BlockSVD.ipynb

{
 "metadata": {
  "language": "Julia",
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This notebook contains an implementation of the block SVD algorithm described in [LAWN 283](http://www.netlib.org/lapack/lawnspdf/lawn283.pdf)"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Block and Unblock Arrays"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "function block(A,s1=5,s2=5)  \n",
      "    m, n=size(A)\n",
      "    mi=[i:min(i+s1-1,m) for i=1:s1:m]\n",
      "    ni=[j:min(j+s2-1,n) for j=1:s2:n]\n",
      "    [A[i,j] for i in mi, j in ni]\n",
      "end\n",
      "\n",
      "unblock(A)=hvcat(tuple([size(A,2) for i=1:size(A,1)]...), A'...) \n",
      "\n",
      "# Key BLAS3 block operator\n",
      "# A few block apply Q's\n",
      "import Base.LinAlg: QRPackedQ, Ac_mul_B\n",
      "import Base.*\n",
      "Ac_mul_B(Q::QRPackedQ,B)=hcat([block(Q'*unblock(B[:,j])) for j in 1:size(B,2)]...)        \n",
      "*{T<:Matrix}(A::Array{T},Q::QRPackedQ)=vcat([block(unblock(A[i,:])*Q) for i in 1:size(A,1)]...)   \n",
      "                                        \n",
      "# A few block qrQ's\n",
      "qrQ{T<:Number}(A::Array{T})=qrfact(A)[:Q]\n",
      "qrQ{T<:Matrix}(A::Array{T})=qrQ(unblock(A))  \n",
      "qrQc{T<:Matrix}(A::Array{T})=qrQ(unblock(A)')\n",
      "                                 \n",
      "spyt{T<:Number}(A::Array{T})=spy(A, precision=sqrt(eps(T)), alpha=0.8)                                    \n",
      "spy{T<:Matrix}(A::Array{T})=spy(unblock(A), precision=sqrt(eps()), alpha=0.7)  # Threshold for convenience\n",
      "\n",
      "#Convenience drawing functions\n",
      "using PyPlot\n",
      "using PyCall\n",
      "@pyimport matplotlib.patches as patches\n",
      "\n",
      "rect_red(x0, y0, dx, dy)=gca()[:add_patch](patches.Rectangle((x0-1.5,y0-1.5),dx,dy,linewidth=5,facecolor=\"none\",edgecolor=\"red\"))\n",
      "rect_blue(x0, y0, dx, dy)=gca()[:add_patch](patches.Rectangle((x0-1.5,y0-1.5),dx,dy,linewidth=3,facecolor=\"none\",edgecolor=\"blue\"))\n",
      "rect_gray(x0, y0, dx, dy)=gca()[:add_patch](patches.Rectangle((x0-1.5,y0-1.5),dx,dy,linewidth=1,facecolor=\"none\",edgecolor=\"#aaaaaa\"))\n",
      "rect_red(yr, xr)=rect_red(xr.start,yr.start,xr.len,yr.len)\n",
      "rect_blue(yr, xr)=rect_blue(xr.start,yr.start,xr.len,yr.len)\n",
      "rect_gray(yr, xr)=rect_gray(xr.start,yr.start,xr.len,yr.len)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "LoadError",
       "evalue": "PyPlot not found\nwhile loading In[1], in expression starting on line 26",
       "output_type": "pyerr",
       "traceback": [
        "PyPlot not found\nwhile loading In[1], in expression starting on line 26",
        " in require at loading.jl:39"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "N=15\n",
      "s=5; #block size\n",
      "A=block(randn(N,N));\n",
      "Q=qrQ(A[1,1])\n",
      "A[1,:]=Q'*A[1,:]\n",
      "\n",
      "spy(A)\n",
      "rect_red(1:s,1:s)  #QR from this block\n",
      "rect_blue(1:s,1:N) #QR applied to this block"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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        "     </g>\n",
        "    </g>\n",
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_31\">\n",
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        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
        "      <!-- 14 -->\n",
        "      <g transform=\"translate(7.2 360.205)scale(0.12 -0.12)\">\n",
        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-34\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "   </g>\n",
        "   <g id=\"patch_5\">\n",
        "    <path d=\"\n",
        "M24.4788 22.8137\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_6\">\n",
        "    <path d=\"\n",
        "M370.079 368.414\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_7\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L370.079 368.414\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_8\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L24.4788 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
