In matlab, say I have a vector:
a = [0.001818443 0.002518386 0.003220336 0.005121008 0.005896566 0.006067186 0.006398329 0.006398407 0.008139209 0.008179847 0.009156658 0.010554859 0.010897468 0.011446512 0.011646556 0.013025077 0.013744086 0.014617856 0.014830682 0.014941674 0.015810817 0.015953685 0.016022438 0.01662184 0.017497373 0.018051816 0.018084908 0.019634522 0.02055418 0.021050675 0.021573997 0.022819828 0.024124407 0.02499767 0.025745151 0.026366919 0.029380223 0.029534435 0.029988118 0.033517171 0.037612906 0.038975473 0.045889922 0.04598939 0.045995714 0.046398796 0.047502087 0.048214192 0.050098857 0.053184072 0.055892719 0.057670042 0.059855042 0.061763503 0.065288778 0.066057267 0.066842804 0.067799739 0.069549949 0.070151584 0.071572852 0.084351815 0.084676596 0.088092878 0.088329724 0.089958848 0.09000399 0.092272165 0.092561834 0.092888091 0.093193395 0.095380669 0.100645564 0.101506295 0.104656067 0.105057051 0.10527394 0.107024689 0.107608649 0.108699789 0.109433298 0.111805635 0.111990726 0.112119163 0.113570537 0.115032624 0.123301615 0.125012672 0.127758465 0.131636854 0.132397883 0.132910662 0.136185494 0.137039002 0.138037293 0.139764132 0.140727482 0.141044291 0.141523184 0.142202565 0.142563209 0.145192227 0.146881752 0.149407941 0.152043489 0.153144103 0.153181689 0.153795372 0.15548845 0.158134807 0.159905274 0.160042269 0.160098768 0.160483614 0.164710118 0.166850893 0.167909098 0.167986172 0.169019205 0.173698541 0.174264483 0.17696023 0.177973442 0.182348008 0.192484859 0.193880575 0.197216088 0.197939827 0.198109045 0.199497862 0.200821988 0.203783239 0.20515055 0.206573438 0.207185798 0.209268239 0.209386896 0.210951877 0.212023024 0.213363487 0.214391326 0.221532866 0.223109522 0.225343507 0.22641709 0.228343987 0.229206318 0.231114414 0.234752015 0.237026193 0.237716285 0.240721044 0.242380638 0.245407553 0.246434245 0.247559843 0.247849238 0.253027915 0.256495379 0.257901113 0.258536851 0.259306669 0.259722973 0.269672307 0.269866791 0.277255751 0.282296038 0.283236904 0.286946602 0.290243971 0.291043929 0.29129401 0.295039384 0.306007647 0.318012708 0.31816788 0.323432941 0.327635294 0.331093206 0.332249017 0.336175038 0.338095934 0.34029032 0.34317957 0.343788501 0.344121892 0.354931564 0.35667793 0.363077884 0.366887155 0.367370204 0.368269666 0.368423655 0.372253797 0.373533628 0.376022623 0.380837432 0.38261496 0.38391646 0.387548982 0.390389207 0.391454753 0.392089937 0.393426643 0.399546308 0.400245613 0.410202767 0.410776868 0.411723243 0.413456921 0.415884043 0.417789874 0.420313779 0.421429254 0.422511926 0.425439714 0.432455519 0.436032696 0.437367296 0.440152475 0.451378258 0.451755234 0.452195559 0.461256878 0.462486697 0.466794805 0.468274083 0.470176312 0.471656017 0.476690087 0.476869314 0.479601939 0.480684241 0.48433634 0.48590973 0.487749692 0.488207469 0.492988875 0.494796745 0.498156249 0.4985104 0.504612947 0.504967424 0.50679421 0.507507695 0.508506011 0.509330529 0.510055669 0.513319728 0.52891378 0.534509478 0.539047817 0.53915951 0.541296687 0.545072863 0.552167571 0.554581857 0.561492014 0.563884635 0.56426438 0.565241463 0.568908009 0.571068798 0.571510656 0.574766859 0.574855866 0.578654534 0.580464471 0.580887919 0.586141679 0.586966123 0.588709274 0.589037758 0.590368048 0.591671348 0.595978448 0.596819829 0.600253407 0.606098247 0.606571956 0.607739275 0.619011439 0.621019538 0.621584422 0.621911881 0.625158613 0.626027273 0.630605849 0.648745354 0.651696835 0.652124313 0.653617078 0.658464598 0.658753146 0.659914726 0.660454081 0.663254931 0.666213877 0.66710949 0.671102828 0.672232077 0.677146974 0.679136682 0.684108254 0.685413256 0.695469558 0.699891217 0.70086933 0.702538999 0.703841471 0.706858722 0.708526759 0.719914701 0.720515776 0.722374479 0.729898476 0.73207238 0.735491621 0.747979179 0.748009317 0.756113996 0.765310468 0.767536693 0.773459493 0.776692483 0.78337608 0.785347933 0.793150735 0.802590758 0.803742726 0.803939618 0.804124158 0.820932029 0.822075589 0.822879052 0.823691124 0.828333937 0.828903924 0.829498182 0.831744237 0.839063743 0.841337078 0.84171847 0.859784354 0.866309271 0.866320299 0.866971295 0.867950201 0.871969488 0.874637485 0.880743292 0.88827141 0.893950376 0.895879931 0.896267286 0.896848582 0.898141369 0.901481362 0.910473103 0.911477969 0.913705886 0.926522732 0.930260635 0.930701078 0.93463515 0.934808147 0.935922692 0.936764529 0.93959948 0.939793801 0.944385802 0.944693766 0.947020268 0.947097561 0.950125145 0.952711274 0.95419146 0.956369148 0.9570486 0.958475028 0.969842914 0.981551219 0.989160935 0.992674135 0.995621611 1.004946727 1.012283438 1.015692666 1.024106096 1.030556733 1.032833092 1.03935138 1.03983552 1.047370018 1.063408518 1.063839459 1.065426157 1.068160918 1.069540521 1.077658708 1.087582646 1.087760841 1.094524538 1.098800356 1.1001774 1.107885842 1.108951101 1.111112066 1.113553249 1.118698485 1.118853872 1.124506817 1.125842913 1.140696534 1.145563833 1.163177388 1.172282341 1.172495225 1.175475612 1.176864362 1.17990075 1.182195585 1.189691417 1.19404695 1.201722268 1.207506808 1.207712757 1.217276704 1.226244517 1.231233705 1.235338344 1.235488468 1.237856505 1.246471414 1.248198622 1.24847215 1.249213122 1.253941679 1.255492087 1.261797214 1.272565441 1.275217172 1.279047194 1.2941275 1.296036211 1.303184537 1.303538428 1.304022026 1.306154543 1.313038716 1.325574114 1.325811852 1.329512083 1.335354282 1.336243495 1.349582224 1.349879286 1.349900576 1.351984631 1.352752927 1.380875102 1.381652802 1.385006548 1.385551407 1.399529901 1.400418216 1.400665522 1.402213831 1.407079557 1.407902968 1.426432367 1.427988618 1.430494495 1.436726215 1.455773986 1.457812821 1.457839075 1.464415454 1.465676132 1.471725239 1.478228056 1.493616649 1.505911081 1.510317752 1.517723479 1.519844042 1.520079555 1.52266623 1.528263582 1.528956908 1.539259874 1.54540469 1.552334282 1.559284266 1.560271081 1.560397723 1.58015835 1.584258957 1.586824283 1.5901615 1.601497093 1.616542626 1.623922568 1.655459388 1.656518418 1.658450231 1.668041767 1.677051536 1.683863037 1.685259883 1.694649161 1.698606755 1.703678803 1.713706728 1.717011705 1.723855901 1.724709626 1.730421966 1.74844195 1.749035987 1.756795943 1.763444653 1.775098962 1.779555761 1.818373597 1.827387112 1.843804423 1.84962867 1.86445448 1.867109055 1.88714409 1.889979731 1.891826361 1.892089882 1.899382375 1.902349674 1.905658074 1.914800201 1.922334951 1.927667035 1.948721828 1.954657495 1.965798927 1.966959101 1.979507708 1.980399089 2.002907363 2.005971219 2.017485761 2.025826577 2.031746032 2.038502827 2.044743806 2.054344832 2.069686195 2.097264843 2.099601236 2.110771315 2.112519282 2.119955879 2.121704608 2.127885945 2.132366059 2.138348477 2.14114747 2.141311108 2.163556408 2.164123085 2.172858142 2.199500097 2.205509788 2.219358975 2.238957728 2.249818992 2.2594448 2.269944498 2.2706867 2.280357357 2.282960593 2.295150671 2.318687227 2.321618718 2.334867032 2.335012279 2.344689038 2.362974205 2.390145632 2.39280766 2.39488483 2.396397248 2.396786702 2.41576171 2.419119918 2.441157923 2.444805269 2.464446901 2.464904486 2.467566697 2.472567888 2.478733367 2.478770886 2.487350756 2.49321811 2.495309064 2.503098264 2.508249701 2.515845321 2.536509644 2.550922635 2.551167925 2.554758102 2.560023347 2.570208707 2.586874641 2.591255858 2.621816341 2.628169732 2.631001714 2.632092126 2.633379668 2.642666194 2.655607509 2.682555117 2.688667321 2.692033844 2.699468672 2.705095951 2.708973091 2.737148617 2.749372431 2.750397407 2.756591892 2.792700138 2.796508678 2.81091224 2.81340476 2.818119651 2.819068516 2.840763732 2.855245731 2.867534546 2.882410894 2.906305385 2.921292046 2.921449315 2.923724053 2.936059643 2.941498451 2.942915417 2.94633052 2.988440975 3.000337153 3.01308498 3.020820735 3.035323578 3.035939809 3.042578546 3.052730332 3.054474708 3.057013298 3.057530131 3.067704681 3.068800023 3.076034658 3.089870019 3.099800517 3.101610913 3.119631497 3.124341072 3.146856917 3.154655951 3.161613073 3.166574531 3.174242956 3.230342089 3.255377691 3.28960399 3.295293223 3.32692446 3.363077516 3.364077103 3.381238529 3.381887576 3.384181674 3.386057784 3.401224741 3.435435804 3.45589793 3.466903497 3.474234492 3.480509064 3.483189477 3.513852304 3.516762563 3.560173959 3.563670036 3.584881386 3.600866595 3.612209011 3.612874405 3.681816583 3.685079285 3.711346042 3.731563626 3.758770274 3.767406987 3.793935874 3.808871162 3.810159575 3.829625617 3.834675737 3.845991621 3.867773548 3.877642315 3.893104221 3.95596396 3.962658928 3.965413469 3.97259321 3.990644309 4.023556719 4.02507181 4.084002607 4.084578556 4.098037962 4.153140723 4.171589196 4.172912226 4.173220429 4.174507202 4.183151827 4.185959555 4.208131209 4.220649959 4.222855241 4.224314464 4.227985127 4.231821774 4.241488572 4.259388079 