diff --git a/Multiplicative Algorithm/Phase2.ipynb b/Multiplicative Algorithm/Phase2.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..c542a3f4b786f3ad9e7a45954eda6bfb4a8977fc
--- /dev/null
+++ b/Multiplicative Algorithm/Phase2.ipynb
@@ -0,0 +1,2526 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import config\n",
+ "from __init__ import *\n",
+ "import numpy as np\n",
+ "\n",
+ "filenames = config.generate_filenames('');\n",
+ "full_link_ids = np.loadtxt(filenames['full_link_ids'])\n",
+ "\n",
+ "D = np.loadtxt('D_trips.txt')\n",
+ "W = np.loadtxt('W_trips.txt')\n",
+ "H = np.loadtxt('H_trips.txt')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Rank= 50, Threshold= 0.5\n",
+ "Initializing W and H...\n",
+ "W, H chosen\n",
+ "Iteration= 0, Error= 47.42513115951605, Sparsity= 0.14878234841185448\n",
+ "Iteration= 1, Error= 47.27939356141551, Sparsity= 0.1480388226704141\n",
+ "Iteration= 2, Error= 47.254940465770034, Sparsity= 0.14740003285495837\n",
+ "Iteration= 3, Error= 47.23150778350247, Sparsity= 0.1468584222785324\n",
+ "Iteration= 4, Error= 47.20764018603474, Sparsity= 0.14641343415744823\n",
+ "Iteration= 5, Error= 47.18203010297705, Sparsity= 0.14607110921091843\n",
+ "Iteration= 6, Error= 47.153263402764054, Sparsity= 0.14584471641133626\n",
+ "Iteration= 7, Error= 47.11965704073741, Sparsity= 0.14575629280483648\n",
+ "Iteration= 8, Error= 47.079090587534736, Sparsity= 0.14583915038594128\n",
+ "Iteration= 9, Error= 47.02880919066814, Sparsity= 0.14614150754900054\n",
+ "Iteration= 10, Error= 46.96518386248703, Sparsity= 0.1467314292811313\n",
+ "Iteration= 11, Error= 46.88342465052259, Sparsity= 0.1477031518593722\n",
+ "Iteration= 12, Error= 46.777262547090125, Sparsity= 0.14918445513468848\n",
+ "Iteration= 13, Error= 46.63866083580378, Sparsity= 0.15134368607074095\n",
+ "Iteration= 14, Error= 46.457707635723224, Sparsity= 0.15439283160919579\n",
+ "Iteration= 15, Error= 46.223001241814124, Sparsity= 0.15857955628285292\n",
+ "Iteration= 16, Error= 45.92304547921768, Sparsity= 0.16415828341501404\n",
+ "Iteration= 17, Error= 45.5492130378439, Sparsity= 0.1713340041861929\n",
+ "Iteration= 18, Error= 45.10013540724041, Sparsity= 0.18018896225629236\n",
+ "Iteration= 19, Error= 44.585462115314655, Sparsity= 0.19062661939756786\n",
+ "Iteration= 20, Error= 44.025365904779974, Sparsity= 0.20237345970542922\n",
+ "Iteration= 21, Error= 43.444625271422424, Sparsity= 0.21504394774916374\n",
+ "Iteration= 22, Error= 42.86537456307679, Sparsity= 0.2282271204910636\n",
+ "Iteration= 23, Error= 42.30319856871292, Sparsity= 0.24155214617052065\n",
+ "Iteration= 24, Error= 41.76683175076107, Sparsity= 0.254723941735953\n",
+ "Iteration= 25, Error= 41.25930461250758, Sparsity= 0.267537768557894\n",
+ "Iteration= 26, Error= 40.77933869842755, Sparsity= 0.2798786358829873\n",
+ "Iteration= 27, Error= 40.32289545820038, Sparsity= 0.2917081195367238\n",
+ "Iteration= 28, Error= 39.88481021958478, Sparsity= 0.30304322709965437\n",
+ "Iteration= 29, Error= 39.46017655579735, Sparsity= 0.31393365364173265\n",
+ "Iteration= 30, Error= 39.045180423634186, Sparsity= 0.3244424943927019\n",
+ "Iteration= 31, Error= 38.63734230209082, Sparsity= 0.33463266649942924\n",
+ "Iteration= 32, Error= 38.2353567279982, Sparsity= 0.3445588799038784\n",
+ "Iteration= 33, Error= 37.83879137246172, Sparsity= 0.3542638001458373\n",
+ "Iteration= 34, Error= 37.447831305193944, Sparsity= 0.36377693303145686\n",
+ "Iteration= 35, Error= 37.06311668895521, Sparsity= 0.3731151839314018\n",
+ "Iteration= 36, Error= 36.68562245131082, Sparsity= 0.382284475401137\n",
+ "Iteration= 37, Error= 36.31651690350004, Sparsity= 0.391282014581468\n",
+ "Iteration= 38, Error= 35.956990336658045, Sparsity= 0.4000988600600048\n",