        "  <clipPath id=\"p7679732b36\">\n",
        "   <rect height=\"345.6\" width=\"345.6\" x=\"24.47875\" y=\"22.81375\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x57676510>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 265,
       "text": [
        "PyObject <matplotlib.patches.Rectangle object at 0x4959a210>"
       ]
      }
     ],
     "prompt_number": 265
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for j=2:3\n",
      "    Q=qrQ(A[[1,j],1])        # There is a special QR for a \"domino\"=[\u25e5;\u25fc]\n",
      "    A[[1,j],:]=Q'*A[[1,j],:] # Q' acts like a square matrix even though Q was \"thin\" \n",
      "    rect_red(1,(j-1)*s+1,s,s)#QR from this block\n",
      "end \n",
      "spy(A)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_31\">\n",
        "      <g>\n",
        "       <use style=\"stroke:#000000;stroke-width:0.5;\" x=\"24.47875\" xlink:href=\"#m728421d6d4\" y=\"356.89375\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"line2d_32\">\n",
        "      <g>\n",
        "       <use style=\"stroke:#000000;stroke-width:0.5;\" x=\"370.07875\" xlink:href=\"#mcb0005524f\" y=\"356.89375\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
        "      <!-- 14 -->\n",
        "      <g transform=\"translate(7.2 360.205)scale(0.12 -0.12)\">\n",
        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-34\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "   </g>\n",
        "   <g id=\"patch_5\">\n",
        "    <path d=\"\n",
        "M24.4788 22.8137\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_6\">\n",
        "    <path d=\"\n",
        "M370.079 368.414\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_7\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L370.079 368.414\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_8\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L24.4788 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
        "  <clipPath id=\"p7679732b36\">\n",
        "   <rect height=\"345.6\" width=\"345.6\" x=\"24.47875\" y=\"22.81375\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x5110cb90>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 266,
       "text": [
        "PyObject <matplotlib.image.AxesImage object at 0x5988ebd0>"
       ]
      }
     ],
     "prompt_number": 266
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Now do this from the right\n",
      "Q=qrfact(A[1,2]')[:Q]  # We really need an LQ\n",
      "A[:,2]*=Q\n",
      "spy(A)\n",
      "rect_red(s+1,1,s,s)  #QR from this block\n",
      "rect_blue(1:s,s+1:N) #QR applied to this block"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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        "     </g>\n",
        "     <g id=\"text_15\">\n",
        "      <!-- 12 -->\n",
        "      <g transform=\"translate(7.72875 314.125)scale(0.12 -0.12)\">\n",
        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-32\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_31\">\n",
        "      <g>\n",
        "       <use style=\"stroke:#000000;stroke-width:0.5;\" x=\"24.47875\" xlink:href=\"#m728421d6d4\" y=\"356.89375\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"line2d_32\">\n",
        "      <g>\n",
        "       <use style=\"stroke:#000000;stroke-width:0.5;\" x=\"370.07875\" xlink:href=\"#mcb0005524f\" y=\"356.89375\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
        "      <!-- 14 -->\n",
        "      <g transform=\"translate(7.2 360.205)scale(0.12 -0.12)\">\n",
        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-34\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "   </g>\n",
        "   <g id=\"patch_5\">\n",
        "    <path d=\"\n",
        "M24.4788 22.8137\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_6\">\n",
        "    <path d=\"\n",
        "M370.079 368.414\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_7\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L370.079 368.414\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_8\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L24.4788 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
