{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "%plot inline -w 480 -h 480\n",
    "format compact"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Planowanie eksperymentu\n",
    "\n",
    "Przykłady są dla MATLAB 2017b (jeśli funkcje są inne dla MATLAB 2014a to zaznaczono to w komentarzach)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generowanie planu eksperymentu"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plan dwupoziomowy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " FF2N   Two-level full-factorial design.\n",
      "    X = FF2N(N) creates a two-level full-factorial design, X.\n",
      "    N is the number of columns of X. The number of rows is 2^N.\n",
      "\n",
      "    Reference page in Doc Center\n",
      "       doc ff2n\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help ff2n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dFF2 =\n",
      "     0     0\n",
      "     0     1\n",
      "     1     0\n",
      "     1     1\n",
      "s =\n",
      "     4\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dFF2 = ff2n(2)\n",
    "[s,~]=size(dFF2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dFF2 =\n",
      "     0     0     0\n",
      "     0     0     1\n",
      "     0     1     0\n",
      "     0     1     1\n",
      "     1     0     0\n",
      "     1     0     1\n",
      "     1     1     0\n",
      "     1     1     1\n",
      "s =\n",
      "     8\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dFF2 = ff2n(3)\n",
    "[s,~]=size(dFF2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " FULLFACT Mixed-level full-factorial designs.\n",
      "    DESIGN=FULLFACT(LEVELS) creates a matrix DESIGN containing the\n",
      "    factor settings for a full factorial design. The vector LEVELS\n",
      "    specifies the number of unique settings in each column of the design.\n",
      " \n",
      "    Example:\n",
      "        LEVELS = [2 4 3];\n",
      "        DESIGN = FULLFACT(LEVELS);\n",
      "    This generates a 24 run design with 2 levels in the first column,\n",
      "    4 in the second column, and 3 in the third column.\n",
      "\n",
      "    Reference page in Doc Center\n",
      "       doc fullfact\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help fullfact"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dFF =\n",
      "     1     1\n",
      "     2     1\n",
      "     1     2\n",
      "     2     2\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dFF=fullfact([2 2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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QBBoAhCLQACAUgQYAoQg0AAhFoAFAKAINAEIRaAAQikADgFAEGgCEItAAIBSBBgChNAc6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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(dFF(:,1),dFF(:,2),'o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dFF3 =\n",
      "     1     1     1\n",
      "     2     1     1\n",
      "     1     2     1\n",
      "     2     2     1\n",
      "     1     1     2\n",
      "     2     1     2\n",
      "     1     2     2\n",
      "     2     2     2\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dFF3=fullfact([2 2 2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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a3ppWmHJpfQ340/D444/PmTNH/mdycvLhw4d//etfKzoq5vRe+iOE4MOnrJhd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\nNAAAoxCgAQAYhQANAMCo/x/V1F+sZaj3VQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot3(dFF3(:,1),dFF3(:,2),dFF3(:,3),'o'), grid on\n",
    "xlabel('x1'),ylabel('x2'),zlabel('x3')\n",
    "view(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " FRACFACT Fractional factorial design for two-level factors.\n",
      "    X = FRACFACT(GEN) produces the fractional factorial design defined by\n",
      "    the generator string GEN.  GEN must be a sequence of \"words\" separated\n",
      "    by spaces.  If the generator string consists of P words using K letters\n",
      "    of the alphabet, then X has N=2^K rows and P columns.  Each word\n",
      "    defines how the corresponding factor's levels are defined as products\n",
      "    of generators from a 2^K full-factorial design.  Alternatively, GEN can\n",
      "    be a cell array of strings, with one word per cell.\n",
      " \n",
      "    [X, CONF] = FRACFACT(GEN) also returns CONF, a cell array of\n",
      "    strings containing the confounding pattern for the design.\n",
      " \n",
      "    [...] = FRACFACT(GEN, 'PARAM1',val1, 'PARAM2',val2,...) specifies one\n",
      "    or more of the following name/value pairs:\n",
      " \n",
      "        'MaxInt'      Maximum level of interaction to include in the\n",
      "                      confounding output (default 2)\n",
      "        'FactorNames' Cell array specifying the name for each factor\n",
      "                      (default names are X1, X2, ...)\n",
      " \n",
      "    Example:\n",
      "       x = fracfact('a b c abc')\n",
      " \n",
      "    produces an 8-run fractional factorial design for four variables, where\n",
      "    the first three columns are an 8-run 2-level full factorial design for\n",
      "    the first three variables, and the fourth column is the product of the\n",
      "    first three columns.  The fourth column is confounded with the\n",
      "    three-way interaction of the first three columns.\n",
      " \n",
      "    See also FF2N, FULLFACT, FRACFACTGEN.\n",
      "\n",
      "    Reference page in Doc Center\n",
      "       doc fracfact\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help fracfact"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dfF3 =\n",
      "    -1    -1     1\n",
      "    -1     1    -1\n",
      "     1    -1    -1\n",
      "     1     1     1\n",
      "confounding =\n",
      "  7x3 cell array\n",
      "    {'Term' }    {'Generator'}    {'Confounding'}\n",
      "    {'X1'   }    {'a'        }    {'X1 + X2*X3' }\n",
      "    {'X2'   }    {'b'        }    {'X2 + X1*X3' }\n",
      "    {'X3'   }    {'ab'       }    {'X3 + X1*X2' }\n",
      "    {'X1*X2'}    {'ab'       }    {'X3 + X1*X2' }\n",
      "    {'X1*X3'}    {'b'        }    {'X2 + X1*X3' }\n",
      "    {'X2*X3'}    {'a'        }    {'X1 + X2*X3' }\n",
      "\n"
     ]
    }
   ],
   "source": [
    "[dfF3,confounding] = fracfact('a b ab')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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dPTaBcPLkyY0bN65du9bo8aBHvtCYp5i1Qbk0Qbn0FJkUoA8dOuR2u8vKyggh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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot3(dfF3(:,1),dfF3(:,2),dfF3(:,3),'o'), grid on\n",
    "xlabel('x1'),ylabel('x2'),zlabel('x3')\n",
    "view(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plan trójpoziomowy i pięciopoziomowy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " BBDESIGN Generate Box-Behnken design.\n",
      "    D=BBDESIGN(NFACTORS) generates a Box-Behnken design for NFACTORS\n",
      "    factors.  The output matrix D is N-by-NFACTORS, where N is the\n",
      "    number of points in the design.  Each row lists the settings for\n",
      "    all factors, scaled between -1 and 1.\n",
      " \n",
      "    D=BBDESIGN(NFACTORS,'PNAME1',pvalue1,'PNAME2',pvalue2,...)\n",
      "    allows you to specify additional parameters and their values.\n",
      "    Valid parameters are the following:\n",
      "  \n",
      "        Parameter    Value\n",
      "        'center'     The number of center points to include.\n",
      "        'blocksize'  The maximum number of points allowed in a block.\n",
      " \n",
      "    [D,BLK]=BBDESIGN(...) requests a blocked design.  The output\n",
      "    vector BLK is a vector of block numbers.\n",
      " \n",
      "    Box and Behnken proposed designs when the number of factors was\n",
      "    equal to 3-7, 9-12, or 16.  This function produces those designs.\n",
      "    For other values of NFACTORS, this function produces designs\n",
      "    that are constructed in a similar way, even though they were not\n",
      "    tabulated by Box and Behnken and they may be too large to be\n",
      "    practical.\n",
      " \n",
      "    See also CCDESIGN, ROWEXCH, CORDEXCH.\n",
      "\n",
      "    Reference page in Doc Center\n",
      "       doc bbdesign\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help bbdesign"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dBB =\n",
