From 44fc725a8d97b02812bbe0571cdc5a1f7c9b660e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=D0=9F=D0=BE=D0=BB=D1=8C=D0=B7=D0=BE=D0=B2=D0=B0=D1=82?= =?UTF-8?q?=D0=B5=D0=BB=D1=8C=20=E2=84=96=2013=20=D0=B0=D1=83=D0=B4=D0=B8?= =?UTF-8?q?=D1=82=D0=BE=D1=80=D0=B8=D0=B8=20=D0=96-202?= Date: Wed, 11 Feb 2026 12:27:33 +0300 Subject: [PATCH] =?UTF-8?q?file:=20=D0=B4=D0=BE=D0=B1=D0=B0=D0=B2=D0=BB?= =?UTF-8?q?=D0=B5=D0=BD=D1=8B=20assets,=20Prog1,=20Perem?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ТЕМА1/Perem | 351 ++++++++++++++++++++++++++++++++++++++ ТЕМА1/Prog1.m | 5 + ТЕМА1/report.md | 404 ++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 760 insertions(+) create mode 100644 ТЕМА1/Perem create mode 100644 ТЕМА1/Prog1.m diff --git a/ТЕМА1/Perem b/ТЕМА1/Perem new file mode 100644 index 0000000..3522ed0 --- /dev/null +++ b/ТЕМА1/Perem @@ -0,0 +1,351 @@ +# Created by Octave 8.3.0, Wed Feb 11 12:15:55 2026 GMT +# name: A +# type: matrix +# rows: 4 +# columns: 6 + -0.73727231346913291 0.61252763556875134 -1.0247603422502973 -0.48163379138569112 0.22966452931337661 1.1971226141126756 + -1.502818910650384 -0.17905606695380771 1.4594763002989175 -0.47079045483830101 0.30012227121004409 0.020586940300524166 + 0.34534485618162197 2.0787797069715035 -1.0798672376220004 -0.7044893565142325 1.252896784998091 0.84114816085338584 + 0.55306389062025596 0.8516157716753715 -0.76826857493889833 1.2280384049799278 -0.7263373574957438 -0.29429814112780134 + + +# name: B +# type: matrix +# rows: 4 +# columns: 7 + 0.59105239060658876 0.095642559923889259 0.91180903661203105 0.39424578547474853 0.22193040133861641 0.71907502413404578 0.82459135092380353 + 0.94275390552909255 0.39913668632638211 0.84966004546821772 0.23745097838092799 0.68745282082163239 0.82789158737183677 0.18911279572064787 + 0.94109544669181544 0.34119623204694649 0.28108673141363094 0.17795676332466015 0.27178786557033852 0.63794937967714971 0.8560881757234946 + 0.30013238231898998 0.87968112363078022 0.58280067970151017 0.5333001805222366 0.63388551753916078 0.015838881753381551 0.27504917746652924 + + +# name: B1 +# type: matrix +# rows: 4 +# columns: 7 + 0.76879931751178654 0.30926131333209017 0.9548869234689682 0.62788994694512235 0.47109489631985657 0.84798291500126688 0.90807012445284396 + 0.97095515114195285 0.63177265398747839 0.92177006106090131 0.48728941952491434 0.82912774698572977 0.90988548036103789 0.43487101043947257 + 0.97010074048617001 0.58412004934512096 0.53017613244433304 0.42184921870813052 0.52133277814687473 0.79871733402822165 0.92525033138253698 + 0.54784339214687072 0.93791317488922199 0.76341383253220541 0.73027404480936919 0.79616927693748696 0.12585261917569118 0.52445131086358177 + + +# name: B1D +# type: matrix +# rows: 4 +# columns: 1 + 0.76879931751178654 + 0.63177265398747839 + 0.53017613244433304 + 0.73027404480936919 + + +# name: B2 +# type: matrix +# rows: 4 +# columns: 7 + -0.52585061811651135 -2.3471373705029488 -0.092324700512675814 -0.93078074317774195 -1.5053914537473123 -0.32978958159472416 -0.19286734757855409 + -0.058950000153664875 -0.91845134851017651 -0.16291895600568987 -1.4377940836294052 -0.37476207605560669 -0.18887306629516837 -1.6654116391836846 + -0.060710713412156017 -1.0752975066643167 -1.2690920045542944 -1.7262146608661322 -1.3027334229624392 -0.44949634098393082 -0.15538189912268596 + -1.2035316272622167 -0.12819579668843345 -0.53991003839287555 -0.62867082287528797 -0.45588691255473801 -4.1452874914653259 -1.2908053701522193 + + +# name: B3 +# type: matrix +# rows: 4 +# columns: 7 + 0.55723518882456657 0.095496811560353265 0.79061273574573154 0.38411194201159027 0.22011308904269311 0.65868898783702878 0.7342704292445873 + 0.80917925659859702 0.3886230327382853 0.75105599747087715 0.23522589537375255 0.63457061759123157 0.73650681538836982 0.18798758240267766 + 0.80820369708058359 0.3346146066099952 0.27739989430765039 0.17701897560099394 0.26845410227566069 0.59554939303711385 0.75528455029163566 + 0.29564667373130898 0.77053566727371769 0.55036444839846288 0.50837800219706897 0.59227990787181195 0.015838219511181712 0.27159426626067934 + + +# name: BS1 +# type: matrix +# rows: 4 +# columns: 7 + 0.30013238231898998 0.095642559923889259 0.28108673141363094 0.17795676332466015 0.22193040133861641 0.015838881753381551 0.18911279572064787 + 0.59105239060658876 0.34119623204694649 0.58280067970151017 0.23745097838092799 0.27178786557033852 0.63794937967714971 0.27504917746652924 + 0.94109544669181544 0.39913668632638211 0.84966004546821772 0.39424578547474853 0.63388551753916078 0.71907502413404578 0.82459135092380353 + 0.94275390552909255 0.87968112363078022 0.91180903661203105 0.5333001805222366 0.68745282082163239 0.82789158737183677 0.8560881757234946 + + +# name: BS2 +# type: matrix +# rows: 4 +# columns: 7 + 0.59105239060658876 0.095642559923889259 0.91180903661203105 0.39424578547474853 0.22193040133861641 0.71907502413404578 0.82459135092380353 + 0.94109544669181544 0.34119623204694649 0.28108673141363094 0.17795676332466015 0.27178786557033852 0.63794937967714971 0.8560881757234946 + 0.94275390552909255 0.39913668632638211 0.84966004546821772 0.23745097838092799 0.68745282082163239 0.82789158737183677 0.18911279572064787 + 0.30013238231898998 0.87968112363078022 0.58280067970151017 0.5333001805222366 0.63388551753916078 0.015838881753381551 0.27504917746652924 + + +# name: C +# type: double_range +# base, limit, increment +4 27 1 + + +# name: D +# type: matrix +# rows: 4 +# columns: 6 + 4 8 12 16 20 24 + 5 9 13 17 21 25 + 6 10 14 18 22 26 + 7 11 15 19 23 27 + + +# name: D1 +# type: scalar +22 + + +# name: D2 +# type: matrix +# rows: 1 +# columns: 3 + 18 22 26 + + +# name: D3 +# type: matrix +# rows: 2 +# columns: 3 + 13 17 21 + 14 18 22 + + +# name: D4 +# type: matrix +# rows: 1 +# columns: 5 + 19 20 21 22 23 + + +# name: D5 +# type: matrix +# rows: 2 +# columns: 3 + 6 14 26 + 7 15 27 + + +# name: DB +# type: diagonal matrix +# rows: 4 +# columns: 4 +0.76879931751178654 +0.63177265398747839 +0.53017613244433304 +0.73027404480936919 + + +# name: DDD +# type: matrix +# rows: 4 +# columns: 6 + 64 512 1728 4096 8000 13824 + 125 729 2197 4913 9261 15625 + 216 1000 2744 5832 10648 17576 + 343 1331 3375 6859 12167 19683 + + +# name: DL +# type: bool matrix +# rows: 4 +# columns: 6 + 0 0 0 0 1 1 + 0 0 0 0 1 1 + 0 0 0 0 1 1 + 0 0 0 0 1 1 + + +# name: DP1 +# type: matrix +# rows: 1 +# columns: 6 + 840 7920 32760 93024 212520 421200 + + +# name: DS1 +# type: matrix +# rows: 1 +# columns: 6 + 22 38 54 70 86 102 + + +# name: DS2 +# type: matrix +# rows: 4 +# columns: 1 + 84 + 90 + 96 + 102 + + +# name: Dstolb +# type: matrix +# rows: 24 +# columns: 1 + 4 + 5 + 6 + 7 + 8 + 9 + 10 + 11 + 12 + 13 + 14 + 15 + 16 + 17 + 18 + 19 + 20 + 21 + 22 + 23 + 24 + 25 + 26 + 27 + + +# name: Dsum +# type: scalar +22.547300573537278 + + +# name: Dsum2 +# type: scalar +-0.057010896737607175 + + +# name: E +# type: matrix +# rows: 7 +# columns: 6 + -1.3615601059651763 2.4051577041657137 -0.47660048596686944 -1.022927977372607 1.3797833104717792 1.4302429032552979 + -0.06599454314041181 1.4455379880627621 -0.55975816400814127 0.60593865914243417 -0.069706088261014543 0.15082093809630465 + -1.5297388736122668 1.4870110910353938 -0.44561084060522976 -0.32149087600351833 0.39327485227217829 1.1739575485970415 + -0.29110679745070261 1.023069153614264 -0.65934081875611439 0.22787271087229993 -0.0025857875468198732 0.46958768681780938 + -0.75230050784941283 1.117659909401818 -0.0045935093155337059 0.15642869455968733 0.1373968543088564 0.3218929861503898 + -1.5452527897305821 1.6318591788852228 -0.22966056633712781 -1.1660720800323485 1.2013950857470637 1.4098133212944439 + -0.44438524249162564 2.4850781416685117 -1.7047760846414701 -0.75151761265019712 1.1189479765487891 1.6301807403191899 + + +# name: F +# type: matrix +# rows: 4 +# columns: 13 + -0.73727231346913291 0.61252763556875134 -1.0247603422502973 -0.48163379138569112 0.22966452931337661 1.1971226141126756 0.59105239060658876 0.095642559923889259 0.91180903661203105 0.39424578547474853 0.22193040133861641 0.71907502413404578 0.82459135092380353 + -1.502818910650384 -0.17905606695380771 1.4594763002989175 -0.47079045483830101 0.30012227121004409 0.020586940300524166 0.94275390552909255 0.39913668632638211 0.84966004546821772 0.23745097838092799 0.68745282082163239 0.82789158737183677 0.18911279572064787 + 0.34534485618162197 2.0787797069715035 -1.0798672376220004 -0.7044893565142325 1.252896784998091 0.84114816085338584 0.94109544669181544 0.34119623204694649 0.28108673141363094 0.17795676332466015 0.27178786557033852 0.63794937967714971 0.8560881757234946 + 0.55306389062025596 0.8516157716753715 -0.76826857493889833 1.2280384049799278 -0.7263373574957438 -0.29429814112780134 0.30013238231898998 0.87968112363078022 0.58280067970151017 0.5333001805222366 0.63388551753916078 0.015838881753381551 0.27504917746652924 + + +# name: FF +# type: matrix +# rows: 2 +# columns: 4 + 1 1 1 1 + 1 1 1 1 + + +# name: G +# type: matrix +# rows: 4 +# columns: 6 + -2.9490892538765316 4.9002210845500107 -12.297124107003569 -7.706140662171058 4.5932905862675319 28.730942738704215 + -7.5140945532519199 -1.6115046025842694 18.973191903885926 -8.0034377322511165 6.302567695410926 0.51467350751310414 + 2.0720691370897319 20.787797069715033 -15.118141326708006 -12.680808417256184 27.563729269958003 21.869852182188033 + 3.8714472343417916 9.3677734884290871 -11.524028624083474 23.332729694618628 -16.705759222402108 -7.9460498104506359 + + +# name: GG +# type: matrix +# rows: 5 +# columns: 5 + 0 0 0 0 0 + 0 0 0 0 0 + 0 0 0 0 0 + 0 0 0 0 0 + 0 0 0 0 0 + + +# name: H +# type: string +# elements: 1 +# length: 24 +This is a symbols vector + + +# name: L +# type: complex matrix +# rows: 1 +# columns: 2 + (-2,23.100000000000001) (3,-5.5999999999999996) + + +# name: M +# type: matrix +# rows: 4 +# columns: 6 + -0.65535316752811812 1.0889380187888913 -2.732694246000793 -1.7124757027046795 1.0207312413927849 6.3846539419342703 + -1.6697987896115378 -0.35811213390761543 4.2162648675302057 -1.7785417182780259 1.4005705989802057 0.11437189055846758 + 0.46045980824216265 4.6195104599366736 -3.3595869614906682 -2.81795742605693 6.125273171101778 4.8599671515973411 + 0.86032160763150922 2.0817274418731304 -2.5608952497963275 5.1850510432485839 -3.7123909383115796 -1.7657888467668079 + + +# name: NN +# type: matrix +# rows: 1 +# columns: 20 + 11.5 12.689473684210526 13.878947368421052 15.06842105263158 16.257894736842104 17.44736842105263 18.63684210526316 19.826315789473686 21.015789473684212 22.205263157894738 23.394736842105264 24.58421052631579 25.773684210526316 26.963157894736842 28.152631578947371 29.342105263157897 30.531578947368423 31.721052631578949 32.910526315789475 34.100000000000001 + + +# name: ans +# type: scalar +0 + + +# name: dinv +# type: matrix +# rows: 4 +# columns: 4 + 0.52600040745740051 -0.043198551377800619 -0.24925039922686401 0.047027740270817152 + -0.043198551377800619 0.43540238432892597 0.08064099872952471 0.31914673291725865 + -0.24925039922686401 0.08064099872952471 0.24810891368783075 -0.0022361058657988484 + 0.047027740270817152 0.31914673291725865 -0.0022361058657988484 0.51804403619424122 + + +# name: dt +# type: scalar +135.51250352394734 + + +# name: elem +# type: scalar +28 + + +# name: i +# type: scalar +19 + + +# name: k +# type: scalar +7 + + +# name: nm +# type: matrix +# rows: 1 +# columns: 2 + 4 7 + + diff --git a/ТЕМА1/Prog1.m b/ТЕМА1/Prog1.m new file mode 100644 index 0000000..3089023 --- /dev/null +++ b/ТЕМА1/Prog1.m @@ -0,0 +1,5 @@ +D1=D(3,5) +D2=D(3,4:end) +D3=D(2:3,3:5) +D4=D(16:20) +D5=D(3:4,[1,3,6]) diff --git a/ТЕМА1/report.md b/ТЕМА1/report.md index e69de29..ddd0f6d 100644 --- a/ТЕМА1/report.md +++ b/ТЕМА1/report.md @@ -0,0 +1,404 @@ +#ОТЧЁТ 1 + +##2 + +##3 + +##4 + +##5 +>> help randn +'randn' is a built-in function from the file libinterp/corefcn/rand.cc + + -- X = randn (N) + -- X = randn (M, N, ...) + -- X = randn ([M N ...]) + -- X = randn (..., "single") + -- X = randn (..., "double") + -- V = randn ("state") + -- randn ("state", V) + -- randn ("state", "reset") + -- V = randn ("seed") + -- randn ("seed", V) + -- randn ("seed", "reset") + + ##6 +матрица А со случайными, нормально распределенными элементами, с 4 строками и 6 столбцами +>> A=randn(4,6) +A = + + -0.737272 0.612528 -1.024760 -0.481634 0.229665 1.197123 + -1.502819 -0.179056 1.459476 -0.470790 0.300122 0.020587 + 0.345345 2.078780 -1.079867 -0.704489 1.252897 0.841148 + 0.553064 0.851616 -0.768269 1.228038 -0.726337 -0.294298 + +матрица В 4х7 со случайными элементами, равномерно распределенными в диапазоне от 0 до 1 +>> B=rand(4,7) +B = + + 0.591052 0.095643 0.911809 0.394246 0.221930 0.719075 0.824591 + 0.942754 0.399137 0.849660 0.237451 0.687453 0.827892 0.189113 + 0.941095 0.341196 0.281087 0.177957 0.271788 0.637949 0.856088 + 0.300132 0.879681 0.582801 0.533300 0.633886 0.015839 0.275049 + +вектор С с целыми числами от 4 до 27 +>> C = 4:27 +C = + + 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 + +символьный вектор Н +>> H = "This is a symbols vector" +H = This is a symbols vector + +вектор-строка L с 2 комплексными элементами +L = + + -2.0000 + 23.1000i 3.0000 - 5.6000i + +##7 +преобразование матрицы С в матрицу с 6 столбцами +>> D = reshape(C,[],6) +D = + + 4 8 12 16 20 24 + 5 9 13 17 21 25 + 6 10 14 18 22 26 + 7 11 15 19 23 27 + +матричное перемножение В и А с транспонированием матрицы В (число столбцов в В должно совпадать с числом строк в А) +>> E = B'*A +E = + + -1.3616e+00 2.4052e+00 -4.7660e-01 -1.0229e+00 1.3798e+00 1.4302e+00 + -6.5995e-02 1.4455e+00 -5.5976e-01 6.0594e-01 -6.9706e-02 1.5082e-01 + -1.5297e+00 1.4870e+00 -4.4561e-01 -3.2149e-01 3.9327e-01 1.1740e+00 + -2.9111e-01 1.0231e+00 -6.5934e-01 2.2787e-01 -2.5858e-03 4.6959e-01 + -7.5230e-01 1.1177e+00 -4.5935e-03 1.5643e-01 1.3740e-01 3.2189e-01 + -1.5453e+00 1.6319e+00 -2.2966e-01 -1.1661e+00 1.2014e+00 1.4098e+00 + -4.4439e-01 2.4851e+00 -1.7048e+00 -7.5152e-01 1.1189e+00 1.6302e+00 + +создание