        "  <clipPath id=\"p7679732b36\">\n",
        "   <rect height=\"345.6\" width=\"345.6\" x=\"24.47875\" y=\"22.81375\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x4f6880d0>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 267,
       "text": [
        "PyObject <matplotlib.patches.Rectangle object at 0x541aecd0>"
       ]
      }
     ],
     "prompt_number": 267
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for j=3:3\n",
      "    Q=qrQ(unblock(A[1,[2,j]])') # This is a special LQ for a \"domino\"=[\u25e5;\u25fc]'                       \n",
      "    A[:,[2,j]]*=Q\n",
      "    rect_red((j-1)*s+1,1,s,s)#QR from this block\n",
      "end\n",
      "spy(A)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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        "     </g>\n",
        "     <g id=\"text_16\">\n",
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        "   </g>\n",
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        "    <path d=\"\n",
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        "   </g>\n",
        "   <g id=\"patch_5\">\n",
        "    <path d=\"\n",
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        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
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        "    <path d=\"\n",
        "M24.4788 368.414\n",
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        "   <g id=\"patch_7\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L24.4788 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
        "  <clipPath id=\"p7679732b36\">\n",
        "   <rect height=\"345.6\" width=\"345.6\" x=\"24.47875\" y=\"22.81375\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x4b1e3710>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 268,
       "text": [
        "PyObject <matplotlib.image.AxesImage object at 0x4d1ea150>"
       ]
      }
     ],
     "prompt_number": 268
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "function BandBidiagonal(A::Array{Array{Float64,2},2}) \n",
      "    (m,n)=size(A)\n",
      "    for i=1:n\n",
      "        Q=qrQ(A[i,i])\n",
      "        A[i,:]=Q'*A[i,:]\n",
      "        for j=(i+1):n\n",
      "          Q=qrQ(A[[i,j],i])         # QR for a \"domino\"=[\u25e5;\u25fc]\n",
      "          A[[i,j],:]=Q'*A[[i,j],:]  # Q' acts like a square matrix even though Q was \"thin\" \n",
      "        end\n",
      "        i==n && return A\n",
      "        Q=qrQ(A[i,i+1]')            # We really need an LQ\n",
      "        A[:,i+1]*=Q\n",
      "        for j=(i+2):n\n",
      "          Q=qrQc(A[i,[i+1,j]])      # LQ for a \"domino\"=[\u25e5;\u25fc]'                       \n",
      "          A[:,[i+1,j]]*=Q                       \n",
      "        end\n",
      "    end\n",
      "end\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 269,
       "text": [
        "BandBidiagonal (generic function with 1 method)"
       ]
      }
     ],
     "prompt_number": 269
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "A=block(randn(15,15))\n",
      "A_after=BandBidiagonal(A)\n",
      "spy(A_after)\n",
      "[svdvals(unblock(A))[1:5] svdvals(unblock(A_after))[1:5]]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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        "     </g>\n",
        "     <g id=\"text_16\">\n",
        "      <!-- 14 -->\n",
        "      <g transform=\"translate(7.2 360.205)scale(0.12 -0.12)\">\n",
        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-34\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "   </g>\n",
        "   <g id=\"patch_3\">\n",
        "    <path d=\"\n",
        "M24.4788 22.8137\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_4\">\n",
        "    <path d=\"\n",