      "    -1    -1     0\n",
      "    -1     1     0\n",
      "     1    -1     0\n",
      "     1     1     0\n",
      "    -1     0    -1\n",
      "    -1     0     1\n",
      "     1     0    -1\n",
      "     1     0     1\n",
      "     0    -1    -1\n",
      "     0    -1     1\n",
      "     0     1    -1\n",
      "     0     1     1\n",
      "     0     0     0\n",
      "     0     0     0\n",
      "     0     0     0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dBB = bbdesign(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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WlClTpkyZkqEvrmd5DqA/BDSYmJ7lOYD+8M8aDFBSUpKW\ngjej5TmA4TBnBwDAKPSDBgBgFCpoAABGIaABABiFgAYAYBQCGgCAUQhoAABGIaABABiFgAYAYBQC\nGgCAUQhoAABGIaABABiFgAYAYBQCGgCAUQhoAABGIaABABiFgAYAYBQCGgCAUQhoAABGIaABABiF\ngAYAYBQCGgCAUQhoAABGIaABABiFgAYAYBQCGgCAUQhoAABGIaABABiFgAYAYBQCGgCAUQhoAABG\nIaABABiFgAYAYBQCGgCAUf8fBHUJeK45plEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot3(dBB(:,1),dBB(:,2),dBB(:,3),'o')\n",
    "\n",
    "X = [1 -1 -1 -1 1 -1 -1 -1 1 1 -1 -1;\n",
    "     1 1 1 -1 1 1 1 -1 1 1 -1 -1];\n",
    "\n",
    "Y = [-1 -1 1 -1 -1 -1 1 -1 1 -1 1 -1; \n",
    "      1 -1 1 1 1 -1 1 1 1 -1 1 -1];\n",
    "\n",
    "Z = [1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1;\n",
    "     1 1 1 1 -1 -1 -1 -1 1 1 1 1];\n",
    "\n",
    "line(X,Y,Z,'Color','k')\n",
    "axis square equal\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " CCDESIGN Generate central composite design.\n",
      "    D=CCDESIGN(NFACTORS) generates a central composite design for\n",
      "    NFACTORS factors.  The output matrix D is N-by-NFACTORS, where N is\n",
      "    the number of points in the design.  Each row represents one run of\n",
      "    the design, and it has the settings of all factors for that run.\n",
      "    Factor values are normalized so that the cube points take values\n",
      "    between -1 and 1.\n",
      "    \n",
      "    D=CCDESIGN(NFACTORS,'PNAME1',pvalue1,'PNAME2',pvalue2,...)\n",
      "    allows you to specify additional parameters and their values.\n",
      "    Valid parameters are the following:\n",
      "    \n",
      "       Parameter    Value\n",
      "       'center'     The number of center points to include, or 'uniform'\n",
      "                    to select the number of center points to give uniform\n",
      "                    precision, or 'orthogonal' (the default) to give an\n",
      "                    orthogonal design.\n",
      "       'fraction'   Fraction of full factorial for cube portion expressed\n",
      "                    as an exponent of 1/2:  0 = whole design, 1 = 1/2\n",
      "                    fraction, 2 = 1/4 fraction, etc.\n",
      "       'type'       Either 'inscribed', 'circumscribed', or 'faced'.\n",
      "       'blocksize'  The maximum number of points allowed in a block.\n",
      "    \n",
      "    [D,BLK]=CCDESIGN(...) requests a blocked design.  The output\n",
      "    vector BLK is a vector of block numbers.  Blocks are groups of\n",
      "    runs that are to be measured under similar conditions (for example,\n",
      "    on the same day).  Blocked designs minimize the effect of between-\n",
      "    block differences on the parameter estimates.\n",
      " \n",
      "    See also BBDESIGN, ROWEXCH, CORDEXCH.\n",
      "\n",
      "    Reference page in Doc Center\n",
      "       doc ccdesign\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help ccdesign"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dCCD_1 =\n",
      "    -1    -1\n",
      "    -1     1\n",
      "     1    -1\n",
      "     1     1\n",
      "    -1     0\n",
      "     1     0\n",
      "     0    -1\n",
      "     0     1\n",
      "     0     0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dCCD_1=ccdesign(2,'center',1, 'type','faced')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
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IHb7++uvJH7a/eaZqae22suczOiJke/XE+B9PjPd0/vuk29ktmOpKu8Vhn7PY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\nQCgCDQBCEWgAEIpAA4BQ/xfn8kib8B2ZewAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(dCCD_1(:,1),dCCD_1(:,2),'o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dCCD_2 =\n",
      "   -1.0000   -1.0000\n",
      "   -1.0000    1.0000\n",
      "    1.0000   -1.0000\n",
      "    1.0000    1.0000\n",
      "   -1.4142         0\n",
      "    1.4142         0\n",
      "         0   -1.4142\n",
      "         0    1.4142\n",
      "         0         0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dCCD_2=ccdesign(2,'center',1, 'type','circumscribed')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dCCD_3 =\n",
      "   -0.7071   -0.7071\n",
      "   -0.7071    0.7071\n",
      "    0.7071   -0.7071\n",
      "    0.7071    0.7071\n",
      "   -1.0000         0\n",
      "    1.0000         0\n",
      "         0   -1.0000\n",
      "         0    1.0000\n",
      "         0         0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dCCD_3=ccdesign(2,'center',1, 'type','inscribed')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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aZDLl5OQUFRXFx8cbjcbU1NTx48fHxsbarlNWVrZgwYIpU6Z4vjwAkIQK56B3\n7tzZvXv3+Ph4IUR4ePioUaN27dplt055eXn//v2NRmNjY6PnKwQAGagQ0DU1NQMHDrQ+DAkJOXbs\nmO0KJpPp3Llzr7766s9+9rP77rtv4cKFzQ2l1Wq1Wm1BQUEHlgvgNlBQUKDkidqF/IA6pzg0mu//\nYtBoNGaz2XaFysrKtLS0559/PioqqrKyMiMjo7Cw8IknnnAcqqKiosPLBXAbyMzMzMzMFEJIldEq\nHEEHBASYTCbrQ7PZ7Of3g78noqKi8vPzo6KihBA9e/Z88MEHDx486OkqAUBtKgR0jx49vvnmG+vD\n6urqIUOG2K5w9uzZNWvWWB/evHmzc+fOnqsPAOSgQkAnJSUJIXbs2CGEOH78+J49e4YPHy6EOHz4\n8IULF4QQ9fX1OTk5J06cEEJUVlZu2bJl3Lhxnq8TANSlwjlojUbzxhtvzJ07Nz4+vqysbPHixZGR\nkUKIvLy8Rx99ND09XavVLliwICMjIyEh4euvv87MzORL0ABuQ50sFovaNbSTVqvlIiEA95IqWOjF\nAQCSIqABQFIENABIioAGAEkR0AAgKQIaACRFQAOApAhoAJAUAQ0AkiKgAUBSBDQASIqABgBJEdAA\nICkCGgAkRUADgKQIaACQFAENAJIioAFAUgQ0AEiKgAYASRHQACApAhoAJEVAA4CkCGgAkBQBDQCS\nIqABQFIENABIioAGAEkR0AAgKQIaACRFQAOApAhoAJAUAQ0AkiKgAUBSBDQASIqABgBJEdAAICkC\nGgAkRUADgKQIaACQFAENAJIioAFAUgQ0AEiKgAYASRHQACApAhoAJEVAA4CkCGgAkBQBDQCSIqAB\nQFIENABIioAGAEkR0AAgKd8M6MZL+osrshsv6dUuBFJgf4CVd+0MfmoX0CEuvpXtf2eMISe939v7\n1K7le2eM9X86cKFBv0YIcSHkZ+9PvlvtinyfMueD9vx2aP0RQ85eqfYHXyX5fi5nODRH3iNovV6/\nefPmioqKNr8wZ1LwPbpes/NCx2RcXJHdEbW1wxljfb9Fe4QQz8WuzwgtGt2/e79Fe84Y69Wuy5cp\nc97/oxkp2mPVQ3qFjslYPWcac96hJN/P5QwHFyQN6A0bNkyePHnTpk2zZs1avnx5619YVbRUCBGR\nMc/6X2WJ6kYvXV+ccfO52L+Zaw1xfeKf6LW7OOPmwv8pVLsuXzZ66fo1PT5K0R7rHNIprk98yPAf\npdx1Y/37L6pdly+TeT+XNhxc6GSxWNSuwZ7JZEpKSioqKoqPjzcajampqX/9619jY2PtVtNqtXbH\n17VleypXzLH9l0vjJb0hJz0iY17omAwPVN6cDw5cuP/0z/sGXvaLGBbQd5Imwp5jaQAAEjpJREFU\nKLquYrm5znDGWF8z5IuU/mEq1uarmpvzxkv6gN5/UHd/8FUy7+etDwfHYFGRjEfQO3fu7N69e3x8\nvBAiPDx81KhRu3btcrqmVqvVarUFBQXKw8oVc5S/GK38e8T0nP3mle1/6eiaXTtrrF92/TVNcHRA\n30kBMen+kcMC+k4SQiy7/tqOEzXq1uarzhrrr3xx03TdYjfnRTVzVd8ffJXM+3mL4VBQUKDkiRrV\nNUvGgK6pqRk4cKD1YUhIyLFjx5yuWVFRUVFRkZmZqTyMyJjn+G+WqqKldhvG80bHdy+50DVIm1VX\nsdxcazDXGhrOre16/5KSC11Hx3dXtzZfNTq++/LOE2sPm+zm/L4jm1TfH3yVzPt5i+GQmZmp5InH\nS3NFxoA2mUwazfeFaTQas9ncmheGjsmwO/evXBMIvkfn/irbIjYsSAixed9GIcTVPU9cPzTfXGfY\nvH+jEILzGx0kNizoUN8HD/1okLCZ88q3f7Ev8G7V9wdfJfN+Lm04uCZjQAcEBJhMJutDs9ns59fa\nrwPanvu3vSagrtjwwG2zBp+rj9TXR3zVb/3l2FcLL46INn8l2zeQfIky5xdCExtOnTMZH7sc++qp\nM+HBCT8aMnOB2qX5LMn3cznDwTUZLxLu27fv2WefLSkpUR7OmjVr7Nix48aNs1utuXP5yrn/oHuG\n15XJ9b1Xc63hV+uvfXDgQmx44LSf9B4d3131wwqfZ641vPjpqf/199n7A+/OCDpz9tmNzHlHk3k/\nb004SHWRUMaANpvNo0ePzs3NHT169PHjx9PT07ds2RIZGWm3mot5bLykrypaGjomQ/J/v8Az2B9g\n1eLOQEC3bN++fXPnzo2Pjy8rK8vNzX3kkUcc15FqHgH4BqmCRdKfej/wwAO7d+9WuwoAUJOMFwkB\nAIKABgBpEdAAICkCGgAkRUADgKQIaACQFAENAJIioAFAUgQ0AEiKgAYASRHQACApAhoAJEVAA4Ck\nCGgAkBQBDQCSIqABQFIENABIioAGAEkR0AAgKQIaACRFQAOApAhoAJAUAQ0AkiKgAUBSBDQASIqA\nBgBJEdAAICkCGgAkRUADgKQIaACQFAENAJIioAFAUgQ0AEiKgAYASRHQACApAhoAJEVAA4CkCGgA\nkBQBDQCSIqABQFIENABIioAGAEkR0AAgKQIaACRFQAOApAhoAJAUAQ0AkiKgAUBSBDQASIqABgBJ\nEdAAICkCGgAkRUADgKQIaACQlJ9ab6zX6ysqKmJiYrRardMVjEbjqVOnrA8HDBgQGhrqqeoAQH3q\nBPSGDRtef/11nU538ODB8ePHZ2VlOa6zbt26ZcuWBQQEKA/z8/OTk5M9WyYAqEmFgDaZTDk5OUVF\nRfHx8UajMTU1dfz48bGxsXarlZWVLViwYMqUKZ6vEABkoMI56J07d3bv3j0+Pl4IER4ePmrUqF27\ndjmuVl5e3r9/f6PR2NjY2NxQWq1Wq9UWFBR0YLkAbgMFBQVKnqhdyA+ocARdU1MzcOBA68OQkJBj\nx47ZrWMymc6dO/fqq68ajcaampqJEyfm5uY6DlVRUdGxtQK4PWRmZmZmZgohpMpoFY6gTSaTRvP9\n+2o0GrPZbLdOZWVlWlraO++8s2fPnm3btpWUlBQWFnq2TABQmYcCOjc3d/DgwYMHDx45cmRAQIDJ\nZLI+ZTab/fzsD+SjoqLy8/OjoqKEED179nzwwQcPHjzomVIBQBIeOsUxZcqU1NRUIYSfn5/FYvnm\nm2+sT1VXV48dO9Zu/bNnzx44cCA9PV15ePPmzc6dO3umVACQhIeOoOPi4nQ6nU6nGzp0aFJSkhBi\nx44dQojjx4/v2bNn+PDhymqHDx++cOGCEKK+vj4nJ+fEiRNCiMrKyi1btowbN84zpQKAJFS4SKjR\naN544425c+fGx8eXlZUtXrw4MjJSeSovL+/RRx9NT0/XarULFizIyMhISEj4+uuvMzMz+RI0gNtN\nJ4vFonYN7aTVavkWBwD3kipY6MUBAJIioAFAUgQ0AEiKgAYASRHQACApAhoAJEVAA4CkCGgAkBQB\nDQCSIqABQFIENABIioAGAEkR0AAgKQIaACRFQAOApAhoX9Z4ubSuIk/tKiCLBv0ac61B7SrQBgS0\nL7upX1tXsbzxcqnahUAKNw7Nb9CvUbsKtIEKt7xCR7MeJTVWlfpFDLupX9s5OFoIoQmOVrUuqEPZ\nHxqrSjXB0Q36tQEx6YKdwUsQ0D6ormJ5g36NJjjaP2JYkDbr+qH5NZtHCiG66Qr9I4epXR08qvFy\n6bU9T2iCozVB0V3vX9JUVXp1zxPmWkOQNitIm612dWgBAe2DgrRZQghTraFr4hLl4bU9pUHaLNL5\nNuQfOSxIm9WgXxuSuEQTHO0fOazx8j5NUDTp7BU4B+2DNMHRSkabaw3mWkNTVSmHS7ezIG12kDar\nrmK5EELZH0JHFKpdFFqFI2jfpAmObqoqvX5ovnVJkFbFcqCyhnNrhRA1m0f++3z05VL+OeUVOIL2\nTco3N/wjHwhJXOIf+YC5zsD3q25nTVWlQojuaSXKP62Uh5BfJ4vFonYN7aTVaisqKtSuQl7mWoP1\nSr3tnwG4IFWwcATts2wTmXQGvBEBDQCSIqABQFIENABIioAGAEkR0AAgKQIaACRFQAOApAhoAJAU\nAQ0AkiKgAUBSBDQASIqABgBJEdAAICkCGgAkRUADgKQIaACQFAENAJIioAFAUgQ0AEiKgAYASRHQ\nACApAhoAJEVAA4CkCGgAkBQBDQCSIqABQFIENABIioD2tMZL+osrshsv6dUuBOhA7OduQUB71PaT\n1Rffyv7TPy8YctLVruV2sf1k9Xs7Dmzet/GDAxfUruV2wX7uLrIHdElJidoluM2YlV8actIv9R5c\n/8TrX/Z9cPWcaWpX5PvGrPzymdVH7jz7f+sq8v504EK/RXvUrsj3sZ+7USeLxaJ2Dc1auXJlYWFh\ncxmt1WorKio8XFK7jVn55c9O/09G8OmYl9cqSy6uyN59LWTSC7nqFubDxqz8cmpS72lJvY3r+wkh\nuukKXzvYc/vJ6m2/G6x2aT7LB/ZzqYJF0iPompqaF1544d1331W7EPc4Y6yvLds78XqJda8VQkRk\nzBt8rvjqtiIVC/NhZ4z1c0N+/9iVDOP6fl0TlwTEpN/4an5W56fnhvx++8lqtavzTeznbidpQOfl\n5YWHh7/22muuV9NqtVqttqCgwDNVtdv2k9WvV62KyJhnu9C/R8z/u+v/XNn+F7Wq8m3bT1YbNPeb\naw0BMekBMelB2qwgbZa51mDQ3H/GWK92db7Jq/fzgoICJU/ULuQHJA3oF198cf78+UFBQa5Xq6io\nqKioyMzM9ExV7RYbHlhwx6SqoqV2y2df+fR62v9WpSSfFxseWHQ1o3taianWIITQBEc3nFvbNXHJ\nfr+papfms7x6P8/MzFTyRO1CfkDSgNZoJC2sfWLDgg71fTB0TMbFFdnWhfqcSUW1/YLu0alYmA+L\nDQs6U13fWFUqhLhxaH7N5pHmOoMQYvvJ6pT+YWpX55vYz91OlhzMzc0dPHjw4MGDR44cqXYt7hcb\nHjjtJ71/cny4EEI5vqgqWrrjZE1ExrzY8EC1q/NNypy/+/lfzXWGLjGTAmImmWsNX2x7N+ehfsx5\nB2E/dzs/tQv4tylTpqSmpgoh/PxkKcm9ch7u96PwwJ/8efhHuxZV7v36gfoj0S9v5FCuQ+U83G/r\n18/ft7pcs88sxNCYgPyXHu43LqG32nX5MvZz95IlDePi4uLi4tSuomNNS+qd0n98nyZdVdHS0DFv\n9mOv7XipCT/e0SdeCHGmuo6Y8Az2czeSJaBvE7HhgULE9Jqdp3YhtxHlH9f8E9uT2M/dRZZz0E6N\nHj3al35JCABtInVAA8DtjIAGAEkR0AAgKQIaACRFQAOApAhoAJAUAQ0AkiKgAUBSBDQASIqABgBJ\nEdAAICkCGgAkRUADgKQIaACQFAENAJIioAFAUgQ0AEiKgAYASRHQACApAhoAJEVAA4CkCGgAkBQB\nDQCSIqABQFIENABIioAGAEkR0AAgKQIaACRFQAOApAhoAJAUAQ0AkiKgAUBSBDQASIqABgBJEdAA\nICkCGgAkRUADgKQIaACQFAENAJIioAFAUgQ0AEiKgIbva7ykv7giu/GSXu1CgLYhoOH7Lr6VLYQw\n5KSrXQjQNgQ0fJw+Z1LwPbpes/NCx2RcXJGtdjlAGxDQ8GVVRUuFEBEZ86z/VZYAXoGAhs+qLdtz\ndVtRzMtrrUsiMuZd3VZ0dVuRilUBrUdAw2dVrpijHDVb+feI6Tn7zSvb/6JWSUCbENDwWREZ8xxP\naFQVLbVLbUBaBDR8VuiYDLsLg8oFw+B7dCpWBbQeAQ1fZnth0PaCIeAV/NQuAOhYERnzDDnpjZf0\ndWV7+729T+1ygDbgCBo+zr9HTPTLa4QQPWe/qXYtQNtwBA3f598jptfsPLWrANqMI2gAkJTKAV1S\nUtLcU0aj8Z82rl696snCOlRBQYHaJbQTlXseld/OOlksFrXee+XKlYWFhc1l9H//938vW7YsICBA\neZifn5+cnGy7glarraio6PAqOwCVex6Ve56XVi5V2eqcg66pqVm8ePGmTZu6du3a3DplZWULFiyY\nMmWKJwsDAHmoE9B5eXnh4eGvvfbaokWLmlunvLz88ccfNxqN3bp18/f3d1xh6NChWq22I8vsQFTu\neVTued5Y+dChQ9Uu4XvqnOIwm80ajWbHjh0LFy50eorDZDIlJCTExcUZjcaampqJEyfm5uZ6vk4A\nUJE6Fwk1mhbet7KyMi0t7Z133tmzZ8+2bdtKSkoKCws9UxsASMJDAZ2bmzt48ODBgwePHDmyNetH\nRUXl5+dHRUUJIXr27Pnggw8ePHiwg2sEALl46Bz0lClTUlNThRB+fq16x7Nnzx44cCA9/d/3KLp5\n82bnzp07sD4AkI+HAjouLi4uLq7F1Q4fPtyjR4/evXvX19fn5OTcf//98fHxlZWVW7ZsWbx4sQfq\nBAB5yPVLwry8vN27dwshtFrtggULMjIypk6d+tOf/nTGjBl2X4IGAJ+n5g9VAAAuyHUEDQCwIqAB\nQFLe1260pKTE6Xf1jEbjqVOnrA8HDBgQGhrqwbrarLkPIhW9Xl9RURETE+P0J2FeMeeuP4JUfGC2\nbXnFHq6QN1UsXuWtt95KTk52+tS77747aNCgxP8oKSnxcG1t4uKDyGP9+vU6ne7ZZ58dM2ZMXl6e\n4wryz3mLH0EePjDbtrxiD1fInCpeE9DV1dXPP/98YmJic1M5Z86cjz/+2MNVtUOLH0QSTU1NiYmJ\nx48ft1gsVVVV99133+nTp+3WkXzOW/MRJOEDs23lLXu4xRtSxWvOQVv7KzW3Qnl5ef/+/Y1GY2Nj\noycLa6sWP4gkdu7c2b179/j4eCFEeHj4qFGjdu3aZbeO5HPemo8gCR+YbStv2cOFN6SK15yDfvHF\nF5X+Sk6fNZlM586de/XVV+VvruT6g8ijpqZm4MCB1ochISHHjh2zXUH+OW/xI8jDB2bbylv2cOEN\nqeI1R9Cu+yt5UXOlFhtFScJkMtmWqtFozGaz7Qryz3mLH0EePjDbVt6yhwtvSBV5p7JN/ZVkbq7U\n1kZRKrItNSAgwGQyWZ8ym812fVRknnNFix9BHj4w275HhjmXdH8VbeyvJHNzpbY2ilKRbakWi+Wb\nb76xPlVdXT127FjblWWec0WPHj1cfwR5tFiq/LPte6SYcxUvULbD9u3bba+3fvXVV+fPn7dYLEeP\nHh00aJByEfzixYs6nU7yLyHZfRAJmUym5OTk7du3WyyWY8eO3Xvvvd99953Fq+a8uY8gIR+YbTvy\n7+FWMqeKdwf0tGnTPvnkE+XPH3/8cWJi4tNPP52YmPjee++pVGBrecXuW1paqtPpnn766SFDhnz+\n+efKQu+ac6cfQU4+MNu2vGIPV8icKj7VLMlsNtfX1wcGBnrRZQr51dbWuphSr5hz1x9BKj4w2z5G\n3Tn3qYAGAF/C38MAICkCGgAkRUADgKQIaACQFAENAJIioAFAUgQ0AEiKgAYASRHQACApAhoAJEVA\nA4CkCGgAkBQBDQCSIqABQFIENABIioAGAEkR0AAgKQIaACRFQAOApAhoAJAUAQ0AkiKgAUBSBDQA\nSIqABgBJEdAAICkCGgAkRUADgKQIaACQFAENAJIioAFAUgQ0AEiKgAYASf1/yPYaatiI1sQAAAAA\nSUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(dCCD_1(:,1),dCCD_1(:,2),'o',dCCD_2(:,1),dCCD_2(:,2),'d',dCCD_3(:,1),dCCD_3(:,2),'p')\n",
    "legend('trójpoziomowy  (face-centered)', 'pięciopoziomowy - rotalny (circumscribed)','pięciopoziomowy - rotalny przeskalowany (inscribed)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Plany równomiernie wypełniające przestrzeń"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%plot inline -w 600 -h 600"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plan losowy o rozkładzie prawdopodobieństwa jednostajnym"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " RAND Uniformly distributed pseudorandom numbers.\n",
      "    R = RAND(N) returns an N-by-N matrix containing pseudorandom values drawn\n",
      "    from the standard uniform distribution on the open interval(0,1).  RAND(M,N)\n",
      "    or RAND([M,N]) returns an M-by-N matrix.  RAND(M,N,P,...) or\n",
      "    RAND([M,N,P,...]) returns an M-by-N-by-P-by-... array.  RAND returns a\n",
      "    scalar.  RAND(SIZE(A)) returns an array the same size as A.\n",
      " \n",
      "    Note: The size inputs M, N, P, ... should be nonnegative integers.\n",
      "    Negative integers are treated as 0.\n",
      " \n",
      "    R = RAND(..., CLASSNAME) returns an array of uniform values of the \n",
      "    specified class. CLASSNAME can be 'double' or 'single'.\n",
      " \n",
      "    R = RAND(..., 'like', Y) returns an array of uniform values of the \n",
      "    same class as Y.\n",
      " \n",
      "    The sequence of numbers produced by RAND is determined by the settings of\n",
      "    the uniform random number generator that underlies RAND, RANDI, and RANDN.\n",
      "    Control that shared random number generator using RNG.\n",
      " \n",
      "    Examples:\n",
      " \n",
      "       Example 1: Generate values from the uniform distribution on the\n",
      "       interval (a, b).\n",
      "          r = a + (b-a).*rand(100,1);\n",
      " \n",
      "       Example 2: Use the RANDI function, instead of RAND, to generate\n",
      "       integer values from the uniform distribution on the set 1:100.\n",
      "          r = randi(100,1,5);\n",
      " \n",
      "       Example 3: Reset the random number generator used by RAND, RANDI, and\n",
      "       RANDN to its default startup settings, so that RAND produces the same\n",
      "       random numbers as if you restarted MATLAB.\n",
      "          rng('default')\n",
      "          rand(1,5)\n",
      " \n",
      "       Example 4: Save the settings for the random number generator used by\n",
      "       RAND, RANDI, and RANDN, generate 5 values from RAND, restore the\n",
      "       settings, and repeat those values.\n",
      "          s = rng\n",
      "          u1 = rand(1,5)\n",
      "          rng(s);\n",
      "          u2 = rand(1,5) % contains exactly the same values as u1\n",
      " \n",
      "       Example 5: Reinitialize the random number generator used by RAND,\n",
      "       RANDI, and RANDN with a seed based on the current time.  RAND will\n",
      "       return different values each time you do this.  NOTE: It is usually\n",
      "       not necessary to do this more than once per MATLAB session.\n",
      "          rng('shuffle');\n",
      "          rand(1,5)\n",
      " \n",
      "    See <a href=\"matlab:helpview([docroot '\\techdoc\\math\\math.map'],'update_random_number_generator')\">Replace Discouraged Syntaxes of rand and randn</a> to use RNG to replace\n",
      "    RAND with the 'seed', 'state', or 'twister' inputs.\n",
      " \n",
      "    See also RANDI, RANDN, RNG, RANDSTREAM, RANDSTREAM/RAND,\n",
      "             SPRAND, SPRANDN, RANDPERM.\n",
      "\n",
      "    Reference page in Doc Center\n",
