Revised list of TBCs

1 files changed, 43 insertions, 54 deletions

diff --git a/MECHANICS_OF_SOLIDS_by_S.S._Bhavikatti/Chapter6.ipynb b/MECHANICS_OF_SOLIDS_by_S.S._Bhavikatti/Chapter6.ipynb
index 85985309..55339520 100644
--- a/MECHANICS_OF_SOLIDS_by_S.S._Bhavikatti/Chapter6.ipynb
+++ b/MECHANICS_OF_SOLIDS_by_S.S._Bhavikatti/Chapter6.ipynb
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 19,
    "metadata": {
     "collapsed": false
    },
@@ -68,7 +68,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 20,
    "metadata": {
     "collapsed": false
    },
@@ -115,14 +115,16 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "source": [
     "# Example 6.3"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 21,
    "metadata": {
     "collapsed": false
    },
@@ -174,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 22,
    "metadata": {
     "collapsed": false
    },
@@ -192,7 +194,6 @@
        "/* Put everything inside the global mpl namespace */\n",
        "window.mpl = {};\n",
        "\n",
-       "\n",
        "mpl.get_websocket_type = function() {\n",
        "    if (typeof(WebSocket) !== 'undefined') {\n",
        "        return WebSocket;\n",
@@ -251,9 +252,6 @@
        "    this.ws.onopen =  function () {\n",
        "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
        "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
        "            fig.send_message(\"refresh\", {});\n",
        "        }\n",
        "\n",
@@ -323,15 +321,6 @@
        "    this.canvas = canvas[0];\n",
        "    this.context = canvas[0].getContext(\"2d\");\n",
        "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
        "    var rubberband = $('<canvas/>');\n",
        "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
        "\n",
@@ -388,9 +377,8 @@
        "        canvas_div.css('width', width)\n",
        "        canvas_div.css('height', height)\n",
        "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
        "\n",
        "        rubberband.attr('width', width);\n",
        "        rubberband.attr('height', height);\n",
@@ -523,10 +511,10 @@
        "}\n",
        "\n",
        "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    var x0 = msg['x0'];\n",
+       "    var y0 = fig.canvas.height - msg['y0'];\n",
+       "    var x1 = msg['x1'];\n",
+       "    var y1 = fig.canvas.height - msg['y1'];\n",
        "    x0 = Math.floor(x0) + 0.5;\n",
        "    y0 = Math.floor(y0) + 0.5;\n",
        "    x1 = Math.floor(x1) + 0.5;\n",
@@ -682,8 +670,8 @@
        "        this.canvas_div.focus();\n",
        "    }\n",
        "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "    var x = canvas_pos.x;\n",
+       "    var y = canvas_pos.y;\n",
        "\n",
        "    this.send_message(name, {x: x, y: y, button: event.button,\n",
        "                             step: event.step,\n",
@@ -804,7 +792,6 @@
        "};\n",
        "\n",
        "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
        "    fig.root.unbind('remove')\n",
        "\n",
        "    // Update the output cell to use the data from the current canvas.\n",
@@ -813,7 +800,7 @@
        "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
        "    // the notebook keyboard shortcuts fail.\n",
        "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
        "    fig.close_ws(fig, msg);\n",
        "}\n",
        "\n",
@@ -824,9 +811,8 @@
        "\n",
        "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
        "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
        "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
        "}\n",
        "\n",
        "mpl.figure.prototype.updated_canvas_event = function() {\n",
@@ -915,9 +901,12 @@
        "    // Check for shift+enter\n",
        "    if (event.shiftKey && event.which == 13) {\n",
        "        this.canvas_div.blur();\n",
-       "        // select the cell after this one\n",
-       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
-       "        IPython.notebook.select(index + 1);\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
        "    }\n",
        "}\n",
        "\n",
@@ -966,7 +955,7 @@
     {
      "data": {
       "text/html": [
-       "<img 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\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1023,7 +1012,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 23,
    "metadata": {
     "collapsed": false
    },
@@ -1078,7 +1067,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 24,
    "metadata": {
     "collapsed": false
    },
@@ -1123,7 +1112,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 25,
    "metadata": {
     "collapsed": false
    },
@@ -1157,7 +1146,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 26,
    "metadata": {
     "collapsed": false
    },
@@ -1192,7 +1181,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 27,
    "metadata": {
     "collapsed": false
    },
@@ -1230,7 +1219,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 28,
    "metadata": {
     "collapsed": false
    },
@@ -1264,7 +1253,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 29,
    "metadata": {
     "collapsed": false
    },
@@ -1303,7 +1292,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 30,
    "metadata": {
     "collapsed": false
    },
@@ -1341,7 +1330,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 31,
    "metadata": {
     "collapsed": false
    },
@@ -1378,7 +1367,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false
    },
@@ -1387,7 +1376,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Effort is 348.376068376 N\n"
+      "Effort is 1741.88034188 N\n"
      ]
     }
    ],
@@ -1398,7 +1387,7 @@
     "W=40000.0              #effort\n",
     "R = 400  #Lever length\n",
     "u = 0.12    #coefficient of friction between screw and nut\n",
-    "P = (D/(2*R))*W*((u+(p/(3.14*D)))/(1-u*(p/(3.14*D))))   #Effort\n",
+    "P = (d/(2*R))*W*((u+(p/(3.14*D)))/(1-u*(p/(3.14*D))))   #Effort\n",
     "print \"Effort is\",P,\"N\"\n"
    ]
   },
@@ -1411,7 +1400,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 33,
    "metadata": {
     "collapsed": false
    },
@@ -1459,7 +1448,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 34,
    "metadata": {
     "collapsed": false
    },
@@ -1495,7 +1484,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 35,
    "metadata": {
     "collapsed": false
    },
@@ -1547,7 +1536,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 36,
    "metadata": {
     "collapsed": false
    },
@@ -1582,9 +1571,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda root]",
+   "display_name": "Python [Root]",
    "language": "python",
-   "name": "conda-root-py"
+   "name": "Python [Root]"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1596,7 +1585,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.13"
+   "version": "2.7.12"
   }
  },
  "nbformat": 4,