From 75d9bb7329893077b60a673e2866a8e54f092229 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?=
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 =?UTF-8?q?=D1=82=D0=BE=D1=80=D0=B8=D0=B8=20=D0=96-202?=
 <u202-08@public.mpei.local>
Date: Thu, 12 Feb 2026 11:00:02 +0300
Subject: [PATCH] =?UTF-8?q?=D0=BB=D0=B0=D0=B1=D0=B0=20=D0=B1=D0=B5=D0=B7?=
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MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
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---
 ТЕМА2/Hist.jpg         | Bin 0 -> 27199 bytes
 ТЕМА2/params           | 991 +++++++++++++++++++++++++++++++++++++
 ТЕМА2/photos/plot1.png | Bin 0 -> 10128 bytes
 ТЕМА2/photos/plot2.png | Bin 0 -> 9664 bytes
 ТЕМА2/prtcl.txt        | 319 ++++++++++++
 ТЕМА2/report.md.txt    | 548 ++++++++++++++++++++
 ТЕМА2/res.mat          | Bin 0 -> 2504 bytes
 ТЕМА2/task1.m          |  10 +
 ТЕМА2/tri.m            |  32 ++
 9 files changed, 1900 insertions(+)
 create mode 100644 ТЕМА2/Hist.jpg
 create mode 100644 ТЕМА2/params
 create mode 100644 ТЕМА2/photos/plot1.png
 create mode 100644 ТЕМА2/photos/plot2.png
 create mode 100644 ТЕМА2/prtcl.txt
 create mode 100644 ТЕМА2/report.md.txt
 create mode 100644 ТЕМА2/res.mat
 create mode 100644 ТЕМА2/task1.m
 create mode 100644 ТЕМА2/tri.m

diff --git a/ТЕМА2/Hist.jpg b/ТЕМА2/Hist.jpg
new file mode 100644
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diff --git a/ТЕМА2/params b/ТЕМА2/params
new file mode 100644
index 0000000..c54bdf5
--- /dev/null
+++ b/ТЕМА2/params
@@ -0,0 +1,991 @@
+# Created by Octave 8.3.0, Thu Feb 12 09:47:35 2026 GMT <unknown@w10prog-45>
+# name: Delt
+# type: scalar
+95.272650848977378
+
+
+# name: GlComp
+# type: matrix
+# rows: 11
+# columns: 1
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diff --git a/ТЕМА2/prtcl.txt b/ТЕМА2/prtcl.txt
new file mode 100644
index 0000000..b892063
--- /dev/null
+++ b/ТЕМА2/prtcl.txt
@@ -0,0 +1,319 @@
+Eigenvalues:
+ 22.946585 
+Eigenvalues:
+ 1931.665464 
+Eigenvalues:
+ 2593.979592 
+Eigenvalues:
+ 3457.339562 
+Eigenvalues:
+ 5625.151474 
+Eigenvalues:
+ 8672.065947 
+Eigenvalues:
+ 18914.627989 
+Eigenvalues:
+ 47522.678185 
+Eigenvalues:
+ 57483.681267 
+Eigenvalues:
+ 225653.068540 
+Eigenvalues:
+ 7494628.795394 
+
+Delta= 95 
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+ 133  134.000000 
+ 135  136.000000 
+ 137  138.000000 
+ 139  140.000000 
+ 141  142.000000 
+ 143  144.000000 
+ 146  147.000000 
+ 148  149.000000 
+ 150  151.000000 
+ 152  153.000000 
+ 154  162.000000 
+ 166  167.000000 
+ 168  170.000000 
+ 171  172.000000 
+ 173  174.000000 
+ 175  176.000000 
+ 177  178.000000 
+ 179  180.000000 
+ 181  182.000000 
+ 183  184.000000 
+ 185  186.000000 
+ 187  188.000000 
+ 189  190.000000 
+ 191  192.000000 
+ 193  194.000000 
+ 92.5416  73.432513 
+ 5.88547  35.300393 
+ 70.2081  28.096191 
+ 87.1363  79.776499 
+ 36.243  18.249808 
+ 49.6665  45.067095 
+ 81.7854  5.555862 
+ 105.361  4.575460 
+ 381.204  26.712747 
+ 8.03762  119.627795 
+ 10.0615  63.762947 
+ 9.08766  41.684105 
