{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-24T08:08:06.174626Z",
"start_time": "2018-11-24T07:52:46.148236Z"
}
},
"outputs": [],
"source": [
"import warnings\n",
"warnings.filterwarnings(\"ignore\",category =RuntimeWarning)\n",
"import numpy as np\n",
"import makeqx as mkq\n",
"import de2 as de\n",
"import multiprocessing as mp\n",
" \n",
"# def arc_0(qx, lam_min=400, lam_max=800, npoints=50):\n",
"# cthick = qx[0]\n",
"# q_x = qx[1:]\n",
"# Rs0, Rp0 = mkq.tmm_lam_parallel(q_x, cthick, 0, n_par=12, lam_low=lam_min, lam_high=lam_max, lam_pts=npoints, n_subs=1.52)\n",
"# return np.mean(Rs0)\n",
" \n",
"# def arc_dig_0(qx, lam_min=400, lam_max=800, npoints=50):\n",
"# cthick = qx[0]\n",
"# q_x = mkq.digitize_qx(qx[1:], dlevels=2)\n",
"# Rs0, Rp0 = mkq.tmm_lam_parallel(q_x, cthick, 0, n_par=12, lam_low=lam_min, lam_high=lam_max, lam_pts=npoints, n_subs=1.52)\n",
"# return np.mean(Rs0)\n",
"\n",
"\n",
"def tmm_wrapper2(arg):\n",
" args, kwargs = arg\n",
" return mkq.tmm_eval_wsweep(*args, **kwargs)\n",
"\n",
"\n",
"def arc_par(pop, **kwargs):\n",
" jobs = []\n",
" pool=mp.Pool(60)\n",
" for indiv in pop:\n",
" indivi = mkq.digitize_qx(indiv[1:], dlevels=2)\n",
" jobs.append((indivi, indiv[0], 0))\n",
" arg = [(j, kwargs) for j in jobs]\n",
" answ = np.array(pool.map(tmm_wrapper2, arg))\n",
" pool.close()\n",
" return np.mean(answ, axis=1)\n",
"\n",
" \n",
"num_layers = 35 \n",
"bnds = [(0, 1)]*num_layers\n",
"bnds = [(300, 400)] + bnds\n",
"its_first = 0\n",
"psnew = 500\n",
"its_second = 500\n",
"\n",
"pop = np.ones((psnew, 1+ num_layers))\n",
"for indiv in range(psnew):\n",
" pop[indiv,1:] = mkq.make_qx(num_layers)\n",
" pop[indiv,0] = np.random.uniform( bnds[0][0], bnds[0][1], 1 )\n",
" \n",
"b, c, hstry = de.de_cp(fobj=arc_par, bounds=bnds, pop=pop, history=[], it_start=its_first, popsize=psnew, its=its_second, lam_low=400, lam_high=800, lam_pts=50)\n",
"\n",
"\n",
"#m1 = mkq.tmm_eval2(qx=pop[0][1:], cthick=pop[0][0]) \n",
"#m2 = mkq.tmm_eval(qx=pop[0][1:], cthick=pop[0][0]) \n",
"\n",
"#arc_par(pop, lam_low=400, lam_high=800, lam_pts=50)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-25T10:33:20.269270Z",
"start_time": "2018-11-25T10:32:36.651677Z"
}
},
"outputs": [],
"source": [
"import warnings\n",
"warnings.filterwarnings(\"ignore\",category =RuntimeWarning)\n",
"import numpy as np\n",
"import makeqx as mkq\n",
"import de2 as de\n",
"import multiprocessing as mp\n",
"import qxnew as qn \n",
"# def arc_0(qx, lam_min=400, lam_max=800, npoints=50):\n",
"# cthick = qx[0]\n",
"# q_x = qx[1:]\n",
"# Rs0, Rp0 = mkq.tmm_lam_parallel(q_x, cthick, 0, n_par=12, lam_low=lam_min, lam_high=lam_max, lam_pts=npoints, n_subs=1.52)\n",
"# return np.mean(Rs0)\n",
" \n",
"# def arc_dig_0(qx, lam_min=400, lam_max=800, npoints=50):\n",
"# cthick = qx[0]\n",
"# q_x = mkq.digitize_qx(qx[1:], dlevels=2)\n",
"# Rs0, Rp0 = mkq.tmm_lam_parallel(q_x, cthick, 0, n_par=12, lam_low=lam_min, lam_high=lam_max, lam_pts=npoints, n_subs=1.52)\n",
"# return np.mean(Rs0)\n",
"\n",
"\n",
"def tmm_wrapper2(arg):\n",
" args, kwargs = arg\n",
" return qn.tmm_eval_wsweep(*args, **kwargs)\n",
"\n",
"\n",
"def arc_par(pop, **kwargs):\n",
" jobs = []\n",
" pool=mp.Pool(90)\n",
" for indiv in pop:\n",
" indiv = indiv.reshape((int(indiv.size/2), 2))\n",
" indiv[:,1] = mkq.digitize_qx(indiv[:,1], dlevels=2)\n",
" indiv = indiv.flatten()\n",
" jobs.append((indiv, 0.5, 8 , 0))\n",
" arg = [(j, kwargs) for j in jobs]\n",
" answ = np.array(pool.map(tmm_wrapper2, arg))\n",
" pool.close()\n",
" return np.mean(answ, axis=1)\n",
"\n",
" \n",
"num_layers = 30\n",
"d_min = 0.5\n",
"d_max = 8\n",
"\n",
"bnds = [(d_min, d_max), (0,1) ]*num_layers\n",
"#bnds = [(300, 400)] + bnds\n",
"its_first = 0\n",
"psnew = 160\n",
"its_second = 500\n",
"\n",
"pop = np.ones((psnew, 2*num_layers))\n",
"for indiv in range(psnew):\n",
" pop[indiv] = qn.make_qxn(num_layers, dlevels=2)\n",
" #pop[indiv][::2] = (d_max - d_min)*pop[indiv][::2] + d_min\n",
" pop[indiv,0] = np.random.uniform( bnds[0][0], bnds[0][1], 1 )\n",
" \n",
"b, c, hstry = de.de_cp(fobj=arc_par, bounds=bnds, pop=pop, history=[], it_start=its_first, popsize=psnew, its=its_second, lam_low=400, lam_high=800, lam_pts=50)\n",
"\n",
"np.sum(b[::2]), b[::2], b[1::2], c\n",
"\n",
"#m1 = mkq.tmm_eval2(qx=pop[0][1:], cthick=pop[0][0]) \n",
"#m2 = mkq.tmm_eval(qx=pop[0][1:], cthick=pop[0][0]) \n",
"\n",
"#"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-27T02:07:24.693765Z",