        "M370.079 368.414\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_5\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L370.079 368.414\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_6\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L24.4788 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
        "  <clipPath id=\"p7679732b36\">\n",
        "   <rect height=\"345.6\" width=\"345.6\" x=\"24.47875\" y=\"22.81375\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x4b1e3490>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 270,
       "text": [
        "5x2 Array{Float64,2}:\n",
        " 6.94917  6.94917\n",
        " 6.10788  6.10788\n",
        " 5.63312  5.63312\n",
        " 5.15745  5.15745\n",
        " 4.64259  4.64259"
       ]
      }
     ],
     "prompt_number": 270
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "A=unblock(A_after)\n",
      "Q1=qrQ(A[1,2:6]')\n",
      "A[1:6,2:6]*=Q1\n",
      "spyt(A)\n",
      "rect_red(1:1,2:6)  #QR from this block\n",
      "rect_blue(1:6,2:6) #QR applied to this block"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-30\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_29\">\n",
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        "     <g id=\"text_15\">\n",
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        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
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        "     <g id=\"line2d_31\">\n",
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        "     </g>\n",
        "     <g id=\"text_16\">\n",
        "      <!-- 14 -->\n",
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        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-34\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "   </g>\n",
        "   <g id=\"patch_5\">\n",
        "    <path d=\"\n",
        "M24.4788 22.8137\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_6\">\n",
        "    <path d=\"\n",
        "M370.079 368.414\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_7\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L370.079 368.414\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_8\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L24.4788 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
        "  <clipPath id=\"p7679732b36\">\n",
        "   <rect height=\"345.6\" width=\"345.6\" x=\"24.47875\" y=\"22.81375\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x4fdec150>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 271,
       "text": [
        "PyObject <matplotlib.patches.Rectangle object at 0x4c572c50>"
       ]
      }
     ],
     "prompt_number": 271
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Q2=qrQ(A[2:6,2:2])\n",
      "A[2:6,2:11]=Q2'*A[2:6,2:11]\n",
      "spyt(A)\n",
      "rect_red(2:6,2:2)  #QR from this block\n",
      "rect_blue(2:6,2:11) #QR applied to this block"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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        "      </g>\n",
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        "     <g id=\"line2d_30\">\n",
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        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
        "      <!-- 12 -->\n",
        "      <g transform=\"translate(7.72875 314.125)scale(0.12 -0.12)\">\n",
        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-32\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_31\">\n",
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        "       <use style=\"stroke:#000000;stroke-width:0.5;\" x=\"24.47875\" xlink:href=\"#m728421d6d4\" y=\"356.89375\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"line2d_32\">\n",
        "      <g>\n",
        "       <use style=\"stroke:#000000;stroke-width:0.5;\" x=\"370.07875\" xlink:href=\"#mcb0005524f\" y=\"356.89375\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
        "      <!-- 14 -->\n",
        "      <g transform=\"translate(7.2 360.205)scale(0.12 -0.12)\">\n",
        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-34\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "   </g>\n",
        "   <g id=\"patch_5\">\n",