4.263468946 4.282045733 4.288305453 4.304823313 4.310640075 4.331544589 4.338609003 4.344069461 4.363020386 4.365779429 4.434026574 4.443658027 4.445552171 4.458995767 4.461726934 4.510391248 4.532732835 4.542138659 4.568639576 4.570014035 4.573206687 4.575751995 4.589402326 4.605047841 4.622323071 4.636166135 4.673524319 4.681138622 4.709371139 4.726125431 4.735985256 4.748036113 4.754775561 4.7898461 4.817652595 4.819981496 4.852599072 4.861427993 4.873198393 4.916237331 4.944985527 4.983621954 4.990559388 5.011228086 5.02263706 5.033602557 5.04242782 5.07142307 5.077103479 5.084454227 5.107782036 5.108177848 5.139172114 5.14602394 5.169859202 5.19055459 5.201668423 5.231342813 5.232983951 5.258868191 5.311131019 5.31147458 5.319985913 5.331571645 5.334387459 5.374502171 5.383714419 5.389127887 5.398610789 5.413844942 5.430625633 5.454193653 5.461147117 5.551461175 5.55504706 5.572079631 5.575226254 5.606465418 5.609777635 5.636819706 5.691040865 5.711001366 5.797257382 5.832854236 5.872064428 5.885662913 5.911236598 5.926000643 5.929960434 5.970604957 6.030512704 6.072797244 6.084662323 6.089095146 6.09767178 6.129215378 6.130779201 6.140639601 6.185673432 6.196016262 6.214613781 6.238313568 6.23967845 6.262093588 6.287798627 6.294757385 6.294860108 6.306692101 6.324505655 6.33114857 6.346750162 6.35080133 6.377059989 6.409799872 6.441791892 6.456490203 6.470616951 6.490994893 6.495216304 6.504149783 6.51133435 6.529616293 6.554242015 6.563788821 6.574289471 6.675696283 6.706237255 6.815277245 6.848451976 6.861974205 6.870363281 6.923362317 6.944020698 6.953295743 6.975414311 6.990631801 6.99181595 7.01527874 7.049029831 7.05414657 7.061968486 7.067915256 7.083725481 7.102351907 7.178389796 7.188927953 7.261522761 7.329386611 7.337841565 7.366825602 7.415734232 7.422489262 7.449612784 7.507455626 7.513671627 7.577525944 7.607591991 7.624664035 7.644811627 7.654470544 7.659726779 7.685903748 7.698781716 7.755233245 7.75726382 7.787416073 7.791738149 7.823246891 7.848729438 7.88055532 7.916344428 7.933637101 8.052955848 8.061876592 8.093245158 8.135817543 8.229182156 8.231153497 8.292577565 8.293196389 8.310932629 8.359817339 8.382278849 8.486130879 8.497274212 8.513191393 8.520059806 8.531728685 8.551517339 8.63099511 8.731577387 8.773074614 8.785621099 8.797526496 8.801953626 8.867708805 8.875775979 8.890890846 8.92786783 8.930072044 8.948634182 8.95947549 8.993463349 9.021759389 9.065522174 9.066607499 9.18597126 9.211974214 9.278943217 9.285298969 9.292735164 9.297881382 9.330560213 9.346856284 9.362442017 9.463406307 9.514100703 9.541914729 9.547789765 9.594764117 9.595234072 9.648102154 9.735946803 9.821788718 9.823759483 9.829945041 9.848021775 9.872404584 9.937685997 9.959654081 9.976479435 10.00791486 10.05620645 10.12287679 10.12499188 10.17909741 10.18975744 10.20577633 10.2433325 10.27136529 10.29255376 10.34823888 10.39016358 10.41304212 10.47108998 10.63086866 10.68955759 10.71339859 10.74459232 10.84826166 10.85718965 10.97740794 10.9949358 11.09449533 11.15480336 11.36431605 11.38700787 11.56534977 11.57884273 11.68961891 11.72718832 11.75086244 11.7878205 11.79060213 11.80027204 11.93916165 11.97550108 12.01606679 12.01988832 12.06850911 12.12522649 12.13468457 12.15637778 12.28496449 12.3241934 12.3567588 12.41535966 12.42641234 12.52211911 12.5495154 12.63792312 12.64636968 12.7161962 12.80776972 12.9823528 13.00946217 13.02536536 13.03684527 13.03839246 13.10679708 13.1898096 13.21333112 13.29003554 13.62959195 13.64877815 13.66468181 13.69215619 13.72924638 13.75728252 13.7675569 13.7781745 13.87187016 13.96994881 13.97634277 14.41400461 14.42070179 14.58428262 14.63292194 14.64057473 14.67792634 14.90358289 14.98742641 15.03138384 15.04855809 15.22142024 15.3402956 15.41190777 15.43961804 15.47839991 15.4911976 15.6170645 15.68655453 15.71274657 15.77939183 15.8035472 15.84056131 15.87909318 16.02980161 16.27711189 16.35797931 16.3583065 16.38899328 16.46642327 16.55407558 16.63715839 16.71513487 16.75128795 16.75550167 16.76896911 16.82665579 17.05255205 17.13938188 17.16063562 17.41296051 17.47135839 17.79953459 17.91682862 17.96619569 18.04741571 18.28219072 18.29825624 18.48877239 18.56389121 18.67257919 18.72659176 18.88700095 19.11471922 19.26338257 19.38571335 19.43066237 19.64007118 19.68477554 19.7217025 19.72342152 19.80809684 20.08500157 20.2281949 20.23408746 20.26717402 20.36890317 20.40159183 20.44363581 20.74424096 20.84529545 20.84720985 21.14482651 21.46914233 21.6470655 21.69253532 21.70090504 21.70602816 21.72131465 21.95895814 22.07347892 22.21577931 22.2849362 22.34874269 22.45750917 22.65377765 22.89616117 22.89635362 23.05070609 23.25564534 23.25854648 23.28086666 23.32730012 23.62007017 23.66984343 23.73242553 23.92740621 24.00710248 24.0830936 24.21839848 24.22970524 24.66308578 24.68442369 24.91228705 24.91527908 24.98555417 25.06629978 25.16017433 25.21857915 25.35128007 25.62813255 25.75263393 25.81792471 26.08284422 26.40101296 26.41750062 26.43655566 26.51821946 26.53432084 26.80518789 26.9407059 27.16758256 27.37817782 27.45974753 27.56781368 27.57669769 27.58689416 27.67386353 27.97201817 28.01228268 28.21530739 28.21651995 28.38803945 28.39096406 28.54988691 28.65557034 28.94937953 29.26877666 29.4765128 29.55383246 29.60462513 29.78065403 29.91792006 29.97044766 30.17358948 30.30735398 30.31935447 30.35064917 30.43326751 30.44565905 30.76413655 30.79665738 30.97695592 31.31780255 31.37471449 31.48237066 31.82262949 31.89693573 32.41723524 32.55331076 32.67155862 32.71822895 32.77151628 32.92258489 33.15746872 33.57903841 33.73093896 33.98002961 34.17219525 34.65446244 34.90279608 35.45626237 35.5241996 35.70128305 35.91639727 36.28963251 36.6179128 36.78614422 36.82855 36.88248154 37.14681563 37.3858884 37.5584267 37.78273088 37.95433285 38.0141844 38.20579882 38.61139354 38.71197557 38.81971052 38.89243288 39.27586824 39.63179926 39.69638447 39.79397234 39.8909006 39.89643666 40.14741915 40.19321582 40.49790551 40.52193466 40.81903561 41.44493735 41.64104201 41.81487882 42.11722559 42.53734269 42.95017037 43.22917039 43.30541042 43.39627629 43.40861238 43.48180606 43.85063727 44.2266316 44.36612852 44.51972943 44.94693119 45.34841364 45.62810404 45.77405118 45.88222365 45.89073235 45.9119187 46.01771085 46.07127283 46.66639614 47.05895083 47.43992499 47.81663312 47.82761532 47.86883046 48.2014739 48.54603032 48.63044372 48.70010921 48.7910734 48.86808673 49.15782972 49.40652428 49.42372063 50.14221114 50.27655324 50.43580963 50.63471687 51.68464104 53.06125543 53.30141397 53.32807367 53.87642112 54.12031574 54.9002525 54.95469438 55.90919979 56.15597807 56.57558623 56.86188239 57.00016647 57.23543285 58.29812557 59.19059651 59.35832334 59.96093498 60.38809964 60.91651668 60.93820445 62.05446948 62.88614528 64.06701329 64.31584913 64.97603869 65.36011188 65.46090908 65.91746278 66.01861276 66.10054487 66.11981109 66.89842836 67.64679472 68.73083861 69.09862961 69.84462461 70.4403659 70.67025218 70.85349131 71.08545333 71.26070124 72.52012446 72.71293451 72.77612011 72.93786536 73.6271521 74.30867045 74.63206204 74.73578701 75.6251108 75.78932026 76.05126953 76.46070144 76.49657027 77.73048678 78.97516162 79.28223044 79.68921943 81.27161479 81.50809168 81.66888119 82.5865971 83.08810921 83.50421593 84.40827757 86.26260607 86.87435262 87.27078585 87.5994372 87.64750239 88.12698297 88.81877472 89.31621846 89.45445382 90.43136513 90.49132345 90.53365314 90.71531255 92.39073166 92.53686428 93.28025667 93.73380501 94.62475292 94.99247679 95.29272327 95.31878839 95.63409563 96.46097353 97.92518178 98.40146494 100.0649063 102.6639004 102.8976923 103.5657057 103.8999049 104.9240993 105.4414008 107.7505096 108.1026438 109.270818 111.2510214 113.5101647 113.8946232 113.9781542 115.3161036 115.9817177 116.5624953 117.2820183 118.0944469 118.953348 119.6646578 120.0059882 120.3735732 120.5806064 122.3075783 123.2275944 123.6494634 123.9340035 125.8758385 125.9303952 126.6133989 127.5382831 128.4079674 128.5269655 129.0113829 129.5429383 135.4811223 136.1812859 136.6736278 137.0891762 138.7559387 139.2772697 139.3840935 139.789502 139.9916157 140.3898549 141.7290604 141.9185029 142.5719652 142.5751902 143.8109603 144.1959902 144.4704693 147.8294179 148.1587086 148.7231367 153.9398283 155.4449585 155.6160379 158.0906255 158.0993521 159.0389249 161.743865 162.8224182 164.1843306 165.1361921 168.047419 168.1347924 168.4336237 172.3179544 172.9612555 173.8019683 175.065944 175.6201286 178.2311487 181.905015 183.3521152 183.651063 189.4327919 190.3673356 190.8849041 191.0022347 192.7700608 192.8114358 194.2930955 196.1248388 196.2128253 197.9181938 198.3261076 199.1326284 199.7267043 200.0776785 200.0779721 201.942553 202.9503529 203.0970175 204.0950601 204.9311342 205.6896386 205.7617685 206.0285753 208.2302891 211.5614611 211.8798052 213.1198424 