"start_time": "2018-11-26T12:51:52.517421Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"==============================\n",
"Epoch #:1\n",
"==============================\n",
"----------------- I-1---------------------\n",
"19 0.8167181998184866\n",
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"443.137080144755\n",
"----------------- I-2---------------------\n",
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"----------------- I-3---------------------\n",
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"----------------- I-4---------------------\n",
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"----------------- I-5---------------------\n",
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"----------------- I-6---------------------\n",
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"----------------- I-7---------------------\n",
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"----------------- I-8---------------------\n",
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"----------------- I-9---------------------\n",
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"----------------- I-10---------------------\n",
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"322.35717787876524\n",
"Round robin best migration\n",
"==============================\n",
"Epoch #:2\n",
"==============================\n",
"----------------- I-1---------------------\n",
"19 0.3867376372827681\n",
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"----------------- I-2---------------------\n",
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"----------------- I-3---------------------\n",
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},
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"----------------- I-4---------------------\n",
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"----------------- I-5---------------------\n",
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"----------------- I-6---------------------\n",
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"----------------- I-7---------------------\n",
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"270.4053258463316\n",
"----------------- I-8---------------------\n",
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"----------------- I-9---------------------\n",
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"306.8461067415562\n",
"----------------- I-10---------------------\n",
"19 0.2669138768924974\n",
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"326.48592570142057\n",
"Round robin best migration\n",
"==============================\n",
"Epoch #:3\n",
"==============================\n",
"----------------- I-1---------------------\n",
"19 0.3595592355510012\n",
"39 0.3595592355510012\n",
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"434.00704380345314\n",
"----------------- I-2---------------------\n",
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"395.9427324022142\n",
"----------------- I-3---------------------\n",
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"345.9247031338667\n",
"----------------- I-4---------------------\n",
"19 0.26703909811968685\n",
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"323.0408720441064\n",
"----------------- I-5---------------------\n",
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"----------------- I-6---------------------\n",
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]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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"----------------- I-7---------------------\n",
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"----------------- I-8---------------------\n",
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"----------------- I-9---------------------\n",
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"----------------- I-10---------------------\n",
"19 0.2587176476693035\n",
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"479 0.25554134901556536\n",
"499 0.25554134901556536\n",
"324.1596986263086\n",
"Round robin best migration\n",
"==============================\n",
"Epoch #:4\n",
"==============================\n",
"----------------- I-1---------------------\n",
"19 0.3387378338113142\n",
"39 0.3363317158305087\n",
"59 0.3363317158305087\n",
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"433.875866560529\n",
"----------------- I-2---------------------\n",
