Animation of precision_vs_zoom

author Sam Moore <[email protected]>

Wed, 17 Sep 2014 16:09:00 +0000 (00:09 +0800)

committer Sam Moore <[email protected]>

Wed, 17 Sep 2014 16:09:00 +0000 (00:09 +0800)
author Sam Moore <[email protected]>
Wed, 17 Sep 2014 16:09:00 +0000 (00:09 +0800)
committer Sam Moore <[email protected]>
Wed, 17 Sep 2014 16:09:00 +0000 (00:09 +0800)
diff --git a/src/bezier.h b/src/bezier.h

index 206cbc8..0d3be54 100644 (file)
--- a/src/bezier.h
+++ b/src/bezier.h
@@ -293,7 +293,7 @@ namespace IPDF
                         {
                                 Real t1 = *it;
                                 if (t1 == t0) continue;
                         {
                                 Real t1 = *it;
                                 if (t1 == t0) continue;
-                               Debug(" -- t0: %f to t1: %f: %f", Double(t0), Double(t1), (t1 + t0)/Real(2));
+                               Debug(" -- t0: %f to t1: %f: %f", Double(t0), Double(t1), Double((t1 + t0)/Real(2)));
                                 Real ptx, pty;
                                 Evaluate(ptx, pty, ((t1 + t0) / Real(2)));
                                 if (r.PointIn(ptx, pty))
                                 Real ptx, pty;
                                 Evaluate(ptx, pty, ((t1 + t0) / Real(2)));
                                 if (r.PointIn(ptx, pty))
diff --git a/src/main.h b/src/main.h

index 43b8c51..b4b789c 100644 (file)
--- a/src/main.h
+++ b/src/main.h
@@ -129,9 +129,9 @@ inline void MainLoop(Document & doc, Screen & scr, View & view, int max_frames =
                 scr.DebugFontPrintF("[REALTIME] Render+Present+Cruft took %lf ms (%lf FPS) (total %lf s, avg FPS %lf)\n", real_frame*1e3, 1.0/real_frame, total_real_time,frames/total_real_time);
                 scr.DebugFontPrintF("View bounds: %s\n", view.GetBounds().Str().c_str());
                 scr.DebugFontPrintF("type of Real == %s\n", g_real_name[REALTYPE]);
                 scr.DebugFontPrintF("[REALTIME] Render+Present+Cruft took %lf ms (%lf FPS) (total %lf s, avg FPS %lf)\n", real_frame*1e3, 1.0/real_frame, total_real_time,frames/total_real_time);
                 scr.DebugFontPrintF("View bounds: %s\n", view.GetBounds().Str().c_str());
                 scr.DebugFontPrintF("type of Real == %s\n", g_real_name[REALTYPE]);
-               #if REALTYPE == REAL_MPFRCPP
-                       scr.DebugFontPrintf("Precision: %s\nRounding: %s\n");
-               #endif 
+               //#if REALTYPE == REAL_MPFRCPP
+               //      scr.DebugFontPrintf("Precision: %s\nRounding: %s\n");
+               //#endif 
  
                 if (view.UsingGPUTransform())
                 {
  
                 if (view.UsingGPUTransform())
                 {
diff --git a/tools/analysis.ipynb b/tools/analysis.ipynb

index dd7c259..e9edb9f 100644 (file)
--- a/tools/analysis.ipynb
+++ b/tools/analysis.ipynb
@@ -7,6 +7,25 @@
   "worksheets": [
    {
     "cells": [
   "worksheets": [
    {
     "cells": [
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "%pylab inline"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "Populating the interactive namespace from numpy and matplotlib\n"
+       ]
+      }
+     ],
+     "prompt_number": 283
+    },
      {
       "cell_type": "code",
       "collapsed": false,
      {
       "cell_type": "code",
       "collapsed": false,
@@ -22,7 +41,7 @@
       "language": "python",
       "metadata": {},
       "outputs": [],
       "language": "python",
       "metadata": {},
       "outputs": [],
-     "prompt_number": 106
+     "prompt_number": 284
      },
      {
       "cell_type": "code",
      },
      {
       "cell_type": "code",
@@ -33,20 +52,23 @@
        "    \"ipdf_src\" : \"../src/\",\n",
        "    \"ipdf_bin\" : \"../bin/ipdf\",\n",
        "    \"local_bin\" : \"./\",\n",
        "    \"ipdf_src\" : \"../src/\",\n",
        "    \"ipdf_bin\" : \"../bin/ipdf\",\n",
        "    \"local_bin\" : \"./\",\n",
-      "    \"ignore\" : [\"virtual\", \"Rational_Arbint\", \"mpfrc++\", \"iRRAM\", \"ParanoidNumber\"],\n",
