Untitled9.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "x =\n",
      "\n",
      "   327   354   381   408   435   462   489   516   543   570   597   624     1    28    55    82   109   136   163   190   217   244   271   298   325\n",
      "   353   380   407   434   461   488   515   542   569   596   623    25    27    54    81   108   135   162   189   216   243   270   297   324   326\n",
      "   379   406   433   460   487   514   541   568   595   622    24    26    53    80   107   134   161   188   215   242   269   296   323   350   352\n",
      "   405   432   459   486   513   540   567   594   621    23    50    52    79   106   133   160   187   214   241   268   295   322   349   351   378\n",
      "   431   458   485   512   539   566   593   620    22    49    51    78   105   132   159   186   213   240   267   294   321   348   375   377   404\n",
      "   457   484   511   538   565   592   619    21    48    75    77   104   131   158   185   212   239   266   293   320   347   374   376   403   430\n",
      "   483   510   537   564   591   618    20    47    74    76   103   130   157   184   211   238   265   292   319   346   373   400   402   429   456\n",
      "   509   536   563   590   617    19    46    73   100   102   129   156   183   210   237   264   291   318   345   372   399   401   428   455   482\n",
      "   535   562   589   616    18    45    72    99   101   128   155   182   209   236   263   290   317   344   371   398   425   427   454   481   508\n",
      "   561   588   615    17    44    71    98   125   127   154   181   208   235   262   289   316   343   370   397   424   426   453   480   507   534\n",
      "   587   614    16    43    70    97   124   126   153   180   207   234   261   288   315   342   369   396   423   450   452   479   506   533   560\n",
      "   613    15    42    69    96   123   150   152   179   206   233   260   287   314   341   368   395   422   449   451   478   505   532   559   586\n",
      "    14    41    68    95   122   149   151   178   205   232   259   286   313   340   367   394   421   448   475   477   504   531   558   585   612\n",
      "    40    67    94   121   148   175   177   204   231   258   285   312   339   366   393   420   447   474   476   503   530   557   584   611    13\n",
      "    66    93   120   147   174   176   203   230   257   284   311   338   365   392   419   446   473   500   502   529   556   583   610    12    39\n",
      "    92   119   146   173   200   202   229   256   283   310   337   364   391   418   445   472   499   501   528   555   582   609    11    38    65\n",
      "   118   145   172   199   201   228   255   282   309   336   363   390   417   444   471   498   525   527   554   581   608    10    37    64    91\n",
      "   144   171   198   225   227   254   281   308   335   362   389   416   443   470   497   524   526   553   580   607     9    36    63    90   117\n",
      "   170   197   224   226   253   280   307   334   361   388   415   442   469   496   523   550   552   579   606     8    35    62    89   116   143\n",
      "   196   223   250   252   279   306   333   360   387   414   441   468   495   522   549   551   578   605     7    34    61    88   115   142   169\n",
      "   222   249   251   278   305   332   359   386   413   440   467   494   521   548   575   577   604     6    33    60    87   114   141   168   195\n",
      "   248   275   277   304   331   358   385   412   439   466   493   520   547   574   576   603     5    32    59    86   113   140   167   194   221\n",
      "   274   276   303   330   357   384   411   438   465   492   519   546   573   600   602     4    31    58    85   112   139   166   193   220   247\n",
      "   300   302   329   356   383   410   437   464   491   518   545   572   599   601     3    30    57    84   111   138   165   192   219   246   273\n",
      "   301   328   355   382   409   436   463   490   517   544   571   598   625     2    29    56    83   110   137   164   191   218   245   272   299\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "x = magic(25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "e =\n",
      "\n",
      "   4.5561 + 0.0000i\n",
      "   0.6977 + 0.4054i\n",
      "   0.6977 - 0.4054i\n",
      "  -0.5916 + 0.0000i\n",
      "  -0.2515 + 0.0930i\n",
      "  -0.2515 - 0.0930i\n",
      "   0.1563 + 0.3522i\n",
      "   0.1563 - 0.3522i\n",
      "   0.0187 + 0.2538i\n",
      "   0.0187 - 0.2538i\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "e = eig(rand(10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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UMxJUy7frSLWEpFFtUNXquLupZiRahG0Uz8B2rGczvA8W2Ia4/qv5hZVqRqI51cYljWqz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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(magic(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "area(magic(8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "x =\n",
      "\n",
      "    12\n",
      "\n",
      "\n",
      "r =\n",
      "\n",
      "    0.0963    0.4865    0.7384    0.1807    0.6780    0.7188    0.2982    0.0484    0.6417    0.1668    0.4839    0.8345\n",
      "    0.5344    0.1984    0.9388    0.5136    0.4255    0.3514    0.7444    0.1405    0.3920    0.4701    0.8732    0.4511\n",
      "    0.7568    0.1437    0.4970    0.2870    0.5281    0.0144    0.4872    0.4127    0.5539    0.0789    0.9628    0.3635\n",
      "    0.9844    0.0820    0.6205    0.7827    0.8811    0.4092    0.8545    0.4724    0.8736    0.4771    0.3231    0.9027\n",
      "    0.9236    0.8985    0.0379    0.6292    0.3076    0.1050    0.2145    0.8789    0.9131    0.6856    0.0888    0.8336\n",
      "    0.6811    0.9895    0.0341    0.3554    0.8308    0.6433    0.9694    0.7133    0.1374    0.0647    0.5403    0.7377\n",
      "    0.5854    0.1639    0.8882    0.4908    0.5958    0.8703    0.9752    0.3194    0.9475    0.0623    0.1689    0.7367\n",
      "    0.1618    0.1257    0.9401    0.8154    0.1943    0.9914    0.8498    0.1760    0.7441    0.6764    0.2865    0.1788\n",
      "    0.1693    0.4164    0.7555    0.4319    0.6330    0.8111    0.3891    0.4877    0.9149    0.8533    0.7537    0.8828\n",
      "    0.3323    0.1745    0.9242    0.4491    0.8043    0.7461    0.3484    0.2188    0.9237    0.2983    0.9398    0.4876\n",
      "    0.2422    0.0578    0.6188    0.5839    0.0513    0.7957    0.7308    0.2656    0.5476    0.0416    0.7053    0.2799\n",
      "    0.8373    0.6618    0.3721    0.7318    0.7948    0.1724    0.2193    0.5947    0.5712    0.9370    0.0524    0.7368\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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McOObD1usagZsaaqJyAVNqqlGXxcUqgXSNefByby1pg4dVINqzOnaJFXrLk6l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\nAoGgxv8Ho2z8u7ub3MwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = 12\n",
    "r = rand(x)\n",
    "plot(r)\n",
    "title('Some random stuff')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "x =\n",
      "\n",
      "    0.9300    0.8090    0.1558    0.6368    0.4220    0.6784\n",
      "\n",
      "The variable x has length 6\n",
      "\n"
     ]
    }
   ],
   "source": [
    "x = rand(1,6)\n",
    "fprintf('The variable x has length %d\\n',length(x))"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Matlab",
   "language": "matlab",
   "name": "matlab"
  },
  "language_info": {
   "codemirror_mode": "octave",
   "file_extension": ".m",
   "help_links": [
    {
     "text": "MetaKernel Magics",
     "url": "https://github.com/calysto/metakernel/blob/master/metakernel/magics/README.md"
    }
   ],
   "mimetype": "text/x-matlab",
   "name": "matlab",
   "version": "0.11.0+9.g2f6b71e"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}