+ 35.9074  76.139589 
+ 23.7525  142.216169 
+ 67.7558  20.597788 
+ 76.8188  104.284923 
+ 18.5416  4.473983 
+ 3.58088  224.758597 
+ 26.8636  212.911324 
+ 50.9215  33.628254 
+ 42.1683  103.701129 
+ 136.061  713.711764 
+ 34.0272  4.102289 
+ 27.0867  2.667541 
+ 2.49756  103.829221 
+ 7.46072  34.755449 
+ 4.35974  5.741187 
+ 15.9894  45.399798 
+ 2.46225  6.424390 
+ 66.503  73.935542 
+ 11.1305  3.684256 
+ 9.97049  28.031419 
+ 1.35241  40.905330 
+ 11.7227  30.793455 
+ 42.7163  10.023429 
+ 32.2605  25.495269 
+ 36.8701  42.948416 
+ 87.9632  228.668981 
+ 99.1461  28.749899 
+ 9.62216  1.359974 
+ 54.2136  107.547742 
+ 116.106  299.102890 
+ 14.3332  20.479493 
+ 144.909  14.952535 
+ 25.9761  268.149429 
+ 12.3536  4.526119 
+ 104.665  91.264814 
+ 209.33  196.452926 
+ 4.81212  1.387719 
+ 50.733  118.633179 
+ 212.529  37.744725 
+ 30.1025  320.669960 
+ 0  41.450044 
+ 141.123  405.347359 
+ 12.8752  117.612150 
+ 8.98989  74.655250 
+ 89.5664  37.992598 
+ 40.5997  37.339465 
+ 142.929  9.122607 
+ 53.4638  93.289532 
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+ 5.49147  85.213352 
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+ 57.8107  7.372961 
+ 9.61494  1.846687 
+ 17.6469  153.910670 
+ 119.836  5.010210 
+ 2.69196  379.300890 
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+ 0.369757  10.360736 
+ 3.85509  81.568715 
+ 54.6366  23.501931 
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+ 6.3233  59.415851 
+ 46.9662  56.660855 
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+ 113.59  11.709047 
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+ 122.672  59.978744 
+ 7.49106  12.504248 
+ 24.2085  400.110964 
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+ 5.17176  48.085148 
+ 5.34789  2.124571 
+ 0.0820775  21.635603 
+ 52.0571  25.625192 
+ 9.75023  36.202865 
+ 4.62665  3.190574 
+ 9.57829  6.374896 
+ 3.68445  5.784829 
+ 8.23676  6.872598 
+ 41.3048  1.988474 
+ 7.57132  1.231125 
+ 5.08109  21.547440 
+ 30.2999  45.503740 
+ 9.09391  10.369658 
+ 7.12594  14.133228 
+ 26.1024  5.071976 
+ 12.0853  0.713469 
+ 0.675086  4.092547 
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+ 10.4554  7.448129 
+ 6.24252  8.860180 
+ 39.992  6.891026 
+ 5.16071  15.489599 
+ 5.59047  27.378151 
+ 10.8012  23.750968 
+ 11.4263  8.473236 
+ 6.89837  3.416283 
+ 208.747  12.158394 
+ 3.56316  4.158866 
+ 0  1.847873 
+ 8.47882  1.277897 
+ 0.0353056  0.070611 
+ 0.0353056  3.039279 
+ 0  4.205715 
+ 30.0949  20.128055 
+ 5.77372  31.539990 
+ 147.387  18.314164 
+ 32.846  14.511067 
+ 19.2355  0.000000 
+ min: 0.000000
+ max: 1898.884523
+ mean: 67.928804 
+ std: 145.954386
\ No newline at end of file
diff --git a/ТЕМА2/report.md.txt b/ТЕМА2/report.md.txt
new file mode 100644
index 0000000..a260ec7
--- /dev/null
+++ b/ТЕМА2/report.md.txt
@@ -0,0 +1,548 @@
+#Вторая лаба отчет
+
+###Читаю файл и проверяю размер матрицы
+
+XX=load('dan_vuz.txt')
+size(XX)
+
+ans =
+
+   290    15
+
+>>
+
+###Данные о скольких вузах России представлены в этой матрице?
