diff --git a/docs/examples/bunching.ipynb b/docs/examples/bunching.ipynb new file mode 100644 index 0000000..d26f062 --- /dev/null +++ b/docs/examples/bunching.ipynb @@ -0,0 +1,434 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d6490636-6e3c-4d4b-9122-394a314e10d3", + "metadata": {}, + "source": [ + "# Bunching\n", + "\n", + "Bunching at some wavelength $\\lambda$ for a list of particles $z$ is given by the weighted sum of complex phasors:\n", + "\n", + "$$B(z, \\lambda) \\equiv \\frac{\\left|\\sum_j w_j e^{i k z_j}\\right|}{\\sum w_j}\n", + "$$\n", + "\n", + "where $k = 2\\pi/\\lambda$ and $w_j$ are the weights of the particles.\n", + "\n", + "See for example [D. Ratner's disseratation](https://www.osti.gov/servlets/purl/1443197). " + ] + }, + { + "cell_type": "markdown", + "id": "c72d25c9-ec8d-4a3a-88ef-e6aba001d113", + "metadata": {}, + "source": [ + "## Add bunching to particles\n", + "\n", + "This uses a simple method to add perfect bunching at 0.1 µm" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "89d98045-89b5-4d05-a1b3-33f956ba329c", + "metadata": {}, + "outputs": [], + "source": [ + "from pmd_beamphysics import ParticleGroup\n", + "%config InlineBackend.figure_format = 'retina'" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "4e90f855-514d-4224-8bc1-4c8ce425b57d", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "2808d05b-41dc-44eb-ac98-ae00ec7ba97b", + "metadata": {}, + "outputs": [], + "source": [ + "P = ParticleGroup( 'data/bmad_particles2.h5')\n", + "P.drift_to_t()\n", + "\n", + "wavelength = 0.1e-6\n", + "dz = (P.z/wavelength % 1) * wavelength\n", + "P.z -= dz" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "f92a71d1-2804-4fba-a38b-3089351a910d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Sz3/+8znppJPywgsv1Nq+Y8eOGThw4Gqfmz17dg444IDss88+Ofzww/OpT30qPXv2TLlczquvvpqJEydm4sSJlVkyV1xxRfr06dN4FwUAAAC0KG0ylPnpT39a2f7Nb36TPfbYo8722223XWbPnr3WfVOnTs3UqVNrPbZr1665+uqrc8opp2xQrQAAAEDr1CZDmYaw11575bbbbsvUqVPz7LPPZt68eVmwYEGqq6uzxRZb5BOf+ES+8IUv5Gtf+1p69uxZdLkAAABAM9MmQ5mGeET1pptumuOOOy7HHXdcA1QEAAAAtDVtcqFfAAAAgKIJZQAAAAAKIJQBAAAAKIBQBgAAAKAAQhkAAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAAIACCGUAAAAACiCUAQAAACiAUAYAAACgAEIZAAAAgAIIZQAAAAAKIJQBAAAAKIBQBgAAAKAAQhkAAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAAIACCGUAAAAACiCUAQBgraqqqoouAQBaNaEMAAAAQAGEMgAAAAAFEMoAANDo3AoFAGsSygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABRAKAMAAABQAKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABRAKAMAAABQAKEMAABrqKqqKroEAGj1hDIAAAAABRDKAAAAABRAKAMAQKNyKxQArJ1QBgAAAKAAQhkAAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAAIACCGUAAAAACiCUAQAAACiAUAYAAACgAEIZAAAAgAIIZQAAAAAKIJQBAAAAKIBQBgAAAKAAQhkAAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAAIACCGUAAAAACiCUAQAAACiAUAYAAACgAEIZAAAAgAIIZQAAAAAKIJQBAAAAKIBQBgAAAKAAQhkAAJpUVVVV0SUAQLMglAEAAAAogFAGAAAAoABCGQAAAIACCGUAAAAACiCUAQCgEBb8BaCtE8oAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAA0OQs8gsAQhkAAACAQghlAABoMmbIAMD/EsoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABRAKAMAwGqqqqqKLgEA2gShDAAAAEABhDIAAAAABRDKAAAAABRAKAMAAABQgDYbyjz//PO59NJLc8ghh6Rfv37p1KlTunfvnoEDB2bMmDF54okn1qu/Rx55JKNHj07fvn3TqVOn9O3bN6NHj84jjzzSSFcAAAAAtGQdii6gCMOHD8+UKVPW+PyyZcvyyiuv5JVXXsmtt96a448/PhMmTEjHjh1r7atcLue0007L+PHjV/v83Llzc9999+W+++7LKaeckuuvvz6lUqnBrwUAAABomdrkTJm5c+cmSXr37p2zzjorEydOzLRp0zJ16tRcddVV6dOnT5Lkxz/+ccaMGVNnX9/73vcqgcyee+6ZO+64I9OmTcsdd9yRPffcM0kyfvz4/Ou//mvjXRAAAADQ4rTJmTK77LJLLr300hx11FFp3779avuGDRuW448/Pvvuu2/+8pe/5I477sjpp5+ez372s2v0M3PmzFx++eVJksGDB2fKlCnp0qVLkmTIkCE54ogjMnz48Dz77LO57LLLcuKJJ2bHHXds/AsEAAAAmr02OVNm0qRJOfroo9cIZFbp0aNHrrzyysrHEydOXGu7q6++OtXV1UmSa6+9thLIrNK1a9dce+21SZLq6upcc801DVA9AAAA0Bq0yVCmPvbff//K9qxZs9bYXy6X88ADDyT5cObNsGHD1trPsGHDsvPOOydJ7r///pTL5YYvFgAAAGhxhDK1WLZsWWW7Xbs1v0yvvfZaZW2a4cOH19nXqv1z5szJ7NmzG65IAAAAoMVqk2vK1MfkyZMr27vssssa+2fMmFHn/ppq7p8xY0a23377etcxZ86cOvfPmzev3n0BAAAAzYdQZi1WrlyZcePGVT4++uij12jzxhtvVLb79u1bZ3/9+vVb63H1UfNYAIC2oKqqKmPHji26DABodG5fWourr74606ZNS5KMGjUqgwcPXqPNwoULK9vdu3evs79u3bpVtt9///0GqhIAAABoycyU+YjJkyfn29/+dpKkZ8+eue6669babsmSJZXtjh071tlnp06dKtuLFy9er3rWNbNm3rx5GTp06Hr1CQAAABRPKFPDn//854waNSrV1dXp1KlT7r777vTq1WutbTt37lzZrrko8NosXbq0sv3Rx2avy7pujQIAAABaJrcv/X+vvfZaDj744Lzzzjtp37597rjjjjqfqrTppptWttd1S9IHH3xQ2V7XrU4AAABA2yCUSfLmm2/mwAMPzJtvvplSqZSbbropo0aNqvOYmjNY1vWEpJq3IFm4FwBgTVVVVUWXAABNrs2HMgsWLMhBBx2UV199NUly7bXX5qtf/eo6j9t1110r2y+99FKdbWvuHzRo0AZWCgDQ+glnAGhL2nQo8+677+aLX/xiXnzxxSTJuHHj8vWvf71ex26//fbp3bt3kg8XB67LlClTkiR9+vRJ//79N7xgAAAAoNVos6HMokWLMmLEiDz//PNJkgsvvDAXXHBBvY8vlUoZOXJkkg9nwjz99NNrbff0009XZsqMHDkypVJpIysHAAAAWoM2GcosW7Yso0aNylNPPZUkOeuss/L9739/vfs5++yz06HDhw+wOvPMM9d43PXixYtz5plnJkk6dOiQs88+e+MKBwAAAFqNNvlI7GOPPTaPPvpokuTzn/98TjrppLzwwgu1tu/YsWMGDhy4xucHDhyY888/P+PGjcuzzz6bfffdNxdccEF23HHHzJo1K5dddlmmT5+eJPnWt76VnXbaqXEuCAAAAGhx2mQo89Of/rSy/Zvf/CZ77LFHne232267zJ49e637LrnkksyfPz833XRTpk+fnmOOOWaNNieddNIGzcQBAAAAWq