julia_shift.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "julia_shift.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/evaneschneider/parallel-programming/blob/master/julia_shift.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "metadata": {
        "id": "jC5UnYKRhIRb",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import math\n",
        "from numba import vectorize, cuda\n",
        "from matplotlib import pyplot as plt\n",
        "plt.style.use('default')\n",
        "%matplotlib inline\n",
        "from matplotlib import animation, rc\n",
        "from IPython.display import HTML\n",
        "rc('animation', html='html5')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "3bXKwKrVhOov",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.environ['NUMBAPRO_LIBDEVICE'] = \"/usr/local/cuda-10.0/nvvm/libdevice\"\n",
        "os.environ['NUMBAPRO_NVVM'] = \"/usr/local/cuda-10.0/nvvm/lib64/libnvvm.so\""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "GcIRC-WOhdhp",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "@cuda.jit(device=True)\n",
        "def julia(x, y, max_iters, cin):\n",
        "    \"\"\"\n",
        "    Given the real and imaginary parts of a complex number,\n",
        "    determine if it is a candidate for membership in the Julia\n",
        "    set given a fixed number of iterations.\n",
        "    \"\"\"\n",
        "    i = 0\n",
        "    #c = complex(-0.8, 0.156)\n",
        "    #c = complex(0.274, -0.008)\n",
        "    #c = complex(0.28, 0.008)\n",
        "    #c = complex(0.3, -0.01)\n",
        "    c = complex(cin[0], cin[1])\n",
        "    a = complex(x,y)\n",
        "    for i in range(max_iters):\n",
        "        a = a*a + c\n",
        "        if (a.real*a.real + a.imag*a.imag) > 1000:\n",
        "            return int((i/max_iters)*255)\n",
        "    return 255"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "V_ESU6cKhory",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "@cuda.jit\n",
        "def create_fractal(min_x, max_x, min_y, max_y, image, iters, c):\n",
        "    height = image.shape[0]\n",
        "    width = image.shape[1]\n",
        "\n",
        "    pixel_size_x = (max_x - min_x) / width\n",
        "    pixel_size_y = (max_y - min_y) / height\n",
        "    \n",
        "    x, y = cuda.grid(2)\n",
        "    \n",
        "    if x < width and y < height:\n",
        "      real = min_x + x * pixel_size_x\n",
        "      imag = min_y + y * pixel_size_y\n",
        "      color = julia(real, imag, iters, c)\n",
        "      image[y, x] = color"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "iToJxbWDhu5t",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "image = np.zeros((1800, 1800), dtype=np.uint8)\n",
        "threadsperblock = 16\n",
        "threads_per_block = (16, 16)\n",
        "xblocks = (image.shape[1] + (threadsperblock - 1)) // threadsperblock\n",
        "yblocks = (image.shape[0] + (threadsperblock - 1)) // threadsperblock\n",
        "blocks_per_grid = (xblocks, yblocks)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "wLc4dP2twz-R",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "reals = np.linspace(0.3,0.28,100)\n",
        "imags = np.linspace(-0.01,0.008,100)\n",
        "reals = np.linspace(0.28,-0.12,200)\n",
        "imags = np.linspace(0.008,-0.77,200)\n",
        "c = np.column_stack((reals, imags))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "vJhaTTKghzbn",
        "colab_type": "code",
        "outputId": "8a5e872c-1fd3-4bf9-930e-faa1ecc9f3a9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        }
      },
      "cell_type": "code",
      "source": [
        "i = 199\n",
        "create_fractal[blocks_per_grid, threads_per_block](-1.5, 1.5, -1.5, 1.5, image, 200, c[i])\n",
        "plt.figure(figsize=(8,8))\n",
        "plt.imshow(image, cmap=\"plasma\")\n",
        "plt.axis('off')\n",
        "plt.show()"
      ],
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe4AAAHWCAYAAACxPmqWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwrJmlFlu7gAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "g5qTv6d4R9tJ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        },
        "outputId": "966ec16b-d42d-4bc9-f942-209191749e72"
      },
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&scope=email%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdocs.test%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive.photos.readonly%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fpeopleapi.readonly&response_type=code\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/gdrive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "KBTSh37mh5J7",
        "colab_type": "code",
        "outputId": "e4eec2ba-4abd-4906-8466-67b1234fb9e4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 3417
        }