      "       doc rand\n",
      "\n",
      "    Other functions named rand\n",
      "\n",
      "       codistributed.rand      codistributor2dbc/rand    gpuArray.rand\n",
      "       codistributor1d/rand    distributed.rand          RandStream/rand\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help rand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RANDd =\n",
      "    0.8147    0.1576\n",
      "    0.9058    0.9706\n",
      "    0.1270    0.9572\n",
      "    0.9134    0.4854\n",
      "    0.6324    0.8003\n",
      "    0.0975    0.1419\n",
      "    0.2785    0.4218\n",
      "    0.5469    0.9157\n",
      "    0.9575    0.7922\n",
      "    0.9649    0.9595\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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u8xqx3NqyI+CMUAM4n9oESQbHRJBkcEwESQbHRJBkcExwxlszuHFG2Byu49vW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\nTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RANDd=rand(10,2)\n",
    "plot(RANDd(:,1),RANDd(:,2),'o'),xlabel('x1'),ylabel('x2'),grid on, grid minor\n",
    "xlim([0 1]),ylim([0 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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8880dHR2LFy/+67/+629+85slnaLK6vE5myVzPHKVNW+wF19faMQXGo0kpK5+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\nCAEAAABZA44QAAAAkDXgCAEAAABZ8/8B2N63MZhW3NoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RANDd=rand(100,2);\n",
    "plot(RANDd(:,1),RANDd(:,2),'o'),xlabel('x1'),ylabel('x2'),grid on, grid minor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "covM =\n",
      "    0.0803   -0.0180\n",
      "   -0.0180    0.0796\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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8+fK//uu/7osNRzVm06ZNJ5xwwogRI8rLy1966aX9+/ensmTq1Km7d+++9957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\n+YFTPAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%doc cov\n",
    "covM=cov(RANDd)\n",
    "%doc hist\n",
    "hist(RANDd(:,1),20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plan losowy o rozkładzie prawdopodobieństwa normalnym"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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woUVx4YoE9k7i/Ska5t0w0lCMHI6Kmgrbx4ioz8Z9xYYWdL1vmZoRdnZ21p9Z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\njxZljHlm2od1StNhtYQifUkLoS8QSTpZKh1vY0dlgV2/jEi/Gsi5ps0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AjlAyNH5bpBEF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\nRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RANDNd=randn(100,2);\n",
    "plot(RANDNd(:,1),RANDNd(:,2),'o'),xlabel('x1'),ylabel('x2'),grid on, grid minor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "covM =\n",
      "    1.0653    0.0035\n",
      "    0.0035    0.8834\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "covM=cov(RANDNd)\n",
    "hist(RANDNd(:,1),20)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plan na podstawie wielowymiarowych sześcianów łacińskich (ang. LHS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " LHSDESIGN Generate a latin hypercube sample.\n",
      "    X=LHSDESIGN(N,P) generates a latin hypercube sample X containing N\n",
      "    values on each of P variables.  For each column, the N values are\n",
      "    randomly distributed with one from each interval (0,1/N), (1/N,2/N),\n",
      "    ..., (1-1/N,1), and they are randomly permuted.\n",
      " \n",
      "    X=LHSDESIGN(...,'PARAM1',val1,'PARAM2',val2,...) specifies parameter\n",
      "    name/value pairs to control the sample generation.  Valid parameters\n",
      "    are the following:\n",
      " \n",
      "       Parameter    Value\n",
      "       'smooth'     'on' (the default) to produce points as above, or\n",
      "                    'off' to produces points at the midpoints of\n",
      "                    the above intervals:  .5/N, 1.5/N, ..., 1-.5/N.\n",
      "       'iterations' The maximum number of iterations to perform in an\n",
      "                    attempt to improve the design (default=5)\n",
      "       'criterion'  The criterion to use to measure design improvement,\n",
      "                    chosen from 'maximin' (the default) to maximize the\n",
      "                    minimum distance between points, 'correlation' to\n",
      "                    reduce correlation, or 'none' to do no iteration.\n",
      " \n",
      "    Latin hypercube designs are useful when you need a sample that is\n",
      "    random but that is guaranteed to be relatively uniformly distributed\n",
      "    over each dimension.\n",
      " \n",
      "    Example:  The following commands show that the output from lhsdesign\n",
      "              looks uniformly distributed in two dimensions, but too\n",
      "              uniform (non-random) in each single dimension.  Repeat the\n",
      "              same commands with x=rand(100,2) to see the difference.\n",
      " \n",
      "       x = lhsdesign(100,2);\n",
      "       subplot(2,2,1); plot(x(:,1), x(:,2), 'o');\n",
      "       subplot(2,2,2); hist(x(:,2));\n",
      "       subplot(2,2,3); hist(x(:,1));\n",
      " \n",
      "    See also LHSNORM, UNIFRND.\n",
      "\n",
      "    Reference page in Doc Center\n",
      "       doc lhsdesign\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help lhsdesign"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LHSd =\n",
      "    0.0500    0.5500\n",
      "    0.2500    0.9500\n",
      "    0.1500    0.2500\n",
      "    0.3500    0.7500\n",
      "    0.4500    0.4500\n",
      "    0.7500    0.6500\n",
      "    0.5500    0.8500\n",
      "    0.8500    0.0500\n",
      "    0.6500    0.3500\n",
      "    0.9500    0.1500\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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LLo1qAGf5QpBkcEwESQbHRJBkcEwESQbHBGe8NQJnhIQQQhxNlG4Bo7S2th4+fHjQoEGp\nqakXPaGlpeXo0aNf+tKXhg4darEbIYQQ+2KPGWF5eXlubm5FRUV+fv7q1au7n1BUVPS9732voqLi\noYceWrhwYU/b5zq+Zd0xLAplGBa1bTIsCqtshu77Ny7Pp59+OmLEiCNHjvj9/rNnzw4fPrzLH5/0\n+XxpaWlNTU1+v/+DDz5IS0s7dOhQ93Zw7msJ88czrQdHBsfEjySDY+JHksEx8SPJ4JjgjLdGsMHS\n6Pbt22NjY5OTk0UkPj5+7NixO3bs6LIh7Pf7Y2JiROTKK690uVznz5+/aFPBZdW8vLzp06dH1vvS\nnDhxQlfX3cGRwTERJBkcE0GSwTERJBm9JiUlJaWlpRoFTGODRNje3j5kyJDgYf/+/ZuamkJPcLlc\nBQUFc+bMmTBhQl1d3bRp04YPH37RpnB+xQTyy64AODI4JoIkg2MiSDI4JoIko9Fk0aJFixYtCpQv\n9WMOTGywR+jz+VyuzzxdLldnZ2eXc/bs2fOFL3zhmmuuiY2NbW5uPnfuXI+64Dq+Zd0xLAplGBa1\nbTIsCqtshu612cvz2muv/eAHPwgePvbYYwUFBaEnvPnmm1//+tc//fTTwOGsWbN+/etfd28HZ80a\nZx3fjySDY+JHksEx8SPJ4Jj4kWRwTHDGWyPYYEY4cODAAwcOBA+9Xm96enroCV6vNyUlpV+/foHD\nG2+8sbW11VJFQgghtsUGiTAjI0NEqqurReTIkSN1dXWjR48Wkf3797e1tYlIWlpabW3tsWPHROTD\nDz/cs2fPqFGjtCoTQgixDTZIhC6Xa9WqVfPnz585c+Z3v/vdFStWDBgwQEQKCwtra2tFZOjQofPn\nz7/rrrtmzpyZk5Pz1a9+9T/+4z961AXX8S3rjmFRKMOwqG2TYVFYZS/4rFEN4DwPUJBkcEwESQbH\nRJBkcEwESQbHBGe8NYINZoSEEEJI5GAiJIQQ4micmAhD17UD5dD/djln586dF31dRNatW2euzTBl\n022a9gxTNtdm6Nt71GZjY6PyNk17himbazP858HcNTLdpmlPc9fI3OfW9DUy3aZpzzDlSPybDX+N\nlLdp2tNGcI9QAzjr+IIkg2MiSDI4JoIkg2MiSDI4JjjjrRGcOCMkhBBCgjAREkIIcTRMhCK818fC\n7hgWhTIMi9o2GRaFVfaCe4QawFnHFyQZHBNBksExESQZHBNBksExwRlvjcAZISGEEEfDREgIIcTR\nMBGKcB3fwu4YFoUyDIvaNhkWhVX2gnuEGsBZxxckGRwTQZLBMREkGRwTQZLBMcEZb43gxBmhuSdE\nsBzpcpinlrAMUuY1YrmnZVvAGaEGcL61CZJML00WV7if2OJOjI9p8XRkJ8UW5aYlxsfoklEIjokg\nyeCYCJIMjgnOeGsEJ84Iu8N1fMu6i1BYZm98p6rZ6/9FjntBlntBVsGkweOfbWjxdDg8LGqrTMsw\nLGq76wNhQYMzQg3gfGsTJBnTJlXN3sUV7so5Iy/7ogUyysExESQZHBNBksExwRlvjcAZIbE9xfWn\nZmYkdHkxMe7Kqub2Fk+HFiVCiI1gIiR9ge7bgYnxMb3ZIySEOAcmQhGu41vYXSTC0u8f7y+ucHd/\nvcXT0Xa4sfvrvTEJ/0aosPDTolCGYVFoAgj3CDWAs44vSDKmTVo8HYu3uGdmXJedFBd8cfzahuyk\nuIJJgy2WUQ6OiSDJ4JgIkgyOCc54a4Qo3QKE9JbE+JiC2wYv3uIurj81Lin2uKdj/Z623mRBQoij\nYCIkfYFALqxq9lY3tyfGxVTmj+QGISHEIE7cI+z+BITQ/3Y5Z+fOnZd6YsK6devMtRmmbLpN055h\nyubaDH17j9oM89QSI20mxsfMykgoyh1629WnglnQtGeYsrk2w38ezF0j022a9jR3jcx9bk1fI9Nt\nmvYMU47Ev9nw10h5m6Y9bQT3CDWAs44vSDI4JoIkg2MiSDI4JoIkg2OCM94awYkzQkIIISQIEyEh\nhBBHw0Qownt9LOyOYVEow7CobZNhUVhlL7hHqAGcdXxBksExESQZHBNBksExESQZHBOc8dYInBES\nQghxNEyEhBBCHA0ToQjX8S3sjmFRKMOwqG2TYVFYZTP8jiElJSVQqKurC76opex2u7U7BMtut1u7\nQ4CysjLtDoDXKHCB9DoEyzjXCOdzC3WNcD63wfHWFvDHMhrA2dAWJBkcE0GSwTERJBkcE0GSwTHB\nGW+NwKVRQgghjoaJUITr+BZ2x7AolGFY1LbJsCisshdcGtUAzvKFIMngmAiSDI6JIMngmAiSDI4J\nznhrBM4ICSGEOBomQkIIIY7GNomwtbV169atF51rezyePf9MS0tLjxrnOr5l3TEsCmUYFrVtMiwK\nq+yFPfYIy8vLly9fnpWVtXfv3ilTpsydOze0dsuWLY8++mjwsKOj46677nriiSe6NIKzZo2zji9I\nMjgmgiSDYyJIMjgmgiSDY4Iz3hohSrfA5fH5fAUFBS+//HJycrLH48nJyZkyZUroxb7ttttuu+22\nQHnHjh0LFiz48Y9/rMeVEEKI3bBBIty+fXtsbGxycrKIxMfHjx07dseOHRf91nPu3LnHHnts2bJl\nsbGxF20qNTU1UMjLy5s+fXrElC/DiRMndHXdHRwZHBNBksExESQZHBNBktFrUlJSUlpaqlHAPJqf\nbGOAsrKy/Pz84OFjjz22aNGii55ZWFh43333XaqdMI/8CX04kJKq8LXBBzIpbNO0pzkZhkVtdwxL\nT2sZFoUmpmXCVPERa4rZtGlTVVXV008/HThcuHChiCxdurTLaZ988klmZmZJScmwYcMu2g7OmjXO\nOr4gyeCYCJIMjokgyeCYCJIMjgnOeGsEG/xqNDo62ufzBQ87Ozujoi6yovvnP/950KBBl8qChBBC\nyEWxQSIcOHDggQMHgoderzc9Pb37adXV1RMnTrTQixBCSF/ABokwIyNDRKqrq0XkyJEjdXV1o0eP\nFpH9+/e3tbUFT9u1a9fw4cPNdcF7fSzrjmFRKMOwqG2TYVFYZTN0b1IaYteuXVlZWTNmzEhPT3/9\n9dcDL86aNeuVV14JlH0+X0pKypkzZ8I0grN5G2ZD23pwZHBM/EgyOCZ+JBkcEz+SDI4JznhrBBvc\nPiEimZmZtbW1XV4sKioKll0ul402ZgkhhOBgg6VRQgghJHIwEYpwHd/C7hgWhTIMi9o2GRaFVTZD\n99qsdQTXrENvAtVSdrvd2h2C5cCmAoJPWVmZdgfAaxTc9UHwwblGOJ9bqGuE87m11x6hDW6oVwXO\nDZ44N70KkgyOiSDJ4JgIkgyOiSDJ4JjgjLdG4NIoIYQQR8NEKMJ1fAu7Y1gUyjAsattkWBRW2Qsu\njWoAZ/lCkGRwTARJBsdEkGRwTARJBscEZ7w1AmeEhBBCHA0TISGEEEfDRCjCdXwLu2NYFMowLGrb\nZFgUVtkL7hFqAGcdX5BkcEwESQbHRJBkcEwESQbHBGe8NQJnhIQQQhyNExNh6HSeZZxyY2OjdgeW\nw5f70jUq21pX1eytavaC+PTVsj3Q/GQbCwnzyJ/QhwMpqQpfG+ZPpZhu07SnORmGRW13DEtPa3sZ\nlif+fEzmvZm4tDb7mb3Zz+ytPOrpjWefCYvCKj5iDRScNWucdXxBksExESQZHBNBkumNyfi1DYnx\nVxblDv3fpjwdszceKpg0ODspznoZteCY4Iy3RnDi0ighxLGsr28TkWAWFJHE+JiCSYNnb3xHnxTR\nDBMhIcRBVDe3z8xI6PJiYtyVLZ6OwH4hcSBMhCK818fC7hgWhTIMi4l3nTlzJjE+psuLifExifEx\nHvclJ4V9PiwWf1rQ4B6hBnDW8QVJBsdEkGRwTARJxrTJ+vq24vq2yjkju7x+xU+2+X+RY7GMcnBM\ncMZbI3BGSAhxEIFfxCyucIe+OH5tg3tBliYjop8o3QKEEGIdifExRblpszceqlrrDSTF9XvaCm4b\n3H29lDgHzghFuI5vYXcMi0IZhsVcm4FcGPzJTGX+yFkZCb3xNCeDFha1VTZD942M1hG8wTP0JlAt\nZbfbrd0hWA7cgYvgU1ZWpt0B8BoFb5FG8MG5RjifW6hrhPO55Q31oOBs3uJsaAuSDI6JIMngmAiS\nDI6JIMngmOCMt0bg0ighhBBHw0QownV8C7tjWBTKMCxq22RYFFbZCy6NagBn+UKQZHBMBEkGx0SQ\nZHBMBEkGxwRnvDUCZ4SEEEIcDRMhIYQQR8NEKMJ1fAu7Y1gUyjAsattkWBRW2QvuEWoAZx1fkGRw\nTARJBsdEkGRwTARJBscEZ7w1ghNnhKHfYljGKTc2Nmp3YDl8mdeI5Z6WbQFnhBrA+dYmSDI4JoIk\ng2MiSDI4JoIkg2OCM94awYkzwu5wHd+y7hgWhTIMi9o2GRaFVfaCM0IN4HxrEyQZHBNBksExESQZ\nHBNBksExwRlvjcAZISGEEEfDREgIIcTRMBGKcB3fwu4YFoUyDIvaNhkWhVX2wjZ7hK2trYcPHx40\naFBqaupFT/B4PPv27bvqqqsyMzMvegLOmjXOOr4gyeCYCJIMjokgyeCYCJIMjgnOeGuEKN0Chigv\nL1++fHlWVtbevXunTJkyd+7cLidUV1c/9thjWVlZx48fj46OfvHFF10uTnYJIYRcHhskQp/PV1BQ\n8PLLLycnJ3s8npycnClTpoR+6/H5fI899lhhYeGoUaNE5Jvf/OaWLVtuv/12bcaEEELsgw0S4fbt\n22NjY5OTk0UkPj5+7NixO3bsCE2E1dXVX/rSlwJZUET++Mc/Xqqp4LJqXl7e9OnTg683NjaOGDHi\nom8xVxW+9sSJEybeFSFPczIMi9ruGJae1jIsCk1UeZaUlJSWll6qC2RssEe4efPmN954Y+3atYHD\n+fPnR0VFLVmyJHjCH/7wh9ra2v79+7/66qv9+vV74IEH7r333u7t4KxZ46zjC5IMjokgyeCYCJIM\njokgyeCY4Iy3RrDBRprP5wvd8HO5XJ2dnaEnHD16tKKi4uabb96/f/9LL7303HPP7dixw3JNQggh\ntsQGiTA6Otrn8wUPOzs7o6L+aUX3y1/+8o033jht2jQRSU1NnThx4p/+9CerLQkhhNgTGyTCgQMH\nHjhwIHjo9XrT09NDT/jiF78YeuhyuXr6k1He62NZdwyLQhmGRW2bDIvCKpvhh8fn840ZM6aqqsrv\n9zc1Nd1yyy3vv/++3+/ft2/fyZMn/X7/+fPnMzMzt23b5vf7z549O3bs2F27dnVvJyUlxVrxS+J2\nu3UrfAaODI6JH0kGx8SPJINj4keSwTHBGW+NYINfjbpcrlWrVs2bNy85OfngwYMrVqwYMGCAiBQW\nFk6ePHnq1Kmf+9znnn766Z/+9KfPP//80aNH77nnnkvdU08IIYR0wQaJUEQyMzNra2u7vFhUVBQs\n33rrrZWVldZKEUII6QvYYI/QAriOb1l3DItCGYZFbZsMi8Iqe2GD+whVgXNfC869PoIkg2MiSDI4\nJoIkg2MiSDI4JjjjrRGcOCMM/RbDMk65sbFRuwPL4cu8Riz3tGwLOCPUAM63NkGSwTERJBkcE0GS\nwTERJBkcE5zx1ghOnBF2h+v4lnXHsCiUYVjUtsmwKKyyF5wRagDnW5sgyeCYCJIMjokgyeCYCJIM\njgnOeGsEzggJIYQ4GiZCQgghjoaJUITr+BZ2x7AolGFY1LbJsCisshfcI9QAzjq+IMngmAiSDI6J\nIMngmAiSDI4JznhrBM4ICSGEOBomQkIIIY7GiYmw+xMQQv/b5ZydO3cGyi2ejqpm7zOv1VY1ewNV\n69atM9dmmLLpNoOePW0zTNlcm6Fv71GbYZ5aYrpN055hyubaDP95MHeNTLdp2tPcNTL3uTV9jUy3\nadozTDkS/2bDXyPlbZr2tBHcIzREVbN3/NrGxPiY7KS49fVtifEx7gVZpk1w1vEFSQbHRJBkcEwE\nSQbHRJBkcEzstUdojz/DpJeqZu/sje/4f5ETOCzKHbq4wj34Z3W9yYWEEEJAcOLSaE+ZvfGdyvyR\noa8UTBqcGBcTXCMlhBBiX5gIRS53o0yLpyMxPqbL69lJcSv/5y/m2jT9rvCeak0i1B3DolCGYVHb\nJsOisMpecI/w8lx0FXR9fVt1c3tR7lATDeKs4wuSDI6JIMngmAiSDI6JIMngmNhrj5Azwstz0VXQ\n6ub2cUmxWnwIIYQohInw8szMSJi98Z3QV6qavVXN3lkZCbqUCCGEqIKJUORyu5/00QAAIABJREFU\ni+CzMhJm3Zow+Gd1sze+s7jCPX5tw+yN77gXZPX5dXxub1jWHcOiUIZhUdumE/YIxe8YUlJSAoW6\nurrgi8bL7rMfF+0+ee+66sqjnt604/f73W636fcqL7vdbu0OAcrKyrQ7AF6jwAXS6xAs41wjnM8t\n1DXC+dwGx1tbwB/LaABnQ1uQZHBMBEkGx0SQZHBMBEkGxwRnvDUCl0YJIYQ4GiZCEa7jW9gdw6JQ\nhmFR2ybDorDKXnBpVAM4yxeCJINjIkgyOCaCJINjIkgyOCY4460ROCMkhBDiaJgICSGEOBomQhGu\n41vYHcOiUIZhUdsmw6Kwyl5wj1ADOOv4giSDYyJIMjgmgiSDYyJIMjgmOOOtETgjJIQQ4micmAhD\np/Ms45QbGxu1O7AcvsxrxHJPy/ZA85NtLCTMI39CHw6kpCp8bfCBTArbNO1pToZhUdsdw9LTWoZF\noYlpmTBVfMQaKDhr1jjr+IIkg2MiSDI4JoIkg2MiSDI4JjjjrREsXRrt7Oz84x//uGTJkpMnT4a+\nfvLkyby8PCtNCCGEkABRlvXU2dk5dOjQmJiY/v37/+53v7vjjjtWrlwZrG1oaLDMhBBCCAli3Yzw\n4Ycfvvnmm/fv319bW1tWVvbaa689/PDDlvUeHt7rY1l3DItCGYZFbZsMi8Iqe2HdHmFOTs66detu\nuummwOHf/va3r371q/fdd99Pf/rTkydPTpgw4dChQ2He3traevjw4UGDBqWmpnav9Xg8x44dCx6m\npKRcffXVXc7BWbPGWccXJBkcE0GSwTERJBkcE0GSwTHBGW+NYN3SqMvleu+994KJcMCAAZs2bZo6\ndWpycnJmZmb495aXly9fvjwrK2vv3r1TpkyZO3dulxM2b978y1/+Mjo6OnC4Zs2aMWPGKP9fIIQQ\n0vewLhF+//vfv++++yorK6+//vrAK8OGDXvqqaf+3//7fzNmzAjzRp/PV1BQ8PLLLycnJ3s8npyc\nnClTpnT51nPw4MEFCxbcfffdkfMnhBDSJ7Fuj3DatGmTJk0aP378wYMHgy9OmTJl+fLlL774Ypg3\nbt++PTY2Njk5WUTi4+PHjh27Y8eOLuccOnQoKSnJ4/FcuHDBhBvX8S3rjmFRKMOwqG2TYVFYZS+s\nvo/www8/7L579/HHH7/xxht33HHHRd+yefPmN954Y+3atYHD+fPnR0VFLVmyJHiCz+cbNmzYTTfd\n5PF42tvbv/Od7yxdurR7O6Gbi3l5edOnT+/t/4xZTpw4ccMNN+jqvQs4MjgmgiSDYyJIMjgmgiSj\n16SkpKS0tDR4yD3CS3L11VePHz9+zZo1w4YNC764a9euRx999FKJ0OfzuVyfzVxdLldnZ2foCadP\nn54wYcKjjz56/fXXnz59+q677nrppZe++93vdm8K58KAbGgHwJHBMREkGRwTQZLBMREkGY0mixYt\nWrRoUaB80V81wqLhWaOjR4+eOnXq6tWrA4dz5879wQ9+8L3vfe9S50dHR/t8vuBhZ2dnVNQ/5e/r\nr79+zZo1ga3Ha6+9duLEiXv37o2MOyGEkL6GhkS4bNmy3/zmN2vXrh03btzw4cNra2u3bNmyYMGC\nS50/cODAAwcOBA+9Xm96enroCcePH9+0aVPw8Pz58/369euREtfxLeuOYVEow7CobZNhUVhlM3Q9\n5HTdunUpKSkpKSn/8z//E/5Mn883ZsyYqqoqv9/f1NR0yy23vP/++36/f9++fSdPnvT7/e+++25a\nWtqRI0f8fv+pU6eysrJqamq6t4PzENgwD8a1HhwZHBM/kgyOiR9JBsfEjySDY4Iz3hrB6j1CEfF4\nPHfeeeepU6dWr17t9Xofeuih3//+98XFxZc63+VyrVq1at68ecnJyQcPHlyxYsWAAQNEpLCwcPLk\nyVOnTk1NTV2wYMFdd901bNiwt99++0c/+hFvIiSEEGIQDYnwzjvvjI2N3bJlS+D+98mTJ3/jG99I\nS0sL82SZzMzM2traLi8WFRUFy3fffTdvIiSEEGICDXuEDz/88Kuvvhp8CszVV19dW1s7e/Zs602C\ncB3fsu4YFoUyDIvaNhkWhVX2gn+PUAM4zwMUJBkcE0GSwTERJBkcE0GSwTHBGW+NoGFGSAghhODg\nxEQYOp1nGafc2Nio3YHl8GVeI5Z7WrYHun+2ah1hfs5bV1entip8bZifOJtu07SnORmGRW13DEtP\naxkWhSamZcJU2ev2Ce4RagBnHV+QZHBMBEkGx0SQZHBMBEkGxwRnvDWCE5dGCSGEkCBMhIQQQhwN\nE6EI7/WxsDuGRaEMw6K2TYZFYZW94B6hBnDW8QVJBsdEkGRwTARJBsdEkGRwTHDGWyNwRkgIIcTR\nMBESQghxNEyEIlzHt7A7hkWhDMOitk2GRWGVzdB9I6N1BG/wDL0JVEvZ7XZrdwiWA3fgIviUlZVp\nd1B1jf7wRu0Tfz5WtPtk5VFPL32Ct0hrj4kf6RrhfG6hrhHO2MIb6kHB2bzF2dAWJBkcE+mdzPr6\ntsVb3IlxMYnxV7Z4Pm7xdlTmj0yMj7HeRDk4MjgmgiSDY4Iz3hpBw98jJKQPU9XsLa5vcy/ICr6y\nvr5t/LMNoa8QQqDgHqEI1/Et7K7Ph2X2xneKctNCX5yVkZAYF7PopR3m2jT9LqiwmOuOYVEoAxUW\nNLg0qgGc5QtBksExkV7IXPGTbf5f5HR5cX19W3Vze1HuUCtNIgGODI6JIMngmOCMt0bgjJAQZbR4\nOkzvBRJCdMFESIgyEuNjEuNiqpq9XV6vbm4flxSrRYkQclmYCEW4jm9hd30+LDMzEmZvfKfF0xF8\ncX19m4ikftpirk3T74IKi7nuGBaFMlBhQYN7hBrAWccXJBkcE1Fx+4SIZCfFra9vm5WRYG53sPcm\nysGRwTERJBkcE5zx1ghOnBGGfothGafc2Nio3UFJeVZGwi8ypSh36MyM69wLsv7rxnYct16W+8w1\nYtmysi3gjFADON/aBEkGx0SQZHBMBEkGx0SQZHBMcMZbIzhxRtgdruNb1h3DolCGYVHbJsOisMpe\ncEaoAZxvbYIkg2MiSDI4JoIkg2MiSDI4JjjjrRE4IySEEOJomAgJIYQ4GiZCEa7jW9gdw6JQhmFR\n2ybDorDKXnCPUAM46/iCJINjIkgyOCaCJINjIkgyOCY4460ROCMkhBDiaJgICSGEOBonJsLuT0AI\n/W+Xc3bu3HmpJyasW7fOXJthyqbbNO0ZpmyuzdC396jNME8tMd2mac8wZXNthv88mLtGpts07Wnu\nGpn73Jq+RqbbNO0ZphyJf7Phr5HyNk172gjuEWoAZx1fkGRwTARJBsdEkGRwTARJBscEZ7w1ghNn\nhIQQQkgQJkJCCCGOholQhPf6WNgdw6JQhmFR2ybDorDKXnCPUAM46/iCJINjIkgyOCaCJINjIkgy\nOCY4460RbDMjbG1t3bp162Uju3///vfff98aJUIIIX0AeyTC8vLy3NzcioqK/Pz81atXX+q0o0eP\n5uXl7d+/30o3QgghtsYGidDn8xUUFBQXF69cuXLTpk1FRUUtLS3dT7tw4cJPfvKTAQMGmOiC6/iW\ndcewKJRhWNS2ybAorLIXNtgjrKysfPLJJ7dt2xY4fPDBB0eNGpWXl9fltBUrVlx55ZUHDx78z//8\nzwkTJnRvB2fNGmcdX5BkcEwESQbHRJBkcEwESQbHBGe8NUKUboHL097ePmTIkOBh//79m5qaupyz\ne/fut956q6ys7P777w/TVGpqaqCQl5c3ffp05aoGOXHihK6uu4Mjg2MiSDI4JoIkg2MiSDJ6TUpK\nSkpLSzUKmMYGidDn87lcny3hulyuzs7O0BM+/PDDxx9//LnnnrtsUzjfUEC+tQXAkcExESQZHBNB\nksExESQZjSaLFi1atGhRoBycddgCG+wRRkdH+3y+4GFnZ2dU1D/l76eeeiotLe348ePV1dUej+fg\nwYM9TXhcx7esO4ZFoQzDorZNhkVhlb2wwR7hW2+99fDDD9fU1AQO8/Pz//3f//1b3/pW8ITVq1cf\nOnQoUH777bevu+66b33rW7Nnz+7SDs6aNc46viDJ4JgIkgyOiSDJ4JgIkgyOCc54awQbLI1mZGSI\nSHV19bhx444cOVJXV/fkk0+KyP79+wcOHJiQkDB37tzgyffff/+lfixDCCGEdMcGidDlcq1atWre\nvHnJyckHDx5csWJF4B6JwsLCyZMnT506VbcgIYQQG2ODPUIRyczMrK2tLS4u3rNnz+233x54saio\nqHsWfP75501MB7mOb1l3DItCGYZFbZsMi8Iqe2GDPUJV4KxZ46zjC5IMjokgyeCYCJIMjokgyeCY\n4Iy3RrDHjJAQQgiJEEyEhBBCHI0TE2HounagHPrfLufs3Lnzoq+LyLp168y1GaZsuk3TnmHK5toM\nfXuP2mxsbFTepmnPMGVzbYb/PJi7RqbbNO1p7hqZ+9yavkam2zTtGaYciX+z4a+R8jZNe9oI7hFq\nAGcdX5BkcEwESQbHRJBkcEwESQbHBGe8NYITZ4SEEEJIECZCQgghjoaJUIT3+ljYHcOiUIZhUdsm\nw6Kwyl5wj1ADOOv4giSDYyJIMjgmgiSDYyJIMjgmOOOtETgjJIQQ4miYCAkhhDgaJkIRruNb2B3D\nolCGYVHbJsOisMpm+B1DSkpKoFBXVxd8UUvZ7XZrdwiW3W63docAZWVl2h0Ar1HgAul1CJZxrhHO\n5xbqGuF8boPjrS3gj2U0gLOhLUgyOCaCJINjIr2WafF0FNe3tXg7xiXFzspI0GiiFhwZHBOc8dYI\nXBolhFjB+vq28c82iMi4pNji+rbxaxtaPB26pQgRYSIMwHV8y7pjWBTK2CgsVc3e4vo294KsgkmD\nZ2UkVM4ZOTMjYfyzDWVb68y1afpdUGEx110fCAsaXBrVAM7yhSDJ4JgIkgyOifRCZvDP6irzRybG\nx4S+OH5tQ3ZSXMGkwVaaRAIcGRwTnPHWCJwREkIiS1Wzt8XT0SULikjBpMEtXq6OEv0wERJCIkti\n3JXds6CIcI+QgMBEKMJ1fAu7Y1gUytglLG2HG7OT4qqavV1eL65vu8F/1lybpt+FExYnf1rQ4B6h\nBnDW8QVJBsdEkGRwTKQXMi2ejvHPNhTlDs1OigscLt7iFpGi3KEWm0QCHBkcE5zx1ghRugUIIX2f\nxPiYyvyRg39WlxgfkxgXU9XcPisjwXQWJEQtTlwaDZ3Os4xTbmxs1O7Acvhyb65R2+FG/y9yKvNH\nFuWm1U29MpgFEf6/WI5c2R5ofrKNhYR55E/ow4GUVIWvDT6QSWGbpj3NyTAsartjWHpay7AoNDEt\nE6aKj1gDBWfNGmcdX5BkcEwESQbHRJBkcEwESQbHBGe8NYITl0YJIYSQIEyEhBBCHA0ToQjv9bGw\nO4ZFoQzDorZNhkVhlb3gHqEGcNbxBUkGx0SQZHBMBEkGx0SQZHBMcMZbI3BGSAghxNEwERJCCHE0\nTIQiXMe3sDuGRaEMw6K2TYZFYZXN0H0jo3UEb/AMvQlUS9ntdmt3CJYDd+Ai+JSVlWl3ALxGwVuk\nEXxwrhHO5xbqGuF8bnlDPSg4m7c4G9qCJINjIkgyOCaCJINjIkgyOCY4460RuDRKCCHE0TARinAd\n38LuGBaFMgyL2jYZFoVV9oJLoxrAWb4QJBkcE0GSwTERJBkcE0GSwTHBGW+NwBkhIYQQR2ObP8zb\n2tp6+PDhQYMGpaamXvSEw4cPt7a2Jicng3whIoQQYgvsMSMsLy/Pzc2tqKjIz89fvXp19xN+9atf\n/ehHP3rzzTfvu+++559/vqftcx3fsu4YFoUyDIvaNhkWhVU2Q/f9G5fn008/HTFixJEjR/x+/9mz\nZ4cPH97lj082NTV95Stf8Xq9fr//zJkzQ4cOPXv2bPd2cO5rCfPHM60HRwbHxI8kg2PiR5LBMfEj\nyeCY4Iy3RrDBjHD79u2xsbHJyckiEh8fP3bs2B07doSekJSUtHnz5tjYWBH53Oc+5/P5Lly4oMeV\nEEKI3bDBHmF7e/uQIUOCh/37929qago9weVyJScn+3y+TZs2bdiw4YEHHrj22msv2lRwfzEvL2/6\n9OmRcw7PiRMndHXdHRwZHBNBksExESQZHBNBktFrUlJSUlpaqlHAPLqnpJfnlVdeeeCBB4KHCxYs\nWLBgQffTzpw5U1xcfN999911112BZdIuhJmqhz4cSElV+Nowyxem2zTtaU6GYVHbHcPS01qGRaGJ\naZkwVfZaGrXBfYTl5eV/+tOfnn322cDh/PnzP//5zz/xxBOXOn/mzJkjR46cO3dul9dx7mvBuddH\nkGRwTARJBsdEkGRwTARJBscEZ7w1gg32CAcOHHjgwIHgodfrTU9PDz3h2LFjofPx66677tSpU9b5\nEUIIsTM2SIQZGRkiUl1dLSJHjhypq6sbPXq0iOzfv7+trU1EfD7fz3/+82PHjonI3/72tx07dkyc\nOFGrMiGEENtgg0TocrlWrVo1f/78mTNnfve7312xYsWAAQNEpLCwsLa2VkT+5V/+ZeHChd/5znfu\nvffeCRMmzJgxIycnp0dd8F4fy7pjWBTKMCxq22RYFFbZCxvsEaoCZ80aZx1fkGRwTARJBsdEkGRw\nTARJBscEZ7w1gg1mhIQQQkjkYCIkhBDiaJgIRbiOb2F3DItCGYZFbZsMi8Iqm6H7RkbrCN7gGXoT\nqJay2+3W7hAsB+7ARfApKyvT7gB4jYK3SCP44FwjnM8t1DXC+dzyhnpQcDZvcTa0BUkGx0SQZHBM\nBEkGx0SQZHBMcMZbI3BplBBCiKNhIhThOr6F3TEsCmUYFrVtMiwKq+wFl0Y1gLN8IUgyOCaCJINj\nIkgyOCaCJINjgjPeGoEzQkIIIY6GiZAQQoijYSIU4Tq+hd0xLAplGBa1bTIsCqvsBfcINYCzji9I\nMjgmgiSDYyJIMjgmgiSDY4Iz3hrBiTPC0G8xLOOUGxsbtTuwHL7Ma8RyT8u2gDNCDfTyW1uLp6O4\nvq2q2ZsYf+W4pNhZGQkaZRSCYyJIMjgmgiSDYyJIMjgmOOOtEZw4I+yOjdbxWzwdg39WJyLZSXGJ\ncTHVze2LK9y98TQngxYWtVWmZRgWtd0xLAploMKCBmeEGujNt7YrfrKtcs6I7KS4/23K01Fc33Zj\nfIzpeSHOV0gcE0GSwTERJBkcE0GSwTHBGW+NwBmhnVhf3zYrIyGYBUUkMT5mZkbC4i1ujVaEEGJr\nmAjtxHFPx7ik2C4vJsbHJMbFtHg6tCgRQojdYSIUsc86fuuJ1uMXS3hVze0NDQ1qTcK/ESos3PVR\nKMOwKDSJUHd9ICxocI9QA6bX8auavcX1p4pyh4a+uL6+rbq5vcuLFsgoB8dEkGRwTARJBsdEkGRw\nTHDGWyNwRmgnAr8Unb3xnapmb+CVqmbv4i3umRnX6RUjhBD7EqVbgPSMgkmDF1e4x69tTIyPafF0\nJMbHFOUODf35DCGEkB7hxBlh9ycghP63yzk7d+681BMT1q1bZ67NMGUjbd529Sn3gqzK/JH+X+Rs\nyLkikAVNe4Ypm2sz9O09ajPMU0tMt2naM0zZXJvhPw/mrpHpNk17mrtG5v59mb5Gpts07RmmbK5N\nXWOLWk8bwT1CDeCs4wuSDI6JIMngmAiSDI6JIMngmOCMt0Zw4oyQEEIICcJESAghxNEwEYrwXh8L\nu2NYFMowLGrbZFgUVtkL7hFqAGcdX5BkcEwESQbHRJBkcEwESQbHBGe8NQJnhIQQQhwNEyEhhBBH\nw0QownV8C7tjWBTKMCxq22RYFFbZC+4RagBnHV+QZHBMBEkGx0SQZHBMBEkGxwRnvDWCE2eE5p4Q\nwXKky2GeWsIySJnXiOWelm0BZ4QawPnWJkgyOCaCJINjIkgyOCaCJINjgjPeGsGJM8LucB3fsu4Y\nFoUyDIvaNhkWhVX2gjNCDeB8axMkGRwTQZLBMREkGRwTQZLBMcEZb43AGSEhhBBHw0RICCHE0dgm\nEba2tm7dujXMXPvo0aNbt25taGgw0TjX8S3rjmFRKMOwqG2TYVFYZS/ssUdYXl6+fPnyrKysvXv3\nTpkyZe7cuV1OWLp06bZt29LT05uamq666qqioqLo6Ogu5+CsWeOs4wuSDI6JIMngmAiSDI6JIMng\nmOCMt0aI0i1weXw+X0FBwcsvv5ycnOzxeHJycqZMmRJ6sd95553f//73NTU1sbGxIvKtb32rvLx8\n6tSp2owJIYTYBxssjW7fvj02NjY5OVlE4uPjx44du2PHjtATYmNjn3/++UAWFJHBgwefPHlSgygh\nhBAbYoMZYXt7+5AhQ4KH/fv3b2pqCj0hISEhISEhUD5+/HhlZWV+fv5Fm0pNTQ0U8vLypk+fHny9\nsbFxxIgRF32LuarwtSdOnDDxrgh5mpNhWNR2x7D0tJZhUWiiyrOkpKS0tPRSXSBjgz3CTZs2VVVV\nPf3004HDhQsXisjSpUu7n3n69Onc3Ny77rrrookQZ80aZx1fkGRwTARJBsdEkGRwTARJBscEZ7w1\ngg2WRqOjo30+X/Cws7MzKuoiE9m33377zjvvnDFjxqWmg4QQQkh3bJAIBw4ceODAgeCh1+tNT0/v\nck5dXd0999zzxBNPzJ4921o7Qggh9sYGiTAjI0NEqqurReTIkSN1dXWjR48Wkf3797e1tYlIa2vr\nD3/4w6eeemr8+PEXLly4cOFC6AzSCLzXx7LuGBaFMgyL2jYZFoVV9sIGe4Qi8tZbb82bNy85Ofng\nwYNLly69/fbbRWT27NmTJ0+eOnXqihUrfvvb34ae/73vfe/xxx/v0gjOmjXOOr4gyeCYCJIMjokg\nyeCYCJIMjgnOeGsEG/xqVEQyMzNra2u7vFhUVBQoPPLII4888ojlUoQQQvoCNlgaJYQQQiIHE6EI\n1/Et7I5hUSjDsKhtk2FRWGUz/I4hJSUlUKirqwu+qKXsdru1OwTLbrdbu0OAsrIy7Q6A1yhwgfQ6\nBMs41wjncwt1jXA+t8Hx1hbY48cySsDZvMXZ0BYkGRwTQZLBMREkGRwTQZLBMcEZb43ApVFCCCGO\nholQhOv4FnbHsCiUYVjUtsmwKKyyF1wa1QDO8oUgyeCYCJIMjokgyeCYCJIMjgnOeGsEzggJIYQ4\nGiZCQgghjoaJUITr+BZ2x7AolGFY1LbJsCisshfcI9QAzjq+IMngmAiSDI6JIMngmAiSDI4Jznhr\nBM4ICSGEOBonJsLQ6TzLOOXGxkbtDiyHL/MasdzTsj3Q/GQbCwnzyJ/QhwMpqQpfG3wgk8I2TXua\nk2FY1HbHsPS0lmFRaBKsdZ/9+Ik/H8t+Zu+slw4V7T7ZG08+Yg0UnDVrnHV8QZLBMREkGRwTQZLB\nMREkmd6YVDV7Z298Z9atCeOSY1s8HdXN7SJSlDvUXGs4460R7PH3CAkhhESOQBYsyh2anRQnIpIk\nszISFle4Ay/qtos4TtwjJIQQEkqLpyM7Ke5/s+D/MTMjoarZq0vJSpgIRXivj4XdMSwKZRgWtW06\nOSw7/nJkXFJslxcT42NE5JnXatWaAMI9Qg3g7CgIkgyOiSDJ4JgIkgyOiSDJmDZZXOEWkYJJg7u8\nfsVPtrkXZAUyYo/AGW+NwBkhIYQ4nXHJsev3tHV5cX1926yMBBNZ0HYwERJCiNPJToqbdWvC4J/V\nBTYFWzwdiyvci7e4nfBLGWEiDGCXdXxubyiUYVgUmkSoO4ZFocxl2yyYNLjgtsGLK9zj1zaMf7ah\nqtnrXpDVG087oftGRusI3uAZehOolrLb7dbuECwH7sBF8CkrK9PuAHiNgrdII/jgXCOczy3UNVLy\nuXWf/bj3PryhHhSczVucrXVBksExESQZHBNBksExESQZHBOc8dYIXBolhBDiaJgIRWy1jq+2yrQM\nw6K2O4ZFoQzDorZNJ+wRcmlUAzjLF4Ikg2MiSDI4JoIkg2MiSDI4JjjjrRE4IySEEOJomAgJIYQ4\nGiZCEa7jW9gdw6JQhmFR2ybDorDKXnCPUAM46/iCJINjIkgyOCaCJINjIkgyOCY4460ROCMkhBDi\naJyYCEOn8yzjlBsbG7U7sBy+zGvEck/L9kDzk20sJMwjf0IfDqSkKnxt8IFMCts07WlOhmFR2x3D\n0tNahkWhiWmZMFV8xBooOGvWOOv4giSDYyJIMjgmgiSDYyJIMjgmOOOtEZy4NEoIIYQEYSIkhBDi\naJgIRXivj4XdMSwKZRgWtW0yLAqr7IVt9ghbW1sPHz48aNCg1NTUMKfV1NR87Wtfu2gVzpo1zjq+\nIMngmAiSDI6JIMngmAiSDI4JznhrBHvMCMvLy3NzcysqKvLz81evXn2p09auXTt//nwrxQghhNid\nKN0Cl8fn8xUUFLz88svJyckejycnJ2fKlCldvvW0t7evWLGioqLiqquu0qRJCCHElthgRrh9+/bY\n2Njk5GQRiY+PHzt27I4dO7qcU1hYGB8fv2zZMnNdcB3fsu4YFoUyDIvaNhkWhVX2wgZ7hJs3b37j\njTfWrl0bOJw/f35UVNSSJUtCz+ns7HS5XNXV1QsXLqypqbloO6Gbi3l5edOnT4+cc3hOnDhxww03\n6Oq9CzgyOCaCJINjIkgyOCaCJKPXpKSkpLS0NHhooz1CeyyNulyfzVxdLldnZ2eXc0JPCAPOhQHZ\n0A6AI4NjIkgyOCaCJINjIkgyGk0WLVq0aNGiQDn8rxrRsMHSaHR0tM/nCx52dnZGRdkgfxNCCLEF\nNkiEAwcOPHDgQPDQ6/Wmp6er7YLr+JZ1x7AolGFY1LbJsCisshman3VqAJ/PN2bMmKqqKr/f39TU\ndMstt7z//vt+v3/fvn0nT54MPbOqqmrMmDGXagfnIbBhHoxrPTgyOCZ+JBkcEz+SDI6JH0kGxwRn\nvDWCDdYYXS7XqlWr5s2bl5ycfPDgwRUrVgwYMEBECgsLJ0+ePHXqVN30hLuaAAAPv0lEQVSChBBC\nbIwNEqGIZGZm1tbWdnmxqKioyyvjxo271E9GCSGEkItigz1CC+A6vmXdMSwKZRgWtW0yLAqr7IUN\n7iNUBc6z73CeByhIMjgmgiSDYyJIMjgmgiSDY4Iz3hrBiTPC0G8xLOOUGxsbtTuwHL7Ma8RyT8u2\ngDNCDeB8axMkGRwTQZLBMREkGRwTQZLBMcEZb43gxBlhd7iOb1l3DItCGYZFbZsMi8Iqe8EZoQZw\nvrUJkgyOiSDJ4JgIkgyOiSDJ4JjgjLdG4IyQEEKIo2EiJIQQ4miYCEW4jm9hdwyLQhmGRW2bDIvC\nKnvBPUIN4KzjC5IMjokgyeCYCJIMjokgyeCY4Iy3RuCMkBBCiKNhIiSEEOJonJgIuz8BIfS/Xc7Z\nuXPnpZ6YsG7dOnNthimbbtO0Z5iyuTZD396jNsM8tcR0m6Y9w5TNtRn+82DuGplu07SnuWtk7nNr\n+hqZbtO0Z5hyJP7Nhr9Gyts07WkjuEeoAZx1fEGSwTERJBkcE0GSwTGRXsssrnBXNXtFJDH+ypkZ\n12UnxekyUQjOeGsEJ84ICSEEhPFrG0SkYNLgoty0cUmxiyvciyvcuqUchz3+HiEhhPQ9xq9tyE6K\nK5g0OHA4Kz4hOylu9sZDMz0JifExet0cBWeEIrzXx8LuGBaFMgyL2jatD0tVc/vMjITQFxPjY7KT\n4pZu3m2uTdPvsjgsaHCPUAM46/iCJINjIkgyOCaCJINjImZlWjwdszceqpwzssvr6+vbqpvbi3KH\nWmYSCXDGWyNwRkgIIXpo8XZ0f7G6ud16E4fDREgIIRoIrIJ2/2lMVbN3ZsZ1WpQcCxOhCLc3LOyO\nYVEow7CobdP6sBTcNriq2Ru4faLF01HV7B2/tqHgtsHRZ94116bpd3GPkHuEVoOzji9IMjgmgiSD\nYyJIMjgm0juZFk9HcX1bVbM3sExalDuU9xFajxNnhOaeEMFypMthnlrCMkiZ10h5OTE+pmDS4Mo5\nIzfkXOFekBXIgiBuSsq2gDNCDeB8axMkGRwTQZLBMREkGRwTQZLBMcEZb43gxBlhd7i9YVl3DItC\nGYZFbZsMi8Iqe8EZoQZwvrUJkgyOiSDJ4JgIkgyOiSDJ4JjgjLdG4IyQEEKIo2EiJIQQ4miYCEW4\njm9hdwyLQhmGRW2bDIvCKnvBPUIN4KzjC5IMjokgyeCYCJIMjokgyeCY4Iy3RuCMkBBCiKNhIiSE\nEOJonJgIuz8BIfS/Xc7ZuXPnpZ6YsG7dOnNthimbbtO0Z5iyuTZD396jNsM8tcR0m6Y9w5TNtRn+\n82DuGplu07SnuWtk7nNr+hqZbtO0Z5hyJP7Nhr9Gyts07WkjuEeoAZx1fEGSwTERJBkcE0GSwTER\nJBkcE5zx1ghOnBESQgghQZgICSGEOBomQhHe62NhdwyLQhmGRW2bDIvCKpvhdwwpKSm6Ff6XJUuW\n6Fb4DBwZHBM/kgyOiR9JBsfEjySDY4Iz3hqh78wIW1tbt27daovt2dLSUt0Kn4Ejg2MiSDI4JoIk\ng2MiSDI4JvaijyTC8vLy3NzcioqK/Pz81atX69YhhBBiG/pCIvT5fAUFBcXFxStXrty0aVNRUVFL\nS0uPWuA6vmXdMSwKZRgWtW0yLAqr7EWUbgEFbN++PTY2Njk5WUTi4+PHjh27Y8eO7jfTjBo1KjU1\nVYPfxcAxESQZHBNBksExESQZHBNBkgExGTVqlG6FHtAXEmF7e/uQIUOCh/37929qaup+WklJiYVS\nhBBC7EEfWRp1uT77H3G5XJ2dnRp9CCGE2Ii+kAijo6N9Pl/wsLOzMyqqL8x0CSGEWEBfSIQDBw48\ncOBA8NDr9aanp2v0IYQQYiP6QiLMyMgQkerqahE5cuRIXV3d6NGjdUsRQgixB33kr0+89dZb8+bN\nS05OPnjw4NKlS2+//XbdRoQQQuxBH0mEhBBCiDn6wtIoIYQQYhomQkIIIY6m3xNPPKHbIeK0trbW\n19dfuHBhwIABsL3X1NTceOONek2OHj3a0NDQ3t6ekJAQURMjMocPH963b5/L5YqNjdVrEmD//v39\n+vW76qqrNMp4PJ6DBw+e/D/69+8fHR2txSQgs3PnzjNnztxwww0RcrisSZeAnDx58vz58xH9wFw2\nLC0tLXv27Pnkk0+uueaayGkYMQn8c+7Xr1+k/wVdCgvGNFX0/URYXl7+4x//+Pz58y+88EJ7e/u/\n/du/Afa+du3a1atX33PPPRpNli5dumbNmnPnzpWVlZWXl3/zm9+M3O2Yl5X51a9+tWbNmo6Ojuee\ne+7jjz++9dZbdZkEOHr06LRp0/71X//1pptuipCJEZkNGzY88sgjr7/+enl5eXl5+ciRI7/85S9r\nMamurr733ns7Ojpef/3111577dvf/vYVV1xhvUlNTc3cuXPL/49XXnnlwoUL2dnZkTC5rIyIFBUV\nLVy48Pz58y+++OK7776bk5Ojy2TlypU///nPz58//5vf/Ka9vd36B55ZMKapRPffgYosn3766YgR\nI44cOeL3+8+ePTt8+HC32w3Vu9frffTRR0eMGDFmzBiNJocOHfrKV77i9XoDh9/85jdfeeUVXTJN\nTU1BmTNnzgwdOvTs2bNaTAKcP3/+jjvuyM7OfuONNyKhYVzmoYce+t3vfhc5B4Mmn3766ejRo996\n663A4eTJk19//XUtJqHU1NSMHTs2+Bm2Xsbn86WlpTU1Nfn9/g8++CAtLe3QoUNaTP7yl7985Stf\nOXnypN/v7+joGD9+/F/+8pdImFwUa8Y0tfTxPcKLPo8bqvfCwsL4+Phly5bpNYmNjX3++eeDSyiD\nBw8+efKkLpmkpKTNmzcHZD73uc/5fL4LFy5oMQnwy1/+8utf/3pKSkokHHokc+jQoaSkJI/HE6GA\nGDSprq7+0pe+FJxk/PGPf4zQDUvG//2eO3fuscceW7p0aeSWAY3I+P3+mJgYEbnyyitdLtf58+e1\nmBw9evRrX/taYIMjOjo6PT29oqIiEiYXxZoxTS19/FFkBp/HrbH3xx9/3OVyBZ4GoNEkISEhuC94\n/PjxysrK/Px8XTIulys5Odnn823atGnDhg0PPPDAtddeq8VERHbv3v3WW2+VlZXdf//9kXAwLuPz\n+f76178++eSTHo+nvb39O9/5ztKlS7WYeL3eQYMGPf7446+++mq/fv0eeOCBe++9V4tJkBdeeGHI\nkCFf+9rXIqFhUMblchUUFMyZM2fChAl1dXXTpk0bPny4FpPo6Oj33nsvePjhhx+GPo050lgzpqml\nj88I9T6P20jv1nxAjcfh9OnTs2bNmjNnztChQ/XKeDyeTz75ZODAgbW1te3t7VpMPvzww8cff/yX\nv/xlJHrvqczp06cnTJjw3//933V1dZWVlTU1NS+99JIWk6NHj1ZUVNx888379+9/6aWXnnvuuQgt\ntBj8qHzyySdFRUUPPvhgJBx6JLNnz54vfOEL11xzTWxsbHNz87lz57SYZGVlnT59euXKlbt37y4u\nLj5w4ICV456VSVcV9jPuEXqfx43zNHCDJm+//fadd945Y8aMyE0Hjctcc801M2bMeOGFF2JiYoqL\ni7WYPPXUU2lpacePH6+urg78QPHw4cORMDEic/31169Zs+b6668XkWuvvXbixIl79+7VYvLlL3/5\nxhtvnDZtmoikpqZOnDjxT3/6kxaTAH/+858HDRo0bNiwSDgYl9m2bVtjY+OGDRvuvvvu559/XkR+\n+9vfajGJjY0tLS09fvz4mjVrPvroozvuuCNyvy7uG/TxRKj3edw4TwM3YlJXV3fPPfc88cQTs2fP\n1itz7Nix0tLS4OF111136tQpLSbXXHPNP/7xjw0bNmzYsOG9996rrq6uq6uLhIkRmePHj2/atCl4\neP78+X79+mkx+eIXvxh66HK5IjQJMPgvqLq6euLEiZEQ6JGM1+tNSUkJXpQbb7yxtbVVi8nf//73\nf/zjH08//XRpaekPf/jDlpaWESNGRMKk76D71zqRxefzjRkzpqqqyu/3NzU13XLLLe+//7723vft\n2xf4QVeQqqqqiP7C6rImf/3rX0eMGLFt27bz/8enn36qS6apqSktLa25udnv97///vtZWVlvvvmm\nFpNQ/uu//iuivxq9rMy7776blpYW+K3gqVOnsrKyampqtJicP38+MzNz27Ztfr//7NmzY8eO3bVr\nlxaTAKNHjw6cE1EuK3Po0KFbbrkl8Ln94IMPJk+evGnTJi0mJ0+eTEtLO3XqlN/vb2houPXWWz/4\n4INImIQh0mOaWvp4IvT7/bt27crKypoxY0Z6enqEfuTd095nzZrV5eYECz404U2WL1+e8s8sXrxY\nl4zf79+wYcPw4cPvueee4cOHP/fccxpNgkQ6ERqR+d3vfjdixIgZM2aMGDHit7/9rUaT+vr67Ozs\nadOmpaenP/PMMxpNfD5fSkrKmTNnIudgXGbjxo3p6emBE5YtW6bRpLi4eMSIEXl5ednZ2RH6mhIe\neyVCpzx0+9y5czExMbp2cfX2jmkil5Pp7Oz0eDxxcXERWgA0bmIxlw1LR0eHNbaXDcvHH3/8+c9/\nnhcolMAFio6O1h4Wn8/3ySeffOELX4i0Rh/AKYmQEEIIuSgQ37AIIYQQXTAREkIIcTRMhIQQQhwN\nEyEhhBBHw0RICCHE0TAREkIIcTRMhIQQQhwNEyEhtqG8vPzFF1/UbUFIX4OJkBB7UFNT8+ijj1r5\nBzUJcQh9/A/zEtIH+Pvf//7MM8+8+OKLAwYM0O1CSB+EM0JCUNixY8f9999/7NixwOGzzz67cOFC\nEdm+fXtDQ0NZWVmk/+QeIc6EiZAQFMaMGXPu3LlHHnlERGpqagoLC7/97W+LyKRJk37/+9+npqbq\nFiSkb8JESAgQTz31VEtLy6pVqx555JEHHnjg1ltvFREL/o4BIU6GiZAQIBISEgoKCl544YVBgwY9\n+OCDunUIcQRMhIRg8dFHH4mI1+s9d+6cbhdCHAETISFAtLS0LF++/KmnnoqKilq2bJluHUIcAW+f\nIASFzs7Ohx566Ktf/eqUKVNuuummqVOn5uTk5OTk6PYipI/DGSEhKPz6179ua2tbsmSJiAwbNuz7\n3//+woUL//a3v+n2IqSPc4Xf79ftQAghhGiDM0JCCCGOhomQEEKIo2EiJIQQ4miYCAkhhDgaJkJC\nCCGOhomQEEKIo2EiJIQQ4miYCAkhhDgaJkJCCCGOhomQEEKIo2EiJIQQ4miYCAkhhDgaJkJCCCGO\nhomQEEKIo2EiJIQQ4miYCAkhhDgaJkJCCCGOhomQEEKIo2EiJIQQ4miYCAkhhDgaJkJCCCGOhomQ\nEEKIo2EiJIQQ4miYCAkhhDgaJkJCCCGOhomQEEKIo/n/mGaMGfOBajsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "LHSd=lhsdesign(10,2,'smooth','off','criterion','none','iterations',1)\n",
    "plot(LHSd(:,1),LHSd(:,2),'o'),xlabel('x1'),ylabel('x2'),grid on, grid minor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LHSd_1 =\n",
      "    0.4500    0.8500\n",
      "    0.8500    0.9500\n",
      "    0.6500    0.4500\n",
      "    0.5500    0.0500\n",
      "    0.0500    0.1500\n",
      "    0.1500    0.5500\n",
      "    0.2500    0.7500\n",
      "    0.7500    0.2500\n",
      "    0.3500    0.3500\n",
      "    0.9500    0.6500\n",
      "LHSd_2 =\n",
      "    0.0500    0.3500\n",
      "    0.7500    0.7500\n",
      "    0.6500    0.2500\n",
      "    0.1500    0.9500\n",
      "    0.5500    0.6500\n",
      "    0.3500    0.1500\n",
      "    0.8500    0.5500\n",
      "    0.4500    0.8500\n",
      "    0.9500    0.4500\n",
      "    0.2500    0.0500\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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fz8rKOn36dHR09IsvvuhycbJLCCHkytggEfp8vry8vJdffjklJcXj8YwfP37K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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "LHSd_1=lhsdesign(10,2,'smooth','off','criterion','maximin','iterations',100)\n",
    "LHSd_2=lhsdesign(10,2,'smooth','off','criterion','correlation','iterations',100)\n",
    "plot(LHSd_1(:,1),LHSd_1(:,2),'o',LHSd_2(:,1),LHSd_2(:,2),'+'),xlabel('x1'),ylabel('x2'),grid on, grid minor\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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PHvybv/mbyy67rKWlJZlM/vnPf867wNtt+18n9keTaTpLLdzXkTt9pqinm06x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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "LHSd=lhsdesign(100,2,'smooth','off','criterion','maximin','iterations',100);\n",
    "plot(LHSd(:,1),LHSd(:,2),'o'),xlabel('x1'),ylabel('x2'),grid on, grid minor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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5NAAZkYGXT2zevPmVV1754he/OPSZz33ucytXrly7du3VV1+9cOHCadOm1dXVLVq0aMaM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\nCE0IAQhNCAEI7f8BCUxgGc6ObRgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hist(LHSd(:,1),20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plan LHS o rozkładzie prawdopodobieństwa normalnym"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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codEdy0+U5DCgg0OU5ORoStRjoQjwEYYNRjwQCKE/+7cf/fjZS20LIUIoV1HC5CxkZ0AZ\n0ZQRNemab1ncEXb+roFreq/Xfqaq+lr3/Ycf/Z+BywbXcL3R9fLycuAyDPOaCmBHGDYY+b2JEHrw\nh6s3fOep6syYLU4xmW8WUvtCE7zIzoAyoikjatI137K4I+wFokzt4IFwZOf2S7OTUnKhaXkEcUbT\ndNwhoylRksOADg5RkpOjKVGPhSJgRxg2GPm9iV7RtCYbyfyyKHAiz6mGmZ2UQuMdxLA2oEFL4TuM\nqEnXfAvhEwDdJGL8+pFDw89oijOJD+3jAADwD1gIgTAwtIymuKRGsaHhjwvfBhQAGAR8hM4QZWoH\nD8TgeCK5qpuZ8orIc+tHDilz49WZsTO6masoMKCedO6fJG7bw4B60jlFgI8wbDDigUBBaJoptyZi\nkc4tIF4as1OSf1ZZGNCQwYiadM23sCMEgF4pNjTbgicKXDoezVWUoEQCAGBwYCEEgJ7Ap2McPZGi\nMDJ8eQAA8ApYCJ0hytQOHojBGVxyHKHRncV0SW4/9dRTvgrjX+csD2hQnbuFHMnBRxgG6LJZ9w0j\nHggUhKa5iqIaZmd2U1U3pfm6Mjfu35lVGNCQwYiadM23sCMMLapuBi1C2MhOSSLPJfPNYkOryUau\nokjz9ersfggoBACqgTjCEJIpt6xAN5HnwpR4M3CyU9KuBrckt3OLxvSBqK97QQAAhgPsCJ0hytTu\nqv1195xDCFmBbokYn1xobrI7JEdychwtm7efjkcLqVFlbjw7JeFVEFxKnnTunyRu28OAetI5RYCP\nMFTUZOOP/7l16sbxzpvFhlZqaOEr2s6Ir4URNREzmjKiJl3zLewIQ0Wuorx/9A22m4kYrxrgLwQA\nAHCGxYWQhGKVPl2LwsjO7Zfa7muPLqu6ia2jhMjpyTVrBU7hOhzXrL23dLDODHv27Om9cb1ed9W5\nq/b+dX74vsc/XW7abhYePjd9bMUTYYh6LIqi+Nc5OY/FlZpuOyfqscCADt45OY/F1XwbOOAjDBWq\nbv7aXz584lNXdR5lxLVqw1ckgRFfy+BqDr9GVX/AgIYJuuZbCJ8IFaLAHXvfm5MLzUSMn4hFzuhm\nTTZCuQoCvVCTjUy5hRASeS4pLx+elLJTUtBCAQBxwEIYNnZuv7Q6M1ZqaKWGlojxEETILHgVVOYu\nHiFWdbPU0DLlVmdmHAAAEJuHZXqBqHAct+1FgctOSdXZMSvQzavOiXos/knitr3fA9pf55lyqzrz\naswMfitUfa0zXSpRj8U/Sdy2J3NA/ZCEnAENFvARhg1GPBCIGU37U7PY0DLl1vqRQ7b7uGIUmQZS\nGNAwQdd8CztCAAghiRjvaAzYJXAQVAoANmAhBIBw4phXr9TQRB58xgDwGmAhdIYoUzt4IAaHKMmH\noKkocIcnJXxkFFOTDWm+rhomvsA2UqIei3+SuG1P4ID6JAk5Axos4CMMG4x4IBAzmg6iZq6iFE9r\niRgv8tzhRSURi+CUs/gEqa22YuDAgIYJuuZb2BECQGjJTknVmbGJWOTwolJIjVqJ1/EJUoRQ5wlS\nAGAWWAgBIMyIAofTKXQnVRB5rtQ4H4RQAEAWsBA6Q5SpHTwQg0OU5EPWVNXNjU6Qvu4/nh6wc68a\nu4XlAfVQEnIGNFjARxg2GPFAoAE0xR6ymmyIwkg6voPwJJyeDOi2m45XZ/fbNM2UWxOxCDnp9xh5\ndRlRk675FnaEAFsUG1pyoYkQyk5JE7FIptzC5yfDTSE1arOC1mSjJhvkrIIAECAsLoQk1OiC68Gv\n+6jrhveCytz45PbziRg/HY9WZ8b+eflMsaGRo5cf13tfVEWeS+abmXLrI9/4Hr4opEZJkI21a6hH\nSCLBVoEaJizUI1xnptrZel/l66aPrRQePmf7T9VVPXH0kUGEoWVAq6v64fsex//rQxK37aEeoSOM\nfEOhHiGh0GWz7htGPBCoL0233XRcmRu3nRxRdTO50LSqNJAGDGjIYERNuuZbKMMEMEQiFlGNNdtC\nWJMNyDoG9E2uouCDV0SdPAJcwaKPEGCWdDzaHTm3JLcJPzgKkImqm8l8EyGE62AvyW1pvh60UEA/\nwELoDFHhOBClNDi4c5xsDP+ERwipupmrKKq+1l2WiJzH4hZyJCdHTbfte2ycKa9kp6TslDS5/fx0\nPFpIjU4fiOKl0UMYGdBgAR9h2GDEA4H61RQfHD28qCCcaWxSItycBQNKJsWGtiS3u5O1OoZsdkKX\nmn1D13wLPkKALXCazeyUtFG+FcKhVOzwcUY3HV3LiVhE1U0UG75EQP+AaRRgFLqWE1U3M+XWtpuO\nS/N1ab5uBT4CQbFL4BxTlqsG/FKhD1gInSHK1E6Or4Wox+KfJG7b+z2gqm5myisiz60fObR+5FB1\nZuyMbm6UEIccycM9oNj4iasfW+3xn96evWJkQIMFfIRhgxEPBGJGU1VVcw+t2Y7m46UxHY8S7uB0\nBXUDWmxouUWlkBq1FkVpvr65gxBRqGZ/0DXfgo8QAEinJhvZydecaxUFLh2PlhpamBZC6sAPP1dR\nMkYL+2670zUAVAALIQCQglU4HiFkbQHPXngRDsgQy3S4NuXMAj5CZ4gytZPjayHqsfgnidv2nnRe\nkw1cFiMd34Gjs7EXcOf2SxOxiOO5DFEYGVAYoh6Lf5K4bQ/fUE86pwjwEYYNRjwQKFyaduc7VXUz\nt6iIPJfeu6329GW2kDXsIyyk9oVppximAd0ERtSka74F0ygABE9uUXHyAu7IlFvpvW+ejkfP6GYy\n30zHo6LALa22i6e1Qmo0TKsgAAQIi6ZREmp0wfXg12Gq6/YD9WdLchuXCbz52IP4ZiLGq7p59sKL\nCKHslPQu/n9Z9tIjV796Rp8E+eG69+swvbe9XNNBsFWghgnUIxy8c6IeS2jK11VXdXTjA4mjj+BK\ngfgC/yd04wMwoJ50Ts5jYWRAoR4hodBls+4bRjwQKCya4uCz6XhU1deqs2Oowzu4S+CW5Hb2nSMh\nULMXwjGgW8KImnTNtyyaRgGAHHAsIA7KzpRbNdnA3sHi6YvB2kELCADhBw7LAKGlJhv4XAkuF0dm\nvJdqmBOxCEIoOyUVG1oyv4yPwKi62XmIFAAA/4AdoTNEheNAlFIf1GQjU24hhAqp0YlY5NunHsN/\n+iHMII9F1dfO6Ca+no5HcSpRvAT2dyg0rAM6YOfkPBa3kCM5fUdgegZ8hGGDEQ8E2lRTvAradlTW\nujgE2XqnJhu5ioK9gxadte5gQEMGI2rSNd/CjhAIIaXGeVtYHkIoOyk55mcJFpEfScT4XEVRX9kX\n1mQjt6ik4zuGJoP10QDAJuAjBEJITTa6FxJR4ESeIy1vp5U+W5qvJ2KRmtxOxCJWQQO/yVWUw4sK\nfiAiz9k2pgDACLAjdIYoUzt4INwi8tzSaru785rc7nEVHOZjEQUuOyUpc+OF1L71I4eqs2ODrIK9\nC5PMN584+8T6kUPK3Hh1ZiwR46X5uledu23sFqJeRXI0JeqxUAT4CMMGIx4ItJWPsNvxlqsoqmGS\n5iPcEp8G1NFjGqwblZFXlxE16ZpvYUcIhJBEjLfC8hAOUa8oNdnwcIrHfWbKrU73HkU4Wo/T8R0E\nulEBwG9gIQTCSXZKmohFchVFmq/j8kYeOsCskkkTsYhqmJnyCk4BShGOizfObjp8YQAgWMK2EJ44\nccKTfogytYMHoj+m49Hq7JgyN67MjU9uP+/q324ijKqbODYjOyXhpDCf2mPWZKPY0AbvfHB67DwR\ni6i6aWtc3KrkPTkuJaJeRXI0JeqxUESofIT5fP7YsWMbrYV02az7JvQeCFU3cR4y8XXPBqJpptzq\nzlNTbGilhubHqUufBrTY0HKLSnVmrPP0UDLfzE5Jwzmw2k3oX10MI2rSNd+GJHyi3W7fdtttlUrl\n8ssvD1oWwEfwcf9ELIIQWn365x9553p2yh4v6Dc12egOUkzE+NwiTdZRvJAnF5qJGJ+O71habddk\nIx2PBrUKAkCAhMQ0+pWvfEUQhFtvvTVoQQAfSeabqmHiAIPq7Nix973ZlUHSK0SeU401282abIg8\nQeGJvTAdj1ZnxkSeKzXOI4QKqX1kpmMFAL8JyY7wi1/84iWXXLK0tLR5s7179+KL66+//oYbbtik\n5fLy8v79+3sXwFV7Xzs/e/Zs7z277TzAx3J36znTNLPvFFRVvXjrwvkvvWvHdf/008SbnvdWks3b\nv1t6/dHqqvi6N3U2/u4zO9/4n9CrsnknzNmzZ89eeHHn9l6/qm6feXr/foRGEELownn1gsedu3rm\nrl5d+IYO3tjzzu+888677rqr908nh1D5CJeWlr7whS+AjzCUHojuEDes6fDdWla9QGyVVXWz1NBq\nsuGHgzBTbhUbGnbjTR+IDt8OPEzC+uraYERNuubbkOwIgdCzkeFRNUyRHxmqJAKXnZRyiwrOw6Lq\nZiIW8WMVTOabiRivfOpKURTxcpspt6hLCAAA5BMSHyEQeiZ2RxxjvQPJHSoKXCE1Wp0ZK6RGsc/S\n84/IlFuiMGJtAXEaNoTQ8H2iABB6YCF0hqhwHIhSQgjhbZ8tbj2Zb/a4Q/JDclHgsEnWj84dz6am\n4ztKWy2EtAzogAwueU02kvmmNF+X5uuZcqszkwB8Qz3pnCLARxg2QuyBwM65mmxMH4gihA4vKjie\nPWi5fEGar+N6ip0DqupmprwS1hoRw3x1ccVK7HbFZufiac0WVekTIf6GdkLXfBsqH+HExIRXmWUA\nAsHOubSxA1eWOHZNNPV/hHMVRAiJPFeTDdshoJpsiMJQHaKhRNXNZH55/cgh/Cc2O+8SuBD/yAA2\nB0yjQDAUG9q2m45j21Tvfi9sjcxOSdkp6Z1vCfOSkI5H8UHZTkoNrdteCrilJhvdEZPT8WhNbkPO\ncTaBhdAZokzt4fNAJPPNM7pZnd1fSO0rpEZLDS1XUchR0217PzqfjkenD0Sl+fpXvm/gqlLSfD0d\nj25puwtc8r47908SW/slue14CDkRi2BXNHxDPemcIkLlI9wcumzWfUO+BwIfeOkMicOuL7fhgORr\nOjg12ThaXb3iiitEnpvYHQksC+hQjuYObUA3Sgy77abjyty435qy8N4i2ubbUPkIASrApxI672CD\nZ66iJGYh0eVrSMR48XVvCnDeLDa0TLkVsoh+nBjWtrrnKkoiFhl+KA5AArAQAkMFH1Lvnm52CRyS\ngxAI2JhkvikKI3iThI9WWmdZqUYUuOrMWHKhOX0gOrE7ghDCOcfhpAyzgI/QGaJM7WHyQOAl0PFI\nwi+8+JyrzgeUxMP2p06dUnUT14fyQxhXeDWgVk47PGT4aOW+N7xAV9nFjdrjtVA1zFLjfKbc2iVw\nnasgy99QDzunCPARhg3yPRC5iqIapi3+r4+UoeRoiotD4W1TIhYppPZ5aGELSk1pvp6dlGynK3H4\nnU+bQnIG1FcYUZOu+RZMo8CwScejOG3mRCySiPE4YzW9lfCw/dAKSlN1M7nQHE5ott90j4jIj3Rm\nYAGAcACmUWDYiAKXjkdFnis1tORCUzXM7JR950EL2BbaubvFaUgz5ZXghPKGjcouUjpSA6LqZrGh\nFRsaBBqGEhYXwk5L90bXX//61/1rf+rUqV767Lu9q+vO/9+yfadIg7THDqfq7Ng3D20rpEbxzsPt\nM19eXu69vU/P/I7v/jAdj9qeociPPKo9u8m/dfXM3V67GqNNnnl2SsJuws77X763mY7v6LF/ct5b\nt+1tzzCZbyYXmg/+8KdLcjuZX7bFvLp95q7eW0TS3NLfe0sF4CMMG4x4IBAZmmbKrXR8R7cJUZqv\ne2UdDVDNXEUpntbw0cql1XbxtNbtNfQQEga0G2zDt7TGp2fRawNhXUGmmp5D13zL4o4QALxC5Dmc\n+LSTYkMLpDiU52SnpEJqFB+tRAi5XQWLDS2ZbybzTVxe2DcxfaTY0FR9rVNrbNgvnqZSHWAj4LAM\nAPRPOh7NlFcm5NfkfCk1tOrs/gCl8pBEjO/vEFOm3FL1tUSMT8ejNdkoNbQzukldPP4Z3ezOci4K\nnGNKdIBeYEfojFsbt6v2vnbuFnIkJ0fN3tuLAldI7bvx2z/Amx4rI+jmUyQ5mvr0WPBG6tb9z2en\nJFHgpuPRQmpfTTY8PHEa7KuoGuYg9QtdQcKA9tc5RYCPMGww4oFAQ9G0xwBBHEqPUzn3khfbFTQO\nqKOL1DF+tBMCNd0obnLbTcetgBm3EKimH9A134JpFACcwcY9PN+puqkaaxsFp4LKWQAAIABJREFU\nCIoCNy1E2YwrcMTRRTqxO1KrKIHI0zciPzJ9IJqrKJZRFyeID2s5aGaBhRAAHKjJhqqvWWm3RIGz\nAgQhI2UvdLvQVCd/2zCpyQY+2bRL4Hr81YKPxtRkQ5qv48pNNbldSI3Cj56QAT5CZ4gytYMHYnDc\ndo4DBG03RX6kJtvPiPbROTma+iR5IhZZWm3bGpcamhWDODhuJX/3XyzhsMhdAoezh/fYOfZxVmfG\n0vFodkpaP3KoexUM/YD21zlFgI8wbDDigUB+aqrqZm5R8TtAsFdhKBxQbD9MxHhcQxH/KQojm1sU\n/dPUSiBu3clVlKDKTdA4oH1A13wLplEAeBU8ZeNtX002uiPnwhEg6Df4MG1NNpL5Zfynr5H4W1Js\naLazLdkpqZY3IAQCwMBCCAAXUXVTmq8XUqPV2TG8ImbKrc7ot2S+eXiSski4oCDnAFGxoTmKgbeq\nKDZ8iQDiAB+hM0SZ2sEDMTi9dJ4pr1Rn9+NJU3t0GQdLFE9ruYqCAwRFYcQxJBwGtO/GOPgyV1Hc\npp7pXRJR4FR9rbu9amwY1AgD6knnFAE+wrDBiAcC+aBpd3AYdhZaGVICMYqGeECT+SZCKBHj8QGW\n1ad//kT2//T8UzYqjJXMN72tHNmrPOEd0E7omm9hRwgACF087h+x3RQFDhdNxBlSAhGMLnBugV5a\nJvPNdDxanR3DRbiqs2Pvf9sb8NLoLdhDmVxoWoKpuok/HcYUwICPEAAQwiVnnWxlS3J7omuBBLrB\nR2NwHs6M0Zo+EN0ks2ixodXktu3Q5h9ezWf+VffjAMt0PCoKHBYP3wn28A5AGizuCD2vAea2va81\nw9xeu6ox1imS5+2DrUcoCtz0gehHvvG9zvY12cClaD18hn20d3Xt6zPfqP3Re0/iVGTK3Pit+5+v\nzozVZOMj3/jeRv3Iq7K1DnXef/bChR7lcfsML3vqJ+tHDh25GhVSo8rc+OZj6ut7DvUICQR8hGHD\nJw8EzspRPK2JPIdNhZ5/hFs81xSXmlMNcyIWEQVuabVdk43slBTsCXsqXEqO7tXkQtOqumyjJhu5\nimLbEaqqmvlXPR0n4qypf1AxoIND13zL4o4QcAtOPYwQKqRG0/Goapj4z5AhClx2SpqIRZbkdq6i\nIISqs2MQZ7YljvEJ2Ea6UbkJR0P02QsvqoYJDxwYPuAjBLbAnoA/hqbj0Uy5lSm3uhOF4E3VLoET\nBY7SGW067DsSzxEFrtRYc7q/YWZRbIjGUZv4PVF187P3P1VIjcIBFmD4wI7QGbc2blftfe3cLVt2\nXmqcz74SRW41zk5K3YcDk/lmcqGJEMI7qlxF8fWxuAIG1BNJHNtvdM6o8uPzm6xq2SkpOykl88vS\nfH3bTceTC807fv0Xe//xBAPqiSTkfEODBXyEYcNzD0Tnz/ZObGFYtnSOeGuIEPLPm0iXrwUXcupj\nl0yFmtiS3DnWxYZWamg9JvPEieuo0HRwGFGTrvkWTKPAFog8t7Ta7p7Ba3LbWgWLDc2WzhHXr8Hl\n2hk3dhUbWqbcwtV9RYEbcs7u4ZCOR0sNLZlv4vcEWwt6T2kdvgcC0AUshMAWZKekXEXJotds7HIV\npTPrpuhU4E0UuEQsohprLE9zeGNk/UTAKUwDP4nqOfh3zy6Bw2GXCUTEuWIA6BHwETpDlKk9WA9E\nIsYnYnym3KrJxqlTp1TdxCVsOme6pdW2qjscl3j2woWNzg32IckgBDKgNdnILb4mSACXZfhg8X+4\nEsYVQb2K+McQLlqL343eO8cv1a+V/qc0X8+UW728M/AN9UQS8BFiwEcYNnzyQOCdDT4T0Z00BAeN\nvXqy9BW23XRcmRv3aUdIvq+l2NCW5Hb32dpkvtn7ppB8NQfEKl649wrznaNSTTZKDS18m2aL0A8o\nhq75FkyjQE9sHlSAT8N3BlTg2Q1Ow4u8s/qlxvml1TYO3mc8WsOyFauqios3JWJ8pryCplBY10KA\nNMA0CngDDkWX5uvJfDOZb+JjMoxP8aLAdQeZqLqJC/8ifBBJbocyO0Hv1GT7USz842lptR2QRABz\nwELoDFGmdlo8ENPxaHVmLDslZaek9SOHbOkcvZXELYEMqMiPiMIIDi2wkObrv7fv0kJqFD+oQmpU\n5Dlbm0EYXHLssSs2tO5V3PMBVXWzu+gHQggnMBqw877bh/UbOuTOKQJ8hGGDEQ8EokRTXNEQITQR\ni5zRTZys1Z5jcwMP68X/Olw18akovEUrNjR8+MW/j+vUvVPTTLkVVqMxFe/t4NA138KOEAB8BBfD\nw6sgQkjkubTLtJzDJFdRVH1NmRsvpEYLqdH1I4fO6KaHu1XUVbAQp+KzfQRuAw5CYGjAYRkA8Bd8\nAOTiHxV0xmnB29wMODQOLyq2IhLZKUmar0/sjgy+LNkKFloVAbOTUqa8gipo7xUm2m6WGlpNNuCY\nFTBMWNwRDrNO2/Brhrm9dlVjrFMkz9sHW48Qc8/9dVft3T7DNz5/rnhas7UvNrTnzeeteX/AMe37\nmR+996RjjUD+df/bOrfS93tebGg3fvsH60cOKXPj1dmxI1ejUkPDG0Ht0eVCap9qmF/9vnHNXz9U\nk41Cal8ixnv43rpt7+t7DvUICQR8hGGDEQ8E8lpTHCiJ88aJPNeZRtVbchVFNcx0fIdVdUGar1dn\n92+05RragDrWCEQeues2KljY6Rll5NVlRE265lswjQLAxVUwOyVVYzx2UCUXmj4lBcUp67CR8GL2\n0Y1XwWGyURGJmmxkJwfKl7ZJwULwBQIkAAshwDq44KK1X8EuPVHgNjnJOSDZKQkfmSHKDYbP9djK\nTOI82gPK6egWRZsWLAwT+GcWvk7Ho4k3BSsO4ACLPsJecGvjdtXe187dQo7kQamp6mb3fuWyp35i\nO9/YX+cbtRcFzqdVcJBnPh2PijyHE37mKsq2m44nYnznuthf5xO7I45PsiYbIt/nWkjUq7hJ+2S+\nuSS3s1NSIbUvHY/mFpWvfL+nl6o/YYh6LBQBPsKwwYgHAnmnaXctPcxGhRiHAy7oqBrmz3/+899P\n7h6mGNYvAA/D+PDO0law0JaINXyvLvYHv0ZH3byu2Dw2HcJSXDbomm9hRwiwzi6nRGgIV4vtd78y\nIMWGllxoIoTS8R1Xv4XD+7OhfTquI+FtMHshta8mG8l8M1dRchUlmW+WGlp3OvKQUTyt2dyrosC9\nf/QNmfJKUCIBjoCPELBTkw18XH6XU5XB8JGI8blFBZ9bsW7mKsp0QCWF8V7Qck+Kr3v22qt/OVNe\n2dWgeDhw/amabCzJbZHnQlxcohPbS4V551tGvqu8EIg8wEbAjtAZokztw3SeZcotnAMaF1mV5uud\nGU+IeixeSYKrxicXmrjOYrGh5SrKPy+f6X2/4u1jyS0qtuwzosBlpyTrwIWHwgxzQK2ChZ6sgkS9\nihu1T8QcnKMPPbnm6pQQsQM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yzqIwAv54FoCF0BmiwnEgSmlwiJLcao9XlGJDG3D9wLs6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\nIQQAiEYhBACIRiEEAIj2X50e3DCvylKfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mu=[0 0];       %wartość średnia\n",
    "sigma=[1  0\n",
    "       0  1];   %macierz kowariancji\n",
    "n=100;           %liczba punktów\n",
    "flag='off';      %wygładzanie\n",
    "LHSNd = lhsnorm(mu,sigma,n,flag);\n",
    "plot(LHSNd(:,1),LHSNd(:,2),'o'),xlabel('x1'),ylabel('x2'),grid on, grid minor\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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QmhACEJoQAhCaEAIQmhACEJoQAhCaEAIQ2v8Dvx88fQyGwSoAAAAASUVORK5C\nYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hist(LHSNd(:,1),20)"
   ]
  }
 ],
 "metadata": {
  "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-octave",
   "name": "matlab",
   "version": "0.15.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}