214.5731541 216.6101129 219.9069635 227.5796272 230.2397201 230.4063692 231.9003725 239.2404797 250.0713068 251.1254802 255.4013028 260.097996 260.2968768 261.3113352 262.7818007 265.0968477 265.3991589 267.3452987 271.0414238 271.1473274 271.5134846 274.7347786 275.2969279 276.1554546 282.1380694 290.4372799 291.8569258 292.0718615 293.3214296 293.6582807 294.9853797 295.42319 297.3719536 298.8694697 299.2063359 303.9394292 305.2438119 307.0860551 307.6796453 314.5145408 315.0032475 317.309682 320.3379176 321.763225 321.9896681 324.6822886 324.9063174 326.245353 327.1799617 334.8869802 335.0811341 335.4113618 335.930817 336.3242655 337.3164968 339.7864706 342.1695326 343.9553272 344.105026 349.5386625 350.5006064 351.8529144 356.0892428 357.8245825 359.8381275 360.718795 361.5265038 362.7345094 365.2203049 376.3246814 378.9092658 380.9365185 383.0615043 386.6166591 387.3896746 388.6949501 389.0957634 391.585877 392.396914 392.7018224 395.955383 397.5088613 398.5427618 404.2400395 405.6726194 408.8400024 410.7341409 410.9015242 411.6471978 413.6702881 422.5141833 425.2185481 426.7645445 428.8923438 429.1847225 431.1445828 432.9142857 434.0961372 434.1390983 434.4686733 434.5802541 437.8414789 446.3950355 449.9360865 450.4154657 451.6288634 452.2563098 452.9003228 461.4062416 462.1319852 467.9316664 469.9009658 471.5148007 472.0619268 478.7189556 479.8589615 487.3700598 487.8579734 488.3406108 489.9326818 493.1140709 495.5665282 505.4300337 513.1560995 514.6240086 517.8879437 517.980567 520.5132441 522.39984 525.3247976 530.0318291 531.4107488 536.4402306 538.1736923 539.969241 540.7295321 540.8795383 541.1953507 551.5694846 551.8735211 551.964729 554.6435272 557.3549076 562.0335934 564.789119 565.6848531 568.8154236 583.6326851 591.5694653 593.0346403 593.8995019 596.3255246 599.4326289 605.9621218 606.5045992 610.3133159 614.89113 621.9548293 625.5796771 626.2013081 630.2782852 633.9634272 637.2725821 642.2773047 643.1521224 644.9876654 646.2282398 646.8289506 650.0468634 650.522442 654.7364775 658.1029798 658.5419844 660.8198684 664.3005214 664.9485137 665.0417007 665.9994232 666.3414944 673.5066171 677.8900371 678.0265613 679.9531067 681.5948756 685.0576536 691.5712738 694.6728516 697.6744186 709.9893086 714.3601479 715.6820763 716.5968312 716.748184 718.3387661 722.6523124 729.8391509 729.9603565 738.1141906 740.0781311 740.9359117 743.2016098 746.0610388 746.9304326 751.2793689 762.8213655 776.0875421 776.95767 782.0872564 786.4032758 797.0495954 802.3780486 807.0296451 808.4134688 810.8108108 816.0323573 816.4978119 823.8885202 826.5147869 827.2487539 831.590189 834.348693 838.3354074 838.3589181 838.4725936 841.2263536 841.4541433 842.192656 849.8034891 850.9535395 854.6521102 856.3480597 860.9894219 861.2777715 867.731809 871.7094202 872.0127878 873.9274205 874.8131969 877.5821738 883.9551347 885.7897929 886.6123515 895.1637275 897.7273744 901.8215742 904.5114863 911.8290271 914.9009406 915.7225753 918.8056513 919.4782268 929.4124233 936.3934569 937.1626184 941.5547644 951.3016066 952.2462556 960.4722946 969.9117367 971.8824626 972.9233379 976.9839367 977.0776597 981.6542477 981.9170028 982.1510719 982.6343189 991.1366503 996.2903501 999.3212528 1001.832921 1003.265814 1008.174158 1008.72466 1012.023275 1014.930266 1021.126324 1032.625836 1035.032717 1039.372616 1046.249857 1048.009273 1050.798357 1058.660866 1062.921945 1080.118949 1082.565544 1082.888042 1083.929607 1095.310416 1099.583846 1118.99545 1120.118381 1121.25163 1132.685333 1138.290933 1152.251702 1171.481481 1174.900598 1176.808889 1178.082517 1180.369826 1186.108867 1201.24805 1201.774098 1202.855588 1204.03957 1204.281115 1214.158159 1214.199683 1218.984699 1221.895955 1222.208819 1223.897809 1230.963056 1232.844643 1233.635268 1234.306672 1237.009876 1241.778141 1243.046825 1247.00531 1249.379997 1251.524325 1255.726652 1259.327206 1260.648391 1262.076126 1269.515788 1270.063468 1271.763273 1278.042816 1282.812198 1287.196184 1287.808101 1293.255037 1300.467411 1306.916689 1307.965433 1308.996779 1310.090422 1311.752342 1318.07106 1324.414948 1324.916694 1325.200297 1330.182309 1335.026937 1336.526037 1356.292773 1357.132304 1357.487622 1358.221964 1359.690153 1362.726158 1367.896805 1373.650371 1374.224267 1374.426821 1376.090291 1376.767579 1377.709222 1378.992275 1386.34268 1393.237678 1395.764639 1399.046874 1403.381881 1409.649378 1409.764125 1416.008286 1418.132612 1420.75316 1422.064666 1431.052952 1432.217811 1433.785163 1440.760197 1444.829639 1444.973466 1454.365041 1456.299203 1462.53896 1464.775301 1465.840677 1467.512507 1474.858813 1475.138297 1476.249229 1476.272364 1480.023617 1482.224389 1486.00906 1491.764706 1493.101858 1494.370522 1497.375219 1500.214533 1501.058681 1505.500869 1505.855949 1506.72917 1508.678238 1508.848184 1508.957919 1511.338003 1513.778247 1515.673848 1517.282454 1517.801833 1525.706865 1526.162727 1527.398904 1529.231867 1532.500663 1535.63675 1538.160776 1550.196 1551.415908 1554.589619 1557.886322 1565.729567 1567.652141 1573.937574 1580.029757 1593.784378 1597.864491 1604.245393 1607.572744 1607.952827 1608.004008 1608.949155 1615.258382 1615.593876 1616.511864 1617.487798 1636.488051 1636.54517 1643.678591 1645.21835 1645.335513 1646.530894 1649.071555 1654.143848 1655.068151 1659.690971 1667.482004 1668.764776 1677.231907 1678.43389 1680.018626 1681.080011 1681.642036 1686.215979 1693.028329 1696.574678 1697.26473 1699.010764 1699.50461 1699.574827 1699.889703 1703.539823 1704.893495 1705.346165 1708.078973 1708.857574 1711.671005 1712.28974 1718.32623 1720.538478 1730.582461 1730.697847 1733.562219 1737.854236 1742.26224 1744.92597 1746.791975 1749.73444 1749.806068 1754.604788 1760.3735 1763.940348 1778.185828 1781.402007 1782.452126 1783.059196 1783.494646 1791.479627 1793.032542 1796.056038 1796.581084 1810.67445 1811.996046 1814.322865 1815.332067 1818.201264 1820.767308 1826.482686 1828.233819 1830.732533 1830.877894 1836.531339 1836.535165 1838.751353 1849.003077 1852.535901 1856.165601 1856.421761 1856.605105 1858.371169 1862.783262 1863.240753 1866.161551 1876.872951 1877.844603 1881.280883 1884.118732 1890.465139 1891.273181 1902.445269 1902.90357 1905.020741 1910.565364 1911.111421 1918.625541 1920.950517 1926.326659 1928.176102 1929.506964 1934.604217 1939.777123 1939.9775 1941.755309 1943.528118 1944.940437 1948.146898 1949.393129 1952.669934 1957.382105 1974.814187 1974.930052 1977.787028 1978.05484 1981.278578 1985.544084 1985.951329 1987.672333 1989.859323 1999.003701 2000.29839 2010.240822 2011.18677 2013.788559 2015.608553 2017.241148 2018.726592 2023.237331 2024.367796 2025.012118 2030.088672 2030.858289 2031.91155 2047.429465 2056.103201 2060.681174 2067.853485 2068.090404 2070.455076 2074.196306 2075.368651 2079.204847 2085.470085 2085.729643 2088.787981 2090.90702 2096.795218 2098.107784 2109.1462 2111.881475 2112.3375 2119.125894 2132.544339 2134.309156 2137.225421 2137.34022 2140.171403 2141.529288 2150.369762 2151.661726 2154.312051 2155.000962 2156.770678 2157.759589 2164.041693 2164.805817 2165.059708 2168.65522 2169.206429 2174.040541 2188.917693 2192.494984 2208.212818 2208.768799 2216.977084 2218.692144 2220.102318 2230.953269 2234.154411 2234.405244 2235.065111 2236.344979 2249.802239 2264.686865 2267.396929 2273.404114 2273.754356 2277.413755 2280.6782 2283.149105 2285.348922 2289.328316 2290.734348 2295.517396 2312.503918 2320.990391 2322.061912 2323.440401 2324.878674 2333.165823 2333.252925 2335.603857 2337.325547 2345.946966 2358.273812 2366.02324 2370.471418 2371.784879 2375.909149 2379.075768 2385.552289 2389.641257 2389.86403 2390.725414 2395.819447 2407.106186 2408.175752 2429.088981 2434.82175 2440.124058 2467.929505 2471.566345 2477.609812 2489.945091 2491.580836 2510.302527 2511.638942 2515.044217 2515.71574 2517.028608 2524.354087 2524.877922 2526.06623 2535.558951 2535.721585 2536.492167 2537.325694 2537.709872 2539.365845 2540.281295 2553.669496 2558.765222 2571.722037 2572.527088 2574.079989 2582.056893 2582.866113 2588.746023 2591.215869 2599.739431 2608.250835 2609.567659 2609.624241 2610.649666 2619.595179 2621.563198 2636.421069 2639.394226 2642.023428 2669.445731 2675.382826 2680.034969 2694.084625 2696.268191 2704.531319 2707.839333 2716.792796 2730.732111 2732.069684 2737.677226 2778.443114 2782.215594 2785.874988 2791.253987 2791.436181 2801.164946 2805.848603 2806.178239 2810.666466 2813.901345 2830.859735 2853.498852 2856.717434 2868.888741 2870.367911 2878.874877 2883.703936 2885.632474 2905.874322 2907.515485 2916.389413 2923.073962 2929.712875 2931.019447 2933.791531 2933.930571 2935.077087 2949.087886 2976.158269 2981.768596 2983.915934 2989.715087 3001.266498 3002.479299 3011.896758 3011.912842 3020.089709 3025.493187 3042.22217 3043.797986 3044.370623 3045.683447 3053.071336 3054.37784 