{ "cells": [ { "cell_type": "markdown", "id": "1a31ccc5-2a60-4710-af94-f8ce7ab69fa4", "metadata": {}, "source": [ "## ELETTRA-02: Linear optics comparison" ] }, { "cell_type": "code", "execution_count": 1, "id": "524cf7e5-21df-4825-be15-63a090696643", "metadata": {}, "outputs": [], "source": [ "# In this example linear optics is computed for Elettra 2.0 storage ring and compared with ELEGANT\n", "# Note, to get smooth optics output elements are sliced, this results in dispersion being slightly off (no difference without slicing)" ] }, { "cell_type": "code", "execution_count": 2, "id": "04e0808c-1a2e-4cc8-afc3-0c7dcfbd3319", "metadata": {}, "outputs": [], "source": [ "# Import\n", "\n", "import torch\n", "from torch import Tensor\n", "\n", "from pathlib import Path\n", "\n", "import matplotlib\n", "from matplotlib import pyplot as plt\n", "from matplotlib.patches import Rectangle\n", "matplotlib.rcParams['text.usetex'] = True\n", "\n", "from model.library.element import Element\n", "from model.library.line import Line\n", "from model.library.quadrupole import Quadrupole\n", "\n", "from model.command.util import select\n", "from model.command.external import load_sdds\n", "from model.command.external import load_lattice\n", "from model.command.build import build\n", "from model.command.layout import Layout\n", "from model.command.tune import tune\n", "from model.command.orbit import dispersion\n", "from model.command.twiss import twiss\n", "from model.command.advance import advance" ] }, { "cell_type": "code", "execution_count": 3, "id": "a2a06b8d-749d-4cb6-b1df-9e2ff57d8e06", "metadata": {}, "outputs": [], "source": [ "# Set data type and device\n", "\n", "Element.dtype = dtype = torch.float64\n", "Element.device = device = torch.device('cpu')" ] }, { "cell_type": "code", "execution_count": 4, "id": "09180b7b-d6f1-4d50-a587-0ebdd4beaa6d", "metadata": {}, "outputs": [], "source": [ "# Load ELEGANT data at BPMs\n", "\n", "# Note, the following creates a python dictionary using element names as keys\n", "# Repeated elements are collapsed\n", "\n", "path = Path('elettra.twiss')\n", "parameters, columns = load_sdds(path)\n", "\n", "# Tune\n", "\n", "nu_x:Tensor = torch.tensor(parameters['nux'], dtype=dtype)\n", "nu_y:Tensor = torch.tensor(parameters['nuy'], dtype=dtype)\n", "\n", "# Chomaticity\n", "\n", "xi_x:Tensor = torch.tensor(parameters['dnux/dp'], dtype=dtype)\n", "xi_y:Tensor = torch.tensor(parameters['dnuy/dp'], dtype=dtype)\n", "\n", "# Element kind\n", "\n", "kinds = select(columns, 'ElementType', keep=False)\n", "\n", "# Dispersion\n", "\n", "eta_qx = select(columns, 'etax' , keep=False)\n", "eta_px = select(columns, 'etaxp', keep=False)\n", "eta_qy = select(columns, 'etay' , keep=False)\n", "eta_py = select(columns, 'etayp', keep=False)\n", "\n", "eta_qx = torch.tensor([value for (key, value), kind in zip(eta_qx.items(), kinds.values()) if kind == 'MONI'], dtype=dtype)\n", "eta_px = torch.tensor([value for (key, value), kind in zip(eta_px.items(), kinds.values()) if kind == 'MONI'], dtype=dtype)\n", "eta_qy = torch.tensor([value for (key, value), kind in zip(eta_qy.items(), kinds.values()) if kind == 'MONI'], dtype=dtype)\n", "eta_py = torch.tensor([value for (key, value), kind in zip(eta_py.items(), kinds.values()) if kind == 'MONI'], dtype=dtype)\n", "\n", "# Twiss\n", "\n", "a_x = select(columns, 'alphax', keep=False)\n", "b_x = select(columns, 'betax' , keep=False)\n", "a_y = select(columns, 'alphay', keep=False)\n", "b_y = select(columns, 'betay' , keep=False)\n", "\n", "a_x:Tensor = torch.tensor([value for (key, value), kind in zip(a_x.items(), kinds.values()) if kind == 'MONI'], dtype=dtype)\n", "b_x:Tensor = torch.tensor([value for (key, value), kind in zip(b_x.items(), kinds.values()) if kind == 'MONI'], dtype=dtype)\n", "a_y:Tensor = torch.tensor([value for (key, value), kind in zip(a_y.items(), kinds.values()) if kind == 'MONI'], dtype=dtype)\n", "b_y:Tensor = torch.tensor([value for (key, value), kind in zip(b_y.items(), kinds.values()) if kind == 'MONI'], dtype=dtype)\n", "\n", "# Advance (accumulated from lattice start to each BPM position)\n", "\n", "mu_x = select(columns, 'psix', keep=False)\n", "mu_y = select(columns, 'psiy' , keep=False)\n", "\n", "mu_x:Tensor = torch.tensor([value for (key, value), kind in zip(mu_x.items(), kinds.values()) if kind == 'MONI'], dtype=dtype)\n", "mu_y:Tensor = torch.tensor([value for (key, value), kind in zip(mu_y.items(), kinds.values()) if kind == 'MONI'], dtype=dtype)\n", "\n", "# BPM positions\n", "\n", "positions = select(columns, 's', keep=False).items()\n", "positions = [value for (key, value), kind in zip(positions, kinds.values()) if kind == 'MONI']" ] }, { "cell_type": "code", "execution_count": 5, "id": "db2eecba-25fa-49c9-b08f-36807d8e0008", "metadata": {}, "outputs": [], "source": [ "# Load lattice (ELEGANT table)\n", "# Note, lattice is allowed to have repeated elements\n", "\n", "path = Path('elettra.lte')\n", "data = load_lattice(path)" ] }, { "cell_type": "code", "execution_count": 6, "id": "a30a3c0a-d97c-4214-a800-31d5d5d66d18", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'Marker': 12, 'Drift': 708, 'BPM': 168, 'Quadrupole': 360, 'Dipole': 156}" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Build and setup lattice\n", "\n", "ring:Line = build('RING', 'ELEGANT', data)\n", "\n", "# Flatten sublines\n", "\n", "ring.flatten()\n", "\n", "# Remove all marker elements but the ones starting with MLL (long straight section centers)\n", "\n", "ring.remove_group(pattern=r'^(?!MLL_).