+ "Iteration= 39, Error= 35.608096187501225, Sparsity= 0.4087224990089582\n",
+ "Iteration= 40, Error= 35.27064924177423, Sparsity= 0.4171392360796417\n",
+ "Iteration= 41, Error= 34.945191101749, Sparsity= 0.42533624657634894\n",
+ "Iteration= 42, Error= 34.63200439365455, Sparsity= 0.4333031522161829\n",
+ "Iteration= 43, Error= 34.33115185916647, Sparsity= 0.4410330230070618\n",
+ "Iteration= 44, Error= 34.042523537924055, Sparsity= 0.4485228160604494\n",
+ "Iteration= 45, Error= 33.76588143621769, Sparsity= 0.4557733280607129\n",
+ "Iteration= 46, Error= 33.500895059115045, Sparsity= 0.46278872533760207\n",
+ "Iteration= 47, Error= 33.247166130303604, Sparsity= 0.4695757561619939\n",
+ "Iteration= 48, Error= 33.00424537337435, Sparsity= 0.47614288644950803\n",
+ "Iteration= 49, Error= 32.771645106214734, Sparsity= 0.48249963363313997\n",
+ "Iteration= 50, Error= 32.548849521608, Sparsity= 0.4886561810215538\n",
+ "Iteration= 51, Error= 32.3353233140894, Sparsity= 0.49462312851105383\n",
+ "Iteration= 52, Error= 32.130519599386005, Sparsity= 0.5004112038582728\n",
+ "Iteration= 53, Error= 31.93388810100521, Sparsity= 0.5060308951694635\n",
+ "Iteration= 54, Error= 31.744883493027736, Sparsity= 0.5114921048792678\n",
+ "Iteration= 55, Error= 31.5629728794358, Sparsity= 0.5168039577791743\n",
+ "Iteration= 56, Error= 31.387641804218962, Sparsity= 0.5219748026256641\n",
+ "Iteration= 57, Error= 31.218399240096794, Sparsity= 0.5270123152430054\n",
+ "Iteration= 58, Error= 31.054782473810246, Sparsity= 0.5319235669711456\n",
+ "Iteration= 59, Error= 30.89636248535455, Sparsity= 0.5367149833775134\n",
+ "Iteration= 60, Error= 30.742750041851625, Sparsity= 0.5413921998973578\n",
+ "Iteration= 61, Error= 30.593602817071936, Sparsity= 0.5459598661023983\n",
+ "Iteration= 62, Error= 30.448633924406483, Sparsity= 0.5504214636017345\n",
+ "Iteration= 63, Error= 30.30762147899121, Sparsity= 0.5547792035865151\n",
+ "Iteration= 64, Error= 30.170417087098823, Sparsity= 0.5590340628658389\n",
+ "Iteration= 65, Error= 30.036949361923064, Sparsity= 0.5631859939837724\n",
+ "Iteration= 66, Error= 29.907218050997088, Sparsity= 0.5672343007061094\n",
+ "Iteration= 67, Error= 29.781276243194466, Sparsity= 0.5711781157790315\n",
+ "Iteration= 68, Error= 29.659202258393364, Sparsity= 0.575016878877408\n",
+ "Iteration= 69, Error= 29.541067316799353, Sparsity= 0.5787507110180239\n",
+ "Iteration= 70, Error= 29.42690729065563, Sparsity= 0.582380618558284\n",
+ "Iteration= 71, Error= 29.316705337551234, Sparsity= 0.5859085158710833\n",
+ "Iteration= 72, Error= 29.2103879256768, Sparsity= 0.5893371048336467\n",
+ "Iteration= 73, Error= 29.10783217924779, Sparsity= 0.5926696732632493\n",
+ "Iteration= 74, Error= 29.008879789370205, Sparsity= 0.5959098708828688\n",
+ "Iteration= 75, Error= 28.91335253250497, Sparsity= 0.5990615015887121\n",
+ "Iteration= 76, Error= 28.82106585591897, Sparsity= 0.6021283507902354\n",
+ "Iteration= 77, Error= 28.73183882198275, Sparsity= 0.6051140567238842\n",
+ "Iteration= 78, Error= 28.645500203996953, Sparsity= 0.6080220325179636\n",
+ "Iteration= 79, Error= 28.561891459453847, Sparsity= 0.6108554398356014\n",
+ "Iteration= 80, Error= 28.480867674324223, Sparsity= 0.6136172002981573\n",
+ "Iteration= 81, Error= 28.40229747327771, Sparsity= 0.6163100193491109\n",
+ "Iteration= 82, Error= 28.32606252339579, Sparsity= 0.618936402397795\n",
+ "Iteration= 83, Error= 28.252056868424845, Sparsity= 0.6214986607313254\n",
+ "Iteration= 84, Error= 28.18018609633163, Sparsity= 0.6239989180701502\n",
+ "Iteration= 85, Error= 28.110366304867085, Sparsity= 0.6264391285570522\n",
+ "Iteration= 86, Error= 28.04252289619229, Sparsity= 0.6288211080691711\n",
+ "Iteration= 87, Error= 27.97658927890635, Sparsity= 0.6311465724512759\n",
