Updated the slides on object oriented programming.

classes.ipynb

@@ -42,7 +42,7 @@
       "\n",
       "You can use nbconvert to convert the slides to HTML and serve them:\n",
       "\n",
-      "    ipython nbconvert --to slides --post serve matplotlib.ipynb\n",
+      "    ipython nbconvert --to slides --post serve classes.ipynb\n",
       "\n",
       "This will open the slides in a new browser window."
      ]
@@ -73,7 +73,11 @@
     },
     {
      "cell_type": "markdown",
-     "metadata": {},
+     "metadata": {
+      "slideshow": {
+       "slide_type": "slide"
+      }
+     },
      "source": [
       "Imagine we are collecting a number of attributes of some persons:\n",
       "\n",
@@ -378,7 +382,11 @@
     },
     {
      "cell_type": "markdown",
-     "metadata": {},
+     "metadata": {
+      "slideshow": {
+       "slide_type": "slide"
+      }
+     },
      "source": [
       "        class Person(object):\n",
       "            ...\n",
@@ -436,7 +444,11 @@
     },
     {
      "cell_type": "markdown",
-     "metadata": {},
+     "metadata": {
+      "slideshow": {
+       "slide_type": "slide"
+      }
+     },
      "source": [
       "    class Person(object):\n",
       "        ...\n",
@@ -556,7 +568,11 @@
     },
     {
      "cell_type": "markdown",
-     "metadata": {},
+     "metadata": {
+      "slideshow": {
+       "slide_type": "slide"
+      }
+     },
      "source": [
       "    class Person(object):\n",
       "        ...\n",
@@ -607,7 +623,11 @@
       "            self.eye_colour, self.hair_colour, self.weight, self.length)"
      ],
      "language": "python",
-     "metadata": {},
+     "metadata": {
+      "slideshow": {
+       "slide_type": "slide"
+      }
+     },
      "outputs": [],
      "prompt_number": 127
     },
@@ -633,9 +653,75 @@
      "prompt_number": 86
     },
     {
-     "cell_type": "markdown",
-     "metadata": {},
-     "source": []
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "class Read(object):\n",
+      "    def __init__(self):\n",
+      "        self.read = \"\"\n",
+      "        self.qual = []\n",
+      "            \n",
+      "    def __str__(self):\n",
+      "        return self.read\n",
+      "        \n",
+      "    def add(self, base):\n",
+      "        self.read += base[0]\n",
+      "        self.qual.append(base[1])\n",
+      "            \n",
+      "    def quality(self):\n",
+      "        return sum(self.qual) / len(self.read)\n",
+      "        \n",
+      "    def trim(self, score):\n",
+      "        for position in range(len(self.read) - 1, -1, -1):\n",
+      "            if self.qual[position] >= score:\n",
+      "                return self.read[:position]"
+     ],
+     "language": "python",
+     "metadata": {
+      "slideshow": {
+       "slide_type": "slide"
+      }
+     },
+     "outputs": [],
+     "prompt_number": 7
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "from sequencer import Sequencer\n",
+      "\n",
+      "spots = 2\n",
+      "run = Sequencer(spots, readlength=60)\n",
+      "\n",
+      "reads = [Read() for _ in range(spots)]\n",
+      "for tile in run:\n",
+      "    for read_id, base in enumerate(tile):\n",
+      "        reads[read_id].add(base)\n",
+      "\n",
+      "for i in reads:\n",
+      "    print i, i.quality()\n",
+      "    print i.trim(39)"
+     ],
+     "language": "python",
+     "metadata": {
+      "slideshow": {
+       "slide_type": "slide"
+      }
+     },
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "GGTGTGATTCCCGTTCGGTGGGCCGCCTTGGGTCATTGCTCGGTTGAGGAGGGAAGACCT 30\n",
+        "GGTGTGATTCCCGTTCGGTGGGCCGCCTTGGGTCAT\n",
+        "GGCTTTAGAATGTCTCCTGCATCTGATGCTATTAAAAGCTATGTTTTTCACATAGTACGG 29\n",
+        "GGCTTTAGAATGTCTCCTGCATCTGATGCTATTAAAAGCTATGTTTTTCACATAGT\n"
+       ]
+      }
+     ],
+     "prompt_number": 8
     }
    ],
    "metadata": {}