82eftSQ2rXrl1uvPHGPPTQQxk5cmR69+6djh07pnfv3hk5cmQefvjhTJgwIe3a+VIDAAAA/6tNzpQpl8sN3uehhx6aQw89tMH7BQDgw0dljx07tugyAKBBmb4BAEBFVVVV0SUAQJshlAEAAAAogFAGAAAAoABCGQAAAIACCGUAAAAACiCUAQAAACiAUAYAgGbNE6EAaK2EMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAM2OdWQAaAuEMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAIWyfgwAbZVQBgAAAKAAQhkAAACAAghlAAAAAAoglAEAAAAogFAGAIAWw6LAALQmQhkAAACAAghlAAAAAAoglAEAAAAogFAGAACgBbLGErR8QhkAAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAgBbKYr/QsgllAAAAAAoglAEAAAAogFAGAAAAoABCGQAAAIACCGUAAABaAYv+QssjlAEAoEXxxhOA1kIoAwBAiyCMAaC1EcoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAADQjFrWGtkMoAwAAAFAAoQwAAABAAYQyAAAArYRbn6BlEcoAANAiefMJQEsnlAEAAGgBBJHQ+ghlAAAAmjmBDLROQhkAAIAWQjgDrYtQBgCAZssbUABaM6EMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAA0MpYjwlaBqEMAAAAQAGEMgAAAC2YWTHQcgllAAAAAAoglAEAoMUyQwCAlkwoAwBAqyCgoTXy7xpaN6EMAABACyKogdZDKAMAANBMCFygbRHKAACQxJtBAGhqQhkAAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAWjQLFAPQUgllAAAAAAoglAEAAAAogFAGAAAAoAAdijpxdXV1HnrooTzxxBN59dVXs3DhwqxYsaLOY0qlUn796183UYUAAAAAjaeQUObxxx/PiSeemNdff73yuXK5XGv7UqmUcrmcUqnUFOUBAAAANLomD2V+//vf55BDDsmyZctSLpfTuXPn7LTTTtl8883Trp27qQAAAIC2oclDmYsvvjhLly5Np06dctVVV+XEE09M586dm7oMAABaoaqqqowdO7boMgCgXpo8lHnyySdTKpVy4YUX5vTTT2/q0wMAAAA0C01+v9CSJUuSJP/wD//Q1KcGAAAAaDaaPJTp379/kmT58uVNfWoAAACAZqPJQ5kjjzwySTJlypSmPjUAAABAs9HkocxZZ52VbbfdNldccUVmz57d1KcHAAAAaBaaPJTZeuut8/DDD6dLly7Ze++9M2HChLz77rtNXQYAAABAoZr86UtJsscee2TKlCnZe++9c+qpp+a0005Ljx490rVr1zqPK5VKmTVrVhNVCQAAANB4Cgll7r333px00klZuHBhyuVyyuVy5s+fv87jSqVSE1QHAEBrUFVVlbFjxxZdBgDUqslDmalTp+aYY47JihUrkiTbbbdd9thjj2y++eZp167J76YCAAAAKESThzLf//73s2LFimy22Wb5yU9+kkMOOaSpSwAAAAAoXJNPTXnuuedSKpVSVVUlkAEAAFiHqqqqoksAGkmThzIffPBBkmS//fZr6lMDAAAANBtNHspsv/32SZJFixY19akBAAAAmo0mD2VGjx6dcrmcX/ziF019agAAAIBmo8lDmfPOOy877bRTrrnmmjz77LNNfXoAAACAZqHJQ5lNN900v/71r7Pbbrvlc5/7XC688ML88Y9/zJIlS5q6FAAAAIDCNPkjsdu3b1/ZLpfLGTduXMaNG1evY0ulUqqrqxurNAAAAIAm0+QzZcrlcuX10Y/r8wIAgPXlkcIANEdNPlNm7NixTX1KAAAAgGZHKAMAAABQgCa/fQkAAACAFhLKTJ8+PT/60Y/y5z//uehSAAAAABpEiwhl3nvvvYwZMyZnnnlm0aUAAAAANIgmX1Pm3/7t39ar/dKlS/PQQw8lSZ555pnGKAkAAKDVqaqqsqYnNHNNHspcfPHFKZVKG3Tsrrvu2sDVAAAAFEt4Am1XIbcvlcvl9Xq1a9cuxx57bO66664iygUAAABocE0eyqxcuXKdr6VLl2b27Nm58cYbs8MOO2TlypXp3r17+vfv39TlAgAANLmqqqqiSwCaQLNc6HeTTTbJxz/+8Zx44omZNm1a+vfvnwkTJmTChAlFlwYA0Op48wcAxWiWoUxNW265Zc4///yUy+Vcd911Ddbv/PnzM2nSpFx00UU55JBD0qNHj5RKpZRKpYwZM6Zefdxyyy2VY9b1uuWWWxqsdgAAAKDla/KFfjfE4MGDkyR/+ctfGqzPXr16NVhfAAAAzZFFhKF5axGhTLt2H07o6dixY6P0369fvwwaNCiPPvroBvfxi1/8Ir179651f9++fTe4bwAAAKD1aRGhzHPPPZckGTJkSIP1edFFF2XIkCEZMmRIevXqldmzZ2f77bff4P4GDhxoIWIAAACg3pp9KDN//vxcdtll6dChQy688MIG69eCdgAAAECRmjyUmTJlyjrblMvl/M///E/++Mc/5oc//GEWLlyYc889N+VyudbjP/e5zzV0qQAAtBHW3QCgCE0eyuy///4plUr1bl8ul1MqlXLllVfmyiuvXGubUqmU6urqhioRAAAAoNEVcvtSuVxu1PZFGDNmTGbMmJF33nknH/vYxzJgwIAceOCBOf3009OnT58N7nfOnDl17p83b94G9w0A0JaYDQNAc9Pkocxjjz3W1KdsEpMnT65sv/3223n77bfzu9/9LldeeWWuueaanHrqqRvUb79+/RqqRAAA6kmAA0BTaPJQZvjw4U19yka1ww47ZPTo0dlnn30qAcqrr76ae++9NxMnTsySJUty2mmnpVQq5ZRTTim4WgCAtsFDHQBoCRo1lHnuueey1157NeYpCjVq1KiccMIJa6yRM2TIkHz5y1/OpEmTMnr06CxfvjznnHNOjjjiiGyzzTbrdY433nijzv3z5s3L0KFD17t2AIC2wIwXAJqzdo3Z+ZAhQ9K3b9+ceuqpmTRpUpYsWdKYp2tym222WZ2LFh922GGVPwIWLVqUG2+8cb3P0bdv3zpf22677QbXDwDQ1phBA0Bz0qihTJK8+eabmTBhQkaOHJmtttoqhx9+eMaPH58333yzsU/dLJx88smV4KbmujMAAABA29aoocycOXNy/fXX59BDD03nzp2zePHiPPTQQzn99NPTr1+/7LXXXrn44ovz3HPPNWYZherZs2d69OiRJJk7d27B1QAAAADNRaOGMr17984pp5ySBx98MAsWLMgDDzyQk08+Odtuu23K5XKmT5+ef//3f8/QoUPTp0+fStvFixc3ZllNriU80hsAAABoWo1++9IqXbp0yeGHH54bbrghc+bMyTPPPJOLLrooe+65Z8rlcubNm5cbb7wxRx55ZHr06NFqbnOaP39+3n777SQfhlQAABTP2jIANAdNFsp81Kpbl5599tlWfZvT+PHjKzNlWtvjwAEAgJZDGAnNT2GhTE01b3N6++2387Of/azO25xOPfXU/OEPfyi05tmzZ2f69Ol1tpk0aVL+/d//PUnSuXPnnHjiiU1RGgAA0MwJSIAk6VB0AR/VuXPnHHbYYTnssMOSJM8991wmTZqUBx98MNOnT8+8efMyYcKE9OnTJ5/85Cc3+DxPPvlkZs6cWfl4wYIFle2ZM2fmlltuWa39mDFjVvt49uzZOeCAA7LPPvvk8MMPz6c+9an07Nkz5XI5r776aiZOnJiJEydWZslcccUV6dOnzwbXCwAAtF5VVVUZO3Zs0WUATazZhTIftddee2WvvfbK2LFj8+abb2bSpEmZNGlSunbtulH9TpgwIbfeeuta9z311FN56qmnVvvcR0OZVaZOnZqpU6fWep6uXbvm6quvzimnnLLBtQIAAACtT7MPZWpadZtTcwg49tprr9x2222ZOnVqnn322cybNy8LFixIdXV1tthii3ziE5/IF77whXzta19Lz549iy4XAGCt2uItFG3xmgFonho9lJk7d27uvffeJMkee+yR/fffv97HPvbYY/nTn/6UJDn66KOzzTbbNFhdt9xyyxq3KK2PTTfdNMcdd1yOO+64BqsJAAAAaDsaPZQ577zzcs8996Rnz57r/fSkgQMH5thjj81bb72V559/fqNCFAAAAIDmpFGfvjR79uzcc889SZLLL788vXv3Xq/j+/TpkyuvvDLlcjm33XZb3njjjcYoEwAAAKDJNWooc/vtt6dcLmennXbK8ccfv0F9HHfccdlll11SLpdz++23N3CFAAC0ZR9dX8Z6MwA0pUYNZZ544omUSqWMHj16o/o56qijUi6XM3ny5AaqDAAAoBjCP2CVRg1lXnjhhSTJvvvuu1H9DBs2bLX+AAAAAFq6Rg1l/v73vyfJRj81adXxq/oDAAAAaOkaNZRp3759kmT58uUb1c+q40ul0kbXBAAADcVtKABsjEYNZbbeeuskyZw5czaqn1XHr+oPAAAAoKVr1FBmp512SpL85je/2ah+Vh0/cODAja4JAACgrTGrC5qnRg1lDjrooJTL5fzkJz/JggULNqiPBQsW5Pbbb0+pVMqBBx7YwBUCAAAAFKNRQ5ljjjkmnTp1ysKFC/PP//zPWbly5XodXy6Xc9JJJ2XhwoXp2LFjjj322EaqFAAA1s4MAwAaS6OGMn379s0ZZ5yRcrmchx56KIceemjmzZtXr2PnzZuXESNG5MEHH0ypVMrpp5+evn37Nma5AAAAAE2mUUOZJPnBD36QffbZJ+VyOb/85S8zYMCAnHDCCbnnnnsya9asvP/++ymXy3n//fcza9as3HPPPRkzZkwGDBiQX/ziF0mSvffeO+PGjWvsUgEAoFZmzADQ0Do09gk6duyYBx98MF/+8pfz61//OosXL85tt92W2267rc7jyuVykuSAAw7I3XffnY4dOzZ2qQAAAI2iqqoqY8eOLboMoJlp9JkySbLlllvm0UcfzdVXX50+ffqkXC6v89W7d+9cddVV+dWvfpWtttqqKcoEAAAAaDKNPlNmlVKplLPOOitf//rX84tf/CKTJ0/OH/7whyxYsCALFy7Mpptumh49euSTn/xkhg8fnoMPPjibbLJJU5UHAAAA0KSaLJSpnLBDh4wYMSIjRoxo6lMDAAA0G25pAprk9qX6qK6uzltvvZW33nor1dXVRZcDAAD1ZhFgADZEoaHMn//855x55pkZNGhQOnfunG222SbbbLNNOnfunEGDBuXMM8/MCy+8UGSJAAAAAI2ikFBm5cqVOfvss/OpT30qP/zhD/Pyyy9n5cqVlUV+V65cmZdffjk//OEPs+eee+acc87JypUriygVAIA2wmwXAJpak68pkyTHHHNM7r333spjrz/xiU9k6NCh6dWrV8rlcubPn59nnnkmL7zwQlasWJH//M//zJtvvpm77rqriHIBAGiDrPdBYxD+ATU1eSjzk5/8JBMnTkypVMonP/nJjB8/PkOGDFlr22effTannnpqpk+fnokTJ+bOO+/MMccc08QVAwAAADS8Jr996b//+7+TJAMHDsyTTz5ZayCTJIMHD86UKVOy8847p1wu54YbbmiqMgEAaOXMWACgaE0eyvzxj39MqVTKBRdckG7duq2zfbdu3XLBBRckSf7whz80dnkAAAAATaLJQ5lly5YlSfbYY496H7Oq7fLlyxulJgAAgPVhphXQEJo8lNluu+2SJO+++269j3nvvfdWOxYAAKClEOAAtWnyUOaoo45KuVzOvffeW+9jVi0MPGrUqEasDAAAmpY36wBtW5OHMueee2522GGH3HDDDbn77rvX2X7ixIm54YYbsv322+f8889vggoBAAAAGl+ThzKbbbZZfvWrX+XTn/50jj322Bx55JG5//77M3fu3CxfvjzV1dWZO3du7r///owaNSpf/vKX8+lPfzq//vWvs9lmmzV1uQAAAACNokNTn7B9+/aV7XK5nAcffDAPPvhgre3L5XKeffbZ7LDDDrW2KZVKqa6ubtA6AQBgFbcZAdAYmjyUKZfLdX5cn2MAAAAAWromD2XGjh3b1KcEAAAAaHaEMgAAsJ6qqqr8XQvARmvyhX4BAKA1qGudGWvQAFAfQhkAAIBG0FzDueZaF7RFQhkAAACAAghlAAAANkDNGSdmnwAbQigDAABNwJt2AD5KKAMAAABQAKEMAAA0I2bUALQdQhkAANgI1hUBYEMJZQAAABqQcA6oL6EMAACsB2+4AWgoQhkAAACAAghlAAAAAAoglAEAAGhgbnMD6kMoAwAAAFAAoQwAAABAAYQyAAAAbYzbq6B5EMoAAAAAFEAoAwAAAFAAoQwAADQht40AsIpQBgAAAKAAQhkAAGhEZsYAUBuhDAAAQAMQwAHrSygDAAAAUAChDABAG+V/9Yu1tq//+oyJ8QNo+YQyAAAAAAUQygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAABAA2rIpyJ5wlLzY0yAhiSUAQCAFk5QANAyCWUAAAAACiCUAQCAJtLQM1rMkAFo2YQyAABQIMFK82VsgMYmlAEAAAAogFAGAABaCDM3AFoXoQwAAABAAYQyAAAAAAUQygAAQCNxuxEAdRHKAABAC1NX2NNcgqDmUgdAcyaUAQAAACiAUAYAAFirjZ3tYrYMQN2EMgAA0IoJRqjJvwdoXoQyAADQSnjDDdCyCGUAAKANWhXgCHIAiiOUAQAAACiAUAYAAFoZs1+alq83sKGEMgAAALUQuACNSSgDAAAAUAChDAAANAONOSOjIfs2cwSg4QhlAACgGROCALReQhkAAGgF1hXeNHa4s6H9C52AtkwoAwAAAFAAoQwAAABAAYQyAABAg2kNtyO1hmsAWgahDAAAtACCgqb10a+3rz/QGIQyAABAiyIgAVoLoQwAAABAAYQyAABtkJkG1FRVVdWs/k3UVUtzqhNgYwllAACANk3QAxRFKAMAADRLwpLG5esLxRPKAABAG9OWbg9qbdcDtC5CGQAAoMVprLClLQVWQPGEMgAAwGo+Gj40RBjR2IHGhvQvZAGKJpQBAAAAKIBQBgAAIGbOAE1PKAMAAGywlhZktLR6gdatzYYy8+fPz6RJk3LRRRflkEMOSY8ePVIqlVIqlTJmzJj17u+RRx7J6NGj07dv33Tq1Cl9+/bN6NGj88gjjzR88QAA0IKtCkaa4zozAE2pQ9EFFKVXr14N0k+5XM5pp52W8ePHr/b5uXPn5r777st9992XU045Jddff31KpVKDnBMAAJqj5hKCVFVVZezYsUWXAbBObXamTE39+vXLwQcfvEHHfu9736sEMnvuuWfuuOOOTJs2LXfccUf23HPPJMn48ePzr//6rw1WLwAA8KHGeFIUQFNpszNlLrroogwZMiRDhgxJr169Mnv27Gy//fbr1cfMmTNz+eWXJ0kGDx6cKVOmpEuXLkmSIUOG5Igjjsjw4cPz7LPP5rLLLsuJJ56YHXfcscGvBQAAAGh52uxMmaqqqhx22GEbdRvT1Vdfnerq6iTJtddeWwlkVunatWuuvfbaJEl1dXWuueaaDT4XAABtS1ub8dHWrhcgacOhzMYql8t54IEHkiS77LJLhg0bttZ2w4YNy84775wkuf/++1Mul5usRgAAaAsEOkBLJZTZQK+99lrmzp2bJBk+fHidbVftnzNnTmbPnt3YpQEAAAAtQJtdU2ZjzZgxo7K9yy671Nm25v4ZM2as19o1c+bMqXP/vHnz6t0XAAAA0HwIZTbQG2+8Udnu27dvnW379eu31uPqo+axAADQ1Bri1iC3FwGsnduXNtDChQsr2927d6+zbbdu3Srb77//fqPVBAAAqwhCAJo/M2U20JIlSyrbHTt2rLNtp06dKtuLFy9er/Osa2bNvHnzMnTo0PXqEwAA2iJBFdDcCGU2UOfOnSvby5Ytq7Pt0qVLK9sffWz2uqzr1igAAACgZXL70gbadNNNK9vruiXpgw8+qGyv61YnAABgTWa5AK2RUGYD1ZzBsq4nJNW8BcnCvQAAAEAilNlgu+66a2X7pZdeqrNtzf2DBg1qtJoAAKApNPWsFbNkgNZKKLOBtt9++/Tu3TtJMnny5DrbTpkyJUnSp0+f9O/fv7FLAwAAaqgr1BH4AEUSymygUqmUkSNHJvlwJszTTz+91nZPP/10ZabMyJEjUyqVmqxGAAAAoPkSymyEs88+Ox06fPgAqzPPPHONx10vXrw4Z555ZpKkQ4cOOfvss5u6RAAAWI2ZIQDNR5t9JPaTTz6ZmTNnVj5esGBBZXvmzJm55ZZbVms/ZsyYNfoYOHBgzj///IwbNy7PPvts9t1331xwwQXZcccdM2vWrFx22WWZPn16kuRb3/pWdtppp0a5FgAAAKDlabOhzIQJE3Lrrbeudd9TTz2Vp556arXPrS2USZJLLrkk8+fPz0033ZTp06fnmGOOWaPNSSedlO9///sbXTMAALRkVVVVGTt27AbvB2ht3L60kdq1a5cbb7wxDz30UEaOHJnevXunY8eO6d27d0aOHJmHH344EyZMSLt2vtQAALQuboUC2DhtdqbMLbfcssYtShvj0EMPzaGHHtpg/QEAAACtm+kbAAAAAAUQygAAAM2OW6OAtkAoAwAAAFAAoQwAAFAvZq8ANCyhDAAAAEABhDIAAABtlNlPUCyhDAAA0OSKDgOKPj9AIpQBAAAAKIRQBgAAAKAAQhkAAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAAIACCGUAAAAACiCUAQAAACiAUAYAAACgAEIZAAAAgAIIZQAAAAAKIJQBAAAAKIBQBgAAAKAAQhkAAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAAIACCGUAAAAACiCUAQAAACiAUAYAAACgAEIZAACANq6qqqroEqBNEsoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABRAKAMAAABQAKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAQBtRVVVVdAkAQA1CGQAAAIACCGUAANoQs2UAoPkQygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABRAKAMAAABQAKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABRAKAMAAABQAKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAJEmqqqqKLgHaFKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAAAW+YUCCGUAAAAACiCUAQAAACiAUAYAoJVzSwIANE9CGQAAAIACCGUAAAAACiCUAQAAYDVue4SmIZQBAAAAKIBQBgAAAKAAQhkAAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAAIACCGUAAAAACiCUAQAAACiAUAYAAACgAEIZAAAAgAIIZQAAAAAKIJQBAAAAKIBQBgAAAKAAQhkAAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAAIACCGU2UqlUqtdr//33L7pUAAAAoBkRygAAAAAUoEPRBbQWp59+es4444xa93fr1q0JqwEAAACaO6FMA+nZs2d22223ossAAAAAWgi3LwEAAAAUQCgDAAAAUAChDAAAAEABrCnTQO65557ccccdef3119OhQ4dss802+cxnPpMxY8bkgAMO2OB+58yZU+f+efPmbXDfAAAAQHGEMg3kxRdfXO3jmTNnZubMmfnRj36UI488Mrfccks222yz9e63X79+DVUiAAAA0IwIZTZS165dc8QRR+QLX/hCdtlll3Tv3j1vvfVWJk+enOuvvz5vv/127r///owcOTK//OUvs8kmmxRdMgAAANAMCGU20ty5c7P55puv8fmDDjooZ555Zg455JBMnz49kydPznXXXZdvfvOb69X/G2+8Uef+efPmZejQoevVJwAAAFA8ocxGWlsgs0qvXr0yceLEDBo0KMuWLcu111673qFM3759N7JCAAAAoDny9KVGtsMOO+Sggw5K8uE6M2+++WbBFQEAAADNgVCmCey6666V7blz5xZYCQAAANBcCGWaQLlcLroEAAAAoJkRyjSBmo/L7t27d4GVAAAAAM2FUKaRvfrqq/nlL3+Z5MP1Zfr06VNwRQAAAEBzIJTZCA8++GCqq6tr3f+3v/0t//iP/5jly5cnSb7+9a83VWkAAEmSqqqqoksAAGrhkdgb4cwzz8zy5ctz1FFHZZ999kn//v3TpUuXLFiwII8//niuv/76vP3220mS/fbbTygDAAAAVAhlNtKbb76Za6+9Ntdee22tbY466qhMmDAhnTp1asLKAAAAgOZMKLMRbr311kyePDlTp07Nq6++mgULFuS9995L9+7d069fv3zmM5/JCSeckH322afoUgEAAIBmRiizEYYPH57hw4cXXQYAwFpZTwYAmjcL/QIAAAAUQCgDAAAAUAChDAAAAEABhDIAAADUyvpU0HiEMgAAAAAFEMoAAAAAFEAoAwAAwBrctgSNTygDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABRAKAMAAABQAKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAQJ2qqqqKLgFaJaEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwDQylj7AQBaBqEMAAAA67Qq8BX8QsMRygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAsF4s9gsNQygDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABRAKAMAAABQAKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAALBBqqqqii4BWjShDAAAAEABhDIAAACsN7NkYOMJZQAAWhFvkgCg5RDKAAAAABRAKAMAAABQAKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAAAAUQCgDAADABquqqiq6BGixhDIAAAA0CAENrB+hDAAAAEABhDIAAAAABRDKAAC0Am4ZAIrkZxBsGKEMAAAAQAGEMgAAAAAFEMoAAADQoFbdzuS2JqibUAYAAIAGI4iB+hPKAAAAABRAKAMAAABQAKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAQJPwZCZYnVAGAACARiOIgdoJZQAAAGh0whlYU4eiCwAAYMN5kwMALZeZMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAAAAUQCgDAAAAUAChDAAAAIWrqqoqugRockIZAAAAgAIIZQAAAGi2zKChNRPKAAAAABRAKAMAAABQAKEMAAAATW7VbUluT6ItE8oAALRA3sQAQMsnlAEAAKDZE0bTGgllAAAAAAoglAEAAKAQ65r9YnYMrZ1QBgAAAKAAQhkAAACajNkv8L+EMgAAADQbQhvaEqEMAAAALZIAh5ZOKAMA0AJ44wGwOj8XaQ2EMgAAAAAFEMoAAADQ7JgJQ1sglAEAaGG8UQFaKz/faGuEMgAAALRowhxaKqEMAEAL4o0HwNp/Fvr5SEsklAEAAAAogFAGAACAVs9MGpojoQwAAAAtgmCF1kYoAwAAQKthvRlaEqEMAAAArUp9QhhBDc2BUKYBvf766zn//PMzaNCgdOvWLVtuuWWGDh2aK664IosWLSq6PACgBamqqvKGAWAj+BlKS9Ch6AJai4ceeijHHXdc3n333crnFi1alGeeeSbPPPNMJkyYkIcffjg77LBDgVUCAC2RNxYAG+6jP0P9TKU5MVOmAfzhD3/I0UcfnXfffTfdu3fPJZdckt/+9rf59a9/nZNPPjlJ8vLLL2fEiBF5//33C64WAACAmgQ1FEUo0wDOPvvsLFq0KB06dMijjz6a7373u9lnn33y+c9/PuPHj8/ll1+eJHnppZdy1VVXFVwtANBcrXpT4M0BALQNQpmN9Mwzz+Txxx9Pkpx00knZZ5991mhz3nnnZdCgQUmSa665JsuXL2/KEgEAAIBmSCizke6///7K9oknnrjWNu3atctXv/rVJMk777xTCXEAaBpFzTpYn0dy1lXjuuo3q6J58uQPgJal5s9kP59pKkKZjfTEE08kSbp165a99tqr1nbDhw+vbD/55JONXhdAa7A+fxA1xB9P9VkIsL6hSmP9MVfffhv7j0l/rG4YXzeA5qeu3+F+btPYPH1pI82YMSNJMmDAgHToUPuXc5dddlnjmPqYM2dOnfvfeOONyva8efPq3S9AU7rqqqty7rnnrvfn33333XX+HFzVPqn9Z+aqfmo730fb1fZxXX2t7dhVNdVs++677+bcc89do466rrXmvrUdX3P/R79267rmVerT7qPXUZ+xaY0++rWq7Wu3rn8/q9Qcu1Uf13yaY82P69q3Pm0/uq+2z23sedb3vOvqq6Fqaqy+Gurr1FQ1NWTNG1tvQ/Xle8D3QGOcZ22/t+tS1+/Utf0OWeXcc89dr7+Z6vs7noZT8z13dXV1g/RZKpfL5QbpqQ1asmRJunTpkiQZMWJEJk2aVGf77t2754MPPsiwYcMyderUep2jVCptdJ0AAABAw5k2bVqGDBmy0f24fWkjLFy4sLLdvXv3dbbv1q1bkngsNgAAAOD2pY2xZMmSynbHjh3X2b5Tp05JksWLF9f7HDVvT6qthpdeeim9evXK1ltvXectVC3BvHnzMnTo0CQfJo/bbrttwRXRUIxt62VsWy9j27oZ39bL2LZexrb1MrYtQ3V1dd56660kye67794gfbbsd/AF69y5c2V72bJl62y/dOnSJKnc8lQfffv2XWebAQMG1Lu/lmTbbbet1/XT8hjb1svYtl7GtnUzvq2XsW29jG3rZWybt/79+zdof25f2gibbrppZbs+tyR98MEHSep3qxMAAADQugllNkLnzp3To0ePJOt+StI777xTCWX69evX6LUBAAAAzZtQZiMNGjQoSTJz5sw6H4n10ksvrXEMAAAA0HYJZTbSfvvtl+TDW5Oee+65WttNnjy5sr3vvvs2el0AAABA8yaU2UhHHnlkZfvmm29ea5uVK1fmRz/6UZJk8803zwEHHNAUpQEAAADNmFBmIw0dOjSf/exnkyQ33nhjpk6dukabK6+8MjNmzEiSnHXWWdlkk02atEYAAACg+fFI7AbwH//xH9l3332zePHiHHzwwfnud7+bAw44IIsXL86dd96Z8ePHJ0kGDhyY8847r+BqAQAAgOagVC6Xy0UX0Ro8+OCD+cpXvpL33ntvrfsHDhyYhx56KAMGDGjiygAAAIDmSCjTgP7617/mP/7jP/LQQw9lzpw56dixYwYMGJAvfelL+cY3vpGuXbsWXSIAAADQTAhlAAAAAApgoV8AAACAAghlAAAAAAoglAEAAAAogFAGAAAAoABCGQAAAIACCGUAAAAACiCUAQAAACiAUAYAAACgAEIZAAAAgAIIZWg29t9//5RKpXq96uPPf/5zTjvttAwYMCBdunTJ1ltvnc997nO54YYbUl1d3chXQ338/Oc/X21cL7744nodZ2ybj4ceeigXX3xxRowYkUGDBqVHjx7ZZJNNssUWW2SvvfbKeeedl5dffrne/Rnb5uP111/Pddddly9/+cvZeeed061bt3Tu3Dl9+/bNyJEjc8cdd6zXmBjb5uP999/PlClTcsUVV+Too4/O9ttvX/k53L9///Xuz9g2L6+//nrOP//8DBo0KN26dcuWW26ZoUOH5oorrsiiRYuKLo8a5s+fn0mTJuWiiy7KIYcckh49elS+F8eMGbPe/T3yyCMZPXp0+vbtm06dOqVv374ZPXp0HnnkkYYvnjo9//zzufTSS3PIIYekX79+6dSpU7p3756BAwdmzJgxeeKJJ9arP2PbypWhmRg+fHg5Sb1e6zJhwoRyp06daj1+2LBh5QULFjTBVVGb999/v7zddtutNi5jx45d53HGtvlYvnx5vb5fN9lkk/IPfvCDdfZnbJuPf/3Xfy2XSqV1ju3gwYPLf/3rX9fZn7FtXvbff/9ax2K77bZbr76MbfMyadKk8mabbVbreOy8887lWbNmFV0m/19dP19POOGEevezcuXK8imnnFJnf6ecckp55cqVjXcxVHzuc5+r199Hxx9/fHnp0qV19mVs2wahDM3GqlBm8ODB5T/96U91vuryyCOPlNu1a1dOUu7Vq1f5P//zP8u/+93vyj//+c/Lo0ePrvwA+9znPldesWJFE10dH3XOOeeUk5R79uxZ71DG2DYvy5cvL2+22