+ "Iteration= 88, Error= 27.912505548228832, Sparsity= 0.6334171736908201\n",
+ "Iteration= 89, Error= 27.85021720528072, Sparsity= 0.6356345274768735\n",
+ "Iteration= 90, Error= 27.78967399940086, Sparsity= 0.6378002297326986\n",
+ "Iteration= 91, Error= 27.730828990859678, Sparsity= 0.6399158629956518\n",
+ "Iteration= 92, Error= 27.67363787829577, Sparsity= 0.6419829951284888\n",
+ "Iteration= 93, Error= 27.618058538270713, Sparsity= 0.6440031731608319\n",
+ "Iteration= 94, Error= 27.564050667937153, Sparsity= 0.6459779147085775\n",
+ "Iteration= 95, Error= 27.511575444752378, Sparsity= 0.6479086988338384\n",
+ "Iteration= 96, Error= 27.460595178241288, Sparsity= 0.6497969576129564\n",
+ "Iteration= 97, Error= 27.41107297353486, Sparsity= 0.6516440691802431\n",
+ "Iteration= 98, Error= 27.362972438267196, Sparsity= 0.6534513526415779\n",
+ "Iteration= 99, Error= 27.3162574552199, Sparsity= 0.6552200649911114\n",
+ "Iteration= 100, Error= 27.27089202760068, Sparsity= 0.6569513999879084\n",
+ "Iteration= 101, Error= 27.226840190161795, Sparsity= 0.6586464888341965\n",
+ "Iteration= 102, Error= 27.184065970492682, Sparsity= 0.6603064024277967\n",
+ "Iteration= 103, Error= 27.14253338110649, Sparsity= 0.6619321549262709\n",
+ "Iteration= 104, Error= 27.102206424151188, Sparsity= 0.6635247083452671\n",
+ "Iteration= 105, Error= 27.0630490971891, Sparsity= 0.665084977901622\n",
+ "Iteration= 106, Error= 27.02502539966249, Sparsity= 0.6666138377899008\n",
+ "Iteration= 107, Error= 26.988099350530685, Sparsity= 0.6681121270508255\n",
+ "Iteration= 108, Error= 26.952235031599404, Sparsity= 0.6695806551714498\n",
+ "Iteration= 109, Error= 26.9173966658203, Sparsity= 0.6710202070771413\n",
+ "Iteration= 110, Error= 26.883548729026096, Sparsity= 0.6724315472495519\n",
+ "Iteration= 111, Error= 26.850656083652513, Sparsity= 0.6738154228238522\n",
+ "Iteration= 112, Error= 26.81868411858634, Sparsity= 0.6751725656535437\n",
+ "Iteration= 113, Error= 26.78759888077972, Sparsity= 0.6765036934488623\n",
+ "Iteration= 114, Error= 26.757367188889614, Sparsity= 0.6778095101726925\n",
+ "Iteration= 115, Error= 26.727956724029138, Sparsity= 0.6790907059102443\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Iteration= 116, Error= 26.699336096704513, Sparsity= 0.680347956422469\n",
+ "Iteration= 117, Error= 26.671474892353892, Sparsity= 0.6815819225610231\n",
+ "Iteration= 118, Error= 26.644343700465523, Sparsity= 0.6827932496778383\n",
+ "Iteration= 119, Error= 26.617914133322618, Sparsity= 0.6839825671166332\n",
+ "Iteration= 120, Error= 26.59215883969697, Sparsity= 0.6851504878358935\n",
+ "Iteration= 121, Error= 26.567051516846966, Sparsity= 0.6862976081882088\n",
+ "Iteration= 122, Error= 26.542566921891257, Sparsity= 0.6874245078704236\n",
+ "Iteration= 123, Error= 26.518680881724123, Sparsity= 0.6885317500596876\n",
+ "Iteration= 124, Error= 26.495370299711084, Sparsity= 0.6896198817555343\n",
+ "Iteration= 125, Error= 26.4726131578566, Sparsity= 0.6906894343491523\n",
+ "Iteration= 126, Error= 26.450388514701505, Sparsity= 0.6917409244301405\n",
+ "Iteration= 127, Error= 26.428676500705432, Sparsity= 0.6927748548132475\n",
+ "Iteration= 128, Error= 26.407458312817305, Sparsity= 0.6937917157220234\n",
+ "Iteration= 129, Error= 26.386716207487343, Sparsity= 0.6947919860071332\n",
+ "Iteration= 130, Error= 26.366433487023333, Sparsity= 0.6957761342150776\n",
+ "Iteration= 131, Error= 26.34659447006195, Sparsity= 0.6967446192777167\n",
+ "Iteration= 132, Error= 26.3271844360321, Sparsity= 0.6976978905922915\n",
+ "Iteration= 133, Error= 26.30818953799345, Sparsity= 0.6986363873342406\n",
+ "Iteration= 134, Error= 26.289596687759126, Sparsity= 0.6995605370026319\n",
+ "Iteration= 135, Error= 26.27139342847618, Sparsity= 0.7004707534129921\n",