3059.479072 3063.92801 3107.161718 3151.462292 3173.531554 3256.077437 3256.892854 3259.605488 3265.533651 3289.866956 3319.895402 3333.730546 3378.930836 3388.87019 3396.586658 3408.947451 3436.547313 3439.845643 3464.238962 3465.187872 3465.352967 3498.880213 3522.537563 3533.001912 3553.327338 3600.815901 3603.355282 3717.619142 3755.870625 3760.009184 3773.018383 3783.863253 3811.612746 3811.771546 3814.024695 3867.8375 3883.205185 3886.970119 3908.597606 3911.469436 3917.313319 3939.971862 3986.038094 3987.670344 4046.750127 4066.433675 4092.504341 4097.021961 4169.546188 4186.34036 4187.66536 4190.45858 4204.426559 4212.053484 4243.227528 4250.384263 4254.988812 4260.547742 4262.13353 4320.226864 4367.875314 4388.094236 4536.069442 4564.327703 4567.306728 4604.70907 4646.504789 4671.757915 4699.991441 4787.618259 4876.00814 4904.917446 4917.17524 4925.327908 5011.724579 5098.552384 5303.654354 5308.235953 5309.20718 5392.941707 5419.906687 5475.854044 5495.805466 5568.353474 5640.966362 5729.170599 5756.300338 5806.041122 5832.62891 5835.703258 5915.919707 5927.430005 5981.107598 6030.061892 6096.21919 6167.676768 6201.442974 6225.328106 6260.287897 6289.796644 6322.660099 6326.143981 6469.370471 6476.395452 6499.135987 6644.829529 7103.246168 7336.643496 7450.887574 7463.63355 7724.153705 8125.302957 8315.141568 8480.871611 8667.155784 8993.192971 10269.69361 11689.13634 12457.90885 12725.48318 12877.43593];
I want to split a into ~10 discrete groups based on value to make a grouped boxplot of:
data = rand(2348,1);
so that:
boxplot(data,group)
The discrete groups could be like the x-axis in this plot:
Let's say we split into 10 groups by ascending order of values. Try this:
%Note I added 2 extra zero values to start of this matrix to make it divisible by 10
a = [0.000 0.000 0.001818443 0.002518386 0.003220336 0.005121008 0.005896566 0.006067186 0.006398329 0.006398407 0.008139209 0.008179847 0.009156658 0.010554859 0.010897468 0.011446512 0.011646556 0.013025077 0.013744086 0.014617856 0.014830682 0.014941674 0.015810817 0.015953685 0.016022438 0.01662184 0.017497373 0.018051816 0.018084908 0.019634522 0.02055418 0.021050675 0.021573997 0.022819828 0.024124407 0.02499767 0.025745151 0.026366919 0.029380223 0.029534435 0.029988118 0.033517171 0.037612906 0.038975473 0.045889922 0.04598939 0.045995714 0.046398796 0.047502087 0.048214192 0.050098857 0.053184072 0.055892719 0.057670042 0.059855042 0.061763503 0.065288778 0.066057267 0.066842804 0.067799739 0.069549949 0.070151584 0.071572852 0.084351815 0.084676596 0.088092878 0.088329724 0.089958848 0.09000399 0.092272165 0.092561834 0.092888091 0.093193395 0.095380669 0.100645564 0.101506295 0.104656067 0.105057051 0.10527394 0.107024689 0.107608649 0.108699789 0.109433298 0.111805635 0.111990726 0.112119163 0.113570537 0.115032624 0.123301615 0.125012672 0.127758465 0.131636854 0.132397883 0.132910662 0.136185494 0.137039002 0.138037293 0.139764132 0.140727482 0.141044291 0.141523184 0.142202565 0.142563209 0.145192227 0.146881752 0.149407941 0.152043489 0.153144103 0.153181689 0.153795372 0.15548845 0.158134807 0.159905274 0.160042269 0.160098768 0.160483614 0.164710118 0.166850893 0.167909098 0.167986172 0.169019205 0.173698541 0.174264483 0.17696023 0.177973442 0.182348008 0.192484859 0.193880575 0.197216088 0.197939827 0.198109045 0.199497862 0.200821988 0.203783239 0.20515055 0.206573438 0.207185798 0.209268239 0.209386896 0.210951877 0.212023024 0.213363487 0.214391326 0.221532866 0.223109522 0.225343507 0.22641709 0.228343987 0.229206318 0.231114414 0.234752015 0.237026193 0.237716285 0.240721044 0.242380638 0.245407553 0.246434245 0.247559843 0.247849238 0.253027915 0.256495379 0.257901113 0.258536851 0.259306669 0.259722973 0.269672307 0.269866791 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452.2563098 452.9003228 461.4062416 462.1319852 467.9316664 469.9009658 471.5148007 472.0619268 478.7189556 479.8589615 487.3700598 487.8579734 488.3406108 489.9326818 493.1140709 495.5665282 505.4300337 513.1560995 514.6240086 517.8879437 517.980567 520.5132441 522.39984 525.3247976 530.0318291 531.4107488 536.4402306 538.1736923 539.969241 540.7295321 540.8795383 541.1953507 551.5694846 551.8735211 551.964729 554.6435272 557.3549076 562.0335934 564.789119 565.6848531 568.8154236 583.6326851 591.5694653 593.0346403 593.8995019 596.3255246 599.4326289 605.9621218 606.5045992 610.3133159 614.89113 621.9548293 625.5796771 626.2013081 630.2782852 633.9634272 637.2725821 642.2773047 643.1521224 644.9876654 646.2282398 646.8289506 650.0468634 650.522442 654.7364775 658.1029798 658.5419844 660.8198684 664.3005214 664.9485137 665.0417007 665.9994232 666.3414944 673.5066171 677.8900371 678.0265613 679.9531067 681.5948756 685.0576536 691.5712738 694.6728516 697.6744186 709.9893086 714.3601479 715.6820763 716.5968312 716.748184 718.3387661 722.6523124 729.8391509 729.9603565 738.1141906 740.0781311 740.9359117 743.2016098 746.0610388 746.9304326 751.2793689 762.8213655 776.0875421 776.95767 782.0872564 786.4032758 797.0495954 802.3780486 807.0296451 808.4134688 810.8108108 816.0323573 816.4978119 823.8885202 826.5147869 827.2487539 831.590189 834.348693 838.3354074 838.3589181 838.4725936 841.2263536 841.4541433 842.192656 849.8034891 850.9535395 854.6521102 856.3480597 860.9894219 861.2777715 867.731809 871.7094202 872.0127878 873.9274205 874.8131969 877.5821738 883.9551347 885.7897929 886.6123515 895.1637275 897.7273744 901.8215742 904.5114863 911.8290271 914.9009406 915.7225753 918.8056513 919.4782268 929.4124233 936.3934569 937.1626184 941.5547644 951.3016066 952.2462556 960.4722946 969.9117367 971.8824626 972.9233379 976.9839367 977.0776597 981.6542477 981.9170028 982.1510719 982.6343189 991.1366503 996.2903501 999.3212528 1001.832921 1003.265814 1008.174158 1008.72466 1012.023275 1014.930266 1021.126324 1032.625836 1035.032717 1039.372616 1046.249857 1048.009273 1050.798357 1058.660866 1062.921945 1080.118949 1082.565544 1082.888042 1083.929607 1095.310416 1099.583846 1118.99545 1120.118381 1121.25163 1132.685333 1138.290933 1152.251702 1171.481481 1174.900598 1176.808889 1178.082517 1180.369826 1186.108867 1201.24805 1201.774098 1202.855588 1204.03957 1204.281115 1214.158159 1214.199683 1218.984699 1221.895955 1222.208819 1223.897809 1230.963056 1232.844643 1233.635268 1234.306672 1237.009876 1241.778141 1243.046825 1247.00531 1249.379997 1251.524325 1255.726652 1259.327206 1260.648391 1262.076126 1269.515788 1270.063468 1271.763273 1278.042816 1282.812198 1287.196184 1287.808101 1293.255037 1300.467411 1306.916689 1307.965433 1308.996779 1310.090422 1311.752342 1318.07106 1324.414948 1324.916694 1325.200297 1330.182309 1335.026937 1336.526037 1356.292773 1357.132304 1357.487622 1358.221964 1359.690153 1362.726158 1367.896805 1373.650371 1374.224267 1374.426821 1376.090291 1376.767579 1377.709222 1378.992275 1386.34268 1393.237678 1395.764639 1399.046874 1403.381881 1409.649378 1409.764125 1416.008286 1418.132612 1420.75316 1422.064666 1431.052952 1432.217811 1433.785163 1440.760197 1444.829639 1444.973466 1454.365041 1456.299203 1462.53896 1464.775301 1465.840677 1467.512507 1474.858813 1475.138297 1476.249229 1476.272364 1480.023617 1482.224389 1486.00906 1491.764706 1493.101858 1494.370522 1497.375219 1500.214533 1501.058681 1505.500869 1505.855949 1506.72917 1508.678238 1508.848184 1508.957919 1511.338003 1513.778247 1515.673848 1517.282454 1517.801833 1525.706865 1526.162727 1527.398904 1529.231867 1532.500663 1535.63675 1538.160776 1550.196 1551.415908 1554.589619 1557.886322 1565.729567 1567.652141 1573.937574 1580.029757 1593.784378 1597.864491 1604.245393 1607.572744 1607.952827 1608.004008 1608.949155 1615.258382 1615.593876 1616.511864 1617.487798 1636.488051 1636.54517 1643.678591 1645.21835 1645.335513 1646.530894 1649.071555 1654.143848 1655.068151 1659.690971 1667.482004 1668.764776 1677.231907 1678.43389 1680.018626 1681.080011 1681.642036 1686.215979 1693.028329 1696.574678 1697.26473 1699.010764 1699.50461 1699.574827 1699.889703 1703.539823 1704.893495 1705.346165 1708.078973 1708.857574 1711.671005 1712.28974 1718.32623 1720.538478 1730.582461 1730.697847 1733.562219 1737.854236 1742.26224 1744.92597 1746.791975 1749.73444 1749.806068 1754.604788 1760.3735 1763.940348 1778.185828 1781.402007 1782.452126 1783.059196 1783.494646 1791.479627 1793.032542 1796.056038 1796.581084 1810.67445 1811.996046 1814.322865 1815.332067 1818.201264 1820.767308 1826.482686 1828.233819 1830.732533 1830.877894 1836.531339 1836.535165 1838.751353 1849.003077 1852.535901 1856.165601 1856.421761 1856.605105 1858.371169 1862.783262 1863.240753 1866.161551 1876.872951 1877.844603 1881.280883 1884.118732 1890.465139 1891.273181 1902.445269 1902.90357 1905.020741 1910.565364 1911.111421 1918.625541 1920.950517 1926.326659 1928.176102 