матрицы путем «горизонтального» соединения матриц А и В (числа строк у соединяемых матриц должны совпадать) +>> F = [A,B] +F = + + Columns 1 through 12: + + -0.737272 0.612528 -1.024760 -0.481634 0.229665 1.197123 0.591052 0.095643 0.911809 0.394246 0.221930 0.719075 + -1.502819 -0.179056 1.459476 -0.470790 0.300122 0.020587 0.942754 0.399137 0.849660 0.237451 0.687453 0.827892 + 0.345345 2.078780 -1.079867 -0.704489 1.252897 0.841148 0.941095 0.341196 0.281087 0.177957 0.271788 0.637949 + 0.553064 0.851616 -0.768269 1.228038 -0.726337 -0.294298 0.300132 0.879681 0.582801 0.533300 0.633886 0.015839 + + Column 13: + + 0.824591 + 0.189113 + 0.856088 + 0.275049 + +поэлементное перемножение матриц A и D (размеры матриц должны совпадать) +>> G = A.*D +G = + + -2.9491 4.9002 -12.2971 -7.7061 4.5933 28.7309 + -7.5141 -1.6115 18.9732 -8.0034 6.3026 0.5147 + 2.0721 20.7878 -15.1181 -12.6808 27.5637 21.8699 + 3.8714 9.3678 -11.5240 23.3327 -16.7058 -7.9460 + +поэлементное деление элементов матрицы G на 4.5 +>> M = G./4.5 +M = + + -0.6554 1.0889 -2.7327 -1.7125 1.0207 6.3847 + -1.6698 -0.3581 4.2163 -1.7785 1.4006 0.1144 + 0.4605 4.6195 -3.3596 -2.8180 6.1253 4.8600 + 0.8603 2.0817 -2.5609 5.1851 -3.7124 -1.7658 + +поэлементное возведение в степень элементов матрицы D +>> DDD = D.^3 +DDD = + + 64 512 1728 4096 8000 13824 + 125 729 2197 4913 9261 15625 + 216 1000 2744 5832 10648 17576 + 343 1331 3375 6859 12167 19683 + +создание логической матрицы, совпадающей по размерам с D и с элементами по заданному условию +>> DL = D >= 20 +DL = + + 0 0 0 0 1 1 + 0 0 0 0 1 1 + 0 0 0 0 1 1 + 0 0 0 0 1 1 + +превращение матрицы в вектор-столбец +>> Dstolb=D(:) +Dstolb = + + 4 + 5 + 6 + 7 + 8 + 9 + 10 + 11 + 12 + 13 + 14 + 15 + 16 + 17 + 18 + 19 + 20 + 21 + 22 + 23 + 24 + 25 + 26 + 27 + +##8 +математические функции: +>> B1=sqrt(B) +B1 = + + 0.7688 0.3093 0.9549 0.6279 0.4711 0.8480 0.9081 + 0.9710 0.6318 0.9218 0.4873 0.8291 0.9099 0.4349 + 0.9701 0.5841 0.5302 0.4218 0.5213 0.7987 0.9253 + 0.5478 0.9379 0.7634 0.7303 0.7962 0.1259 0.5245 + +>> B2=log(B) +B2 = + + -0.525851 -2.347137 -0.092325 -0.930781 -1.505391 -0.329790 -0.192867 + -0.058950 -0.918451 -0.162919 -1.437794 -0.374762 -0.188873 -1.665412 + -0.060711 -1.075298 -1.269092 -1.726215 -1.302733 -0.449496 -0.155382 + -1.203532 -0.128196 -0.539910 -0.628671 -0.455887 -4.145287 -1.290805 + +>> B3=sin(B) +B3 = + + 0.557235 0.095497 0.790613 0.384112 0.220113 0.658689 0.734270 + 0.809179 0.388623 0.751056 0.235226 0.634571 0.736507 0.187988 + 0.808204 0.334615 0.277400 0.177019 0.268454 0.595549 0.755285 + 0.295647 0.770536 0.550364 0.508378 0.592280 0.015838 0.271594 + +операции с матрицами: +>> k=length(B1) +k = 7 +>> nm=size(B1) +nm = + + 4 7 + +>> elem=numel(B1) +elem = 28 +>> NN=linspace(11.5,34.1,20) +NN = + + Columns 1 through 