WblkSNHli+99NLynXfeWZ48eXL5mWeeKT/wwAPlc845Z7U3B9ddd12tfRnb5uWkk04qJyl369at/JWvfKV88803l5988snys88+W/7xj39cHjJkSGVMdtppp/LChQtr7cvYNj81/xNkiy22KB900EHl7t27r3coY2ybl9///vflrl27lpOUu3fvXr7kkkvKv/3tb8u//vWvyyeffHJlPHbZZZc6v2dpOjXfWPfr16988MEHb1Ao893vfrdy3J577lm+4447ytOmTSvfcccd5T333LOy78ILL2y8i6Fixx13LCcp9+7du3zWWWeVJ06cWJ42bVp56tSp5auuuqrcp0+fypgce+yxdfZlbNsGoQzNxqo/EocPH77BfSxfvrw8YMCAcpLyxz72sfLMmTPXaHPGGWdUfoDdeuutG1ExG+q5554rt2/fvtypU6fy+PHj6xXKGNvmqbq6us79r776anmLLbYoJylvvfXWa21vbJuff/mXfylfdtll5ffee2+t+6urq8tHH310ZUz+7d/+ba3tjG3zdMMNN5Rvv/328iuvvFL53KqZi/UNZYxt87NqBlSHDh3Kv/3tb9fYf/nll1fGo6qqqoAK+aiLLrqo/OCDD5b/53/+p1wul8uvvfbaeocyr7zySrlDhw6V/9hctGjRavs/+OCD8uDBgyv/Ntb2vUrDGjFiRPmuu+6q9W+kt956qzxw4MDKWE+ZMmWt7Yxt2yGUodloiFDm7rvvrvyAq+12iQ8++KDyJnG33Xbb4HOxYaqrq8uf/vSnK38UPvbYY/UKZYxty3XaaadVxu6FF15YY7+xbZkWLFhQ7tixYzlJeY899lhrG2PbcqxvKGNsm5dp06ZVxuPUU09da5sVK1aUBw0aVJkhtWzZsiauknXZkFCmZvg5derUtbaZOnVqpc03vvGNBqyYDfXggw9WxuSb3/zmWtsY27bDQr+0Kvfff39lu7YF0rp27Zqjjz46SfLCCy/klVdeaYLKWOXqq6/O888/n4EDB+aCCy6o93HGtuXq1q1bZXvJkiVr7De2LdNWW22VPfbYI0kya9astbYxtq2XsW1eao7HiSeeuNY27dq1y1e/+tUkyTvvvJPHH3+8CSqjMZXL5TzwwANJkl122SXDhg1ba7thw4Zl5513TvLhv5VyudxkNbJ2+++/f2V7bb9DjW3bIpShVVm1kvnOO++cbbbZptZ2w4cPr2w/+eSTjV4XH5o9e3bGjh2bJPnhD3+YTp061ftYY9syLV68uPJHRbt27TJw4MA12hjblmvp0qVJPhzbtTG2rZexbV5WjUe3bt2y11571drOeLQur732WubOnZtk9bFdm1X758yZk9mzZzd2aazDsmXLKttr+x1qbNsWoQzNzksvvZQhQ4Zk0003Xe3xqz/60Y+yfPnyWo97//33M2fOnCQfJsp1qbl/xowZDVM463T66adn0aJFOe644/KFL3yh3scZ25Zl+fLlef3113PnnXfmM5/5TGbOnJnkw/+93XTTTVdra2xbrvnz51fGYW1jZ2xbL2Pb/Kz62g4YMCAdOnSotZ3xaF1qjqHvxZZl8uTJle21jZ2xbVtq/6kNBfnb3/6Wv/3tb5WP586dm7lz5+ZnP/tZLrvsskycODGDBg1a47g5c+ZUpuz17du3znP069evsv3GG280UOXU5Sc/+UkeeeSRbL755rnyyivX61hj2/zNnj0722+/fa37DzzwwLWOu7Ftuf7P//k/qa6uTpLKLSo1GdvWy9g2L0uWLMmCBQuSrHs8tthii3Tr1i0ffPCB8WgFao6h78WWY+XKlRk3blzl47X9DjW2bYtQhmajXbt2+cIXvpBDDz00n/zkJ7PVVltl4cKFef7553PDDTdkxowZefHFF3PAAQdk2rRp+fjHP77a8QsXLqxsd+/evc5z1Vzj4v3332/YC2ENf//733POOeckSX7wgx+kV69e63W8sW25ttpqq/zXf/1XvvSlL6V9+/Zr7De2LdPvfve7XHPNNUk+/GPxjDPOWKONsW29jG3zsj7jkaQSyhiPls/3Yst09dVXZ9q0aUmSUaNGZfDgwWu0MbZti1CGZuOnP/1pNt988zU+/9nPfjZnnHFGTj755Nx6663529/+lrPPPjs//elPV2tXcwHRjh071nmummuZLF68eOMKZ53OP//8zJ8/P3vvvXdOOeWU9T7e2DZ/ffr0yZ/+9KckSXV1debOnZtHHnkkN954Y84444y8+uqr+c53vpNSqbTacca25fnb3/6Wf/zHf0x1dXVKpVJuvfXWdO3adY12xrb1MrbNy/qMR/K/Y2I8Wj7fiy3P5MmT8+1vfztJ0rNnz1x33XVrbWds2xZryrBeVv0RvrGvW265ZY2+1xbIrLLJJptkwoQJlXsm77vvvsriV6t07ty5sl1z8ay1WbU4ZZJ06dKlHlfe+jXW2D7++OO5+eab0759+1x//fW1LghaF2O7cRrz+3aVTTbZJLvttlt22223fOpTn8qIESNy7bXX5umnn06pVMqFF16Yk046aY3jjO3GaYqxrWnhwoUZMWJEZT2RSy+9NJ///OfX2tbYbpymHtv1YWybl/UZj+R/x8R4tHy+F1uWP//5zxk1alSqq6vTqVOn3H333bXOHje2bYtQhhajQ4cOq72pq7lAVpLVFhBd19S9Dz74oLJdn6m+bJilS5fm1FNPTZJ885vfzKc+9akN6sfYtlx77LFHvv/97ydJbr755jz66KOr7Te2LceSJUsycuTIPPfcc0mSc889t/K/fWtjbFsvY9u8rM94JP87Jsaj5fO92HK89tprOfjgg/POO++kffv2ueOOO+p8qpKxbVvcvsR66dChQ4Os6r3ttttu0HG77rprZfujM2VqLoK16n9xa1NzEayai2O1ZY0xtj/96U/zl7/8JR06dMiuu+6aO++8c432L774YmX7hRdeqLTZe++9KwvHGtuNU/T37ciRIytrjkycODEHH3xwZZ+x3ThNNbbV1dU5+uij89hjjyVJvva1r61zwW5ju3GK/r6ti7FtXjp37pwePXpkwYIF6xyPd955p/IGzni0fL4XW4Y333wzBx54YN58882USqXcdNNNGTVqVJ3HGNu2RSjDelvXY9ka06qnPaxN9+7d069fv7zxxht56aWX6uyn5v61PcmprWrosV01nbK6ujonn3zyOtvfe++9uffee5N8OKtiVShjbDdekd+3W2+9dWX7r3/962r7jO3Ga+yxXblyZY4//vg8+OCDSZIvf/nLueGGG9Z5nLHdeEV+39bF2DY/gwYNyhNPPJGZM2emurq61sdiG4/WpeZ/VvpebJ4WLFiQgw46KK+++mqS5Nprr81Xv/rVdR5nbNsWty/RotScVdG7d+819u+3335Jkpdffjn/8z//U2s/NW992nfffRuwQhqLsW25as5qW9u0WmPbvJ166qmVGWyHHXZYfvzjH9d7bShj23oZ2+Zl1Xh88MEHlVsM18Z4tC7bb7995e/hj97W/1FTpkxJ8uHC/P3792/s0kjy7rvv5otf/GLl/cu4cePy9a9/vV7HGtu2RShDi1FdXZ2bbrqp8vHnPve5NdoceeSRle3aFjdctGhR7r777iQfptADBw5s0Dr5X2PGjEm5XK7ztep2iCQZO3Zs5fNjxoxZrS9j23Ldc889le3dd999jf3Gtvk699xzM2HChCTJF77whUycODGbbLJJvY83tq2XsW1eao7HzTffvNY2K1euzI9+9KMkHz5c4YADDmiK0mhEpVIpI0eOTPLhbImnn356re2efvrpymyKkSNHrvEkRBreokWLMmLEiDz//PNJkgsvvDAXXHBBvY83tm1MGZqB3/zmN+V33nmn1v3Lli0rn3DCCeUk5STlww8/vNZ2O+64YzlJ+WMf+1h55syZa7Q544wzKv3cfPPNDXQFbKjHHnusMh5jx46ttZ2xbX7uu+++8ptvvllnm8mTJ5e7d+9eTlLu0KFD+aWXXlqjjbFtnsaOHVv5mn/mM58pv//+++vdh7FtObbbbrtykvJ2221Xr/bGtvn57Gc/W/lZ+9vf/naN/Zdffnm9ft9SnNdee60yRieccEK9jnn55ZfLHTp0KCcpDx48uLxo0aLV9i9atKg8ePDgyr+Nv/zlL41QOTUtXbq0fPDBB1fG8qyzztqgfoxt21Eql+tYpAOayJgxY3LvvffmiCOOyP7775+dd945H/vYx/L+++/nueeeyw033FBZ8LBnz555+umnK+uNfNTDDz+cww8/PCtXrkyvXr3yve99L0OHDs0777yT//7v/66sWbLffvvl8ccfT/v27ZvsOlnT448/XvnfurFjx+biiy+uta2xbV7GjBmTO+64IyNGjMgXvvCFfOITn8jmm2+epUuXZtasWXnwwQdz9913Z+XKlUmSqqqqXHTRRWvty9g2L9dee22++c1vJvlwOvRdd92VzTbbrM5jdt5557XOojG2zc/MmTPz5JNPrva5888/P2+//Xa22mqrXHHFFavt+4d/+Idss802a/RjbJuX6dOnZ999983ixYvTvXv3fPe7380BBxyQxYsX584778z48eOTJAMHDsyzzz672tNdKMaTTz6ZmTNnVj5esGBBvvWtbyX58Payr33ta6u1/+gs4lW+853vZNy4cUmSPffcMxdccEF23HHHzJo1K5dddlmmT59eaXfppZc2wpVQ01FHHZWf/vSnSZLPf/7zueaaa+qcwdKxY8daZxIa2zai6FQIyuXyarNg6nrtvvvu5T//+c/r7G/8+PHljh071trP0KFDy2+99VYTXBnrUt+ZMqsY2+ajvt+3Xbp0KV9xxRXr7M/YNh/Dhw+v19jWfL322mu19mdsm5ebb755vcb2scceq7UvY9u8/OxnPyt/7GMfq3U8