-      "    \"test\" : [\"single\", \"single-qtree\"]\n",
+      "    \"ignore\" : [\"virtual\", \"Rational_Arbint\", \"iRRAM\", \"ParanoidNumber\"],\n",
+      "    \"test\" : [\"single\", \"double\", \"mpfrc++\"],\n",
+      "    \"built\" : []\n",
        "}"
       ],
       "language": "python",
       "metadata": {},
       "outputs": [],
        "}"
       ],
       "language": "python",
       "metadata": {},
       "outputs": [],
-     "prompt_number": 56
+     "prompt_number": 414
      },
      {
       "cell_type": "markdown",
       "metadata": {},
       "source": [
      },
      {
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-      "# Compile programs"
+      "# Compile programs\n",
+      "\n",
+      "Build for each type of real, then save a local copy of the executable."
       ]
      },
      {
       ]
      },
      {
@@ -77,7 +99,7 @@
       "language": "python",
       "metadata": {},
       "outputs": [],
       "language": "python",
       "metadata": {},
       "outputs": [],
-     "prompt_number": 57
+     "prompt_number": 407
      },
      {
       "cell_type": "code",
      },
      {
       "cell_type": "code",
@@ -90,6 +112,7 @@
        "        continue\n",
        "    try:\n",
        "        build(b, False, False)\n",
        "        continue\n",
        "    try:\n",
        "        build(b, False, False)\n",
+      "        options[\"built\"] += [b]\n",
        "        #display(\"Built %s\" % b)\n",
        "    except:\n",
        "        display(\"Failed to build %s\" % b)\n",
        "        #display(\"Built %s\" % b)\n",
        "    except:\n",
        "        display(\"Failed to build %s\" % b)\n",
@@ -102,7 +125,7 @@
         "output_type": "stream",
         "stream": "stdout",
         "text": [
         "output_type": "stream",
         "stream": "stdout",
         "text": [
-        "\r",
+        " \r",
          "[                  0%                  ]"
         ]
        },
          "[                  0%                  ]"
         ]
        },
@@ -111,7 +134,15 @@
         "stream": "stdout",
         "text": [
          " \r",
         "stream": "stdout",
         "text": [
          " \r",
-        "[*****************50%                  ]  1 of 2 complete"
+        "[*************    33%                  ]  1 of 3 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*****************67%*****             ]  2 of 3 complete"
         ]
        },
        {
         ]
        },
        {
@@ -119,7 +150,7 @@
         "stream": "stdout",
         "text": [
          " \r",
         "stream": "stdout",
         "text": [
          " \r",
-        "[****************100%******************]  2 of 2 complete"
+        "[****************100%******************]  3 of 3 complete"
         ]
        },
        {
         ]
        },
        {
@@ -130,7 +161,27 @@
         ]
        }
       ],
         ]
        }
       ],
-     "prompt_number": 74
+     "prompt_number": 418
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "options[\"built\"]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 419,
+       "text": [
+        "['single', 'double', 'mpfrc++']"
+       ]
+      }
+     ],
+     "prompt_number": 419
      },
      {
       "cell_type": "markdown",
      },
      {
       "cell_type": "markdown",
@@ -150,6 +201,7 @@
        "    binname = options[\"local_bin\"]+exec_name\n",
        "    data = []\n",
        "    p = ProgressBar(sum(xrange(min_frames, max_frames, step)))\n",
        "    binname = options[\"local_bin\"]+exec_name\n",
        "    data = []\n",
        "    p = ProgressBar(sum(xrange(min_frames, max_frames, step)))\n",
+      "    display(\"Time VS Frames for %s\" % exec_name)\n",
        "    p.animate(0)\n",
        "    i = 0\n",
        "    for frames in xrange(min_frames, max_frames+step, step):\n",
        "    p.animate(0)\n",
        "    i = 0\n",
        "    for frames in xrange(min_frames, max_frames+step, step):\n",