+ "Iteration= 136, Error= 26.25356781796462, Sparsity= 0.7013674345506571\n",
+ "Iteration= 137, Error= 26.236108347087306, Sparsity= 0.7022509607840826\n",
+ "Iteration= 138, Error= 26.219003910003757, Sparsity= 0.7031216938502486\n",
+ "Iteration= 139, Error= 26.202243828324058, Sparsity= 0.7039799767853504\n",
+ "Iteration= 140, Error= 26.18581791036912, Sparsity= 0.7048261346907688\n",
+ "Iteration= 141, Error= 26.16971650371721, Sparsity= 0.7056604760319971\n",
+ "Iteration= 142, Error= 26.1539304859748, Sparsity= 0.7064832941483299\n",
+ "Iteration= 143, Error= 26.13845115576091, Sparsity= 0.7072948687787507\n",
+ "Iteration= 144, Error= 26.123270043021535, Sparsity= 0.7080954675673853\n",
+ "Iteration= 145, Error= 26.108378724421392, Sparsity= 0.708885347576041\n",
+ "Iteration= 146, Error= 26.09376874287716, Sparsity= 0.7096647567743429\n",
+ "Iteration= 147, Error= 26.079431663989272, Sparsity= 0.7104339353886253\n",
+ "Iteration= 148, Error= 26.065359212908778, Sparsity= 0.7111931169741613\n",
+ "Iteration= 149, Error= 26.051543402504485, Sparsity= 0.7119425291471808\n",
+ "Iteration= 150, Error= 26.03797660047733, Sparsity= 0.7126823940073708\n",
+ "Iteration= 151, Error= 26.02465153939462, Sparsity= 0.7134129283341164\n",
+ "Iteration= 152, Error= 26.0115613039706, Sparsity= 0.7141343436380372\n",
+ "Iteration= 153, Error= 25.998699327401027, Sparsity= 0.7148468461186147\n",
+ "Iteration= 154, Error= 25.98605941000121, Sparsity= 0.7155506365482678\n",
+ "Iteration= 155, Error= 25.973635755066976, Sparsity= 0.7162459100893162\n",
+ "Iteration= 156, Error= 25.96142300479788, Sparsity= 0.7169328560557744\n",
+ "Iteration= 157, Error= 25.949416253541855, Sparsity= 0.717611657651367\n",
+ "Iteration= 158, Error= 25.937611018627198, Sparsity= 0.7182824917364846\n",
+ "Iteration= 159, Error= 25.926003164685046, Sparsity= 0.7189455286833627\n",
+ "Iteration= 160, Error= 25.914588802402978, Sparsity= 0.719600932358635\n",
+ "Iteration= 161, Error= 25.903364200415307, Sparsity= 0.7202488602315513\n",
+ "Iteration= 162, Error= 25.89232574168924, Sparsity= 0.7208894635694236\n",
+ "Iteration= 163, Error= 25.88146992650592, Sparsity= 0.7215228876727909\n",
+ "Iteration= 164, Error= 25.870793397485485, Sparsity= 0.7221492721212921\n",
+ "Iteration= 165, Error= 25.860292957061944, Sparsity= 0.7227687510264819\n",
+ "Iteration= 166, Error= 25.849965560953674, Sparsity= 0.7233814533008397\n",
+ "Iteration= 167, Error= 25.83980828789062, Sparsity= 0.7239875029503431\n",
+ "Iteration= 168, Error= 25.829818296598127, Sparsity= 0.7245870193898466\n",
+ "Iteration= 169, Error= 25.819992784281155, Sparsity= 0.7251801177744416\n",
+ "Iteration= 170, Error= 25.810328958638568, Sparsity= 0.7257669093378328\n",
+ "Iteration= 171, Error= 25.80082403019574, Sparsity= 0.7263475017271458\n",
+ "Iteration= 172, Error= 25.791475225574278, Sparsity= 0.7269219993186676\n",
+ "Iteration= 173, Error= 25.78227981681608, Sparsity= 0.7274905034909709\n",
+ "Iteration= 174, Error= 25.773235157507447, Sparsity= 0.7280531128266469\n",
+ "Iteration= 175, Error= 25.76433871291807, Sparsity= 0.7286099232216929\n",
+ "Iteration= 176, Error= 25.755588069608677, Sparsity= 0.7291610279107248\n",
+ "Iteration= 177, Error= 25.746980914779886, Sparsity= 0.7297065174609242\n",
+ "Iteration= 178, Error= 25.73851499304874, Sparsity= 0.730246479818226\n",
+ "Iteration= 179, Error= 25.730188072281802, Sparsity= 0.7307810004671583\n",
+ "Iteration= 180, Error= 25.72199795496929, Sparsity= 0.7313101626892523\n",
+ "Iteration= 181, Error= 25.71394253727362, Sparsity= 0.7318340478328352\n",
+ "Iteration= 182, Error= 25.70601986383954, Sparsity= 0.7323527355093421\n",
+ "Iteration= 183, Error= 25.698228104001135, Sparsity= 0.7328663037135594\n",