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"----------------- I-3---------------------\n",
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"----------------- I-4---------------------\n",
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"----------------- I-5---------------------\n",
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"----------------- I-6---------------------\n",
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"----------------- I-7---------------------\n",
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"----------------- I-8---------------------\n",
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{
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"----------------- I-9---------------------\n",
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"----------------- I-10---------------------\n",
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"Round robin best migration\n",
"==============================\n",
"Epoch #:5\n",
"==============================\n",
"----------------- I-1---------------------\n",
"19 0.32148006976682664\n",
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"----------------- I-2---------------------\n",
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"----------------- I-3---------------------\n",
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"----------------- I-4---------------------\n",
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"----------------- I-5---------------------\n",
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"----------------- I-6---------------------\n",
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"----------------- I-7---------------------\n",
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"----------------- I-8---------------------\n",
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"----------------- I-9---------------------\n",
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"----------------- I-10---------------------\n",
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"323.02206146913545\n",
"Round robin best migration\n",
"==============================\n",
"Epoch #:6\n",
"==============================\n",
"----------------- I-1---------------------\n",
"19 0.31363116168282157\n",
"39 0.31363116168282157\n",
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"----------------- I-2---------------------\n",
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"----------------- I-3---------------------\n",
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"----------------- I-4---------------------\n",
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"----------------- I-5---------------------\n",
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"----------------- I-6---------------------\n",
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"----------------- I-7---------------------\n",
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"----------------- I-8---------------------\n",
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"----------------- I-9---------------------\n",
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"----------------- I-10---------------------\n",
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"324.0737161763321\n",
"Round robin best migration\n",
"==============================\n",
"Epoch #:7\n",
"==============================\n",
"----------------- I-1---------------------\n",
"19 0.3032035718411194\n",
"39 0.3032035718411194\n",
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"431.9064995798926\n",
"----------------- I-2---------------------\n",
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"----------------- I-3---------------------\n",
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},
{
"name": "stdout",
"output_type": "stream",
"text": [
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"----------------- I-6---------------------\n",
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"----------------- I-7---------------------\n",
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"----------------- I-8---------------------\n",
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"----------------- I-9---------------------\n",
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"----------------- I-10---------------------\n",
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"459 0.24919047329540672\n",
"479 0.24919047329540672\n",
"499 0.24919047329540672\n",