@@ -179,17 +231,48 @@
       "language": "python",
       "metadata": {},
       "outputs": [],
       "language": "python",
       "metadata": {},
       "outputs": [],
-     "prompt_number": 69
+     "prompt_number": 420
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "def plot_time_vs_frames(tf, new_figure=True):\n",
+      "    if new_figure:\n",
+      "        figure(figsize=(9,7))\n",
+      "        yscale('linear')\n",
+      "        xscale('linear')\n",
+      "        legend([\"GPU\", \"CPU\"])\n",
+      "        xlabel(\"Frames\")\n",
+      "        ylabel(\"Time To Render\")\n",
+      "        title(\"Quick, to the TARDIS of Infinite Precision!\")    \n",
+      "        \n",
+      "    plot(tf[:,0], tf[:,1], 'o-')\n",
+      "    plot(tf[:,0], tf[:,2], 'x-')\n",
+      "    "
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 421
      },
      {
       "cell_type": "code",
       "collapsed": false,
       "input": [
      },
      {
       "cell_type": "code",
       "collapsed": false,
       "input": [
-      "tf = time_vs_frames(\"single\")"
+      "for p in options[\"built\"]:\n",
+      "    plot_time_vs_frames(time_vs_frames(p, bounds=[0.5,0.5,1e-14,1e-14]), False)"
       ],
       "language": "python",
       "metadata": {},
       "outputs": [
       ],
       "language": "python",
       "metadata": {},
       "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "text": [
+        "'Time VS Frames for single'"
+       ]
+      },
        {
         "output_type": "stream",
         "stream": "stdout",
        {
         "output_type": "stream",
         "stream": "stdout",
@@ -286,55 +369,229 @@
          "[****************100%******************]  451 of 450 complete"
         ]
        },
          "[****************100%******************]  451 of 450 complete"
         ]
        },
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "text": [
+        "'Time VS Frames for double'"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[                  0%                  ]"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[                  0%                  ]  1 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[                  0%                  ]  1 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*                 2%                  ]  11 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[***               7%                  ]  31 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*****            14%                  ]  61 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[********         22%                  ]  101 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*************    34%                  ]  151 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*****************47%                  ]  211 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*****************62%****              ]  281 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*****************80%**********        ]  361 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[****************100%******************]  451 of 450 complete"
+       ]
+      },
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "text": [
+        "'Time VS Frames for mpfrc++'"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[                  0%                  ]"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[                  0%                  ]  1 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[                  0%                  ]  1 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*                 2%                  ]  11 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[***               7%                  ]  31 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*****            14%                  ]  61 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[********         22%                  ]  101 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*************    34%                  ]  151 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*****************47%                  ]  211 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*****************62%****              ]  281 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[*****************80%**********        ]  361 of 450 complete"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[****************100%******************]  451 of 450 complete"