+ "Iteration= 184, Error= 25.6905654250701, Sparsity= 0.7333748289583353\n",
+ "Iteration= 185, Error= 25.683029842769027, Sparsity= 0.7338783865385445\n",
+ "Iteration= 186, Error= 25.67561918432928, Sparsity= 0.7343770509758826\n",
+ "Iteration= 187, Error= 25.668331211818607, Sparsity= 0.7348708966043559\n",
+ "Iteration= 188, Error= 25.66116379338199, Sparsity= 0.7353599982146254\n",
+ "Iteration= 189, Error= 25.654114960793255, Sparsity= 0.7358444317036971\n",
+ "Error= 41.1846154973675, Sparsity= 0.8760193232291686\n"
+ ]
+ }
+ ],
+ "source": [
+ "import cSNMF\n",
+ "\n",
+ "# col = D[:, 0].reshape(D.shape[0], 1)\n",
+ "W2, H2, results = cSNMF.factorize(D,\n",
+ " init_W = None,\n",
+ " rank = config.RANK,\n",
+ " beta = None,\n",
+ " threshold = 0.5,\n",
+ " max_iter = 600,\n",
+ " seed_W = None,\n",
+ " seed_H = None,\n",
+ " log = logger,\n",
+ " debug = True,\n",
+ " axing = True,\n",
+ " update_W = True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([1.93448512e+01, 3.01169528e+01, 7.58590743e+00, 1.45644580e+01,\n",
+ " 1.62297844e+01, 5.79756549e+00, 2.42629628e+00, 2.09096457e+00,\n",
+ " 4.44048056e+00, 8.51515333e+00, 1.10057189e+01, 1.31904515e+01,\n",
+ " 2.43889854e+01, 2.34233881e+01, 2.58108583e+01, 2.01992512e+01,\n",
+ " 1.90771020e+01, 2.93252161e+01, 2.57134638e+01, 3.15742349e+01,\n",
+ " 2.18874695e+01, 2.66631428e+01, 2.46733495e+01, 2.79090355e+01,\n",
+ " 1.46045248e+01, 7.89497084e+00, 9.45599082e+00, 4.64092305e+00,\n",
+ " 3.03708836e+00, 1.17340891e+00, 2.00989097e+00, 1.83905619e+00,\n",
+ " 4.15279184e+00, 9.19690783e+00, 1.36688262e+01, 2.13882780e+01,\n",
+ " 2.97986468e+01, 1.84551256e+01, 2.65042600e+01, 2.77011491e+01,\n",
+ " 3.15916373e+01, 3.18799039e+01, 3.07775585e+01, 2.46079735e+01,\n",
+ " 2.21266023e+01, 1.94138796e+01, 1.74587436e+01, 7.02673204e+00,\n",
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+ " 6.20751898e+00, 4.97977611e+00, 7.68458859e+00, 7.81767582e+00,\n",
+ " 9.50124218e+00, 3.20711894e+01, 2.88459159e+01, 3.68987453e+01,\n",
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+ " 5.54575893e+01, 4.97993175e+01, 6.35555128e+01, 6.96521021e+01,\n",
+ " 6.69364353e+01, 5.97342916e+01, 9.89943067e+01, 9.05610547e+01,\n",
+ " 7.66132250e+01, 5.04768021e+01, 5.14603960e+01, 2.89969558e+01,\n",
+ " 9.91421251e+00, 1.15089425e+00, 4.72313604e+00, 5.63465168e+00,\n",
+ " 1.09094286e+01, 2.75831762e+01, 3.42684634e+01, 5.22616525e+01,\n",
+ " 7.28761681e+01, 7.61711097e+01, 7.34503657e+01, 7.97777614e+01,\n",
+ " 5.95804194e+01, 6.36748586e+01, 8.55276703e+01, 9.68360526e+01,\n",
+ " 8.96190835e+01, 7.27281021e+01, 6.42835583e+01, 5.69783414e+01])"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.set_printoptions(threshold=np.nan)\n",
+ "W@H[:,0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "KeyboardInterrupt",
+ "evalue": "",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\IPython\\lib\\pretty.py\u001b[0m in \u001b[0;36mpretty\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 394\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mmeth\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcycle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 395\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0m_default_pprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcycle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 396\u001b[0m \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\IPython\\lib\\pretty.py\u001b[0m in \u001b[0;36m_default_pprint\u001b[1;34m(obj, p, cycle)\u001b[0m\n\u001b[0;32m 509\u001b[0m \u001b[1;31m# A user-provided repr. Find newlines and replace them with p.break_()\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 510\u001b[1;33m \u001b[0m_repr_pprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcycle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 511\u001b[0m \u001b[1;32mreturn\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\IPython\\lib\\pretty.py\u001b[0m in \u001b[0;36m_repr_pprint\u001b[1;34m(obj, p, cycle)\u001b[0m\n\u001b[0;32m 700\u001b[0m \u001b[1;31m# Find newlines and replace them with p.break_()\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 701\u001b[1;33m \u001b[0moutput\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrepr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 702\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0midx\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0moutput_line\u001b[0m \u001b[1;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplitlines\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\numpy\\core\\arrayprint.py\u001b[0m in \u001b[0;36marray_repr\u001b[1;34m(arr, max_line_width, precision, suppress_small)\u001b[0m\n\u001b[0;32m 1333\u001b[0m lst = array2string(arr, max_line_width, precision, suppress_small,\n\u001b[1;32m-> 1334\u001b[1;33m ', ', prefix, suffix=suffix)\n\u001b[0m\u001b[0;32m 1335\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m# show zero-length shape unless it is (0,)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\numpy\\core\\arrayprint.py\u001b[0m in \u001b[0;36marray2string\u001b[1;34m(a, max_line_width, precision, suppress_small, separator, prefix, style, formatter, threshold, edgeitems, sign, floatmode, suffix, **kwarg)\u001b[0m\n\u001b[0;32m 621\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 622\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0m_array2string\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mseparator\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mprefix\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 623\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\numpy\\core\\arrayprint.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 421\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 422\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 423\u001b[0m \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\numpy\\core\\arrayprint.py\u001b[0m in \u001b[0;36m_array2string\u001b[1;34m(a, options, separator, prefix)\u001b[0m\n\u001b[0;32m 443\u001b[0m \u001b[1;31m# find the right formatting function for the array\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 444\u001b[1;33m \u001b[0mformat_function\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_get_format_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 445\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\numpy\\core\\arrayprint.py\u001b[0m in \u001b[0;36m_get_format_function\u001b[1;34m(data, **options)\u001b[0m\n\u001b[0;32m 383\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 384\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mformatdict\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'float'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 385\u001b[0m \u001b[1;32melif\u001b[0m \u001b[0missubclass\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdtypeobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_nt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcomplexfloating\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\numpy\\core\\arrayprint.py\u001b[0m in \u001b[0;36m<lambda>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 319\u001b[0m \u001b[1;34m'float'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;32mlambda\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 320\u001b[1;33m \u001b[0mFloatingFormat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mprec\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfmode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msupp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msign\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlegacy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlegacy\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 321\u001b[0m \u001b[1;34m'longfloat'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;32mlambda\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\numpy\\core\\arrayprint.