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   "source": [
    "# Example-16: Custom (element)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "05dfd677-0519-49da-924a-73f697af4e25",
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   "source": [
    "# In this example steps to build element with custom transformatiion are shown\n",
    "# This element can be used to wrap a custom transformation and used it with other elements\n",
    "# Construction requires transformation to be passed as a parameter\n",
    "# This transformation is expected to have certain signature\n",
    "# The first parameter is state (qx, px, qy, py) followed by other tensor knobs\n",
    "# These knobs are passed simular to deviation parameters in standart elements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "417812bd-a1bb-4fa9-9be8-dbbd84b5a0e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "\n",
    "from model.library.transformations import quadrupole\n",
    "from model.library.quadrupole import Quadrupole\n",
    "from model.library.custom import Custom"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f56c4bcd-818e-4c8b-91a4-9743d71a6b68",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([-0.0101, -0.0189, -0.0173, -0.0385], dtype=torch.float64)\n",
      "tensor([-0.0101, -0.0189, -0.0173, -0.0385], dtype=torch.float64)\n"
     ]
    }
   ],
   "source": [
    "# Build custom element using a transformation\n",
    "\n",
    "state = torch.tensor([0.01, -0.005, -0.005, 0.001], dtype=torch.float64)\n",
    "\n",
    "kn = torch.tensor(5.0, dtype=torch.float64)\n",
    "ks = torch.tensor(1.0, dtype=torch.float64)\n",
    "dp = torch.tensor(0.001, dtype=torch.float64)\n",
    "length = torch.tensor(1.0, dtype=torch.float64)\n",
    "\n",
    "print(quadrupole(state, kn, ks, dp, length))\n",
    "\n",
    "C = Custom('C', quadrupole, ['kn', 'ks', 'dp', 'length'], length=1.0, angle=0.0, dp=dp.item())\n",
    "\n",
    "print(C(state, data={**C.data(), **{'kn': kn, 'ks': ks, 'dp': dp, 'length': length}}, alignment=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dc1a5880-bcc5-4f9f-aeaa-5f863c1edbda",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([-0.0149, -0.0080, -0.0454, -0.1485], dtype=torch.float64)\n",
      "tensor([-0.0149, -0.0080, -0.0454, -0.1485], dtype=torch.float64)\n",
      "tensor([-0.0149, -0.0080, -0.0454, -0.1485], dtype=torch.float64)\n"
     ]
    }
   ],
   "source": [
    "# Use regular element step\n",
    "\n",
    "state = torch.tensor([0.01, -0.005, -0.005, 0.001], dtype=torch.float64)\n",
    "\n",
    "kn = torch.tensor(5.0, dtype=torch.float64)\n",
    "ks = torch.tensor(1.0, dtype=torch.float64)\n",
    "dp = torch.tensor(0.001, dtype=torch.float64)\n",
    "dl = torch.tensor(0.0, dtype=torch.float64)\n",
    "\n",
    "Q = Quadrupole('Q', 1.0, 5.0, 1.0, dp=0.001, dx=-0.001)\n",
    "print(Q(state, data={**Q.data(), **{'kn': kn, 'ks': ks, 'dp': dp, 'dl': dl}}, alignment=False))\n",
    "\n",
    "print(Q._step(state, kn, ks, dp, dl))\n",
    "\n",
    "C = Custom('C', Q._step, ['kn', 'ks', 'dp', 'dl'], length=1.0, angle=0.0, dp=0.001, dx=-0.001)\n",
    "print(C(state, data={**C.data(), **{'kn': kn, 'ks': ks, 'dp': dp, 'dl': dl}}, alignment=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ab3c99c7-74ee-4f6a-9ab6-ff3073978df5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([-0.0168, -0.0074, -0.0441, -0.1447], dtype=torch.float64)\n",
      "tensor([-0.0168, -0.0074, -0.0441, -0.1447], dtype=torch.float64)\n"
     ]
    }
   ],
   "source": [
    "# Alignment support\n",
    "\n",
    "print(Q(state, data={**Q.data(), **{'kn': kn, 'ks': ks, 'dp': dp, 'dl': dl}}, alignment=True))\n",
    "print(C(state, data={**C.data(), **{'kn': kn, 'ks': ks, 'dp': dp, 'dl': dl}}, alignment=True))"
   ]
  }
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