+
+290
+
+###Выделите в отдельную матрицу данные о показателях результативности:
+
+X=XX(:,3:13)
+
+###Рассчитайте матрицу корреляций между показателями результативности:
+
+R=corr(X)
+
+R =
+
+ Columns 1 through 10:
+
+   1.0000e+00   4.4320e-01   4.5229e-01   4.4779e-01   3.8123e-01   4.6516e-01   3.1487e-01   6.5579e-02   2.9153e-01   4.8811e-01
+   4.4320e-01   1.0000e+00   8.5319e-01   8.5331e-01   8.6240e-01   8.5436e-01   5.5145e-01   2.5082e-02   4.2348e-01   8.2170e-01
+   4.5229e-01   8.5319e-01   1.0000e+00   8.4660e-01   8.8651e-01   9.0335e-01   5.5091e-01   3.8840e-03   4.4396e-01   7.8358e-01
+   4.4779e-01   8.5331e-01   8.4660e-01   1.0000e+00   8.7038e-01   9.3849e-01   7.0924e-01   4.9500e-02   4.5873e-01   8.5183e-01
+   3.8123e-01   8.6240e-01   8.8651e-01   8.7038e-01   1.0000e+00   9.3605e-01   5.7668e-01   3.7562e-02   3.8322e-01   7.7266e-01
+   4.6516e-01   8.5436e-01   9.0335e-01   9.3849e-01   9.3605e-01   1.0000e+00   6.3033e-01   4.7121e-02   4.7592e-01   8.3810e-01
+   3.1487e-01   5.5145e-01   5.5091e-01   7.0924e-01   5.7668e-01   6.3033e-01   1.0000e+00   7.9448e-02   4.1878e-01   6.2936e-01
+   6.5579e-02   2.5082e-02   3.8840e-03   4.9500e-02   3.7562e-02   4.7121e-02   7.9448e-02   1.0000e+00   4.7985e-02   5.6462e-02
+   2.9153e-01   4.2348e-01   4.4396e-01   4.5873e-01   3.8322e-01   4.7592e-01   4.1878e-01   4.7985e-02   1.0000e+00   6.2616e-01
+   4.8811e-01   8.2170e-01   7.8358e-01   8.5183e-01   7.7266e-01   8.3810e-01   6.2936e-01   5.6462e-02   6.2616e-01   1.0000e+00
+   3.9815e-01   2.6183e-01   2.6408e-01   3.4420e-01   1.8751e-01   3.3118e-01   2.8287e-01   1.3662e-01   4.5537e-01   3.8799e-01
+
+ Column 11:
+
+   3.9815e-01
+   2.6183e-01
+   2.6408e-01
+   3.4420e-01
+   1.8751e-01
+   3.3118e-01
+   2.8287e-01
+   1.3662e-01
+   4.5537e-01
+   3.8799e-01
+   1.0000e+00
+
+>>
+
+###Пусть для исследования результативности применяется метод главных компонент, основу которого составляет получение собственных значений и собственных векторов от квадратичной формы:
+
+[vect,lambda]=eig(X'*X)
+
+lambda =
+
+Diagonal Matrix
+
+ Columns 1 through 10:
+
+   2.2947e+01            0            0            0            0            0            0            0            0            0
+            0   1.9317e+03            0            0            0            0            0            0            0            0
+            0            0   2.5940e+03            0            0            0            0            0            0            0
+            0            0            0   3.4573e+03            0            0            0            0            0            0
+            0            0            0            0   5.6252e+03            0            0            0            0            0
+            0            0            0            0            0   8.6721e+03            0            0            0            0
+            0            0            0            0            0            0   1.8915e+04            0            0            0
+            0            0            0            0            0            0            0   4.7523e+04            0            0
+            0            0            0            0            0            0            0            0   5.7484e+04            0
+            0            0            0            0            0            0            0            0            0   2.2565e+05
+            0            0            0            0            0            0            0            0            0            0