        "    <path d=\"\n",
        "M24.4788 22.8137\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_6\">\n",
        "    <path d=\"\n",
        "M370.079 368.414\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_7\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L370.079 368.414\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_8\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L24.4788 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
        "  <clipPath id=\"p7679732b36\">\n",
        "   <rect height=\"345.6\" width=\"345.6\" x=\"24.47875\" y=\"22.81375\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x58bea310>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 272,
       "text": [
        "PyObject <matplotlib.patches.Rectangle object at 0x47fa3e90>"
       ]
      }
     ],
     "prompt_number": 272
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Q3=qrQ(A[2,7:11]')#Clear the fill-in from the previous block\n",
      "A[2:11,7:11]*=Q3\n",
      "spyt(A)\n",
      "rect_red(2:2,7:11)  #QR from this block\n",
      "rect_blue(2:11,7:11) #QR applied to this block"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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        "       <use style=\"stroke:#000000;stroke-width:0.5;\" x=\"24.47875\" xlink:href=\"#m728421d6d4\" y=\"310.81375\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"line2d_30\">\n",
        "      <g>\n",
        "       <use style=\"stroke:#000000;stroke-width:0.5;\" x=\"370.07875\" xlink:href=\"#mcb0005524f\" y=\"310.81375\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
        "      <!-- 12 -->\n",
        "      <g transform=\"translate(7.72875 314.125)scale(0.12 -0.12)\">\n",
        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-32\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_31\">\n",
        "      <g>\n",
        "       <use style=\"stroke:#000000;stroke-width:0.5;\" x=\"24.47875\" xlink:href=\"#m728421d6d4\" y=\"356.89375\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"line2d_32\">\n",
        "      <g>\n",
        "       <use style=\"stroke:#000000;stroke-width:0.5;\" x=\"370.07875\" xlink:href=\"#mcb0005524f\" y=\"356.89375\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
        "      <!-- 14 -->\n",
        "      <g transform=\"translate(7.2 360.205)scale(0.12 -0.12)\">\n",
        "       <use xlink:href=\"#BitstreamVeraSans-Roman-31\"/>\n",
        "       <use x=\"63.623046875\" xlink:href=\"#BitstreamVeraSans-Roman-34\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "    </g>\n",
        "   </g>\n",
        "   <g id=\"patch_5\">\n",
        "    <path d=\"\n",
        "M24.4788 22.8137\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_6\">\n",
        "    <path d=\"\n",
        "M370.079 368.414\n",
        "L370.079 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_7\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L370.079 368.414\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "   <g id=\"patch_8\">\n",
        "    <path d=\"\n",
        "M24.4788 368.414\n",
        "L24.4788 22.8137\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
        "  <clipPath id=\"p7679732b36\">\n",
        "   <rect height=\"345.6\" width=\"345.6\" x=\"24.47875\" y=\"22.81375\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x5a1a3dd0>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 273,
       "text": [
        "PyObject <matplotlib.patches.Rectangle object at 0x47fbad50>"
       ]
      }
     ],
     "prompt_number": 273
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "A=block(randn(25,25),5,5);\n",
      "A=BandBidiagonal(A);\n",
      "s=size(A[1,1],1) #Square block size\n",
      "n=size(A,1)      #Number of blocks\n",
      "A=unblock(A)\n",
      "i=1\n",
      "Q=qrQ(A[i,i+(1:s)]') #odd\n",
      "A[i+(0:s),i+(1:s)]*=Q\n",
      "rect_red(i:i,i+(1:s))  #QR from this block\n",
      "rect_blue(i+(0:s),i+(1:s)) #QR applied to this block\n",
      "for i=1:s:((n-2)*s)\n",
      "    Q=qrQ(A[i+(1:s),i+1:i+1]) #even\n",