Bg4cWH7llVeKLpP/r76/R1e9arNixYryP//zP9d57EknnVResWJFE15d27W+vz/rmqFobNsGa8rQLFxwwQW5+uqrc/TRR2e33XZLr169sskmm6R79+7Zcccd8+Uvfzn33HNPpk+fvtpq5LU5+eST89xzz+Xkk0/ODjvskM6dO2errbbKfvvtl+uuuy5PPfVUevTo0QRXRkMzts3HFVdckbvuuiunnnpqhgwZkn79+qVTp07p0qVL+vTpk4MPPjjjxo3LrFmzct55562zP2Pbehnb1svYNi+HH354/vjHP+acc87JwIED07Vr12y++eYZPHhw5X/VBwwYUHSZNLB27drlxhtvzEMPPZSRI0emd+/e6dixY3r37p2RI0fm4YcfzoQJE+q9SDvNh7FtG9y+BAAAAFAAkRoAAABAAYQyAAAAAAUQygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABRAKAMAAABQAKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAABsoOXLl2fnnXdOqVTKXXfdVXQ5DeKMM85IqVTKCSecUHQpANDqlcrlcrnoIgAAWqKrrroq5513XgYNGpQXXngh7dq1/P/veuONNzJgwIAsX748v/vd7zJkyJCiSwKAVqvl/+UAAFCA999/Pz/4wQ+SJBdddFGrCGSSpF+/fjnhhBNSLpfzve99r+hyAKBVax1/PQAANLHrrrsuCxYsSL9+/XL00UcXXU6DOu+885Ikjz76aJ555pmCqwGA1ksoAwCwnlasWJH/+q//SpIce+yxrWaWzCo777xzPv3pTydJ/uM//qPgagCg9Wpdf0EAADSBX/7yl3n99deTJF/5ylcKrqZxHHfccUmSe++9N++++27B1QBA6ySUAQBapQEDBqRUKtXr1blz51RXV9e777vvvjtJstNOO2X33Xevtd2YMWNSKpXSv3//Ovu75ZZbKrXMnj17jf0XX3xxZX+SvPfee7n44ouz++67p3v37unVq1cOPfTQ/Pa3v13tuPnz5+d73/tePvGJT6Rbt27ZaqutMnLkyEyfPn2d13jUUUclSZYsWZIHHnhgne0BgPUnlAEAWp2FCxfm1VdfrXf7T3ziE+nQoUO92z/22GNJkmHDhq13bRvrjTfeyJAhQ1JVVZUXXnghH3zwQebPn5+f//zn+dznPpd77rknSfLHP/4xn/70p3PJJZfkxRdfzKJFi/L3v/89P/vZz7LPPvvkN7/5TZ3n2W677bLtttsmSR5//PHGviwAaJPq/9cHAEAL0alTp/zxj3+ss81FF12U++67L0nWa6HeOXPmVGazFPG46C996UuZM2dOvvOd7+Qf/uEf0rVr1zz55JMZO3Zs3nvvvZx00kkZPHhwDjvssCxevDiXXHJJhg8fnk022SSPPPJILrnkkixdujQnnnhiXnnllXTs2LHWcw0ZMiQ/+9nP8sQTTzThFQJA2yGUAQBanY4dO2a33Xardf93vvOdSiDz7W9/OxdccEG9+655i9Cee+654UVuoN///veZPHly9t5778rnBg8enIEDB2bEiBFZuHBh9t5775TL5UybNi077rhjpd3QoUPTo0ePfP3rX8/rr7+ehx56KKNGjar1XHvttVd+9rOfZebMmZk/f3569uzZqNcGAG2N25cAgDblO9/5TsaNG5fkw0DmBz/4wXodP2fOnMp2ESHF2WefvVogs8qhhx6a7bbbLkny1ltv5fvf//5qgcwqJ554Yjp37pwk65wBU/P65s6duzFlAwBrIZQBANqMjQ1kkg8Dj1W22GKLBqutvo455pha9+2xxx5JklKpVOstWV26dMlOO+2UJOtcd2fLLbesbNe8bgCgYQhlAIA2oSECmST5+9//XtkuIpQZOHBgrfs233zzJEmPHj3qrG1Vu4ULF9Z5rpp9vP322/UvEgCoF6EMANDqNVQgk6Ry60+SLF68eKNrW19du3atdV+7du3W2aZmuxUrVtTZrub1denSpb4lAgD1JJQBAFq1hgxkkmTrrbeubNecNdMa1by+mtcNADQMoQwA0Go1dCCTrB5OvPPOO/U6plwu17l/2bJlG1VTY6l5fUIZAGh4QhkAoFVqjEAmSXbffffK9l/+8pd6HTN//vw6g5l58+ZtdF2NYdX1devWLTvssEPB1QBA6yOUAQBancYKZJJk8ODBlfVVnnnmmXods2TJkjoDnN/85jcNUltDW3V9w4YNS4cOHQquBgBaH6EMANCqNGYgkyQdO3bM0KFDkyTTpk2r93EXXXTRWj9///33Z8qUKZWPly5dunEFNpClS5fmj3/8Y5Lks5/9bMHVAEDr5L88AIBWY9y4cZVA5sgjj8xxxx2XF154odb2W2yxRfr06bPe5xkxYkQmT56cadOmZeHChdl0003rbF8qlXL33Xdn6dKl+drXvpa+ffvm73//ex588MH83//7f9OuXbusXLkySXLzzTdnt912y1e+8pX1rqshTZkyJcuXL0/y4fUCAA1PKAMAtBp33313Zfv+++/P/fffX2f77373u7nkkkvW+zz/9E//lO985ztZsmRJ7rvvvnz1q1+ts/3HP/7xDBs2LHfddVceeOCB1fZ16tQpd911V4499tgsXbo0l112WZIUHsr85Cc/SZLsvPPOGTx4cKG1AEBr5fYlAKBVqK6uzosvvrhex+yxxx4bdK4+ffpk5MiRSZLbb7+9Xsfcfvvtueyyy7Lrrrumc+fO2XLLLTNy5MhMnTo1o0aNyvXXX5+tt946W2+9dU466aQNqquhrAqbkuSMM84otBYAaM1K5XU9oxEAgDU8/fTT2WeffdK+ffvMnDkz/fv3X6PNmDFjcuutt2a77bbL7Nmzm7zGDXXbbbfl+OOPz5ZbbpnZs2ev8/YsAGDDmCkDALABhg0blkMOOSQrVqxo8MWEi7Ry5cpceumlSZLzzz9fIAMAjUgoAwCwgS677LK0b98+N998c15//fWiy2kQ99xzT2bMmJF+/frl7LPPLrocAGjVLPQLALCBdt9999xyyy2ZOXNmXn/99Xz84x8vuqSNtmLFiowdOzaf//zn06VLl6LLAYBWTSgDALARin5KUkP7p3/6p6JLAIA2w+1LAAAAAAXw9CUAAACAApgpAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABRAKAMAAABQAKEMAAAAQAGEMgAAAAAFEMoAAAAAFEAoAwAAAFAAoQwAAABAAYQyAAAAAAUQygAAAAAUQCgDAAAAUAChDAAAAEABhDIAAAAABRDKAAAAABTg/wFkL0auYAF5qgAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 438, + "width": 562 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "P.plot('z')" + ] + }, + { + "cell_type": "markdown", + "id": "ecc456e2-226a-426f-82f3-6f20ce9a4441", + "metadata": {}, + "source": [ + "## Calculate bunching\n", + "\n", + "All of these methods will calculate the bunching." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "95d51518-4dad-478d-a67f-4416e5e5a989", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P.bunching(wavelength)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "9a0ba850-3e57-4b70-b0d1-31376166da55", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P['bunching_0.1e-6']" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "1627bba1-710e-47b6-b923-9c64a6d32903", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P['bunching_0.1_um']" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "8e93a423-a3bc-4eac-9832-46888bd23f24", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P['bunching_0.1_µm']" + ] + }, + { + "cell_type": "markdown", + "id": "0d8186ef-a9ab-4db8-8963-b7bc1bdb9365", + "metadata": {}, + "source": [ + "# Simple plot" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "d24b9496-e828-45f1-a055-4e27e7aeba31", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "import matplotlib.pyplot as plt\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "c6b5c501-bfdd-492d-891e-ba10e6b546ef", + "metadata": {}, + "outputs": [], + "source": [ + "wavelengths = wavelength * np.linspace(0.9, 1.1, 