+
+ Column 11:
+
+            0
+            0
+            0
+            0
+            0
+            0
+            0
+            0
+            0
+            0
+   7.4946e+06
+
+>>
+
+Sobst=diag(lambda);
+
+###Представьте их на экране с заголовком:
+
+fprintf('Eigenvalues:\n %f \n',Sobst)
+
+Eigenvalues:
+ 22.946585
+Eigenvalues:
+ 1931.665464
+Eigenvalues:
+ 2593.979592
+Eigenvalues:
+ 3457.339562
+Eigenvalues:
+ 5625.151474
+Eigenvalues:
+ 8672.065947
+Eigenvalues:
+ 18914.627989
+Eigenvalues:
+ 47522.678185
+Eigenvalues:
+ 57483.681267
+Eigenvalues:
+ 225653.068540
+Eigenvalues:
+ 7494628.795394
+>>
+
+###Выделите наибольшее собственное значение и соответствующий ему собственный вектор:
+
+>> SobMax=Sobst(end)
+SobMax = 7.4946e+06
+
+ 뫤גּ>> GlComp=vect(:,end)
+GlComp =
+
+   3.5306e-02
+   4.6772e-02
+   4.8953e-02
+   6.1556e-01
+   2.4277e-01
+   7.3685e-01
+   9.5893e-02
+   1.6945e-04
+   1.7911e-02
+   5.9523e-02
+   1.7425e-02
+
+>>
+
+###Рассчитайте долю информации о результативности НИР, содержащуюся в главной компоненте и отобразите ее на экране:
+
+>> Delt=100*SobMax/sum(Sobst)
+Delt = 95.273
+
+܀>> fprintf('Delta= %d \n ',round(Delt))
+Delta= 95
+
+###С использованием главной компоненты рассчитайте оценки обобщенной результативности в каждом из представленных в матрице вузов и отобразите ее с указанием кода вуза:
+
+Res=X*GlComp
+fprintf(' Results \n ')
+fprintf('%d  %f \n ',[XX(:,1),Res] ')
+
+получаю вывод формата Results \n {results}
+
+###Сохраните вектор оценок результативности в отдельном бинарном (mat) файле:
+
+save res.mat Res -mat
+
+в рабочей папке появляется файл res.mat
+
+###Представьте распределение оценок результативности в виде гистограммы с 20 интервалами  и с обозначением осей:
+
+xlabel('Results ')
+ylabel('Number of Unis ')
+hist(Res,20)
+
+вставить фото photos/plot1.png
+
+saveas(gcf, 'Hist.jpg ', 'jpg ')
+
+в папке появлися новый файл Hist
+
+###Наконец, рассчитайте и отобразите оценку корреляции обобщенной результативности с финансированием, выделенным на проведение НИР:
+
+CorFin=corr(Res,XX(:,2))
+fprintf('Correlation of Results and Money = %f \n',CorFin)
+
+Вывод:
+
+Correlation of Results and Money = 0.843710
+>>
+
+##Пункт 3
+
+Создаю файл, содержащий такие строки:
+
+warning('off', 'all')
+graphics_toolkit('gnuplot')
+XX=load('dan_vuz.txt')
+X=XX(:,3:13)
+R=corr(X)
+[vect,lambda]=eig(X'*X)
+Sobst=diag(lambda);
+SobMax=Sobst(end)
+GlComp=vect(:,end)
+Delt=100*SobMax/sum(Sobst)
+Res=X*GlComp
+xlabel('Results ')
+ylabel('Number of Unis '))
+hist(Res,20)
+saveas(gcf, 'Hist.jpg ', 'jpg ')
+
+выводы в консили совпадают с теми, что были ранее, рисунок так же совпадает
+
+вставить Hist.jpeg
+
+##4 Пункт
+
+Я поставил ; в конце каждой строки скрипта и добавил отладочный принт, чтобы точно видеть завершение работы программы и отсутствие других выводов fprintf('Выполнение завершено')
+
+>> tri --> мой файл
+
+DEBUG: FC_WEIGHT didn't match --> такая ошибка уже была, ниче страшного
+Выполнение завершено>>
+
+##5 пункт
+
+сделал все выводы в файл
+
+warning('off', 'all');
+graphics_toolkit('gnuplot');
+fp=fopen('prtcl.txt ','w')
+XX=load('dan_vuz.txt');
+X=XX(:,3:13);
+R=corr(X);
+[vect,lambda]=eig(X'*X);
+Sobst=diag(lambda);
+fprintf(fp,'Eigenvalues:\n %f \n',Sobst)
+fprintf(fp, '\n')
+SobMax=Sobst(end);
+GlComp=vect(:,end);
+Delt=100*SobMax/sum(Sobst);
+fprintf(fp, 'Delta= %d \n ',round(Delt))
+Res=X*GlComp;
+fprintf(fp, ' Results \n ')
+fprintf(fp, '%d  %f \n ',[XX(:,1),Res] ')
+hist(Res,20);
+xlabel('Results ');