+       ]
+      },
        {
         "output_type": "stream",
         "stream": "stdout",
         "text": [
          "\n"
         ]
        {
         "output_type": "stream",
         "stream": "stdout",
         "text": [
          "\n"
         ]
-      }
-     ],
-     "prompt_number": 79
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "def plot_time_vs_frames(tf):\n",
-      "    figure(figsize=(9,7))\n",
-      "    plot(tf[:,0], tf[:,1], 'o-')\n",
-      "    yscale('linear')\n",
-      "    xscale('linear')\n",
-      "    plot(tf[:,0], tf[:,2], 'o-')\n",
-      "    legend([\"GPU\", \"CPU\"])\n",
-      "    xlabel(\"Frames\")\n",
-      "    ylabel(\"Time To Render\")\n",
-      "    title(\"Quick, to the TARDIS of Infinite Precision!\")"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [],
-     "prompt_number": 91
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "plot_time_vs_frames(tf)"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
+      },
        {
         "metadata": {},
         "output_type": "display_data",
        {
         "metadata": {},
         "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAi4AAAHBCAYAAABOsDAVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nmjRpkiQzLZ88eVKSdOLECd16661WNtFr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21rp+5qauEina22lBwQQq9W6+tcQ54gEvOjVFMVBWdmb5Oc/SlDQDPT6p/D07B3LYXxmNFJZuonH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\nRU5ErkJggg==\n",
         "text": [
         "text": [
-        "<matplotlib.figure.Figure at 0x7f94c1219290>"
+        "<matplotlib.figure.Figure at 0x7f94bad311d0>"
         ]
        }
       ],
         ]
        }
       ],
-     "prompt_number": 90
+     "prompt_number": 422
      },
      {
       "cell_type": "markdown",
      },
      {
       "cell_type": "markdown",
@@ -354,8 +611,16 @@
       ],
       "language": "python",
       "metadata": {},
       ],
       "language": "python",
       "metadata": {},
-     "outputs": [],
-     "prompt_number": 190
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "\n"
+       ]
+      }
+     ],
+     "prompt_number": 424
      },
      {
       "cell_type": "code",
      },
      {
       "cell_type": "code",
@@ -367,26 +632,42 @@
        "    out = p.stdout.readlines()\n",
        "    if len(out) != 1:\n",
        "        raise Exception(\"bmpdiff %s %s failed: %s \" % (img1, img2, str(map(lambda e : e.strip(\"\\n\"),p.stderr.readlines()))))\n",
        "    out = p.stdout.readlines()\n",
        "    if len(out) != 1:\n",
        "        raise Exception(\"bmpdiff %s %s failed: %s \" % (img1, img2, str(map(lambda e : e.strip(\"\\n\"),p.stderr.readlines()))))\n",
-      "    return map(float, out[0].strip(\" \\r\\n\").split(\"\\t\"))"
+      "    result = map(float, out[0].strip(\" \\r\\n\").split(\"\\t\"))\n",
+      "    for i in xrange(len(result)):\n",
+      "        if isnan(result[i]):\n",
+      "            result[i] = 0\n",
+      "    return result"
       ],
       "language": "python",
       "metadata": {},
       ],
       "language": "python",
       "metadata": {},
-     "outputs": [],
-     "prompt_number": 191
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "\n"
+       ]
+      }
+     ],
+     "prompt_number": 428
      },
      {
       "cell_type": "code",
       "collapsed": false,
       "input": [
      },
      {
       "cell_type": "code",
       "collapsed": false,
       "input": [
-      "def precision_vs_zoom(exec_name, xy, start_dims, end_dims, steps, test_image=\"svg-tests/rabbit_simple.svg\"):\n",
