{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "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": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "!pkill -9 ipdf" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 62 }, { "cell_type": "code", "collapsed": false, "input": [ "from common import *\n", "import build\n", "import scaling" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 137 }, { "cell_type": "code", "collapsed": false, "input": [ "# If things are changed run this instead of restarting kernel\n", "scaling = reload(scaling)\n", "build = reload(build)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 190 }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Compile programs\n", "\n", "Build for each type of real, then save a local copy of the executable." ] }, { "cell_type": "code", "collapsed": false, "input": [ "options[\"tobuild\"] += [\"mpfrc++\"]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 46 }, { "cell_type": "code", "collapsed": false, "input": [ "build.BuildAll()" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Building: ['single', 'double', 'GMPrat', 'mpfrc++']\n", "\r", "[ 0% ]" ] }, { "output_type": "stream", "stream": "stdout", "text": [ " \r", "[********** 25% ] 1 of 4 complete" ] }, { "output_type": "stream", "stream": "stdout", "text": [ " \r", "[*****************50% ] 2 of 4 complete" ] }, { "metadata": {}, "output_type": "display_data", "text": [ "'Failed to build GMPrat'" ] }, { "output_type": "stream", "stream": "stdout", "text": [ " \r", "[*****************75%********* ] 3 of 4 complete" ] }, { "output_type": "stream", "stream": "stdout", "text": [ " \r", "[****************100%******************] 4 of 4 complete" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n" ] } ], "prompt_number": 47 }, { "cell_type": "code", "collapsed": false, "input": [ "options[\"built\"] = [\"single\", \"double\", \"cumul-single\", \"cumul-double\", \"path-single\", \"path-double\", \"path-rat\"] # Hack for now, these were manually compiled" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 91 }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Accuracy of Rendering VS Scaling" ] }, { "cell_type": "code", "collapsed": false, "input": [ "scaling_data = {}\n", "for b in options[\"built\"]:\n", " scaling_data[b] = scaling.FixedScales(\"./\"+b, fps=100, xz=0.5, yz=0.5)\n", " " ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 92 }, { "cell_type": "markdown", "metadata": {}, "source": [ "
Original | Scaled |