Adapt for use with Google Colab

Author: gjbex

julia.ipynb

@@ -7,9 +7,25 @@
     "# Julia sets"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Install the `sh` module since this is a bit off the beaten track."
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install sh"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-11-13T08:47:27.708360Z",
@@ -27,6 +43,22 @@
     "import time"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Download the source code from GitHub."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!wget https://raw.githubusercontent.com/gjbex/PythonSysProg/master/julia_omp.f90"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -36,7 +68,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-11-13T08:47:27.738239Z",
@@ -50,7 +82,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-11-13T08:47:28.066866Z",
@@ -71,7 +103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-11-13T08:47:28.098178Z",
@@ -92,7 +124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-11-13T08:47:28.147292Z",
@@ -106,31 +138,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-11-13T08:47:33.193509Z",
      "start_time": "2018-11-13T08:47:28.160664Z"
     }
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "user: 0.0, sys: 0.0, CPU: 0.0 %, rss: 12972032 bytes\n",
-      "user: 0.34, sys: 0.04, CPU: 75.1 %, rss: 82718720 bytes\n",
-      "user: 0.75, sys: 0.04, CPU: 81.7 %, rss: 82718720 bytes\n",
-      "user: 1.16, sys: 0.05, CPU: 83.8 %, rss: 82718720 bytes\n",
-      "user: 1.53, sys: 0.05, CPU: 73.8 %, rss: 82718720 bytes\n",
-      "user: 1.9, sys: 0.05, CPU: 73.8 %, rss: 82718720 bytes\n",
-      "user: 2.25, sys: 0.05, CPU: 69.8 %, rss: 82718720 bytes\n",
-      "user: 2.57, sys: 0.06, CPU: 65.8 %, rss: 82718720 bytes\n",
-      "user: 2.95, sys: 0.08, CPU: 79.8 %, rss: 82718720 bytes\n",
-      "user: 3.26, sys: 0.08, CPU: 61.7 %, rss: 0 bytes\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "process = psutil.Process(pid=computation.pid)\n",
     "while psutil.pid_exists(process.pid):\n",
@@ -149,7 +164,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-11-13T08:47:33.225431Z",
@@ -163,7 +178,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-11-13T08:47:38.220802Z",
@@ -177,27 +192,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-11-13T08:47:38.604538Z",
      "start_time": "2018-11-13T08:47:38.253596Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "_ = plt.imshow(data)"
    ]
@@ -211,7 +213,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-11-13T08:47:38.630662Z",
@@ -241,7 +243,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.6"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,