*', kinds=['Marker'])\n", "\n", "# Replace all sextupoles with quadrupoles\n", "\n", "def factory(element:Element) -> None:\n", " table = element.serialize\n", " table.pop('ms', None)\n", " return Quadrupole(**table)\n", "\n", "ring.replace_group(pattern=r'', factory=factory, kinds=['Sextupole'])\n", "\n", "# Set linear dipoles\n", "\n", "def apply(element:Element) -> None:\n", " element.linear = True\n", "\n", "ring.apply(apply, kinds=['Dipole'])\n", "\n", "# Merge drifts\n", "\n", "ring.merge()\n", "\n", "# Split elements (smooth twiss output)\n", "\n", "step = 0.05\n", "for element in ring:\n", " if length := element.length:\n", " ring.split((int(length/step), None, [element.name], None))\n", "\n", "# Describe\n", "\n", "ring.describe" ] }, { "cell_type": "code", "execution_count": 7, "id": "dfc6ad06-bf8e-4c91-aa86-ed93e0714582", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "True\n", "True\n" ] } ], "source": [ "# Compute tunes (fractional part)\n", "\n", "nux, nuy = tune(ring, [], matched=True, limit=1)\n", "\n", "# Compare with elegant\n", "\n", "print(torch.allclose(nu_x % 1, nux))\n", "print(torch.allclose(nu_y % 1, nuy))" ] }, { "cell_type": "code", "execution_count": 8, "id": "50c9ba2d-0a5d-4f98-83cb-26fe472eae65", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "False\n", "False\n", "True\n", "True\n" ] }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Compute and compare dispersion\n", "# Note, the values are not matched exactly due to splitting of dipoles\n", "\n", "orbit = torch.tensor(4*[0.0], dtype=dtype)\n", "etaqx, etapx, etaqy, etapy = dispersion(ring, orbit, [], limit=1)\n", "\n", "mask = [kind == 'BPM' for (_, kind, *_) in ring.layout()]\n", "\n", "etaqx_bpm = etaqx[mask]\n", "etapx_bpm = etapx[mask]\n", "etaqy_bpm = etaqy[mask]\n", "etapy_bpm = etapy[mask]\n", "\n", "print(torch.allclose(eta_qx, etaqx_bpm))\n", "print(torch.allclose(eta_px, etapx_bpm))\n", "print(torch.allclose(eta_qy, etaqy_bpm))\n", "print(torch.allclose(eta_py, etapy_bpm))\n", "\n", "layout = Layout(ring)\n", "_, _, lengths, *_ = layout.slicing_table()\n", "rectangles = layout.profile_1d(scale=0.005, shift=-0.005, text=False, exclude=['Marker', 'BPM'])\n", "\n", "plt.figure(figsize=(12, 6))\n", "plt.errorbar(ring.locations().cpu().numpy(), etaqx.cpu().numpy(), fmt='-', color='red', alpha=0.75)\n", "plt.errorbar(positions, eta_qx.cpu().numpy(), fmt=' ', color='black', alpha=1.0, marker='x')\n", "for rectangle in rectangles:\n", " plt.gca().add_patch(Rectangle(**rectangle))\n", "plt.tight_layout()\n", "plt.xlim(0.5*ring.length/12.0, 