      "    A[i+(1:s),i+(1:2s)]=Q*A[i+(1:s),i+(1:2s)]\n",
      "    rect_red(i+(1:s),i+1:i+1)  #QR from this block\n",
      "    rect_blue(i+(1:s),i+(1:2s)) #QR applied to this block\n",
      "    Q=qrQ(A[i+1,i+s+(1:s)]')  #odd\n",
      "    A[i+(1:2s),i+s+(1:s)]*=Q\n",
      "    rect_red(i+1:i+1,i+s+(1:s))  #QR from this block\n",
      "    rect_blue(i+(1:2s),i+s+(1:s)) #QR applied to this block\n",
      "end\n",
      "i=(n-2)*s+1\n",
      "Q=qrQ(A[i+(1:s),i+1:i+1]) #even\n",
      "A[i+(1:s),i+1:end]=Q*A[i+(1:s),i+1:end]\n",
      "rect_red(i+(1:s),i+1:i+1)  #QR from this block\n",
      "rect_blue(i+(1:s),i+1:(n*s)) #QR applied to this block\n",
      "Q=qrQ(A[i+1,i+s+1:end]')  #odd\n",
      "A[i+1:end,i+s+1:end]*=Q\n",
      "rect_red(i+1:i+1,i+s+1:(n*s))  #QR from this block\n",
      "rect_blue(i+1:(n*s),i+s+1:(n*s)) #QR applied to this block\n",
      "i=(n-1)*s+1\n",
      "Q=qrQ(A[i+1:end,i+1:i+1]) #even\n",
      "A[i+1:end,i+1:end]=Q*A[i+1:end,i+1:end]\n",
      "rect_red(i+1:(n*s),i+1:i+1)  #QR from this block\n",
      "rect_blue(i+1:(n*s),i+1:(n*s)) #QR applied to this block\n",
      "spyt(A)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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        "    <path d=\"\n",
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        " </defs>\n",
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       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x52cf3c50>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 274,
       "text": [
        "PyObject <matplotlib.image.AxesImage object at 0x52162790>"
       ]
      }
     ],
     "prompt_number": 274
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "@pyimport matplotlib.animation as anim\n",
      "\n",
      "function block_bidiagonalize(M,s1=5,s2=5; record_video=false, video_file=\"blocksvd.mp4\")\n",
      "    if record_video\n",
      "        video = anim.FFMpegWriter(fps=6, extra_args=[\"-vcodec\", \"libx264\", \"-pix_fmt\", \"yuv420p\"])\n",
      "        video[:setup](gcf(), video_file)\n",
      "    end\n",
      "    A=BandBidiagonal(block(M,s1,s2))\n",
      "    s=size(A[1,1],1) #Square block size\n",
      "    n=size(A,1)      #Number of blocks\n",
      "    A=unblock(A)\n",
      "    for j=1:n*s-2    #bulge chasing: elimination on row j+1\n",
      "        endb=min(j+s,n*s)\n",
      "        Q=qrQ(A[j,j+1:endb]')           #xGBCW1\n",
      "        A[j:endb,j+1:endb]*=Q\n",
      "        spyt(A)\n",
      "        rect_red(j:j,j+1:endb)  #QR from this block\n",
      "        rect_blue(j:endb,j+1:endb) #QR applied to this block\n",
      "        record_video && video[:grab_frame]()\n",
      "\n",
      "        lastb=((n-floor(j/s)-1)*s)+j                 #index of last block\n",
      "        for i=j:s:lastb\n",
      "            endb, endbp1=min(i+s,n*s), min(i+2s,n*s) #index of end of block and its neighbor\n",
      "            Q=qrQ(A[i+1:endb,i+1:i+1])  #xGBCW2\n",
      "            A[i+1:endb,i+1:endbp1]=Q*A[i+1:endb,i+1:endbp1]\n",
      "            spyt(A)\n",
      "            rect_red(i+1:endb,i+1:i+1)  #QR from this block\n",
      "            rect_blue(i+1:endb,i+1:endbp1) #QR applied to this block\n",
      "            record_video && video[:grab_frame]()\n",
      "            i==lastb && break\n",
      "            Q=qrQ(A[i+1,i+s+1:endbp1]') #xGBCW3\n",
      "            A[i+1:endbp1,i+s+1:endbp1]*=Q\n",
      "            spyt(A)\n",
      "            rect_red(i+1:i+1,i+s+1:endbp1)  #QR from this block\n",
      "            rect_blue(i+1:endbp1,i+s+1:endbp1) #QR applied to this block\n",
      "            record_video && video[:grab_frame]()\n",
      "        end\n",
      "    \n",
      "        #Gray out stuff\n",
      "        clf()\n",
      "        endb=min(j+s,n*s)\n",
      "        rect_gray(j:j,j+1:endb)\n",
      "        rect_gray(j:endb,j+1:endb)\n",
      "        for i=j:s:lastb\n",
      "            endb, endbp1=min(i+s,n*s), min(i+2s,n*s)\n",
      "            rect_gray(i+1:endb,i+1:i+1)\n",