+      "def precision_vs_zoom(exec_name, xy, start_dims, end_dims, steps, test_image=\"svg-tests/rabbit_simple.svg\", show_outputs=False):\n",
        "    binname = options[\"local_bin\"]+exec_name\n",
        "    data = []\n",
        "    bounds = [xy[0], xy[1], start_dims[0], start_dims[1]]\n",
        "    dw = float(end_dims[0] - start_dims[0])/float(steps)\n",
        "    dh = float(end_dims[1] - start_dims[1])/float(steps)\n",
        "    p = ProgressBar(steps)\n",
        "    binname = options[\"local_bin\"]+exec_name\n",
        "    data = []\n",
        "    bounds = [xy[0], xy[1], start_dims[0], start_dims[1]]\n",
        "    dw = float(end_dims[0] - start_dims[0])/float(steps)\n",
        "    dh = float(end_dims[1] - start_dims[1])/float(steps)\n",
        "    p = ProgressBar(steps)\n",
+      "    display(\"Precision vs Zoom of \\\"%s\\\" using %s\" % (test_image, exec_name))\n",
        "    p.animate(0)\n",
        "    p.animate(0)\n",
+      "    im = None\n",
+      "    figure(figsize=(10,10))\n",
        "    for i in xrange(steps+1):\n",
        "    for i in xrange(steps+1):\n",
+      "       \n",
        "        cmd = binname + \" -l -b %s %s %s %s %s\" % tuple(map(str, bounds) + [test_image])\n",
        "        \n",
        "        # Don't show the windows\n",
        "        cmd = binname + \" -l -b %s %s %s %s %s\" % tuple(map(str, bounds) + [test_image])\n",
        "        \n",
        "        # Don't show the windows\n",
@@ -400,21 +681,69 @@
        "        pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"cpu\"+str(max(i-1,0))+\".bmp\")[3]]\n",
        "        pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"cpu0.bmp\")[3]]\n",
        "        pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"gpu\"+str(i)+\".bmp\")[3]]\n",
        "        pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"cpu\"+str(max(i-1,0))+\".bmp\")[3]]\n",
        "        pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"cpu0.bmp\")[3]]\n",
        "        pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"gpu\"+str(i)+\".bmp\")[3]]\n",
+      "\n",
+      "        if show_outputs != False:\n",
+      "            clear_output()\n",
+      "            if i == 0:\n",
+      "                im = imshow(imread(\"cpu0.bmp\"), cmap=get_cmap(\"gray\"))\n",
+      "            else:\n",
+      "                im.set_data(imread(\"cpu\"+str(i)+\".bmp\"))\n",
+      "                draw()\n",
+      "            title(\"Bounds: %s\" % str(bounds))\n",
+      "            \n",
+      "        display(\"Precision vs Zoom of \\\"%s\\\" using %s\" % (test_image, exec_name))\n",
+      "        p.animate(i)\n",
+      "        \n",
+      "        if show_outputs != False:\n",
+      "            display(gcf())        \n",
+      "            \n",
+      "        \n",
        "        # [step, x, y, w, h, gpu_delta, gpu_total_delta, cpu_delta, cpu_total_delta, gpu_vs_cpu\n",
        "        data += [pt]\n",
        "        bounds[2] += dw\n",
        "        bounds[3] += dh\n",
        "\n",
        "        # [step, x, y, w, h, gpu_delta, gpu_total_delta, cpu_delta, cpu_total_delta, gpu_vs_cpu\n",
        "        data += [pt]\n",
        "        bounds[2] += dw\n",
        "        bounds[3] += dh\n",
        "\n",
-      "        p.animate(i)\n",
        "        \n",
        "        \n",
-      "    start = rgb2gray(imread(\"cpu0.bmp\"))\n",
-      "    end = rgb2gray(imread(\"cpu\"+str(steps)+\".bmp\"))\n",
-      "    imsave(\"compare.png\",asarray(list(start.T)+list(end.T)).T)\n",
+      "    close(gcf())\n",
        "    return asarray(data)"
       ],
       "language": "python",
       "metadata": {},
        "    return asarray(data)"
       ],
       "language": "python",
       "metadata": {},
+     "outputs": [],
+     "prompt_number": 429
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "pz = precision_vs_zoom(\"single\", [0.5,0.5],[1e-5,1e-5],[1e-6,1e-6], 100, \"svg-tests/fox-vector.svg\", show_outputs=True)"
+     ],
+     "language": "python",
+     "metadata": {},
       "outputs": [