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, data, precision, floatmode, suppress_small, sign, **kwarg)\u001b[0m\n\u001b[0;32m 777\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 778\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfillFormat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 779\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\numpy\\core\\arrayprint.py\u001b[0m in \u001b[0;36mfillFormat\u001b[1;34m(self, data)\u001b[0m\n\u001b[0;32m 807\u001b[0m for x in finite_vals)\n\u001b[1;32m--> 808\u001b[1;33m \u001b[0mfrac_strs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexp_strs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpartition\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'e'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0ms\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mstrs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 809\u001b[0m \u001b[0mint_part\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfrac_part\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'.'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0ms\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfrac_strs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\numpy\\core\\arrayprint.py\u001b[0m in \u001b[0;36m<genexpr>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m 807\u001b[0m for x in finite_vals)\n\u001b[1;32m--> 808\u001b[1;33m \u001b[0mfrac_strs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexp_strs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpartition\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'e'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0ms\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mstrs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 809\u001b[0m \u001b[0mint_part\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfrac_part\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'.'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0ms\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfrac_strs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;31mKeyboardInterrupt\u001b[0m: ",
+ "\nDuring handling of the above exception, another exception occurred:\n",
+ "\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
+ "\u001b[1;32m<ipython-input-15-54195b2c0f31>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mcol\u001b[0m \u001b[1;33m-\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mW\u001b[0m\u001b[1;33m@\u001b[0m\u001b[0mH1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcol\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mflatten\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\IPython\\core\\displayhook.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, result)\u001b[0m\n\u001b[0;32m 255\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart_displayhook\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 256\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite_output_prompt\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 257\u001b[1;33m \u001b[0mformat_dict\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmd_dict\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcompute_format_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 258\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate_user_ns\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 