+ylabel('Number of Unis ');
+saveas(gcf, 'Hist.jpg ', 'jpg ');
+fclose(fp)
+
+файл:
+Eigenvalues:
+ 22.946585 
+Eigenvalues:
+ 1931.665464 
+Eigenvalues:
+ 2593.979592 
+Eigenvalues:
+ 3457.339562 
+Eigenvalues:
+ 5625.151474 
+Eigenvalues:
+ 8672.065947 
+Eigenvalues:
+ 18914.627989 
+Eigenvalues:
+ 47522.678185 
+Eigenvalues:
+ 57483.681267 
+Eigenvalues:
+ 225653.068540 
+Eigenvalues:
+ 7494628.795394 
+
+Delta= 95 
+  Results 
+ 197  92.541636 
+ 198  73.432513 
+ 199  5.885468 
+ 200  35.300393 
+ 201  70.208100 
+ 202  28.096191 
+ 203  87.136298 
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+ 207  49.666520 
+ 208  45.067095 
+ 209  81.785392 
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+ 226  67.755801 
+ 227  20.597788 
+ 228  76.818771 
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+ 230  18.541601 
+ 231  4.473983 
+ 232  3.580878 
+ 233  224.758597 
+ 234  26.863645 
+ 235  212.911324 
+ 236  50.921549 
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+ 97  5.347890 
+ 99  2.124571 
+ 100  0.082078 
+ 101  21.635603 
+ 102  52.057076 
+ 103  25.625192 
+ 104  9.750228 
+ 105  36.202865 
+ 107  4.626653 
+ 108  3.190574 
+ 109  9.578291 
+ 110  6.374896 
+ 111  3.684
+
+##6 пункт
+
+код с выводом в файл:
+
+warning('off', 'all');
+graphics_toolkit('gnuplot');
+fp=fopen('prtcl.txt ','w')
+XX=load('dan_vuz.txt');
+X=XX(:,3:13);
+R=corr(X);
+[vect,lambda]=eig(X'*X);
+Sobst=diag(lambda);
+fprintf(fp,'Eigenvalues:\n %f \n',Sobst)
+fprintf(fp, '\n')
+SobMax=Sobst(end);
+GlComp=vect(:,end);
+Delt=100*SobMax/sum(Sobst);
+fprintf(fp, 'Delta= %d \n ',round(Delt))
+Res=X*GlComp;
+
+# 6 пункт
+
+minres = min(Res)
+maxres = max(Res)
+meanres = mean(Res)
+stdres = std(Res)
+
+fprintf(fp, ' Results \n ')
+fprintf(fp, '%d  %f \n ',[XX(:,1),Res] )
+# fprintf(fp, 'min: %f', minres, '\n', 'max: %f', maxres, '\n', 'mean: %f', meanres, '\n', 'std: %f', stdres)
+fprintf(fp, 'min: %f\n max: %f\n mean: %f \n std: %f', [minres, maxres, meanres, stdres])
+hist(Res,20);
+xlabel('Results ');
+ylabel('Number of Unis ');
+saveas(gcf, 'Hist.jpg ', 'jpg ');
+fclose(fp)
+
+вывод метрик в конце:
+
+ min: 0.000000
+ max: 1898.884523
+ mean: 67.928804 
+ std: 145.954386
\ No newline at end of file
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diff --git a/ТЕМА2/task1.m b/ТЕМА2/task1.m
new file mode 100644
index 0000000..2ced88a
--- /dev/null
+++ b/ТЕМА2/task1.m
@@ -0,0 +1,10 @@
+warning('off', 'all')
+graphics_toolkit('gnuplot')
+
+XX=load('dan_vuz.txt')
+size(XX)
+
+hist(Res,20)
+xlabel('Results ')
+ylabel('Number of Unis ')
+
diff --git a/ТЕМА2/tri.m b/ТЕМА2/tri.m
new file mode 100644
index 0000000..6ea97a9
--- /dev/null
+++ b/ТЕМА2/tri.m
@@ -0,0 +1,32 @@
+warning('off', 'all');
+graphics_toolkit('gnuplot');
+fp=fopen('prtcl.txt ','w')
+XX=load('dan_vuz.txt');
+X=XX(:,3:13);
+R=corr(X);
+[vect,lambda]=eig(X'*X);
+Sobst=diag(lambda);
+fprintf(fp,'Eigenvalues:\n %f \n',Sobst)
+fprintf(fp, '\n')
+SobMax=Sobst(end);
+GlComp=vect(:,end);
+Delt=100*SobMax/sum(Sobst);
+fprintf(fp, 'Delta= %d \n ',round(Delt))
+Res=X*GlComp;
+
+# 6 пункт
+minres = min(Res)
+maxres = max(Res)
+meanres = mean(Res)
+stdres = std(Res)
+
+fprintf(fp, ' Results \n ')
+fprintf(fp, '%d  %f \n ',[XX(:,1),Res] )
+# fprintf(fp, 'min: %f', minres, '\n', 'max: %f', maxres, '\n', 'mean: %f', meanres, '\n', 'std: %f', stdres)
+fprintf(fp, 'min: %f\n max: %f\n mean: %f \n std: %f', [minres, maxres, meanres, stdres])
+hist(Res,20);
+xlabel('Results ');
+ylabel('Number of Unis ');
+saveas(gcf, 'Hist.jpg ', 'jpg ');
+fclose(fp)
+