200)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "50cda5af-4a97-4aa0-bf9c-c3984140d39c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'bunching')" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 432, + "width": 569 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(wavelengths*1e6, list(map(P.bunching, wavelengths)))\n", + "plt.xlabel('wavelength (µm)')\n", + "plt.ylabel('bunching')" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "42b088fa-aaef-43df-910f-07cddac21bb0", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 434, + "width": 627 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "P.slice_plot('bunching_0.1_um')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "bbc674b0-67d8-4a5c-abe0-583bdf0270f2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P.in_z_coordinates" + ] + }, + { + "cell_type": "markdown", + "id": "aaa2cc83-9988-4249-a39c-9ee0e15529a3", + "metadata": {}, + "source": [ + "## Units\n", + "\n", + "Bunching is dimensionless" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "01b2f6d7-734c-4bea-add3-48ffa215dacc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "pmd_unit('', 1, (0, 0, 0, 0, 0, 0, 0))" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P.units('bunching_0.1_um')" + ] + }, + { + "cell_type": "markdown", + "id": "8a0a3ee9-3fbe-4299-ba9f-7055cf2869ab", + "metadata": {}, + "source": [ + "## Bunching function\n", + "\n", + "This is the function that is used." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "ac7ee4c6-1b02-40a1-96a3-3be6629da002", + "metadata": {}, + "outputs": [], + "source": [ + "from pmd_beamphysics.statistics import bunching" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "af2982d8-a19d-481f-b9ec-940d5d02e290", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\u001b[0;31mSignature:\u001b[0m \u001b[0mbunching\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mz\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwavelength\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mDocstring:\u001b[0m\n", + "Calculate the normalized bunching parameter, which is the magnitude of the \n", + "complex sum of weighted exponentials at a given point.\n", + "\n", + "The formula for bunching is given by:\n", + "\n", + "$$\n", + "B(z, \\lambda) = \f", + "rac{\\left|\\sum w_i e^{i k z_i}\r", + "ight|}{\\sum w_i}\n", + "$$\n", + "\n", + "where:\n", + "- \\( z \\) is the position array,\n", + "- \\( \\lambda \\) is the wavelength,\n", + "- \\( k = \f", + "rac{2\\pi}{\\lambda} \\) is the wave number,\n", + "- \\( w_i \\) are the weights.\n", + "\n", + "Parameters\n", + "----------\n", + "z : np.ndarray\n", + " Array of positions where the bunching parameter is calculated.\n", + "wavelength : float\n", + " Wavelength of the wave.\n", + "weight : np.ndarray, optional\n", + " Weights for each exponential term. Default is 1 for all terms.\n", + "\n", + "Returns\n", + "-------\n", + "float\n", + " The normalized bunching parameter.\n", + "\n", + "Raises\n", + "------\n", + "ValueError\n", + " If `wavelength` is not a positive number.\n", + "\u001b[0;31mFile:\u001b[0m ~/Code/GitHub/openPMD-beamphysics/pmd_beamphysics/statistics.py\n", + "\u001b[0;31mType:\u001b[0m function\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "?bunching" + ] + } + ], + "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": "3.11.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/mkdocs.yml b/mkdocs.yml index e09ca80..f1c1265 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -12,6 +12,7 @@ nav: - examples/read_examples.ipynb - examples/write_examples.ipynb - examples/plot_examples.ipynb + - examples/bunching.ipynb - Fields: - examples/fields/field_examples.ipynb - examples/fields/field_expansion.ipynb diff --git a/pmd_beamphysics/labels.py b/pmd_beamphysics/labels.py index d6b7069..7d2c896 100644 --- a/pmd_beamphysics/labels.py +++ b/pmd_beamphysics/labels.py @@ -1,4 +1,4 @@ -from pmd_beamphysics.units import pg_units +from pmd_beamphysics.units import pg_units, parse_bunching_str, nice_array TEXLABEL = { @@ -119,6 +119,11 @@ def texlabel(key: str): tex1 = texlabel(subkeys[1]) return fr'\left<{tex0}, {tex1}\right>' + if key.startswith('bunching'): + wavelength = parse_bunching_str(key) + x, _, prefix = nice_array(wavelength) + return f'\mathrm{{bunching~at}}~{x:.1f}~\mathrm{{ {prefix}m }}' + return None diff --git a/pmd_beamphysics/particles.py b/pmd_beamphysics/particles.py index 559491f..54f635b 100644 --- a/pmd_beamphysics/particles.py +++ b/pmd_beamphysics/particles.py @@ -1,4 +1,4 @@ -from pmd_beamphysics.units import dimension, dimension_name, SI_symbol, pg_units, c_light +from pmd_beamphysics.units import dimension, dimension_name, SI_symbol, pg_units, c_light, parse_bunching_str from pmd_beamphysics.interfaces.astra import write_astra from pmd_beamphysics.interfaces.bmad import write_bmad @@ -17,6 +17,8 @@ from pmd_beamphysics.species import charge_of, mass_of