](http://opencircuitdesign.com/magic/) | Linux / macOS | Full DRC + extraction; steeper learning curve |\n",
    "| [GDS3D](https://github.com/trilomix/GDS3D) | Windows / Linux | 3D visualisation of GDS layers |\n"
   ]
  }
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