1929.506964 1934.604217 1939.777123 1939.9775 1941.755309 1943.528118 1944.940437 1948.146898 1949.393129 1952.669934 1957.382105 1974.814187 1974.930052 1977.787028 1978.05484 1981.278578 1985.544084 1985.951329 1987.672333 1989.859323 1999.003701 2000.29839 2010.240822 2011.18677 2013.788559 2015.608553 2017.241148 2018.726592 2023.237331 2024.367796 2025.012118 2030.088672 2030.858289 2031.91155 2047.429465 2056.103201 2060.681174 2067.853485 2068.090404 2070.455076 2074.196306 2075.368651 2079.204847 2085.470085 2085.729643 2088.787981 2090.90702 2096.795218 2098.107784 2109.1462 2111.881475 2112.3375 2119.125894 2132.544339 2134.309156 2137.225421 2137.34022 2140.171403 2141.529288 2150.369762 2151.661726 2154.312051 2155.000962 2156.770678 2157.759589 2164.041693 2164.805817 2165.059708 2168.65522 2169.206429 2174.040541 2188.917693 2192.494984 2208.212818 2208.768799 2216.977084 2218.692144 2220.102318 2230.953269 2234.154411 2234.405244 2235.065111 2236.344979 2249.802239 2264.686865 2267.396929 2273.404114 2273.754356 2277.413755 2280.6782 2283.149105 2285.348922 2289.328316 2290.734348 2295.517396 2312.503918 2320.990391 2322.061912 2323.440401 2324.878674 2333.165823 2333.252925 2335.603857 2337.325547 2345.946966 2358.273812 2366.02324 2370.471418 2371.784879 2375.909149 2379.075768 2385.552289 2389.641257 2389.86403 2390.725414 2395.819447 2407.106186 2408.175752 2429.088981 2434.82175 2440.124058 2467.929505 2471.566345 2477.609812 2489.945091 2491.580836 2510.302527 2511.638942 2515.044217 2515.71574 2517.028608 2524.354087 2524.877922 2526.06623 2535.558951 2535.721585 2536.492167 2537.325694 2537.709872 2539.365845 2540.281295 2553.669496 2558.765222 2571.722037 2572.527088 2574.079989 2582.056893 2582.866113 2588.746023 2591.215869 2599.739431 2608.250835 2609.567659 2609.624241 2610.649666 2619.595179 2621.563198 2636.421069 2639.394226 2642.023428 2669.445731 2675.382826 2680.034969 2694.084625 2696.268191 2704.531319 2707.839333 2716.792796 2730.732111 2732.069684 2737.677226 2778.443114 2782.215594 2785.874988 2791.253987 2791.436181 2801.164946 2805.848603 2806.178239 2810.666466 2813.901345 2830.859735 2853.498852 2856.717434 2868.888741 2870.367911 2878.874877 2883.703936 2885.632474 2905.874322 2907.515485 2916.389413 2923.073962 2929.712875 2931.019447 2933.791531 2933.930571 2935.077087 2949.087886 2976.158269 2981.768596 2983.915934 2989.715087 3001.266498 3002.479299 3011.896758 3011.912842 3020.089709 3025.493187 3042.22217 3043.797986 3044.370623 3045.683447 3053.071336 3054.37784 3059.479072 3063.92801 3107.161718 3151.462292 3173.531554 3256.077437 3256.892854 3259.605488 3265.533651 3289.866956 3319.895402 3333.730546 3378.930836 3388.87019 3396.586658 3408.947451 3436.547313 3439.845643 3464.238962 3465.187872 3465.352967 3498.880213 3522.537563 3533.001912 3553.327338 3600.815901 3603.355282 3717.619142 3755.870625 3760.009184 3773.018383 3783.863253 3811.612746 3811.771546 3814.024695 3867.8375 3883.205185 3886.970119 3908.597606 3911.469436 3917.313319 3939.971862 3986.038094 3987.670344 4046.750127 4066.433675 4092.504341 4097.021961 4169.546188 4186.34036 4187.66536 4190.45858 4204.426559 4212.053484 4243.227528 4250.384263 4254.988812 4260.547742 4262.13353 4320.226864 4367.875314 4388.094236 4536.069442 4564.327703 4567.306728 4604.70907 4646.504789 4671.757915 4699.991441 4787.618259 4876.00814 4904.917446 4917.17524 4925.327908 5011.724579 5098.552384 5303.654354 5308.235953 5309.20718 5392.941707 5419.906687 5475.854044 5495.805466 5568.353474 5640.966362 5729.170599 5756.300338 5806.041122 5832.62891 5835.703258 5915.919707 5927.430005 5981.107598 6030.061892 6096.21919 6167.676768 6201.442974 6225.328106 6260.287897 6289.796644 6322.660099 6326.143981 6469.370471 6476.395452 6499.135987 6644.829529 7103.246168 7336.643496 7450.887574 7463.63355 7724.153705 8125.302957 8315.141568 8480.871611 8667.155784 8993.192971 10269.69361 11689.13634 12457.90885 12725.48318 12877.43593];
%ascending order sort
a = sort(a);
%split into 10.
data = reshape(a,235,10);
%boxplot
boxplot(data(:,1:10))
Produces this:
You can compare the values of a with their quantiles to generate groups with similar sizes. This approch automatically handles the case when the size of a is not a multiple of the number of groups.
N = 10; % desired number of groups
thresholds = quantile(a, 0:1/N:1-1/N); % for approximately equal-size groups
group = sum(bsxfun(#ge, a, thresholds.'), 1); % this ranges from 1 to N
For your example a and data, this gives the following group sizes:
>> sum(bsxfun(#eq, group(:), 1:N), 1)
ans =
235 235 234 235 235 235 235 234 235 235
To do the plot, you probably want to use the average of each group as the x-axis value:
a_average_group = accumarray(group(:), a(:), [], #mean);
boxplot(data, a_average_group(group))
produces
Some way to group the data automatically is to use hist. The elements in a are sorted into 10 equally spaced bins along the x-axis between the minimum and maximum values of a. As hist returns the center of the bins, there is some calulation to get the right border of the bin, so one can calculate the correct bin given some value of a. In your example the 8th bin has no values though, resulting in only 9 boxplots drawn.
a = [0.001818443 0.002518386 0.003220336 0.005121008 0.005896566 0.006067186 0.006398329 0.006398407 0.008139209 0.008179847 0.009156658 0.010554859 0.010897468 0.011446512 0.011646556 0.013025077 0.013744086 0.014617856 0.014830682 0.014941674 0.015810817 0.015953685 0.016022438 0.01662184 0.017497373 0.018051816 0.018084908 0.019634522 0.02055418 0.021050675 0.021573997 0.022819828 0.024124407 0.02499767 0.025745151 0.026366919 0.029380223 0.029534435 0.029988118 0.033517171 0.037612906 0.038975473 0.045889922 0.04598939 0.045995714 0.046398796 0.047502087 0.048214192 0.050098857 0.053184072 0.055892719 0.057670042 0.059855042 0.061763503 0.065288778 0.066057267 0.066842804 0.067799739 0.069549949 0.070151584 0.071572852 0.084351815 0.084676596 0.088092878 0.088329724 0.089958848 0.09000399 0.092272165 0.092561834 0.092888091 0.093193395 0.095380669 0.100645564 0.101506295 0.104656067 0.105057051 0.10527394 0.107024689 0.107608649 0.108699789 0.109433298 0.111805635 0.111990726 0.112119163 0.113570537 0.115032624 0.123301615 0.125012672 0.127758465 0.131636854 0.132397883 0.132910662 0.136185494 0.137039002 0.138037293 0.139764132 0.140727482 0.141044291 0.141523184 0.142202565 0.142563209 0.145192227 0.146881752 0.149407941 0.152043489 0.153144103 0.153181689 0.153795372 0.15548845 0.158134807 0.159905274 0.160042269 0.160098768 0.160483614 0.164710118 0.166850893 0.167909098 0.167986172 0.169019205 0.173698541 0.174264483 0.17696023 0.177973442 0.182348008 0.192484859 0.193880575 0.197216088 0.197939827 0.198109045 0.199497862 0.200821988 0.203783239 0.20515055 0.206573438 0.207185798 0.209268239 0.209386896 0.210951877 0.212023024 0.213363487 0.214391326 0.221532866 0.223109522 0.225343507 0.22641709 0.228343987 0.229206318 0.231114414 0.234752015 0.237026193 0.237716285 0.240721044 0.242380638 0.245407553 0.246434245 0.247559843 0.247849238 0.253027915 0.256495379 0.257901113 0.258536851 0.259306669 0.259722973 0.269672307 0.269866791 0.277255751 0.282296038 0.283236904 0.286946602 0.290243971 0.291043929 0.29129401 0.295039384 0.306007647 0.318012708 0.31816788 0.323432941 0.327635294 0.331093206 0.332249017 0.336175038 0.338095934 0.34029032 0.34317957 0.343788501 0.344121892 0.354931564 0.35667793 0.363077884 0.366887155 0.367370204 0.368269666 0.368423655 0.372253797 0.373533628 0.376022623 0.380837432 0.38261496 0.38391646 0.387548982 0.390389207 0.391454753 0.392089937 0.393426643 0.399546308 0.400245613 0.410202767 0.410776868 0.411723243 0.413456921 0.415884043 0.417789874 0.420313779 0.421429254 0.422511926 0.425439714 0.432455519 0.436032696 0.437367296 0.440152475 0.451378258 0.451755234 0.452195559 0.461256878 0.462486697 0.466794805 0.468274083 0.470176312 0.471656017 0.476690087 0.476869314 0.479601939 0.480684241 0.48433634 0.48590973 0.487749692 0.488207469 0.492988875 0.494796745 0.498156249 0.4985104 0.504612947 0.504967424 0.50679421 0.507507695 0.508506011 0.509330529 0.510055669 0.513319728 0.52891378 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715.6820763 716.5968312 716.748184 718.3387661 722.6523124 729.8391509 729.9603565 738.1141906 740.0781311 740.9359117 743.2016098 746.0610388 746.9304326 751.2793689 762.8213655 776.0875421 776.95767 782.0872564 786.4032758 797.0495954 802.3780486 807.0296451 808.4134688 810.8108108 816.0323573 816.4978119 823.8885202 826.5147869 827.2487539 831.590189 834.348693 838.3354074 838.3589181 838.4725936 841.2263536 841.4541433 842.192656 849.8034891 850.9535395 854.6521102 856.3480597 860.9894219 861.2777715 867.731809 871.7094202 872.0127878 