"323.41226023700364\n",
"Round robin best migration\n",
"==============================\n",
"Epoch #:8\n",
"==============================\n",
"----------------- I-1---------------------\n",
"19 0.3007213422460303\n",
"39 0.3007213422460303\n",
"59 0.30053505022154\n",
"79 0.30053505022154\n",
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"----------------- I-2---------------------\n",
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"----------------- I-4---------------------\n",
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"----------------- I-5---------------------\n",
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"----------------- I-6---------------------\n",
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"----------------- I-7---------------------\n",
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"----------------- I-9---------------------\n",
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"----------------- I-10---------------------\n",
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"328.2416558681744\n",
"Round robin best migration\n",
"==============================\n",
"Epoch #:9\n",
"==============================\n",
"----------------- I-1---------------------\n",
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"----------------- I-2---------------------\n",
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"----------------- I-3---------------------\n",
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"----------------- I-4---------------------\n",
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"----------------- I-5---------------------\n",
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"----------------- I-6---------------------\n",
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"----------------- I-7---------------------\n",
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"----------------- I-8---------------------\n",
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"----------------- I-9---------------------\n",
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"----------------- I-10---------------------\n",
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"479 0.24742724190386475\n",
"499 0.24742724190386475\n",
"336.58381818757204\n",
"Round robin best migration\n",
"==============================\n",
"Epoch #:10\n",
"==============================\n",
"----------------- I-1---------------------\n",
"19 0.29609823536795316\n",
"39 0.29609823536795316\n",
"59 0.29609823536795316\n",
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"459 0.29499830204495686\n",
"479 0.29499830204495686\n",
"499 0.29499830204495686\n",
"438.00922123324483\n",
"----------------- I-2---------------------\n",
"19 0.31261613324217247\n",
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"429.643855995255\n",
"----------------- I-3---------------------\n",
"19 0.2542831910233113\n",
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"499 0.2536129891871847\n",
"420.97685669076225\n",
"----------------- I-4---------------------\n",
"19 0.2574321877953261\n",
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"319.7419885796792\n",
"----------------- I-5---------------------\n",
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"321.7237627850665\n",
"----------------- I-6---------------------\n",
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"267.8781091862889\n",
"----------------- I-7---------------------\n",
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"259.5240707444036\n",
"----------------- I-8---------------------\n",
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"[0.2949983 0.31074466 0.25361299 0.2554086 0.24673907 0.29101194\n",
" 0.28694298 0.25346962 0.26070164 0.24769362]\n",
"[ 0.7666913 4.2781245 0.55799714 0.5 14.80588889 0.5\n",
" 1.3639153 15. 15. 15. 0.50795744 0.55961465\n",
" 0.5 5.72134582 7.60885308 0.54132032 5.74816646 0.5\n",
" 2.9680022 0.5 1.40716798 0.57031921 5.10724442 0.5\n",
" 14.73942853 0.5 0.50986541 14.428049 12.00394804 14.13470092\n",
" 13.85557591 2.52747756 11.67481154 0.5 13.08430348 11.46282726\n",
" 13.53558334 14.17958612 0.66028103 15. 4.86920995 14.62300721\n",
" 15. 13.64440326 0.5 0.5 14.70879091 3.44685505\n",
" 0.5 0.62244958]\n"
]
}
],
"source": [
"%reload_ext autoreload\n",
"%autoreload 2\n",
"import warnings\n",
"warnings.filterwarnings(\"ignore\",category =RuntimeWarning)\n",
"import numpy as np\n",
"import de2 as de\n",