      },
      "cell_type": "code",
      "source": [
        "imageList = []\n",
        "image = np.zeros((1800, 1800), dtype=np.uint8)\n",
        "for i in range(200):\n",
        "  print(i)\n",
        "  create_fractal[blocks_per_grid, threads_per_block](-1.5, 1.5, -1.5, 1.5, image, 200, c[i])\n",
        "  fig = plt.figure(figsize=(8,8))\n",
        "  plt.xlim(( 0, 1800))\n",
        "  plt.ylim((0, 1800))\n",
        "  plt.axis('off')\n",
        "  im = plt.imshow(image, cmap='plasma', animated=True, vmin=0, vmax=255)\n",
        "  plt.savefig('/content/gdrive/My Drive/pngs/'+str(i)+'.png')\n",
        "  plt.close()"
      ],
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0\n",
            "1\n",
            "2\n",
            "3\n",
            "4\n",
            "5\n",
            "6\n",
            "7\n",
            "8\n",
            "9\n",
            "10\n",
            "11\n",
            "12\n",
            "13\n",
            "14\n",
            "15\n",
            "16\n",
            "17\n",
            "18\n",
            "19\n",
            "20\n",
            "21\n",
            "22\n",
            "23\n",
            "24\n",
            "25\n",
            "26\n",
            "27\n",
            "28\n",
            "29\n",
            "30\n",
            "31\n",
            "32\n",
            "33\n",
            "34\n",
            "35\n",
            "36\n",
            "37\n",
            "38\n",
            "39\n",
            "40\n",
            "41\n",
            "42\n",
            "43\n",
            "44\n",
            "45\n",
            "46\n",
            "47\n",
            "48\n",
            "49\n",
            "50\n",
            "51\n",
            "52\n",
            "53\n",
            "54\n",
            "55\n",
            "56\n",
            "57\n",
            "58\n",
            "59\n",
            "60\n",
            "61\n",
            "62\n",
            "63\n",
            "64\n",
            "65\n",
            "66\n",
            "67\n",
            "68\n",
            "69\n",
            "70\n",
            "71\n",
            "72\n",
            "73\n",
            "74\n",
            "75\n",
            "76\n",
            "77\n",
            "78\n",
            "79\n",
            "80\n",
            "81\n",
            "82\n",
            "83\n",
            "84\n",
            "85\n",
            "86\n",
            "87\n",
            "88\n",
            "89\n",
            "90\n",
            "91\n",
            "92\n",
            "93\n",
            "94\n",
            "95\n",
            "96\n",
            "97\n",
            "98\n",
            "99\n",
            "100\n",
            "101\n",
            "102\n",
            "103\n",
            "104\n",
            "105\n",
            "106\n",
            "107\n",
            "108\n",
            "109\n",
            "110\n",
            "111\n",
            "112\n",
            "113\n",
            "114\n",
            "115\n",
            "116\n",
            "117\n",
            "118\n",
            "119\n",
            "120\n",
            "121\n",
            "122\n",
            "123\n",
            "124\n",
            "125\n",
            "126\n",
            "127\n",
            "128\n",
            "129\n",
            "130\n",
            "131\n",
            "132\n",
            "133\n",
            "134\n",
            "135\n",
            "136\n",
            "137\n",
            "138\n",
            "139\n",
            "140\n",
            "141\n",
            "142\n",
            "143\n",
            "144\n",
            "145\n",
            "146\n",
            "147\n",
            "148\n",
            "149\n",
            "150\n",
            "151\n",
            "152\n",
            "153\n",
            "154\n",
            "155\n",
            "156\n",
            "157\n",
            "158\n",
            "159\n",
            "160\n",
            "161\n",
            "162\n",
            "163\n",
            "164\n",
            "165\n",
            "166\n",
            "167\n",
            "168\n",
            "169\n",
            "170\n",
            "171\n",
            "172\n",
            "173\n",
            "174\n",
            "175\n",
            "176\n",
            "177\n",
            "178\n",
            "179\n",
            "180\n",
            "181\n",
            "182\n",
            "183\n",
            "184\n",
            "185\n",
            "186\n",
            "187\n",
            "188\n",
            "189\n",
            "190\n",
            "191\n",
            "192\n",
            "193\n",
            "194\n",
            "195\n",
            "196\n",
            "197\n",
            "198\n",
            "199\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "cS07ob2cudIN",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}