       "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "text": [
+        "'Precision vs Zoom of \"svg-tests/fox-vector.svg\" using single'"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        " \r",
+        "[****************100%******************]  100 of 100 complete"
+       ]
+      },
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAlsAAAHNCAYAAAApEr6yAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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REQoLi5OERER8vX11fz586s8xQgAAFCfVRu2BgwYUOmtG9auXVvh8oceekgPPfTQ+VUGAABQD3AH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\nxGGLiIiIyEVfAQcK06wQj5M7AAAAAElFTkSuQmCC\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x7f94bab242d0>"
+       ]
+      },
        {
         "output_type": "stream",
         "stream": "stdout",
        {
         "output_type": "stream",
         "stream": "stdout",
@@ -423,23 +752,22 @@
         ]
        }
       ],
         ]
        }
       ],
-     "prompt_number": 227
+     "prompt_number": 430
      },
      {
       "cell_type": "code",
       "collapsed": false,
       "input": [
      },
      {
       "cell_type": "code",
       "collapsed": false,
       "input": [
-      "pz = precision_vs_zoom(\"single\", [0.5,0.5],[1e-5,1e-5],[1e-6,1e-6], 2)"
+      "pzd = precision_vs_zoom(\"double\", [0.5,0.5],[1e-13,1e-13],[1e-15,1e-15], 100, \"svg-tests/fox-vector.svg\", show_outputs=True)"
       ],
       "language": "python",
       "metadata": {},
       "outputs": [
        {
       ],
       "language": "python",
       "metadata": {},
       "outputs": [
        {
-       "output_type": "stream",
-       "stream": "stdout",
+       "metadata": {},
+       "output_type": "display_data",
         "text": [
         "text": [
-        "\r",
-        "[                  0%                  ]"
+        "'Precision vs Zoom of \"svg-tests/fox-vector.svg\" using double'"
         ]
        },
        {
         ]
        },
        {
@@ -447,15 +775,42 @@
         "stream": "stdout",
         "text": [
          " \r",
         "stream": "stdout",
         "text": [
          " \r",
-        "[*****************50%                  ]  1 of 2 complete"
+        "[****************100%******************]  100 of 100 complete"
+       ]
+      },
+      {
+       "metadata": {},
+       "output_type": "display_data",
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AmtaICIiQhEREZKk4OBgdezYUfn5+VqwYIHee+89SVJaWpoSEhKUkZGh+fPnKzU1VY0aNVJ0dLTa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\nYII=\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x7f94bacc6310>"
         ]
        },
        {
         "output_type": "stream",
         "stream": "stdout",
         "text": [
         ]
        },
        {
         "output_type": "stream",
         "stream": "stdout",
         "text": [
-        " \r",
-        "[*****************50%                  ]  1 of 2 complete"
+        "\n"
+       ]
+      }
+     ],
+     "prompt_number": 437
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "pzmp = precision_vs_zoom(\"mpfrc++\", [0.5,0.5],[1e-13,1e-13],[1e-15,1e-15], 1, \"svg-tests/fox-vector.svg\", show_outputs=True)\n",
+      "# Need to adapt mpfrc++ for required precision. Probably not worth it, just go back to mpfr?"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "text": [
+        "'Precision vs Zoom of \"svg-tests/fox-vector.svg\" using mpfrc++'"
         ]
        },
        {
         ]
        },
        {
@@ -463,7 +818,15 @@
         "stream": "stdout",
         "text": [
          " \r",
         "stream": "stdout",
         "text": [
          " \r",
-        "[****************100%******************]  2 of 2 complete"
+        "[****************100%******************]  1 of 1 complete"
+       ]
+      },
+      {
+       "metadata": {},
+       "output_type": "display_data",
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BQAA4BBhCwAAwCHCFgAAgEOELQAAAIcIWwAAAA55zMzO+k49HgVgt0CDu+CCC07aVllZqdatW5/F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\nQ4QtAAAAh/4XJX37efghybUAAAAASUVORK5CYII=\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x7f94bafb4390>"