259\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfill_exec_result\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\IPython\\core\\displayhook.py\u001b[0m in \u001b[0;36mcompute_format_data\u001b[1;34m(self, result)\u001b[0m\n\u001b[0;32m 149\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 150\u001b[0m \"\"\"\n\u001b[1;32m--> 151\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshell\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdisplay_formatter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 152\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 153\u001b[0m \u001b[1;31m# This can be set to True by the write_output_prompt method in a subclass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\IPython\\core\\formatters.py\u001b[0m in \u001b[0;36mformat\u001b[1;34m(self, obj, include, exclude)\u001b[0m\n\u001b[0;32m 178\u001b[0m \u001b[0mmd\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 179\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 180\u001b[1;33m \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mformatter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 181\u001b[0m \u001b[1;32mexcept\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 182\u001b[0m \u001b[1;31m# FIXME: log the exception\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32m<decorator-gen-10>\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, obj)\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\IPython\\core\\formatters.py\u001b[0m in \u001b[0;36mcatch_format_error\u001b[1;34m(method, self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 222\u001b[0m \u001b[1;34m\"\"\"show traceback on failed format call\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 223\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 224\u001b[1;33m \u001b[0mr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 225\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mNotImplementedError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 226\u001b[0m \u001b[1;31m# don't warn on NotImplementedErrors\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\IPython\\core\\formatters.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 700\u001b[0m \u001b[0mtype_pprinters\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtype_printers\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 701\u001b[0m deferred_pprinters=self.deferred_printers)\n\u001b[1;32m--> 702\u001b[1;33m \u001b[0mprinter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpretty\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 703\u001b[0m \u001b[0mprinter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mflush\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 704\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mstream\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetvalue\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32mC:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\IPython\\lib\\pretty.py\u001b[0m in \u001b[0;36mpretty\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 395\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0m_default_pprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcycle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 396\u001b[0m \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 397\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mend_group\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 398\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 399\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
+ ]
+ }
+ ],
+ "source": [
+ "col - (W@H1).reshape(col.shape).flatten()"
+ ]
+ }
+ ],
+ "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": "3.6.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}