1.5*ring.length/12.0)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 9, "id": "c4808c31-36a1-48fc-8466-8adde3604e13", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "True\n", "True\n", "True\n", "True\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Compute and compare twiss parameters\n", "\n", "ax, bx, ay, by = twiss(ring, [], matched=True, advance=True, full=False).T\n", "\n", "mask = [kind == 'BPM' for (_, kind, *_) in ring.layout()]\n", "ax_bpm = ax[mask]\n", "bx_bpm = bx[mask]\n", "ay_bpm = ay[mask]\n", "by_bpm = by[mask]\n", "\n", "print(torch.allclose(a_x, ax_bpm))\n", "print(torch.allclose(b_x, bx_bpm))\n", "print(torch.allclose(a_y, ay_bpm))\n", "print(torch.allclose(b_y, by_bpm))\n", "\n", "layout = Layout(ring)\n", "_, _, lengths, *_ = layout.slicing_table()\n", "rectangles = layout.profile_1d(scale=2.0, shift=-1.0, text=False, exclude=['Marker', 'BPM'])\n", "\n", "plt.figure(figsize=(12, 6))\n", "plt.errorbar(ring.locations().cpu().numpy(), bx.cpu().numpy(), fmt='-', color='red', alpha=0.75)\n", "plt.errorbar(ring.locations().cpu().numpy(), by.cpu().numpy(), fmt='-', color='blue', alpha=0.75)\n", "plt.errorbar(positions, b_x.cpu().numpy(), fmt=' ', color='black', alpha=1.0, marker='x')\n", "plt.errorbar(positions, b_y.cpu().numpy(), fmt=' ', color='black', alpha=1.0, marker='x')\n", "for rectangle in rectangles:\n", " plt.gca().add_patch(Rectangle(**rectangle))\n", "plt.xlim(0.5*ring.length/12.0, 1.5*ring.length/12.0)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 10, "id": "ad2a4cd6-883b-4355-87d7-c2890a833821", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "True\n", "True\n" ] }, { "data": { "image/png": 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76wGqBKEUAAAAAKB6WZb0xS+a+UUXSZdeandFQNUglAIAAAAAVK8HHpCeekqqr5f+7d/srgaoKoRSAAAAAIDqNDAgbdhglt/7XmnWLHvrAaoMoRQAAAAAoDp95ztSMCidcorU3m53NUDVIZQCAAAAAFSfv/9duvdes/yxj0l1dbaWA1QjQikAAAAAQHUZGZG+9CUzuPnKldIrXmF3RUBVIpQCAAAAAFSX+++Xtm+XGhqkf/1Xu6sBqhahFAAAAACgegSD0h13mOUPfEBqbbW1HKCaEUoBAAAAAKrHt75lrrq3aJH05jfbXQ1Q1QilAAAAAADV4amnpF/+0ix//ONSba299QBVjlAKAAAAAFD5IhHpi180y//4j9JZZ9lbDwBCKQAAAABAFfj5z6WeHqmxUVq92u5qAIhQCgAAAABQ6Q4flr7zHbN89dWS221rOQAMQikAAAAAQGX72tekwUHpZS+TLr/c7moAvIRQCgAAAABQubZsMVNNjfSJT5g5gJLAv0YAAAAAQGXq64sNbv6ud0lLlthbD4AEhFIAAAAAgMpjWSaQCoWkRYukd7/b7ooAJCGUAgAAAABUnl/+Unr4Yam2VrrhBqmuzu6KACQhlAIAAAAAVJbHHot123vf+0xLKQAlh1AKAAAAAFA59u6VfD5peFi65BLpqqvsrghAGoRSAAAAAIDKEAxK//Ef0pEj0llnSWvXSg6H3VUBSINQCgAAAABQ/oJB6ROfkF54QZo7V1q3TnK57K4KQAaEUgAAAACA8nb4sPSxj0mBgNTSIn32s5LbbXdVAMZBKAUAAAAAKF8HDphAas8eaeZM6ctflhYutLsqAFkglAIAAAAAlKc//UlavVp69llpzhzpK1+R5s+3uyoAWaqzuwAAAAAAAHIyPCx997vSj35kbi9ebMaQmjPH3roA5IRQCgAAAABQPrq7pa9/3YwfJUlvepP04Q9LTqe9dQHIGaEUAAAAAKD07dolffvb0qOPmtuNjeZqexddZG9dACaMUAoAAAAAYIuOjg7V1tbK6/WOeczv9ysyPKyON7xB+ulPpW3bzAM1NdKb3yy9971SU1NxCwaQV4RSAAAAAABb1NbWyufzSVJCMOVfs0a+z31OnWefLf3ud+ZOh0O68ELpgx/k6npAhSCUAgAAAADYIhpE+Xw+6YUX5D37bPm/8x35urvV2dYm78yZ0vTp0hvfaFpHnXSSvQUDyCtCKQAAAABAcQwPSzt2SI8/Lm3fLoXD8krS4sXyffObWudwKGxZ6jz1VHnf+lbpH/9Reu1rJZfL5sIBFILDsiwr25W7u7vV1dUlSdq6davuuOMOud1uSVIgENCmTZvk8XgUCAS0evXq0cfGEwqF1NzcrP7+fjXRJxgAAAAAJmTcMZoiEXV0dBSugKEhqbfXTAcPSi+8EJv27zfT8HDKp7oeekhhy5JzyhQNHTggZfn3JIDSk23Ok1NLqa6uLq1Zs0aStH79el122WXa9tJgc1deeeXociAQ0DXXXKONGzdOtH4AAAAAQI7SjtHk98vn86mzszP7FwuHpYEBqb9fCoUSl+On/n4TQvX1SceOjf+6jY3SK14hnXOOWZbkv+suE0g5nQqHw/J/9aspgzUAlSXrUKq7u1u33nrraCjV3t6utWvXKhAIjFnX4/GMtqgCAAAAABRHwhhNL93233yzfB0d6rzuOnnf/Gbp0UdNkDQwEAubouFS/PLQ0MSKcDqlGTOkmTOluXNj00knmfmcOWbQ8pf4/X757rxTnZ2dpt6XArT49wOgMmUdSi1dulR33HHH6O1gMChJamlp0T333KOWlpaE9VtaWtTd3a2lS5fmp1IAAAAAqFaWJR05MraVUnxrpSNHpCNH5D1yRDrvPPl8Pq276SYzRlNbm7zd3VJ3d27bramRmppMi6amJqm52cyTp5YWE0S1tEhTpyaETpnEt+CKBlCpgjUAlSmn7nvt7e2jy3fffbdWrlwpt9s9GlAl6+3tnVRxAAAAAFCxRkakYFA6fDg2DtPhw7Gpry+x69zISNYv7W1uHh003OlwyHvqqeYqdtGAqbk5FjRF56mmadOyDpgmIhKJJARSo/W/dDsSiRRs2wDsN6Gr7wWDQW3atGl0DKlM66UyNDSkobimoKFQaCJlAAAAAEDpGhqSnn1W2rfPzPfvjwVO0TGYcgiaJEn19albLDU3m9Dppcl/110Kb9kSG6Pp4ovlfanlUSnJNOg6LaSAyjehUGrt2rXavHnz6NX13G73mFZRvb29aa++d+utt+rmm2+eyKYBAAAAoPRYlrRnj/SXv0jbt0s7dki7d48fOjkc5ipzra1mammJLc+YEQufovMpU8Ytxe/3y3f77WPHaHI4CHoAlBSHZVlWLk9Yv3692tvb5fF4RltC9fb2Jlx9T5JmzJihXbt2pQymUrWUWrBgwbiXCgQAAACAknHsmPTHP0oPPSQ99pjpapessVFauFCaP98M8h0NnKKT2y3V1uatpFRjNGW6HwAKIRQKqbm5edycJ6eWUps2bdLSpUtHA6l77rlHq1evHhM8BQIBLV++PG1LKZfLJZfLlcumAQAAAKA07Nwp/ehH0iOPSOFw7H6XSzrrLOnss6WXvUw67TQTPBVwTKZkjNEEoJxk3VIqEAho0aJFCfe53W719fWNPr5hwwatWLFCW7du1Q033JA2lEqWbYIGAAAAALbZuVP63vekP/whdt/JJ0sXXyy95jUmiKqb0AgpAFBRss15cu6+VwiEUgAAAABKVjgsff/70o9/bMaOcjikSy+V3v52afHioraEAoByUJDuewAAAABQVXbulD7zGTOIuSRdcon0gQ+YMaIAAJNCKAUAAAAAqfztb9InPykNDpor4X3iE9IFF9hdFQBUDEIpAAAAAEj29NOxQOoVr5A6O82V9AAAeUMoBQAAAADxdu6Urr8+FkjdeqtUX293VQBQcWrsLgAAAAAASsaJE5LfbwKpc88lkAKAAiKUAgAAAICoH/5Q2rdPammR1q0jkAKAAiKUAgAAAADJXGHvrrvM8kc+Ik2fbm89AFDhCKUAAAAAwLKkz39eGh6WXvMa6XWvs7siAKh4hFIAAAAA0NUlPfmkNHWq9NGPSg6H3RUBQMUjlAIAAACAn/7UzN/5Tmn2bHtrAYAqQSgFAAAAoLrt2CFt3y7V1UmXX253NQBQNQilAAAAAFS3n//czC+6SHK7bS0FAKoJoRQAAACA6nXkiPSb35jlK66wtxYAqDKEUgAAAACq169/LQ0NSW1t0jnn2F0NAFQVQikAAAAA1cmypHvvNctvehNX3AOAIiOUAgAAAFCdnnpK2rNHcrmkVavsrgYAqg6hFAAAAIDq9LvfmfmFF0rTptlbCwBUIUIpAAAAANXHsqTf/94sX3ihvbUAQJUilAIAAABQfXbtkl54QXI6pVe+0u5qAKAqEUoBAAAAqD7RVlLLl0v19fbWAgBVilAKAAAAQPWJhlKvfa29dQBAFSOUAgAAAFBd9u+Xdu6UHA7p/PPtrgYAqhahFAAAAIDq8sgjZn7OOZLbbWspAFDNCKUAAAAAVBeuugcAJYFQCgAAAED16O+X/vIXs8x4UgBgK0IpAAAAANXj4Ycly5KWLJFOOsnuagCgqhFKAQAAAKgeDz5o5pdcYm8dAABCKQAAAABVoq9Pevxxs3zxxXZWAgAQoRQAAACAavG735mue6efLs2da3c1AFD1CKUAAAAAVIff/tbM6boHACWBUAoAAABA5Tt8WPrrX80yXfcAoCQQSgEAAACofA89ZLrunXWWNHu23dUAAEQoBQAAAKAaRK+6RyspACgZhFIAAAAAKtvTT0tPPSXV1BBKAUAJIZQCAAAAUNl++EMzf/3rpZkz7a0FADCKUAoAAABA5XrmGenRRyWHQ7rqKrurAQDEIZQCAAAAULn++7/N/NJLpfnz7a0FAJCAUAoAAABAZdqzx1x1T6KVFACUIEIpAAAAAJXHsqTvfMfML7xQOvVUuysCACQhlAIAAABQee69V3r4Yam2VnrPe+yuBgCQAqEUAAAAgMqyfbv0ta+Z5WuvlRYvtrceAEBKhFIAAAAAKsfAgNTRIQ0Pm2577e12VwQASINQCgAAAEBlOHBA+vjHpRdflE4+WVq7VnI47K4KAJAGoRQAAACA8rd9u/ShD0k9PZLbLfn90rRpdlcFAMigzu4CAAAAAGDCTpyQfvIT6fvfl4aGJI9HuuUWac4cuysDAIyDUAoAAABA+RkZMVfX27BBeuEFc9+rXiX5fFJDg721AQCyQigFAAAAoGR0dHSotrZWXq93zGP+zk5F+vvVce650v33mzGkJKm1VVq9Wlq1ijGkAKCMEEoBAAAAKBm1tbXy+XySJO/HPib99rdSICD/j38s3x//qM62Nqm726zc2Ci95S3SO94hTZ1qW80AgIkhlAIAAABgL8uSDh+WenrkPe886aqrTDD13e/K29Ym/+7d8u3erc62NnkXL5bOPFP653+WXvc6yem0u3oAwAQRSgEAAAAFlLE7mt+vSCSijo6O4hdWLCdOSEeOSEePSr290qFDsengQTPt2yeFQqNP8UpSW5t8u3dr3Z49CluWOt/3PvMZLlwo1fFnDABUAr7NAQAAgAJK6I4WF0z5/X75fD51dnbaVZphWSY4ip+Gh82V7I4fj83jl+Pvi94+ejQWPh05ElsOh7Oro6ZGWrBAmjdPcjjkveACrfvsZxWOROR0OuX93vcK+zkAAIqOUAoAAAAooGgQFR9MxQdSY1pQRSIm5EkOgKL3pbt/vHWHhsaGTydOmKvYFZrDYa6I19wszZwpzZpl5tHp5JOlU06RXK7Rp/j9/tFAKhwOy+/3p2xtBgAoX4RSAAAAQLZGRlK3Ejp2bOz9cY97W1ulVavk8/m07uabFY5E1Llihby7dknvfKdpTRR9reFhe99jXZ2ZXC4z1dfH5tEp+X6XS5o2TZo+PTbF325oyOmqeMmhXfS2JIIpAKgghFIAAACoDJZlWhmNExDl/Hj8fdl2RUvBK2mdw2Fa/zgc8k6bJu3alf4JDocZxDs5/EkVCGW6P355ypTYVFdnXr+uLvG+HMKjQkjViixVazMAQPkjlAIAAEBxWFb6sCdfAVIxuqJFuVzS1KljWxHFtyaKPl5XJ/999ylsWXLW1Sk8PCz/4sXyfuhD6QOlKVNsD4jsEIlEUnZrjN6ORCJ2lAUAKABCKQAAABjDw9m1FppogDQ0VLz3UlubPiAaL0BK93j8bacz9+5o9947tjvawoW0+kmS6UqEfFYAUFkIpQAAAMqBZcXGHUoOe/LRwuj4cdP1rVjiWwdNJCBK93j0vrrSOc2lOxoAAKmVzq81AABAOYteMW28MGgyAVKxOBwm9MlXC6Pkx12uquqWRnc0AABSc1iWZdldRCgUUnNzs/r7+9XU1GR3OQAAoNJYlnTiRPZh0ES6qBXzimlTpuS/hVFyK6MqCo0AAEB+ZZvz0FIKAADYb2Rk4mFQts8p1v/DORyFbWFUXy/V1BTnvQAAABQQoRQAAAXW0dGh2tralGPG+P1+RSKRjAP72i45MEoe/DpVAJTrOidOFO/91NUVroVRfX3VXjENAAAgV4RSAAAUWG1tbcrBjOMHP56wbAKjVOHQeOvELxczMJIK18Ioel9tbXHfDwAAAFIilAIAFFTZtxKajJcCI++//7s0MGCCqYMH5f3AB+T/5jfl+9a31Pnud8v78pdL99wzsdZHdgRGqYKfVF3MslknOjmdZl2nk1ZGAAAAVYJQCgBQUAVtJZSrSMQMRh0OmzAnujw0lNsUDseCoSwDI68ktbXJ99Wvat3XvqawZamzrU3effukL30pP+8vOejJJgzKJUwiMAIAAEAeEUoBAAoqGkTFB1OjgdTNN8u7Zo3U329aBEWnaLiTHBjFh0GpHouGQfGPhcOx8MnOC866XPK+4hVat3evwiMjctbUyHvFFbm3LCIwAgAAQIUglAIA5Ec4LB0+LB08aOaHD0tHj0qDg/I2NEivf718Pp/WdXQoPDKiziVL5N2yRfrtb+2rua7OhDku18SnbFofvRQY+f1+hX/2MzmdToXDYflnzkzZrREAAACoBoRSAIDsDQxI+/bFpr17peeeM0HUwEDGp3olrXM4TCshh0PeefMSWy5Fg5ypUxPHGYoPduLDoOjt6HqpHosuT5kydqqtLWrLovjuivGtxSQRTAEAAKAqEUoBAFKLRKTt26W//lV68knp6aelvr7Mz3E6pZkzzdTaKk2fLk2bJk2dKv+99ypsWXLW1Sk8PCz/smXy3nBDLISqqSnO+7JBciAlpe7WCAAAAFQTQikAQMyJE9Ijj0i//730pz+lbv00c6a0YIG0cKGZz58vzZ5t7p8+PWXrI7/fL99PfjK2lVBzc1WEMZFIJCGQiorejkQidpQFAAAA2MphWXaO+mqEQiE1Nzerv79fTU1NdpcDANVn/37p5z+XfvlLM+h4VGOj9IpXSGefLZ11luTxmJZNOUjVSijT/QAAAADKW7Y5Dy2lAKCaDQ5Kd94pbdpkrlAnmW53q1ZJr3mNdOaZZuylSaCVEAAAAIBUaCkFANVqyxbpy1+WgkFz+7zzpH/5F+nVr550EAUAAACgetFSCgCQmmVJ//VfZpLMmFD/9m/Sq15V1KvRAQAAAKhuhFIAUE3CYem226QHHzS33/526eqrpTp+DgAAAAAUF3+FAEC1sCzpllukhx4y3fOuu076p3+yuyoAAAAAVYpQCgCqxU9/agKpujrTWmrpUrsrAgAAAFDFauwuAABQBE89JX3zm2b5Qx8ikAIAAABgO0IpAKh0/f3SzTdLkYh08cXSW95id0UAAAAAQCgFABXvzjulgwfNVfY++UmusAcAAACgJBBKAUAl6+uT7rvPLH/0o1JDg731AAAAAMBLCKUAoJJt3CgNDUmnny4tW2Z3NQAAAAAwilAKACrVwID0s5+Z5Xe/m257AAAAAEoKoRQAVKqf/EQ6dkxatEg6/3y7qwEAAACABIRSAFCJBgdNKCVJ73oXraQAAAAAlBxCKQCoRFu2SEeOSAsWSBddZHc1AAAAADAGoRQAVKLf/tbM3/AGWkkBAAAAKEmEUgBQaYJBqbvbLF98sZ2VAAAAAEBahFIAUGl+/3tpZERaskSaN8/uagAAAAAgJUIpAKg0Dz5o5pdcYm8dAAAAAJABoRQAVJK+Punxx80yXfcAAAAAlDBCKQCoJL/7nWRZ0umnS3Pn2l0NAAAAAKRFKAUAlYSuewAAAADKBKEUAFSK3l7piSfM8kUX2VsLAAAAAIwjp1Cqu7tby5YtS3l/90uXHw8EAqPLAIAieuSRWNe9OXPsrgYAAAAAMso6lNq0aZMkpQycNmzYoGXLlsnhcOjaa6+Vx+PJX4UAgOz8/vdm/trX2lsHAAAAAGShLtsV29vb0z62bNky9fX1SZLcbvekiwIA5GhwUIr+pwGhFAAAAIAykHUoNR7CKACw0R//KA0PSwsWSKecYnc1AAAAADCuvIRSwWBwtHvf1q1bx+3CNzQ0pKGhodHboVAoH2UAQPV6+GEzp5UUAAAAgDKRl1Bq9erVoy2lPB6PVq1apZ6enrTr33rrrbr55pvzsWkAwIkTpqWUJF14ob21AAAAAECWcrr6XjqBQGB02ePxKBAIJNyX7IYbblB/f//otG/fvnyUAQDV6bHHzJhSra3mynsAAAAAUAYm3VKqu7tbl1122ehA51EtLS1pn+NyueRyuSa7aQCAFOu6d8EFksNhby0AAAAAkKUJtZQKBoOjyx6PR7fddtvo7a6uLrW3tzPwOQAUw/Cw9Pvfm2W67gEAAAAoI1m3lOrq6tLmzZslmTGhVqxYMRo+LV++XOvXr5fb7VZPT482btxYsIIBAHF+/3spGDRd917xCrurAQAAAICsOSzLsuwuIhQKqbm5Wf39/WpqarK7HAAoHx//uPT449J73iO9//12VwMAAAAAWec8eRnoHABgg717TSDlcEhvfKPd1QAAAABATgilAKBc3XuvmZ9/vjR7tr21AAAAAECOCKUAoBwNDUkPPGCW3/Qme2sBAAAAgAkglAKAcvTgg9KRI9LcudKKFXZXAwAAAAA5I5QCgHITDkt33WWWr7jCjCkFAAAAAGWGUAoAys0Pfyg9+6zU2ipdfrnd1QAAAADAhBBKAUA52bUr1krqIx+Rpk+3tx4AAAAAmCBCKQAoF5YlfeELUiQiveY10oUX2l0RAAAAAEwYoRQAlIu77pKeekqaOlX66EcZSwoAAABAWSOUAoBysHGj9O1vm+Vrr5Vmz7a3HgAAAACYJEIpACh1P/mJ9I1vmOV3v9tccQ8AAAAAylyd3QUAANJ44QXTOurBB83td71Lev/76bYHAAAAoCIQSgFAqenvl374Q+lnP5OGh00I9Z73SO99L4EUAAAAgIpBKAUApeLZZ6VNm6Rf/UoaGjL3rVhhxpBatMje2gAAAAAgzwilAMBOw8PSn/4k3X+/9Ic/SJZl7j/tNOmaa6Tly+2tDwAAAAAKhFAKAIrtwAHpqaekv/xFeughKRiMPfaa10hXXimdey5d9QAAAABUNEIpAFWlo6NDtbW18nq9Yx7z+/2KRCLq6OiY/IYsSzpyRNqzR9q9W9q1y0y7d0t9fYnrzpghrVolXX65tGDB5LcNAAAAAGWAUApAVamtrZXP55OkhGDK7/fL5/Ops7Mz8wsMDZmWTf39samvTzp0SDp8OHF+/Hjq16ipkRYvls4+23TPW7FCquPrGAAAAEB14a8gAFUlGkSNBlNr18p/443yfeEL6nz/++V9+culH/wgMXSKn6IDkGdr9myprS02nXqqmdfX5/NtAQAAAEDZcVhWdFRd+4RCITU3N6u/v19NTU12lwOgnFiWCYoGBsx05IiZ4m+nmPu3bZPviSfkdDgUtix1trXJ29aW3Tbr6iS3W2puNpPbLc2caabW1sS5y1XANw8AAAAApSfbnIeWUgBKRzg8tmtc/BQfNsUHUMPDOW/K29qqdS8FUk6HQ94LLzThUnzYlG6aOpVByAEAAABgkgilABTe0aPminMHDkgvvmjmBw+aACo+hEo3BlM2amqkxkYzTZ9upvjbSXP/97+v8JYtcjqdCofD8i9ZknLwcwAAAABAYRBKAciPYDB2dbk9e6T9+2Mh1OBg9q9TWxvrEpfcQilT0FRfn3XrJb/fL9/XvqbOzk55vd7RQc4lEUwBAAAAQJEQSgHIXSQibd8uPf649Pe/m+WDBzM/p7FRmjPHDPwdnWbMGBtANTQUtGtc/FX2ogHUmMHPCaYAAAAAoOAIpQBkZ2BA+v3vpUcekR57bGzrJ4dDmjs3dpW5efMSA6gSudpcJBJJCKSiorcjkYgdZQEAAABA1eHqewDSGx6WHn5Y+tWvpG3bTAupqMZG6bzzpLPOkk4/XVq82LRyAgAAAABUNa6+B2DiQiHpF7+QfvYz6dCh2P0ej3TRRdIrXymddpoZXBwAAAAAgAkglAIQMzws/fSn0g9+YK6YJ5nxnq64QrrsMmnhQlvLAwAAAABUDkIpAMb//Z/0ta9Jzz1nbns80tvfLl1yiTRlir21AQAAAAAqDqEUUO1OnJBuv920kJKklhbp6qulN7yB7nkAAAAAgIIhlAKq2fPPSzffLO3YYW63t0vvfz8DlgMAAAAACo5QCqhWzzwjXXedNDAgNTVJN9wgvfrVdlcFAAAAAKgShFJANdq1S/rEJ0wgdfrpUmenNGuW3VUBAAAAAKoIoRRQbfbuNS2kQiHpZS+TPv95ado0u6sCAAAAAFQZRjEGqklvr3T99VIwKC1eLH3ucwRSAAAAAABbEEoB1eLECcnnkw4elBYuNC2kGhvtrgoAAAAAUKUIpYBqYFnSl78sPfWUaRn1mc9Izc12VwUAAAAAqGKEUkA1uPde6f77JYfDtJaaP9/uigAAAAAAVY5QCqh0zz4rff3rZnn1aumVr7S3HgAAAAAARCgFVDb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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Compute and compare phase advances\n", "\n", "mux, muy = advance(ring, [], alignment=False, matched=True).T\n", "mux = mux.cumsum(-1)\n", "muy = muy.cumsum(-1)\n", "\n", "mask = [kind == 'BPM' for (_, kind, *_) in ring.layout()]\n", "mux_bpm = mux[mask]\n", "muy_bpm = muy[mask]\n", "\n", "print(torch.allclose(mux_bpm, mu_x))\n", "print(torch.allclose(muy_bpm, mu_y))\n", "\n", "layout = Layout(ring)\n", "_, _, lengths, *_ = layout.slicing_table()\n", "rectangles = layout.profile_1d(scale=1.5, shift=-0.5, text=False, exclude=['Marker', 'BPM'])\n", "\n", "plt.figure(figsize=(12, 6))\n", "plt.errorbar(ring.locations().cpu().numpy(), mux.cpu().numpy(), fmt='-', color='red', alpha=0.75)\n", "plt.errorbar(ring.locations().cpu().numpy(), muy.cpu().numpy(), fmt='-', color='blue', alpha=0.75)\n", "plt.errorbar(positions, mu_x.cpu().numpy(), fmt=' ', color='black', alpha=1.0, marker='x')\n", "plt.errorbar(positions, mu_y.cpu().numpy(), fmt=' ', color='black', alpha=1.0, marker='x')\n", "for rectangle in rectangles:\n", " plt.gca().add_patch(Rectangle(**rectangle))\n", "plt.xlim(0.5*ring.length/12.0, 1.5*ring.length/12.0)\n", "plt.ylim(-1, 2*torch.pi*max(nu_x, nu_y)/8)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "id": "ef19a92f-959a-4315-9099-e5f313229a73", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "colab": { "collapsed_sections": [ "myt0_gMIOq7b", "5d97819c" ], "name": "03_frequency.ipynb", "provenance": [] }, "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": "3.14.0" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": false, "user_envs_cfg": false } }, "nbformat": 4, "nbformat_minor": 5 }