         ]
        },
        {
         ]
        },
        {
@@ -474,30 +837,21 @@
         ]
        }
       ],
         ]
        }
       ],
-     "prompt_number": 228
-    },
-    {
-     "cell_type": "markdown",
-     "metadata": {},
-     "source": [
-      "# Matplotlib's image display is terrible so we must resort to this sort of horror\n",
-      "\n",
-      "## I can't seem to stop it from being these colours\n",
-      "\n",
-      "<img src=\"compare.png\" width=\"80%\"/>"
-     ]
+     "prompt_number": 439
      },
      {
       "cell_type": "code",
       "collapsed": false,
       "input": [
      },
      {
       "cell_type": "code",
       "collapsed": false,
       "input": [
-      "def plot_precision_vs_zoom(pz):\n",
+      "def plot_precision_vs_zoom(pz, gpu=True):\n",
        "    figure(figsize=(9,7))\n",
        "    figure(figsize=(9,7))\n",
-      "    plot(pz[:,3], pz[:,6], 'o-')\n",
+      "    if gpu:\n",
+      "        plot(pz[:,3], pz[:,6], 'o-')\n",
+      "        legend([\"GPU\", \"CPU\"])\n",
+      "        \n",
        "    yscale('log')\n",
        "    xscale('log')\n",
        "    plot(pz[:,3], pz[:,8], 'o-')\n",
        "    yscale('log')\n",
        "    xscale('log')\n",
        "    plot(pz[:,3], pz[:,8], 'o-')\n",
-      "    legend([\"GPU\", \"CPU\"])\n",
        "    xlabel(\"Width\")\n",
        "    ylabel(\"Average distance to closest pixel in original\")\n",
        "    title(\"Arr Captain We Be Sinking Into The Sea of Precision\")"
        "    xlabel(\"Width\")\n",
        "    ylabel(\"Average distance to closest pixel in original\")\n",
        "    title(\"Arr Captain We Be Sinking Into The Sea of Precision\")"
@@ -505,7 +859,7 @@
       "language": "python",
       "metadata": {},
       "outputs": [],
       "language": "python",
       "metadata": {},
       "outputs": [],
-     "prompt_number": 80
+     "prompt_number": 454
      },
      {
       "cell_type": "code",
      },
      {
       "cell_type": "code",
@@ -519,13 +873,33 @@
        {
         "metadata": {},
         "output_type": "display_data",
        {
         "metadata": {},
         "output_type": "display_data",
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eDjGjBmDESNG6CI2IiIiIo2oHXJq164dLl68iJYtW+LatWvFyvSFQ05EREQ1h06GnGQyGRQKBRo3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sMLG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\n9tOePXuO4BUJIYQQ4m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OCl4+vTpmDlzJszMzJCUlISpU6fi8ccf10dsRERERFrROOQ0aNAgHD16FDKZDKmpqSplhsIhJyIi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\naWs7sVQU1T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nMaJ+aEHlWrVp1pE/hmPc/9TM+Ft730f4ejobzOxLncLhe82j4fAcz6oHm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\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x7f94baa28290>"
+       ]
+      }
+     ],
+     "prompt_number": 384
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "plot_precision_vs_zoom(pzd, False)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
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6tWr8PHxMVmHpiRHkgMAhYXSbsk//CCdfRXC71uT2rQJGDcOWL4ccHBIQmzsTuTnO0KlUuHEiR44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\nYQJHdoIAAAAASUVORK5CYII=\n",
         "text": [
         "text": [
-        "<matplotlib.figure.Figure at 0x7f94c12d8bd0>"
+        "<matplotlib.figure.Figure at 0x7f94bae39bd0>"
         ]
        }
       ],
         ]
        }
       ],
-     "prompt_number": 81
+     "prompt_number": 455
      },
      {
       "cell_type": "code",
      },
      {
       "cell_type": "code",
author	Sam Moore <[email protected]>
	Wed, 17 Sep 2014 16:09:00 +0000 (00:09 +0800)
committer	Sam Moore <[email protected]>
	Wed, 17 Sep 2014 16:09:00 +0000 (00:09 +0800)
src/bezier.h		patch \| blob \| history
src/main.h		patch \| blob \| history
tools/analysis.ipynb		patch \| blob \| history