873.9274205 874.8131969 877.5821738 883.9551347 885.7897929 886.6123515 895.1637275 897.7273744 901.8215742 904.5114863 911.8290271 914.9009406 915.7225753 918.8056513 919.4782268 929.4124233 936.3934569 937.1626184 941.5547644 951.3016066 952.2462556 960.4722946 969.9117367 971.8824626 972.9233379 976.9839367 977.0776597 981.6542477 981.9170028 982.1510719 982.6343189 991.1366503 996.2903501 999.3212528 1001.832921 1003.265814 1008.174158 1008.72466 1012.023275 1014.930266 1021.126324 1032.625836 1035.032717 1039.372616 1046.249857 1048.009273 1050.798357 1058.660866 1062.921945 1080.118949 1082.565544 1082.888042 1083.929607 1095.310416 1099.583846 1118.99545 1120.118381 1121.25163 1132.685333 1138.290933 1152.251702 1171.481481 1174.900598 1176.808889 1178.082517 1180.369826 1186.108867 1201.24805 1201.774098 1202.855588 1204.03957 1204.281115 1214.158159 1214.199683 1218.984699 1221.895955 1222.208819 1223.897809 1230.963056 1232.844643 1233.635268 1234.306672 1237.009876 1241.778141 1243.046825 1247.00531 1249.379997 1251.524325 1255.726652 1259.327206 1260.648391 1262.076126 1269.515788 1270.063468 1271.763273 1278.042816 1282.812198 1287.196184 1287.808101 1293.255037 1300.467411 1306.916689 1307.965433 1308.996779 1310.090422 1311.752342 1318.07106 1324.414948 1324.916694 1325.200297 1330.182309 1335.026937 1336.526037 1356.292773 1357.132304 1357.487622 1358.221964 1359.690153 1362.726158 1367.896805 1373.650371 1374.224267 1374.426821 1376.090291 1376.767579 1377.709222 1378.992275 1386.34268 1393.237678 1395.764639 1399.046874 1403.381881 1409.649378 1409.764125 1416.008286 1418.132612 1420.75316 1422.064666 1431.052952 1432.217811 1433.785163 1440.760197 1444.829639 1444.973466 1454.365041 1456.299203 1462.53896 1464.775301 1465.840677 1467.512507 1474.858813 1475.138297 1476.249229 1476.272364 1480.023617 1482.224389 1486.00906 1491.764706 1493.101858 1494.370522 1497.375219 1500.214533 1501.058681 1505.500869 1505.855949 1506.72917 1508.678238 1508.848184 1508.957919 1511.338003 1513.778247 1515.673848 1517.282454 1517.801833 1525.706865 1526.162727 1527.398904 1529.231867 1532.500663 1535.63675 1538.160776 1550.196 1551.415908 1554.589619 1557.886322 1565.729567 1567.652141 1573.937574 1580.029757 1593.784378 1597.864491 1604.245393 1607.572744 1607.952827 1608.004008 1608.949155 1615.258382 1615.593876 1616.511864 1617.487798 1636.488051 1636.54517 1643.678591 1645.21835 1645.335513 1646.530894 1649.071555 1654.143848 1655.068151 1659.690971 1667.482004 1668.764776 1677.231907 1678.43389 1680.018626 1681.080011 1681.642036 1686.215979 1693.028329 1696.574678 1697.26473 1699.010764 1699.50461 1699.574827 1699.889703 1703.539823 1704.893495 1705.346165 1708.078973 1708.857574 1711.671005 1712.28974 1718.32623 1720.538478 1730.582461 1730.697847 1733.562219 1737.854236 1742.26224 1744.92597 1746.791975 1749.73444 1749.806068 1754.604788 1760.3735 1763.940348 1778.185828 1781.402007 1782.452126 1783.059196 1783.494646 1791.479627 1793.032542 1796.056038 1796.581084 1810.67445 1811.996046 1814.322865 1815.332067 1818.201264 1820.767308 1826.482686 1828.233819 1830.732533 1830.877894 1836.531339 1836.535165 1838.751353 1849.003077 1852.535901 1856.165601 1856.421761 1856.605105 1858.371169 1862.783262 1863.240753 1866.161551 1876.872951 1877.844603 1881.280883 1884.118732 1890.465139 1891.273181 1902.445269 1902.90357 1905.020741 1910.565364 1911.111421 1918.625541 1920.950517 1926.326659 1928.176102 1929.506964 1934.604217 1939.777123 1939.9775 1941.755309 1943.528118 1944.940437 1948.146898 1949.393129 1952.669934 1957.382105 1974.814187 1974.930052 1977.787028 1978.05484 1981.278578 1985.544084 1985.951329 1987.672333 1989.859323 1999.003701 2000.29839 2010.240822 2011.18677 2013.788559 2015.608553 2017.241148 2018.726592 2023.237331 2024.367796 2025.012118 2030.088672 2030.858289 2031.91155 2047.429465 2056.103201 2060.681174 2067.853485 2068.090404 2070.455076 2074.196306 2075.368651 2079.204847 2085.470085 2085.729643 2088.787981 2090.90702 2096.795218 2098.107784 2109.1462 2111.881475 2112.3375 2119.125894 2132.544339 2134.309156 2137.225421 2137.34022 2140.171403 2141.529288 2150.369762 2151.661726 2154.312051 2155.000962 2156.770678 2157.759589 2164.041693 2164.805817 2165.059708 2168.65522 2169.206429 2174.040541 2188.917693 2192.494984 2208.212818 2208.768799 2216.977084 2218.692144 2220.102318 2230.953269 2234.154411 2234.405244 2235.065111 2236.344979 2249.802239 2264.686865 2267.396929 2273.404114 2273.754356 2277.413755 2280.6782 2283.149105 2285.348922 2289.328316 2290.734348 2295.517396 2312.503918 2320.990391 2322.061912 2323.440401 2324.878674 2333.165823 2333.252925 2335.603857 2337.325547 2345.946966 2358.273812 2366.02324 2370.471418 2371.784879 2375.909149 2379.075768 2385.552289 2389.641257 2389.86403 2390.725414 2395.819447 2407.106186 2408.175752 2429.088981 2434.82175 2440.124058 2467.929505 2471.566345 2477.609812 2489.945091 2491.580836 2510.302527 2511.638942 2515.044217 2515.71574 2517.028608 2524.354087 2524.877922 2526.06623 2535.558951 2535.721585 2536.492167 2537.325694 2537.709872 2539.365845 2540.281295 2553.669496 2558.765222 2571.722037 2572.527088 2574.079989 2582.056893 2582.866113 2588.746023 2591.215869 2599.739431 2608.250835 2609.567659 2609.624241 2610.649666 2619.595179 2621.563198 2636.421069 2639.394226 2642.023428 2669.445731 2675.382826 2680.034969 2694.084625 2696.268191 2704.531319 2707.839333 2716.792796 2730.732111 2732.069684 2737.677226 2778.443114 2782.215594 2785.874988 2791.253987 2791.436181 2801.164946 2805.848603 2806.178239 2810.666466 2813.901345 2830.859735 2853.498852 2856.717434 2868.888741 2870.367911 2878.874877 2883.703936 2885.632474 2905.874322 2907.515485 2916.389413 2923.073962 2929.712875 2931.019447 2933.791531 2933.930571 2935.077087 2949.087886 2976.158269 2981.768596 2983.915934 2989.715087 3001.266498 3002.479299 3011.896758 3011.912842 3020.089709 3025.493187 3042.22217 3043.797986 3044.370623 3045.683447 3053.071336 3054.37784 3059.479072 3063.92801 3107.161718 3151.462292 3173.531554 3256.077437 3256.892854 3259.605488 3265.533651 3289.866956 3319.895402 3333.730546 3378.930836 3388.87019 3396.586658 3408.947451 3436.547313 3439.845643 3464.238962 3465.187872 3465.352967 3498.880213 3522.537563 3533.001912 3553.327338 3600.815901 3603.355282 3717.619142 3755.870625 3760.009184 3773.018383 3783.863253 3811.612746 3811.771546 3814.024695 3867.8375 3883.205185 3886.970119 3908.597606 3911.469436 3917.313319 3939.971862 3986.038094 3987.670344 4046.750127 4066.433675 4092.504341 4097.021961 4169.546188 4186.34036 4187.66536 4190.45858 4204.426559 4212.053484 4243.227528 4250.384263 4254.988812 4260.547742 4262.13353 4320.226864 4367.875314 4388.094236 4536.069442 4564.327703 4567.306728 4604.70907 4646.504789 4671.757915 4699.991441 4787.618259 4876.00814 4904.917446 4917.17524 4925.327908 5011.724579 5098.552384 5303.654354 5308.235953 5309.20718 5392.941707 5419.906687 5475.854044 5495.805466 5568.353474 5640.966362 5729.170599 5756.300338 5806.041122 5832.62891 5835.703258 5915.919707 5927.430005 5981.107598 6030.061892 6096.21919 6167.676768 6201.442974 6225.328106 6260.287897 6289.796644 6322.660099 6326.143981 6469.370471 6476.395452 6499.135987 6644.829529 7103.246168 7336.643496 7450.887574 7463.63355 7724.153705 8125.302957 8315.141568 8480.871611 8667.155784 8993.192971 10269.69361 11689.13634 12457.90885 12725.48318 12877.43593];
[counts,centers] = hist(a,10);
borders = centers+(centers(2)-centers(1))/2
b = arrayfun(#(x) sum(x>=borders),a);
boxplot(a,b)
Related
I found "unk" token in the glove vector file glove.6B.50d.txt downloaded from https://nlp.stanford.edu/projects/glove/. Its value is as follows:
unk -0.79149 0.86617 0.11998 0.00092287 0.2776 -0.49185 0.50195 0.00060792 -0.25845 0.17865 0.2535 0.76572 0.50664 0.4025 -0.0021388 -0.28397 -0.50324 0.30449 0.51779 0.01509 -0.35031 -1.1278 0.33253 -0.3525 0.041326 1.0863 0.03391 0.33564 0.49745 -0.070131 -1.2192 -0.48512 -0.038512 -0.13554 -0.1638 0.52321 -0.31318 -0.1655 0.11909 -0.15115 -0.15621 -0.62655 -0.62336 -0.4215 0.41873 -0.92472 1.1049 -0.29996 -0.0063003 0.3954
Is it a token to be used for unknown words or is it some kind of abbreviation?
The unk token in the pretrained GloVe files is not an unknown token!
See this google groups thread where Jeffrey Pennington (GloVe author) writes:
The pre-trained vectors do not have an unknown token, and currently the code just ignores out-of-vocabulary words when producing the co-occurrence counts.
It's an embedding learned like any other on occurrences of "unk" in the corpus (which appears to happen occasionally!)
Instead, Pennington suggests (in the same post):
...I've found that just taking an average of all or a subset of the word vectors produces a good unknown vector.