from pmd_beamphysics.statistics import norm_emit_calc, normalized_particle_coordinate, particle_amplitude, particle_twiss_dispersion, matched_particles, resample_particles, slice_statistics +import pmd_beamphysics.statistics as statistics + from pmd_beamphysics.writers import write_pmd_bunch, pmd_init from h5py import File @@ -675,6 +677,48 @@ def average_current(self): dt = self.z.ptp() / (self.avg('beta_z')*c_light) return self.charge / dt + def bunching(self, wavelength): + """ + Calculate the normalized bunching parameter, which is the magnitude of the + complex sum of weighted exponentials at a given point. + + The formula for bunching is given by: + + $$ + B(z, \lambda) = \frac{\left|\sum w_i e^{i k z_i}\right|}{\sum w_i} + $$ + + where: + - \( z \) is the position array, + - \( \lambda \) is the wavelength, + - \( k = \frac{2\pi}{\lambda} \) is the wave number, + - \( w_i \) are the weights. + + Parameters + ---------- + wavelength : float + Wavelength of the wave. + + + Returns + ------- + float + The normalized bunching parameter. + + Raises + ------ + ValueError + If `wavelength` is not a positive number. + """ + + if self.in_z_coordinates: + # Approximate z + z = self.t * self.avg('beta_z')*c_light + else: + z = self.z + + return statistics.bunching(z, wavelength, weight=self.weight) + def __getitem__(self, key): """ Returns a property or statistical quantity that can be computed: @@ -705,7 +749,10 @@ def __getitem__(self, key): elif key.startswith('max_'): return self.max(key[4:]) elif key.startswith('ptp_'): - return self.ptp(key[4:]) + return self.ptp(key[4:]) + elif key.startswith('bunching_'): + wavelength = parse_bunching_str(key) + return self.bunching(wavelength) else: return getattr(self, key) diff --git a/pmd_beamphysics/statistics.py b/pmd_beamphysics/statistics.py index 679270b..1b9cc41 100644 --- a/pmd_beamphysics/statistics.py +++ b/pmd_beamphysics/statistics.py @@ -521,4 +521,54 @@ def resample_particles(particle_group, n=0): return data +def bunching(z: np.ndarray, wavelength: float, weight: np.ndarray = None) -> float: + """ + Calculate the normalized bunching parameter, which is the magnitude of the + complex sum of weighted exponentials at a given point. + + The formula for bunching is given by: + + $$ + B(z, \lambda) = \frac{\left|\sum w_i e^{i k z_i}\right|}{\sum w_i} + $$ + + where: + - \( z \) is the position array, + - \( \lambda \) is the wavelength, + - \( k = \frac{2\pi}{\lambda} \) is the wave number, + - \( w_i \) are the weights. + + Parameters + ---------- + z : np.ndarray + Array of positions where the bunching parameter is calculated. + wavelength : float + Wavelength of the wave. + weight : np.ndarray, optional + Weights for each exponential term. Default is 1 for all terms. + + Returns + ------- + float + The normalized bunching parameter. + + Raises + ------ + ValueError + If `wavelength` is not a positive number. + """ + if wavelength <= 0: + raise ValueError("Wavelength must be a positive number.") + + if weight is None: + weight = np.ones(len(z)) + if len(weight) != len(z): + raise ValueError(f"Weight array has length {len(weight)} != length of the z array, {len(z)}") + + k = 2 * np.pi / wavelength + f = np.exp(1j * k * z) + return np.abs(np.sum(weight * f)) / np.sum(weight) + + + diff --git a/pmd_beamphysics/units.py b/pmd_beamphysics/units.py index 2bdb49f..ce0e415 100644 --- a/pmd_beamphysics/units.py +++ b/pmd_beamphysics/units.py @@ -442,7 +442,7 @@ def plottable_array(x, nice=True, lim=None): PARTICLEGROUP_UNITS[k] = unit('eV/c') for k in ['x', 'y', 'z', 'r', 'Jx', 'Jy']: PARTICLEGROUP_UNITS[k] = unit('m') -for k in ['beta', 'beta_x', 'beta_y', 'beta_z', 'gamma']: +for k in ['beta', 'beta_x', 'beta_y', 'beta_z', 'gamma', 'bunching']: PARTICLEGROUP_UNITS[k] = unit('1') for k in ['theta']: PARTICLEGROUP_UNITS[k] = unit('rad') @@ -504,10 +504,53 @@ def pg_units(key): return unit('V/m') if key.startswith('magneticField'): return unit('T') + if key.startswith('bunching_'): + return unit('1') raise ValueError(f'No known unit for: {key}') + +# ------------------------- +# Special parsers + +def parse_bunching_str(s): + """ + Parse a string of the on of the forms to extract the wavelength: + 'bunching_1.23e-4' + 'bunching_1.23e-4_nm' + + Returns + ------- + wavelength: float + + """ + assert s.startswith('bunching_') + + x = s.split('_') + + wavelength = float(x[1]) + + if len(x) == 2: + factor = 1 + elif len(x) == 3: + unit = x[2] + if unit == 'm': + factor = 1 + elif unit == 'mm': + factor = 1e-3 + elif unit == 'µm' or unit == 'um': + factor = 1e-6 + elif unit == 'nm': + factor = 1e-9 + else: + raise ValueError(f'Unparsable unit: {unit}') + else: + raise ValueError(f'Cannot parse {s}') + + + return wavelength * factor + # ------------------------- @@ -591,6 +634,9 @@ def write_dataset_and_unit_h5(h5, name, data, unit=None): if unit: write_unit_h5(h5[name], unit) + + +