15: + + 11.500 12.689 13.879 15.068 16.258 17.447 18.637 19.826 21.016 22.205 23.395 24.584 25.774 26.963 28.153 + + Columns 16 through 20: + + 29.342 30.532 31.721 32.911 34.100 + +>> FF=ones(2,4) +FF = + + 1 1 1 1 + 1 1 1 1 + +>> GG=zeros(5) +GG = + + 0 0 0 0 0 + 0 0 0 0 0 + 0 0 0 0 0 + 0 0 0 0 0 + 0 0 0 0 0 + +>> B1D=diag(B1) +B1D = + + 0.7688 + 0.6318 + 0.5302 + 0.7303 + +>> DB=diag(B1D) +DB = + +Diagonal Matrix + + 0.7688 0 0 0 + 0 0.6318 0 0 + 0 0 0.5302 0 + 0 0 0 0.7303 + +>> BS1=sort(B) +BS1 = + + 0.300132 0.095643 0.281087 0.177957 0.221930 0.015839 0.189113 + 0.591052 0.341196 0.582801 0.237451 0.271788 0.637949 0.275049 + 0.941095 0.399137 0.849660 0.394246 0.633886 0.719075 0.824591 + 0.942754 0.879681 0.911809 0.533300 0.687453 0.827892 0.856088 + +>> BS2=sortrows(B,2) +BS2 = + + 0.591052 0.095643 0.911809 0.394246 0.221930 0.719075 0.824591 + 0.941095 0.341196 0.281087 0.177957 0.271788 0.637949 0.856088 + 0.942754 0.399137 0.849660 0.237451 0.687453 0.827892 0.189113 + 0.300132 0.879681 0.582801 0.533300 0.633886 0.015839 0.275049 + +>> DS1=sum(D) +DS1 = + + 22 38 54 70 86 102 + +>> DS2=sum(D,2) +DS2 = + + 84 + 90 + 96 + 102 + +>> DP1=prod(D) +DP1 = + + 840 7920 32760 93024 212520 421200 + +>> dt=det(A*A') +dt = 135.51 +>> dinv=inv(A*A') +dinv = + + 5.2600e-01 -4.3199e-02 -2.4925e-01 4.7028e-02 + -4.3199e-02 4.3540e-01 8.0641e-02 3.1915e-01 + -2.4925e-01 8.0641e-02 2.4811e-01 -2.2361e-03 + 4.7028e-02 3.1915e-01 -2.2361e-03 5.1804e-01 + +##9 +Изучили работу с индексацией элементов матриц: +>> D1=D(3,5) +D1 = 22 +>> D2=D(3,4:end) +D2 = + + 18 22 26 + +>> D3=D(2:3,3:5) +D3 = + + 13 17 21 + 14 18 22 + +>> D4=D(16:20) +D4 = + + 19 20 21 22 23 + +>> D5=D(3:4,[1,3,6]) +D5 = + + 6 14 26 + 7 15 27 + +##10 +цикл по перечислению: +>> Dsum=0 +Dsum = 0 +>> for i=1:6 +Dsum=Dsum+sqrt(D(2,i)) +endfor +Dsum = 2.2361 +Dsum = 5.2361 +Dsum = 8.8416 +Dsum = 12.965 +Dsum = 17.547 +Dsum = 22.547 + +цикл пока выполняется условие: +>> Dsum2=0;i=1 +i = 1 +>> while (D(i)<22) +Dsum2=Dsum2+sin(D(i)) +i=i+1 +endwhile +Dsum2 = -0.7568 +i = 2 +Dsum2 = -1.7157 +i = 3 +Dsum2 = -1.9951 +i = 4 +Dsum2 = -1.3382 +i = 5 +Dsum2 = -0.3488 +i = 6 +Dsum2 = 0.063321 +i = 7 +Dsum2 = -0.4807 +i = 8 +Dsum2 = -1.4807 +i = 9 +Dsum2 = -2.0173 +i = 10 +Dsum2 = -1.5971 +i = 11 +Dsum2 = -0.6065 +i = 12 +Dsum2 = 0.043799 +i = 13 +Dsum2 = -0.2441 +i = 14 +Dsum2 = -1.2055 +i = 15 +Dsum2 = -1.9565 +i = 16 +Dsum2 = -1.8066 +i = 17 +Dsum2 = -0.8937 +i = 18 +Dsum2 = -0.057011 +i = 19 + +условие if: +D(3,5)>=20 + +##11 +>> graphics_toolkit('gnuplot') +>> plot(D(1,:),B([2,4],1:6)) +>> hist(A(:),6) +>> pie(C) +>> bar(C) + +##12 +>> Prog1 +D1 = 22 +D2 = + + 18 22 26 + +D3 = + + 13 17 21 + 14 18 22 + +D4 = + + 19 20 21 22 23 + +D5 = + + 6 14 26 + 7 15 27 + +##13 +Создали файл "Perem" \ No newline at end of file