You can do that with the following code (should work with any pretrained GloVe file):
import numpy as np
GLOVE_FILE = 'glove.6B.50d.txt'
# Get number of vectors and hidden dim
with open(GLOVE_FILE, 'r') as f:
for i, line in enumerate(f):
pass
n_vec = i + 1
hidden_dim = len(line.split(' ')) - 1
vecs = np.zeros((n_vec, hidden_dim), dtype=np.float32)
with open(GLOVE_FILE, 'r') as f:
for i, line in enumerate(f):
vecs[i] = np.array([float(n) for n in line.split(' ')[1:]], dtype=np.float32)
average_vec = np.mean(vecs, axis=0)
print(average_vec)
For glove.6B.50d.txt this gives:
[-0.12920076 -0.28866628 -0.01224866 -0.05676644 -0.20210965 -0.08389011
0.33359843 0.16045167 0.03867431 0.17833012 0.04696583 -0.00285802
0.29099807 0.04613704 -0.20923874 -0.06613114 -0.06822549 0.07665912
0.3134014 0.17848536 -0.1225775 -0.09916984 -0.07495987 0.06413227
0.14441176 0.60894334 0.17463093 0.05335403 -0.01273871 0.03474107
-0.8123879 -0.04688699 0.20193407 0.2031118 -0.03935686 0.06967544
-0.01553638 -0.03405238 -0.06528071 0.12250231 0.13991883 -0.17446303
-0.08011883 0.0849521 -0.01041659 -0.13705009 0.20127155 0.10069408
0.00653003 0.01685157]
And because it is fairly compute intensive to do this with the larger glove files, I went ahead and computed the vector for glove.840B.300d.txt for you:
0.22418134 -0.28881392 0.13854356 0.00365387 -0.12870757 0.10243822 0.061626635 0.07318011 -0.061350107 -1.3477012 0.42037755 -0.063593924 -0.09683349 0.18086134 0.23704372 0.014126852 0.170096 -1.1491593 0.31497982 0.06622181 0.024687296 0.076693475 0.13851812 0.021302193 -0.06640582 -0.010336159 0.13523154 -0.042144544 -0.11938788 0.006948221 0.13333307 -0.18276379 0.052385733 0.008943111 -0.23957317 0.08500333 -0.006894406 0.0015864656 0.063391194 0.19177166 -0.13113557 -0.11295479 -0.14276934 0.03413971 -0.034278486 -0.051366422 0.18891625 -0.16673574 -0.057783455 0.036823478 0.08078679 0.022949161 0.033298038 0.011784158 0.05643189 -0.042776518 0.011959623 0.011552498 -0.0007971594 0.11300405 -0.031369694 -0.0061559738 -0.009043574 -0.415336 -0.18870236 0.13708843 0.005911723 -0.113035575 -0.030096142 -0.23908928 -0.05354085 -0.044904727 -0.20228513 0.0065645403 -0.09578946 -0.07391877 -0.06487607 0.111740574 -0.048649278 -0.16565254 -0.052037314 -0.078968436 0.13684988 0.0757494 -0.006275573 0.28693774 0.52017444 -0.0877165 -0.33010918 -0.1359622 0.114895485 -0.09744406 0.06269521 0.12118575 -0.08026362 0.35256687 -0.060017522 -0.04889904 -0.06828978 0.088740796 0.003964443 -0.0766291 0.1263925 0.07809314 -0.023164088 -0.5680669 -0.037892066 -0.1350967 -0.11351585 -0.111434504 -0.0905027 0.25174105 -0.14841858 0.034635577 -0.07334565 0.06320108 -0.038343467 -0.05413284 0.042197507 -0.090380974 -0.070528865 -0.009174437 0.009069661 0.1405178 0.02958134 -0.036431845 -0.08625681 0.042951006 0.08230793 0.0903314 -0.12279937 -0.013899368 0.048119213 0.08678239 -0.14450377 -0.04424887 0.018319942 0.015026873 -0.100526 0.06021201 0.74059093 -0.0016333034 -0.24960588 -0.023739101 0.016396184 0.11928964 0.13950661 -0.031624354 -0.01645025 0.14079992 -0.0002824564 -0.08052984 -0.0021310581 -0.025350995 0.086938225 0.14308536 0.17146006 -0.13943303 0.048792403 0.09274929 -0.053167373 0.031103406 0.012354865 0.21057427 0.32618305 0.18015954 -0.15881181 0.15322933 -0.22558987 -0.04200665 0.0084689725 0.038156632 0.15188617 0.13274793 0.113756925 -0.095273495 -0.049490947 -0.10265804 -0.27064866 -0.034567792 -0.018810693 -0.0010360252 0.10340131 0.13883452 0.21131058 -0.01981019 0.1833468 -0.10751636 -0.03128868 0.02518242 0.23232952 0.042052146 0.11731903 -0.15506615 0.0063580726 -0.15429358 0.1511722 0.12745973 0.2576985 -0.25486213 -0.0709463 0.17983761 0.054027 -0.09884228 -0.24595179 -0.093028545 -0.028203879 0.094398156 0.09233813 0.029291354 0.13110267 0.15682974 -0.016919162 0.23927948 -0.1343307 -0.22422817 0.14634751 -0.064993896 0.4703685 -0.027190214 0.06224946 -0.091360025 0.21490277 -0.19562101 -0.10032754 -0.09056772 -0.06203493 -0.18876675 -0.10963594 -0.27734384 0.12616494 -0.02217992 -0.16058226 -0.080475815 0.026953284 0.110732645 0.014894041 0.09416802 0.14299914 -0.1594008 -0.066080004 -0.007995227 -0.11668856 -0.13081996 -0.09237365 0.14741232 0.09180138 0.081735 0.3211204 -0.0036552632 -0.047030564 -0.02311798 0.048961394 0.08669574 -0.06766279 -0.50028914 -0.048515294 0.14144728 -0.032994404 -0.11954345 -0.14929578 -0.2388355 -0.019883996 -0.15917352 -0.052084364 0.2801028 -0.0029121689 -0.054581646 -0.47385484 0.17112483 -0.12066923 -0.042173345 0.1395337 0.26115036 0.012869649 0.009291686 -0.0026459037 -0.075331464 0.017840583 -0.26869613 -0.21820338 -0.17084768 -0.1022808 -0.055290595 0.13513643 0.12362477 -0.10980586 0.13980341 -0.20233242 0.08813751 0.3849736 -0.10653763 -0.06199595 0.028849555 0.03230154 0.023856193 0.069950655 0.19310954 -0.077677034 -0.144811
Since I can't comment, writing another answer.
If anyone's having trouble using the above vector given by #jayelm because copy pasting won't work. I am writing 2 lines of code that will give you the vector ready to be used in python.
vec_string = '0.22418134 -0.28881392 0.13854356 0.00365387 -0.12870757 0.10243822 0.061626635 0.07318011 -0.061350107 -1.3477012 0.42037755 -0.063593924 -0.09683349 0.18086134 0.23704372 0.014126852 0.170096 -1.1491593 0.31497982 0.06622181 0.024687296 0.076693475 0.13851812 0.021302193 -0.06640582 -0.010336159 0.13523154 -0.042144544 -0.11938788 0.006948221 0.13333307 -0.18276379 0.052385733 0.008943111 -0.23957317 0.08500333 -0.006894406 0.0015864656 0.063391194 0.19177166 -0.13113557 -0.11295479 -0.14276934 0.03413971 -0.034278486 -0.051366422 0.18891625 -0.16673574 -0.057783455 0.036823478 0.08078679 0.022949161 0.033298038 0.011784158 0.05643189 -0.042776518 0.011959623 0.011552498 -0.0007971594 0.11300405 -0.031369694 -0.0061559738 -0.009043574 -0.415336 -0.18870236 0.13708843 0.005911723 -0.113035575 -0.030096142 -0.23908928 -0.05354085 -0.044904727 -0.20228513 0.0065645403 -0.09578946 -0.07391877 -0.06487607 0.111740574 -0.048649278 -0.16565254 -0.052037314 -0.078968436 0.13684988 0.0757494 -0.006275573 0.28693774 0.52017444 -0.0877165 -0.33010918 -0.1359622 0.114895485 -0.09744406 0.06269521 0.12118575 -0.08026362 0.35256687 -0.060017522 -0.04889904 -0.06828978 0.088740796 0.003964443 -0.0766291 0.1263925 0.07809314 -0.023164088 -0.5680669 -0.037892066 -0.1350967 -0.11351585 -0.111434504 -0.0905027 0.25174105 -0.14841858 0.034635577 -0.07334565 0.06320108 -0.038343467 -0.05413284 0.042197507 -0.090380974 -0.070528865 -0.009174437 0.009069661 0.1405178 0.02958134 -0.036431845 -0.08625681 0.042951006 0.08230793 0.0903314 -0.12279937 -0.013899368 0.048119213 0.08678239 -0.14450377 -0.04424887 0.018319942 0.015026873 -0.100526 0.06021201 0.74059093 -0.0016333034 -0.24960588 -0.023739101 0.016396184 0.11928964 0.13950661 -0.031624354 -0.01645025 0.14079992 -0.0002824564 -0.08052984 -0.0021310581 -0.025350995 0.086938225 0.14308536 0.17146006 -0.13943303 0.048792403 0.09274929 -0.053167373 0.031103406 0.012354865 0.21057427 0.32618305 0.18015954 -0.15881181 0.15322933 -0.22558987 -0.04200665 0.0084689725 0.038156632 0.15188617 0.13274793 0.113756925 -0.095273495 -0.049490947 -0.10265804 -0.27064866 -0.034567792 -0.018810693 -0.0010360252 0.10340131 0.13883452 0.21131058 -0.01981019 0.1833468 -0.10751636 -0.03128868 0.02518242 0.23232952 0.042052146 0.11731903 -0.15506615 0.0063580726 -0.15429358 0.1511722 0.12745973 0.2576985 -0.25486213 -0.0709463 0.17983761 0.054027 -0.09884228 -0.24595179 -0.093028545 -0.028203879 0.094398156 0.09233813 0.029291354 0.13110267 0.15682974 -0.016919162 0.23927948 -0.1343307 -0.22422817 0.14634751 -0.064993896 0.4703685 -0.027190214 0.06224946 -0.091360025 0.21490277 -0.19562101 -0.10032754 -0.09056772 -0.06203493 -0.18876675 -0.10963594 -0.27734384 0.12616494 -0.02217992 -0.16058226 -0.080475815 0.026953284 0.110732645 0.014894041 0.09416802 0.14299914 -0.1594008 -0.066080004 -0.007995227 -0.11668856 -0.13081996 -0.09237365 0.14741232 0.09180138 0.081735 0.3211204 -0.0036552632 -0.047030564 -0.02311798 0.048961394 0.08669574 -0.06766279 -0.50028914 -0.048515294 0.14144728 -0.032994404 -0.11954345 -0.14929578 -0.2388355 -0.019883996 -0.15917352 -0.052084364 0.2801028 -0.0029121689 -0.054581646 -0.47385484 0.17112483 -0.12066923 -0.042173345 0.1395337 0.26115036 0.012869649 0.009291686 -0.0026459037 -0.075331464 0.017840583 -0.26869613 -0.21820338 -0.17084768 -0.1022808 -0.055290595 0.13513643 0.12362477 -0.10980586 0.13980341 -0.20233242 0.08813751 0.3849736 -0.10653763 -0.06199595 0.028849555 0.03230154 0.023856193 0.069950655 0.19310954 -0.077677034 -0.144811'
import numpy as np
average_glove_vector = np.array(vec_string.split(" "))
print(average_glove_vector)
I am finding and plotting local maximas and minimas on a waveform with the function findpeaks. I would like to be able to select some of those peaks with a pointer directly from the plot and get the coordinates into the workspace.
