From be511dd531d7e1d15e3939b60426a2a460eb9ca3 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=2012=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 12:28:34 +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 | 418 ++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 774 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..0986162 --- /dev/null +++ b/ТЕМА1/Perem @@ -0,0 +1,351 @@ +# Created by Octave 8.3.0, Wed Feb 11 12:16:26 2026 GMT +# name: A +# type: matrix +# rows: 4 +# columns: 6 + -0.7051571199484552 -0.88179450715020191 -1.1144049175772983 -0.49983091636335197 0.80840661784520551 -0.8140870012861241 + -0.71356520039087279 0.28649457280020335 -0.27474499334127955 -1.941373292643567 -0.68445281544335912 -0.42130829726717756 + -0.9316641000515139 0.4764351481510109 -1.1302362269341515 0.24824863467958955 -1.3404175089410415 -0.60400871436213655 + -2.0625226747527567 1.1710365095254567 0.23320666779954835 -0.16560634546901296 0.33837193758010109 -1.2632795600181634 + + +# name: B +# type: matrix +# rows: 4 +# columns: 7 + 0.30214806704946751 0.40409442769479464 0.23456721302917516 0.84005767746636939 0.3769672775924694 0.056362134853508494 0.87804683029516695 + 0.43283745578216881 0.91732899553934311 0.36649026778199267 0.25103109317549377 0.2753769836191976 0.23136902913417301 0.14464393182336366 + 0.83846241946131228 0.83936583114391883 0.019972206982809437 0.76613445900878152 0.84915636079520762 0.93618147136069207 0.65294400358631732 + 0.91017724807744727 0.24121666030738809 0.29524982943157585 0.36584571518072162 0.10396673725177785 0.64040855587093437 0.13225228992422355 + + +# name: B1 +# type: matrix +# rows: 4 +# columns: 7 + 0.54967996784444262 0.63568422010837633 0.48432139435417798 0.91654660408861333 0.61397660997180459 0.23740710784116911 0.93704153072057961 + 0.65790383475259417 0.95777293527189578 0.60538439671170308 0.50103003220914188 0.52476374076263843 0.4810083462209081 0.38032082749090096 + 0.91567593583172879 0.916169106193785 0.1413230589210743 0.87529107102082415 0.92149680454964555 0.96756471171735692 0.80804950565316069 + 0.95403210012947015 0.49113812752360009 0.54336896252139377 0.60485181257951237 0.32243873410584195 0.80025530668089562 0.3636650793301765 + + +# name: B1D +# type: matrix +# rows: 4 +# columns: 1 + 0.54967996784444262 + 0.95777293527189578 + 0.1413230589210743 + 0.60485181257951237 + + +# name: B2 +# type: matrix +# rows: 4 +# columns: 7 + -1.1968380935160072 -0.90610669641422759 -1.4500131094385555 -0.17428472585157853 -0.97559689213814094 -2.8759577137920305 -0.13005534930339088 + -0.83739301225971818 -0.0862890973080368 -1.0037833124909741 -1.3821784703292967 -1.2896142705475888 -1.4637413144325939 -1.9334801991944361 + -0.17618551749331554 -0.17510863519670858 -3.9134136227478953 -0.26639759069180474 -0.16351193908015538 -0.065945941637918101 -0.42626390593041885 + -0.094115920330949079 -1.42205974392998 -1.2199334016132968 -1.005543577677164 -2.2636842651161246 -0.44564893775061304 -2.0230438932766308 + + +# name: B3 +# type: matrix +# rows: 4 +# columns: 7 + 0.29757165012340164 0.39318628524827959 0.23242207218341049 0.74468161629692975 0.36810238592920114 0.056332298752240335 0.7694929452433894 + 0.41944827094590165 0.79398063560502408 0.35834099213336079 0.24840286654904203 0.27190973618605779 0.22931028713817786 0.14414008899459307 + 0.74361596229862847 0.74421968612588274 0.019970879226840245 0.69335493145547344 0.75072335019666958 0.80530009585332851 0.60752745328754343 + 0.78961251254164666 0.23888423856353935 0.29097887838327607 0.35773916937707029 0.1037795409455215 0.59752309244290702 0.13186709678943936 + + +# name: BS1 +# type: matrix +# rows: 4 +# columns: 7 + 0.30214806704946751 0.24121666030738809 0.019972206982809437 0.25103109317549377 0.10396673725177785 0.056362134853508494 0.13225228992422355 + 0.43283745578216881 0.40409442769479464 0.23456721302917516 0.36584571518072162 0.2753769836191976 0.23136902913417301 0.14464393182336366 + 0.83846241946131228 0.83936583114391883 0.29524982943157585 0.76613445900878152 0.3769672775924694 0.64040855587093437 0.65294400358631732 + 0.91017724807744727 0.91732899553934311 0.36649026778199267 0.84005767746636939 0.84915636079520762 0.93618147136069207 0.87804683029516695 + + +# name: BS2 +# type: matrix +# rows: 4 +# columns: 7 + 0.91017724807744727 0.24121666030738809 0.29524982943157585 0.36584571518072162 0.10396673725177785 0.64040855587093437 0.13225228992422355 + 0.30214806704946751 0.40409442769479464 0.23456721302917516 0.84005767746636939 0.3769672775924694 0.056362134853508494 0.87804683029516695 + 0.83846241946131228 0.83936583114391883 0.019972206982809437 0.76613445900878152 0.84915636079520762 0.93618147136069207 0.65294400358631732 + 0.43283745578216881 0.91732899553934311 0.36649026778199267 0.25103109317549377 0.2753769836191976 0.23136902913417301 0.14464393182336366 + + +# 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 +0.54967996784444262 +0.95777293527189578 +0.1413230589210743 +0.60485181257951237 + + +# 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 + -3.1803461542887126 1.3228968307891731 -1.1910364139300591 -0.93390599886377734 -0.86790958692924014 -2.0845797468473566 + -2.2190459544456815 0.58885843202271038 -1.5947847026014119 -1.8144324886012142 -1.3446755118492355 -1.5271546910738913 + -1.054488297909342 0.25342118378527267 -0.3158133048571975 -0.87267553506041184 0.011913552649320189 -0.73040997142160813 + -2.2398447590311314 0.12459287393120072 -1.7857292029483249 -0.77762639710676762 -0.39585887220966964 -1.7145588217053258 + -1.4678828419663219 0.27280311818149588 -1.4312541803914047 -0.52944506541480196 -0.98678433734040372 -1.0671396645417168 + -2.3979048839154453 1.2125577081772101 -1.0351363911861409 -0.35099513988523134 -1.1509754124509566 -1.5178381786725819 + -1.6034716844696375 -0.26685943746647467 -1.7253787528003504 -0.5794921789829357 -0.2196501891587766 -1.3372016824738153 + + +# name: F +# type: matrix +# rows: 4 +# columns: 13 + -0.7051571199484552 -0.88179450715020191 -1.1144049175772983 -0.49983091636335197 0.80840661784520551 -0.8140870012861241 0.30214806704946751 0.40409442769479464 0.23456721302917516 0.84005767746636939 0.3769672775924694 0.056362134853508494 0.87804683029516695 + -0.71356520039087279 0.28649457280020335 -0.27474499334127955 -1.941373292643567 -0.68445281544335912 -0.42130829726717756 0.43283745578216881 0.91732899553934311 0.36649026778199267 0.25103109317549377 0.2753769836191976 0.23136902913417301 0.14464393182336366 + -0.9316641000515139 0.4764351481510109 -1.1302362269341515 0.24824863467958955 -1.3404175089410415 -0.60400871436213655 0.83846241946131228 0.83936583114391883 0.019972206982809437 0.76613445900878152 0.84915636079520762 0.93618147136069207 0.65294400358631732 + -2.0625226747527567 1.1710365095254567 0.23320666779954835 -0.16560634546901296 0.33837193758010109 -1.2632795600181634 0.91017724807744727 0.24121666030738809 0.29524982943157585 0.36584571518072162 0.10396673725177785 0.64040855587093437 0.13225228992422355 + + +# name: FF +# type: matrix +# rows: 2 +# columns: 4 + 1 1 1 1 + 1 1 1 1 + + +# name: G +# type: matrix +# rows: 4 +# columns: 6 + -2.8206284797938208 -7.0543560572016153 -13.372859010927581 -7.9972946618136316 16.16813235690411 -19.53808803086698 + -3.5678260019543639 2.5784511552018303 -3.5716849134366342 -33.003345974940636 -14.373509124310541 -10.532707431679439 + -5.5899846003090836 4.7643514815101087 -15.823307177078121 4.4684754242326115 -29.489185196702913 -15.70422657341555 + -14.437658723269298 12.881401604780024 3.4981000169932255 -3.1465205639112463 7.7825545643423251 -34.108548120490411 + + +# 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 + -0.6268063288430713 -1.5676346793781368 -2.9717464468727957 -1.7771765915141404 3.5929183015342465 -4.3417973401926622 + -0.79285022265652527 0.5729891456004067 -0.79370775854147424 -7.3340768833201411 -3.1941131387356756 -2.3406016514843198 + -1.2422188000686853 1.0587447736689131 -3.5162904837951379 0.99299453871835808 -6.5531522659339805 -3.4898281274256777 + -3.2083686051709552 2.8625336899511162 0.77735555933182787 -0.69922679198027693 1.72945656985385 -7.5796773601089802 + + +# 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 + 0.27761029902559703 -0.051542238893041825 -0.0055300565821513117 -0.039597093542427166 + -0.051542238893041825 0.25608419158315432 -0.065103753526283364 -0.049108544850378057 + -0.0055300565821513117 -0.065103753526283364 0.28355665129427221 -0.073055806077880509 + -0.039597093542427166 -0.049108544850378057 -0.073055806077880509 0.18320037973549641 + + +# name: dt +# type: scalar +407.92283062066855 + + +# 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..b88de7d 100644 --- a/ТЕМА1/report.md +++ b/ТЕМА1/report.md @@ -0,0 +1,418 @@ +#ОТЧЁТ + +##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") + Return a matrix with normally distributed random elements having + zero mean and variance one. + + +##6 +матрица А со случайными, нормально распределенными элементами, с 4 строками и 6 столбцами +>> A=randn(4,6) +A = + + -0.7052 -0.8818 -1.1144 -0.4998 0.8084 -0.8141 + -0.7136 0.2865 -0.2747 -1.9414 -0.6845 -0.4213 + -0.9317 0.4764 -1.1302 0.2482 -1.3404 -0.6040 + -2.0625 1.1710 0.2332 -0.1656 0.3384 -1.2633 + + + матрица В 4х7 со случайными элементами, равномерно распределенными в диапазоне от 0 до + >> B=rand(4,7) +B = + + 0.302148 0.404094 0.234567 0.840058 0.376967 0.056362 0.878047 + 0.432837 0.917329 0.366490 0.251031 0.275377 0.231369 0.144644 + 0.838462 0.839366 0.019972 0.766134 0.849156 0.936181 0.652944 + 0.910177 0.241217 0.295250 0.365846 0.103967 0.640409 0.132252 + +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+23.1j, 3-5.6j] +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 = + + -3.180346 1.322897 -1.191036 -0.933906 -0.867910 -2.084580 + -2.219046 0.588858 -1.594785 -1.814432 -1.344676 -1.527155 + -1.054488 0.253421 -0.315813 -0.872676 0.011914 -0.730410 + -2.239845 0.124593 -1.785729 -0.777626 -0.395859 -1.714559 + -1.467883 0.272803 -1.431254 -0.529445 -0.986784 -1.067140 + -2.397905 1.212558 -1.035136 -0.350995 -1.150975 -1.517838 + -1.603472 -0.266859 -1.725379 -0.579492 -0.219650 -1.337202 + - создание матрицы путем «горизонтального» соединения матриц А и В (числа строк у соединяемых матриц должны совпадать) + >> F=[A,B] +F = + + Columns 1 through 9: + + -0.705157 -0.881795 -1.114405 -0.499831 0.808407 -0.814087 0.302148 0.404094 0.234567 + -0.713565 0.286495 -0.274745 -1.941373 -0.684453 -0.421308 0.432837 0.917329 0.366490 + -0.931664 0.476435 -1.130236 0.248249 -1.340418 -0.604009 0.838462 0.839366 0.019972 + -2.062523 1.171037 0.233207 -0.165606 0.338372 -1.263280 0.910177 0.241217 0.295250 + + Columns 10 through 13: + + 0.840058 0.376967 0.056362 0.878047 + 0.251031 0.275377 0.231369 0.144644 + 0.766134 0.849156 0.936181 0.652944 + 0.365846 0.103967 0.640409 0.132252 + + - поэлементное перемножение матриц A и D (размеры матриц должны совпадать) + G=A.*D +G = + + -2.8206 -7.0544 -13.3729 -7.9973 16.1681 -19.5381 + -3.5678 2.5785 -3.5717 -33.0033 -14.3735 -10.5327 + -5.5900 4.7644 -15.8233 4.4685 -29.4892 -15.7042 + -14.4377 12.8814 3.4981 -3.1465 7.7826 -34.1085 + + поэлементное деление элементов матрицы G на 4.5 + M=G./4.5 +M = + + -0.6268 -1.5676 -2.9717 -1.7772 3.5929 -4.3418 + -0.7929 0.5730 -0.7937 -7.3341 -3.1941 -2.3406 + -1.2422 1.0587 -3.5163 0.9930 -6.5532 -3.4898 + -3.2084 2.8625 0.7774 -0.6992 1.7295 -7.5797 + +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 = + + 0.5497 0.6357 0.4843 0.9165 0.6140 0.2374 0.9370 + 0.6579 0.9578 0.6054 0.5010 0.5248 0.4810 0.3803 + 0.9157 0.9162 0.1413 0.8753 0.9215 0.9676 0.8080 + 0.9540 0.4911 0.5434 0.6049 0.3224 0.8003 0.3637 + + >> B2=log(B) +B2 = + + -1.196838 -0.906107 -1.450013 -0.174285 -0.975597 -2.875958 -0.130055 + -0.837393 -0.086289 -1.003783 -1.382178 -1.289614 -1.463741 -1.933480 + -0.176186 -0.175109 -3.913414 -0.266398 -0.163512 -0.065946 -0.426264 + -0.094116 -1.422060 -1.219933 -1.005544 -2.263684 -0.445649 -2.023044 + +B3=sin(B) +B3 = + + 0.297572 0.393186 0.232422 0.744682 0.368102 0.056332 0.769493 + 0.419448 0.793981 0.358341 0.248403 0.271910 0.229310 0.144140 + 0.743616 0.744220 0.019971 0.693355 0.750723 0.805300 0.607527 + 0.789613 0.238884 0.290979 0.357739 0.103780 0.597523 0.131867 + + 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 = + + 0.5497 + 0.9578 + 0.1413 + 0.6049 + +>> DB=diag(B1D) +DB = + +Diagonal Matrix + + 0.5497 0 0 0 + 0 0.9578 0 0 + 0 0 0.1413 0 + 0 0 0 0.6049 + +>> BS1=sort(B) +BS1 = + + 0.302148 0.241217 0.019972 0.251031 0.103967 0.056362 0.132252 + 0.432837 0.404094 0.234567 0.365846 0.275377 0.231369 0.144644 + 0.838462 0.839366 0.295250 0.766134 0.376967 0.640409 0.652944 + 0.910177 0.917329 0.366490 0.840058 0.849156 0.936181 0.878047 + +>> BS2=sortrows(B,2) +BS2 = + + 0.910177 0.241217 0.295250 0.365846 0.103967 0.640409 0.132252 + 0.302148 0.404094 0.234567 0.840058 0.376967 0.056362 0.878047 + 0.838462 0.839366 0.019972 0.766134 0.849156 0.936181 0.652944 + 0.432837 0.917329 0.366490 0.251031 0.275377 0.231369 0.144644 + +>> 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 = 407.92 +>> dinv=inv(A*A') +dinv = + + 2.7761e-01 -5.1542e-02 -5.5301e-03 -3.9597e-02 + -5.1542e-02 2.5608e-01 -6.5104e-02 -4.9109e-02 + -5.5301e-03 -6.5104e-02 2.8356e-01 -7.3056e-02 + -3.9597e-02 -4.9109e-02 -7.3056e-02 1.8320e-01 + + ##9 + Изучите 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 +if (D(3,5)>=20) +printf('D(3,5)>=20') +else +printf('D(3,5)<20') +endif +D(3,5)>=20> + +##11 +рассмотрите функцию построения графиков +>> plot(D(1,:),B([2,4],1:6)) +примените функцию расчета и построения гистограммы +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 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