"import multiprocessing as mp\n",
"import makeqx as mkq\n",
"import qxnew as qn \n",
"\n",
"def tmm_wrapper2(arg):\n",
" args, kwargs = arg\n",
" return qn.tmm_eval_wsweep(*args, **kwargs)\n",
"\n",
"def arc_par(pop, **kwargs):\n",
" jobs = []\n",
" pool=mp.Pool(90)\n",
" for indiv in pop:\n",
" indiv = indiv.reshape((int(indiv.size/2), 2))\n",
" indiv[:,1] = mkq.digitize_qx(indiv[:,1], dlevels=2)\n",
" indiv = indiv.flatten()\n",
" jobs.append((indiv, 0, 1, 0))\n",
" arg = [(j, kwargs) for j in jobs]\n",
" answ = np.array(pool.map(tmm_wrapper2, arg))\n",
" pool.close()\n",
" return np.mean(answ, axis=1)\n",
"\n",
" \n",
"num_layers = 50\n",
"d_min = 0.5\n",
"d_max = 15\n",
"\n",
"bnds = [(d_min, d_max), (0,1)]*num_layers\n",
"#bnds = [(300, 400)] + bnds\n",
"its_first = 0\n",
"psnew = 40\n",
"islands = 10 \n",
"its_second = 500\n",
"numgens = 10 \n",
"\n",
"isl = np.ones((psnew*islands, 2*num_layers))\n",
"for indiv in range(psnew*islands):\n",
" isl[indiv] = qn.make_qxn(num_layers, dlevels=2)\n",
"poplist = np.split(isl, islands)\n",
"\n",
"bids = np.zeros(islands, dtype=int)\n",
"bfits = np.zeros(islands)\n",
"bests = isl[0:islands]\n",
"\n",
"\n",
"for gen in range(numgens):\n",
" print(\"==============================\")\n",
" print(\"Epoch #:\" + str(gen + 1))\n",
" print(\"==============================\")\n",
" for isln in range(islands):\n",
" print(\"----------------- I-\" + str(isln + 1)+ \"---------------------\")\n",
" poplist[isln], bids[isln], bfits[isln], bests[isln] = de.de_cp(\n",
" fobj=arc_par, \n",
" bounds=bnds, \n",
" pop=poplist[isln], \n",
" history=[], \n",
" it_start=its_first, \n",
" popsize=psnew, \n",
" its=its_second, \n",
" lam_low=400, \n",
" lam_high=800, \n",
" lam_pts=50)\n",
" print(np.sum(bests[isln][::2]))\n",
" if gen < (numgens - 1):\n",
" print(\"Round robin best migration\")\n",
" stmp = poplist[islands-1][bids[islands-1]] \n",
" for isln in range(1, islands):\n",
" poplist[isln][bids[isln]] = poplist[isln-1][bids[isln-1]]\n",
" poplist[0][bids[0]] = stmp \n",
"\n",
"print(bfits) \n",
"print(bests[np.argmin(bfits)][::2])\n",
"#np.sum(b[::2]), b[::2], b[1::2], c\n",
"\n",
"#m1 = mkq.tmm_eval2(qx=pop[0][1:], cthick=pop[0][0]) \n",
"#m2 = mkq.tmm_eval(qx=pop[0][1:], cthick=pop[0][0]) "
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-27T04:39:19.806762Z",
"start_time": "2018-11-27T04:39:19.740844Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"321.7237627850665\n"
]
}
],
"source": [
"print(np.sum(bests[np.argmin(bfits)][::2]))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-25T08:46:16.654004Z",
"start_time": "2018-11-25T08:46:15.567261Z"
}
},
"outputs": [],
"source": [
"isl = np.split(pop,8)\n",
"isl[0].shape\n",
"arc_par(pop)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-26T10:52:44.968511Z",
"start_time": "2018-11-26T10:52:44.892890Z"
}
},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2\n",
"import qxnew as qn\n",
"import makeqx as mkq\n",
"\n",
"qn.make_qxn(10)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-26T10:52:28.147240Z",
"start_time": "2018-11-26T10:52:28.076907Z"
}
},
"outputs": [],
"source": [
"qx = qn.make_qxn(40,5)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-24T09:33:50.326789Z",
"start_time": "2018-11-24T09:33:50.307053Z"
}
},
"outputs": [],
"source": [
"qx"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-24T07:07:44.202457Z",
"start_time": "2018-11-24T07:07:44.180095Z"
}
},
"outputs": [],
"source": [
"qn.make_nxdx(qx, d_min=2, d_max=10, wavelen=550, n_substrate=1.52)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-24T07:07:45.345103Z",
"start_time": "2018-11-24T07:07:45.322470Z"
}
},
"outputs": [],
"source": [
"qn.tmm_eval_wbk(qx, 2, 10, 0, 550, 1.52)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-24T07:07:47.293093Z",
"start_time": "2018-11-24T07:07:47.155314Z"
}
},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from jupyterthemes import jtplot\n",
"# currently installed theme will be used to\n",
"# set plot style if no arguments provided\n",
"jtplot.style()\n",
"Rs = qn.tmm_eval_wsweep(qx, d_min=2 , d_max=10, inc_ang=0, lam_low=400, lam_high=800, lam_pts=50, n_subs=1.52) # in nm\n",
"lams = np.linspace(400, 800, endpoint=True, num=50)\n",
"plt.plot(lams, Rs )\n",
"plt.xlabel('Wavelength (nm)')\n",
"plt.ylabel('Reflectance (%)')\n",
"plt.ylim([0,100])\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.0"
},
"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": 2
}