Is that possible?
Here is a subset of an example dataset:
data = [-4.89540984473946e-06 -4.89046450287593e-06 -4.88283149336408e-06 -4.87095198116254e-06 -4.90712807029133e-06 -4.91927636347547e-06 -4.84407526018980e-06 -4.87589730823133e-06 -4.92470545237800e-06 -4.84429026519065e-06 -4.94884075275366e-06 -4.97668505593799e-06 -5.05091858731457e-06 -4.91637367843710e-06 -4.84267768702634e-06 -4.89191584860588e-06 -4.84660167647784e-06 -4.83337832656191e-06 -4.79032179995216e-06 -4.76624025231771e-06 -4.75887604778215e-06 -4.70856280330800e-06 -4.64964899691363e-06 -4.72963414438675e-06 -4.83950621114218e-06 -4.81381203536647e-06 -4.83251825696249e-06 -4.87320964430400e-06 -4.90336533160774e-06 -4.83783986967173e-06 -4.80376018565747e-06 -4.74447010720748e-06 -4.84961187054251e-06 -4.83536719945138e-06 -4.79919111834559e-06 -4.85611601862430e-06 -4.82606784644511e-06 -4.85471844872184e-06 -4.84386025701412e-06 -4.81515589140679e-06 -4.83353956282112e-06 -4.88793805514151e-06 -4.79279444702247e-06 -4.81897238803632e-06 -4.80263134571406e-06 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prominence_factor_localp2p = 0.0000004;
figure;
subplot(2,1,1)
findpeaks (data,'MinPeakProminence', prominence_factor_localp2p);
subplot(2,1,2)
findpeaks (-data,'MinPeakProminence', prominence_factor_localp2p);
Try
[x,y] = ginput(1) % Returns x and y after one mouse click
if you want to get one peak or:
[X,Y] = ginput() % Returns X=[x1..xN] and Y=[y1..yN] after N clicks, stop with ENTER
if you want to get multiple peaks in vector format
Unfortunately, I don't have the Signal Processing Toolbox (findpeaks is part of the SPT) so I'll answer this without it.
Say you have a function:
x = sin(linspace(0, 2*pi, 1000)) + 0.1*rand(1, 1000);
plot(linspace(0, 2*pi, 1000),x);
This gives be the following plot:
Now, using the function "Data Cursor" ,
you can select a point on the plot by clicking at it. You can drag the data tip around if you didn't hit the correct point at the first try. If you right click on the frame that comes up, you can export the [x,y] values to the workspace:
This gives the following variable (struct) in the workspace:
peak_value_1
peak_value_1 =
Target: [1x1 Line]
Position: [1.5849 1.0984]
DataIndex: 253
Now you have the positions of the maximum point:
position = peak_value_1.Position
position =
1.5849 1.0984
How you want to proceed from here is your call. Note that you can create multiple data tips by holding the Shift button while clicking.
I'm using MATLAB to plot a colormap of the following data matrix:
1010.89914200000 1006.07847500000 1013.91775300000 1016.37012500000 1012.64447500000 1005.15384200000 998.323644400000 1007.09643600000 1010.39007800000 1010.71070000000 1007.75920300000 1003.43986900000 1001.77407500000 1000.93290600000 1009.19935000000 1010.79651100000 1006.15733600000 1001.08001400000 1006.62765600000 1008.98760600000 1012.59690300000 1014.13669400000 1012.41850000000 1002.83265600000
1010.20939200000 1006.22354400000 1014.13985000000 1016.01628600000 1012.16700600000 1004.47184200000 1000.64279200000 1006.93063300000 1009.98950000000 1010.53409400000 1007.46695300000 1003.07056100000 1001.31949400000 1001.61572800000 1009.12864700000 1010.45935000000 1006.24603900000 1001.40907500000 1006.31782500000 1009.00493300000 1012.13883300000 1013.93106700000 1011.88797800000 1003.01553600000
1009.70062500000 1006.35064700000 1014.37573900000 1015.70891100000 1011.51357800000 1003.79413100000 1001.69951400000 1006.79389200000 1009.72253100000 1010.41560600000 1007.01026100000 1002.91738300000 1000.86708100000 1002.11736400000 1009.09675300000 1009.98591400000 1005.46058600000 1000.94756700000 1006.18716400000 1008.73213100000 1012.14396700000 1013.51734400000 1010.97627200000 1003.29271400000
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1009.26808100000 1006.29626900000 1014.67797500000 1015.67235600000 1011.20240600000 1003.14341400000 1000.42042500000 1006.97025800000 1009.47529700000 1010.42883100000 1006.41034400000 1003.31582500000 1001.22851700000 1003.87331700000 1009.01971100000 1009.26751700000 1004.97643300000 1000.38995600000 1006.25921900000 1008.81359400000 1012.25596700000 1013.53560600000 1010.21200300000 1004.63438300000
1009.71863900000 1006.81711100000 1014.88478900000 1016.09375300000 1011.26197200000 1003.11559200000 1000.71963300000 1007.50932500000 1009.46868300000 1010.70578900000 1006.41695000000 1003.87943100000 1001.47584700000 1004.88967200000 1009.38281100000 1009.50196100000 1005.06519200000 1001.66275800000 1006.49482200000 1009.35829200000 1012.54210000000 1013.92888300000 1009.72913100000 1005.35431100000
1010.74544400000 1007.71330600000 1015.30482800000 1016.41307200000 1011.40723900000 1003.05097800000 1001.88330600000 1007.78023100000 1009.79253600000 1011.11156400000 1006.55320300000 1004.49287800000 1001.40507500000 1005.91256700000 1009.88450300000 1009.38280000000 1004.75816700000 1003.58816900000 1006.68395600000 1009.83212800000 1012.71196100000 1014.27383300000 1009.46791900000 1005.91156100000
1011.06202800000 1008.61448600000 1016.07176900000 1016.77051900000 1011.43023100000 1002.91816900000 1003.01835800000 1008.37585300000 1010.16145800000 1011.46680800000 1006.80956900000 1004.88291700000 1001.64883900000 1006.73743100000 1010.37819200000 1009.44031900000 1005.11520300000 1004.70793600000 1007.29316900000 1010.53632800000 1013.30822200000 1014.53464700000 1009.54564700000 1006.43934700000
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using:
imagesc(data)
Now I need to normalize each column separately in the following way: finding the maximum value of each column and set it's color, and finding the lowest value of each column and set it's color as well.
So in the end I need a colormap which have the same color for every local maximum and minimum of a column.
I'm quite new to plotting, so I tried looking for normalized colormaps here and on the web, but didn't find anything that can help me.
You're not going to be able to do this strictly with a colormap because the colormap is applied globally to the image and the color used for the local max in one column would be applied to all elements with that value regardless of whether they were the local max of their respective column.
Instead, you can normalize each column of your data and then display that.
%// Subtract off the minimum of each column
D = bsxfun(#minus, data, min(data, [], 1));
%// Divide by the maximum
D = bsxfun(#rdivide, D, max(D, [], 1));
%// Display the result
imagesc(D);
I have a data that are being recorded and the time is used in epoch. I want to draw a figure where the x axis from zero to the time that the recorder stopped recording in seconds.
From my search I found that the output for decoding is a string that represent a date for example 01-Jan-1970 00:00:01 for all the data. how can I get different data using variable double or float array with the seconds only.
The method I used is :
output = datastr(datenum('1970','yyyy') + **timeinepoch** / 86400)
The problem is that all numbers give me the same output ?? and I want my data to be in array of seconds
here is a sample of my data timeinepoch
1.431344867477355
1.431344857732564
1.431344856832909
Here is the full data set:
1.43134485683291 1.43134485693360 1.43134485703513 1.43134485713490 1.43134485723280 1.43134485733824 1.43134485743525 1.43134485753449 1.43134485763714 1.43134485773256 1.43134485783254 1.43134485793235 1.43134485803481 1.43134485813486 1.43134485823259 1.43134485835510 1.43134485845240 1.43134485855250 1.43134485863259 1.43134485875249 1.43134485901518 1.43134485905522 1.43134485915475 1.43134485925273 1.43134485935277 1.43134485961262 1.43134485965299 1.43134485975277 1.43134486003268 1.43134486005289 1.43134486015272 1.43134486025242 1.43134486035263 1.43134486045254 1.43134486055257 1.43134486065708 1.43134486075720 1.43134486085483 1.43134486095482 1.43134486105451 1.43134486115239 1.43134486125257 1.43134486135232 1.43134486145473 1.43134486156251 1.43134486166082 1.43134486175443 1.43134486185417 1.43134486195630 1.43134486205711 1.43134486215445 1.43134486225478 1.43134486235478 1.43134486245782 1.43134486255472 1.43134486265428 1.43134486275417 1.43134486285418 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% vector of epoch times... (this is one of the values you posted)
epoch = 1.431344867477355;
% something is funky with your times, they are scaled
% by a factor of 1e9, so we'll fix that here
epoch = epoch * 1e9;
% epoch time -> MATLAB datenum
dnum = datenum(1970,1,1,0,0,epoch);
% split time into parts
[Y, M, D, H, MN, S] = datevec(dnum);
% S is the seconds
The output is:
Y =
2015
M =
5
D =
11
H =
11
MN =
47
S =
47.4774
This command gives you the milliseconds since epoch(1-Jan-1970) in matlab.
>> int64(milliseconds(datetime('now','Timezone','UTC')-datetime('1970-01-01','Timezone','UTC')))
I verified it using https://www.epochconverter.com/
I'd like to make one period representative signal.
There are several signals in different periods.
I don't want to cut one period signal from several signals.
How can I solve this problem in matlab?
Below is the signal data values.
Thank you.
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If by "one period representative signal" you mean "get the average signal over all the periods", this is how.
This is what your data looks like:
If you know in advance how many cycles are in your signal (9 for your data above), then just reshape your signal into a 9x178 matrix (==numel(signal)/9) and find column means (ie a 1x178 matrix with the average signal).
nwaves = 9;
sig2 = reshape(sig,[numel(sig)/nwaves nwaves])';
avgSig = mean(sig2,1);
plot(avgSig);
If you don't know how many cycles in your signal...you could try doing the fourier transform, but it's not guaranteed...and if the number of data points isn't an exact multiple of the period length, then you'll have to modify the code to deal with that.
% get fourier transform
a = fft(sig);
% get period with max amplitude (but not period=0)
[val ix] = max(abs(a(2:end))) % don't include period=0
nwaves = ix + 1 % add 1 because of the offset above
% then calculate avg & plot as before with this `nwaves`.
(If you plot each 'cycle' though you'll notice that splitting into every 178 elements doesn't quite section your wave into parts from minimum to minimum - you might need to find a smarter way of doing that).