      "            rect_gray(i+1:endb,i+1:endbp1)\n",
      "            rect_gray(i+1:i+1,i+s+1:endbp1)\n",
      "            rect_gray(i+1:endbp1,i+s+1:endbp1)\n",
      "        end\n",
      "    end\n",
      "    clf()\n",
      "    spyt(A)\n",
      "    if record_video\n",
      "        video[:grab_frame]()\n",
      "        video[:finish]()\n",
      "    end\n",
      "    A\n",
      "end"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 275,
       "text": [
        "block_bidiagonalize (generic function with 3 methods)"
       ]
      }
     ],
     "prompt_number": 275
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "function block_svdvals(M,s1=5,s2=5)\n",
      "    A=block_bidiagonalize(M,s1,s2)\n",
      "    B=Bidiagonal(diag(A), diag(A,1), true)\n",
      "    svdvals(B)\n",
      "end\n",
      "\n",
      "[block_svdvals(M) svdvals(M)]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
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        "   <rect height=\"345.6\" width=\"345.6\" x=\"24.79375\" y=\"22.81375\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x4f664190>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 276,
       "text": [
        "25x2 Array{Float64,2}:\n",
        " 9.47961   9.47961 \n",
        " 9.06957   9.06957 \n",
        " 8.10747   8.10747 \n",
        " 7.56554   7.56554 \n",
        " 6.84574   6.84574 \n",
        " 6.6843    6.6843  \n",
        " 6.49103   6.49103 \n",
        " 6.27427   6.27427 \n",
        " 5.59487   5.59487 \n",
        " 5.28317   5.28317 \n",
        " 5.1632    5.1632  \n",
        " 4.4533    4.4533  \n",
        " 4.06357   4.06357 \n",
        " 3.80315   3.80315 \n",
        " 3.3645    3.3645  \n",
        " 2.98093   2.98093 \n",
        " 2.82718   2.82718 \n",
        " 2.59303   2.59303 \n",
        " 2.41564   2.41564 \n",
        " 1.69782   1.69782 \n",
        " 1.43786   1.43786 \n",
        " 1.10352   1.10352 \n",
        " 0.537197  0.537197\n",
        " 0.470536  0.470536\n",
        " 0.133043  0.133043"
       ]
      }
     ],
     "prompt_number": 276
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "M=randn(25,25)\n",
      "A=block_bidiagonalize(M,5,5)\n",
      "spyt(A) #imshow(A, cmap=\"bwr\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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        "L24.7938 22.8138\" style=\"fill:none;stroke:#000000;\"/>\n",
        "   </g>\n",
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
        "  <clipPath id=\"pe3d5e96ce9\">\n",
        "   <path d=\"\n",
        "M24.7938 368.414\n",
        "L370.394 368.414\n",
        "L370.394 22.8137\n",
        "L24.7938 22.8137\n",
        "z\n",
        "\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text": [
        "Figure(PyObject <matplotlib.figure.Figure object at 0x555cec10>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 277,
       "text": [
        "PyObject <matplotlib.image.AxesImage object at 0x4cb1c250>"
       ]
      }
     ],
     "prompt_number": 277
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      ";ls -l *.mp4\n",
      "embed_video(filename)=display(\"text/html\", string(\"\"\"<video autoplay controls><source src=\"data:video/x-m4v;base64,\"\"\",\n",
      "                            base64(open(readbytes,filename)),\"\"\"\" type=\"video/mp4\"></video>\"\"\"))\n",
      "embed_video(\"blocksvd.mp4\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "bash: no job control in this shell\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "-rw-rw-r-- 1 ec2-user ec2-user   172226 Nov  8 23:27 blocksvd.mp4\n",
        "-rw-rw-r-- 1 ec2-user ec2-user 17802402 Nov  9 00:37 turkey_svd.mp4\n",
        "-rw-rw-r-- 1 ec2-user ec2-user    52700 Nov  8 21:47 writer_test.mp4\n"
       ]
      },
      {
       "html": [
        "<video autoplay controls><source 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       ],
       "metadata": {},
       "output_type": "display_data"
      }
     ],
     "prompt_number": 285
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}