Merge branch 'master' of https://github.com/JamesFergusson/Introducti…

…on-to-Research-Computing
manuel-morales-a · Nov 10, 2020 · 63f0a12 · 63f0a12
2 parents 8073608 + ad0c30b
commit 63f0a12
Show file tree

Hide file tree

Showing 2 changed files with 63 additions and 44 deletions.
diff --git a/02_PythonBasics.ipynb b/02_PythonBasics.ipynb
@@ -183,7 +183,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -402,24 +402,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Pi is: 3.14\n",
-      "a, b, c\n",
-      "The complex number (1+2j) is formed from the real part 1.0 and the imaginary part 2.0.\n",
-      "Coordinates: 37.24N, -115.81W\n",
-      "list element 0: 1;  list element 3: cat\n",
-      "1,234,567,890\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "pi = 3.14159265\n",
     "list = [1,2,3,'cat',True,3.1415]\n",
@@ -447,22 +434,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Pi is: 3.14\n",
-      "a, b, c\n",
-      "The complex number (1+2j) is formed from the real part 1.0 and the imaginary part 2.0.\n",
-      "Coordinates: 37.24N, -115.81W\n",
-      "list element 0: 1;  list element 3: cat\n",
-      "1,234,567,890\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "pi = 3.14159265\n",
     "list = [1,2,3,'cat',True,3.1415]\n",
@@ -1028,7 +1002,7 @@
     "for n in range(5):\n",
     "    print(n) \n",
     "\n",
-    "print('\\nrange2')  b\n",
+    "print('\\nrange2')  \n",
     "for n in range(5,10):\n",
     "    print(n)  \n",
     "\n",
@@ -1190,7 +1164,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Here `A=[]` first allocates an empty list to `A` <b>when the function is created</b> not when it is run. Now whenever you edit `A` it's storded at the same address so is kept for subsequent calls to the function.  So as we have pointed `a` and `c` to the same list editing one edits both.\n",
+    "Here `A=[]` first allocates an empty list to `A` <b>when the function is created</b> not when it is run. Now whenever you edit `A` it's stored at the same address so is kept for subsequent calls to the function.  So as we have pointed `a` and `c` to the same list editing one edits both.\n",
     "\n",
     "The following would fix this behaviour:"
    ]
@@ -1338,11 +1312,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "list = [-1,-2,-3,-4,-5,2,3,4,5,6,7,8]\n",
-    "list.sort()\n",
-    "print(list)\n",
-    "list = sorted(list,key=lambda x: abs(x))\n",
-    "print(list)"
+    "list1 = [-1,-2,-3,-4,-5,2,3,4,5,6,7,8]\n",
+    "list1.sort()\n",
+    "print(list1)\n",
+    "list1 = sorted(list1,key=lambda x: abs(x))\n",
+    "print(list1)"
    ]
   },
   {

diff --git a/04_Advanced_Python.ipynb b/04_Advanced_Python.ipynb
@@ -80,7 +80,7 @@
     "        return 6.67e-11 * self.mass / dist\n",
     "\n",
     "        \n",
-    "earth = CelObj(6e24, [0,0,0], [3e4,0,0])\n",
+    "earth = CelObj1(6e24, [0,0,0], [3e4,0,0])\n",
     "print(earth.mass)\n",
     "print(earth.position)\n",
     "print(earth.velocity)\n",
@@ -504,7 +504,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "So far so trivial. This isn't very generic as we had to specify the arguments for the function.  We could generalise it with:|"
+    "So far so trivial. This isn't very generic as we had to specify the arguments for the function.  We could generalise it with:"
    ]
   },
   {
@@ -691,13 +691,58 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Another useful decorator would be one to time how long specific functions take.\n",
+    "Another useful decorator would be one to time how long specific functions take. In numpy there are some built in decorators like `np.vectorize` which modify simple functions to take vector input. My solution for notebook 3 used the explicit version of it on my function `intmono`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "...\n",
+    "\n",
+    "# Vectorise just converts a scalar function to one that accepts vectors\n",
+    "# Needed for numpy.fromfunction\n",
+    "tmp = np.vectorize(intmono)\n",
+    "\n",
+    "# Creates an array with entries calculated from the function which takes array indexes as input\n",
+    "M = np.fromfunction(tmp,(6,6))\n",
+    "\n",
+    "..."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "here we could have used `@np.vectorize` on the definition of `intmono` instead."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@np.vectorize\n",
+    "def intmono(n,m):\n",
+    "    \n",
+    "...\n",
     "\n",
+    "# Creates an array with entries calculated from the function which takes array indexes as input\n",
+    "M = np.fromfunction(intmono,(6,6))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "### Exercise:\n",
     "Design a decorator to time how long functions take to run and output it as a string.\n",
     "You will need commands from the builtin module `time`\n",
     "\n",
-    "Another is to `cache` results for a function.  This just memorises the output for a specific input so if it's called again the function just returns the answer from memory.  This can help with performance but is a bit beyond this course, example given in solutions."
+    "Another is to `cache` results for a function.  This just memorises the output for a specific input so if it's called again the function just returns the answer from memory.  This can help with performance but is a bit beyond this course, an example given in solutions."
    ]
   },
   {
@@ -735,7 +780,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.0"
+   "version": "3.7.8"
   }
  },
  "nbformat": 4,