00 intro

00_intro_numerical_methods-extra-examples.ipynb

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+   "source": [
+    "<table>\n",
+    " <tr align=left><td><img align=left src=\"./images/CC-BY.png\">\n",
+    " <td>Text provided under a Creative Commons Attribution license, CC-BY. All code is made available under the FSF-approved MIT license. (c) Kyle T. Mandli</td>\n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "hide_input": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from __future__ import print_function\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import numpy\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "Note to lecturers:  This notebook is designed to work best as a classic Jupyter Notebook with nbextensions \n",
+    "* hide_input: to hide selected python cells particularly for just plotting\n",
+    "* RISE:  Interactive js slide presentations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "## Why should I care?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "*Because I have to be here for a requirement...*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "*or I might actually need to solve something important...like can I ever retire?*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "### An example: The Retirement Problem\n",
+    "\n",
+    "$$A = \\frac{P}{r} \\left((1+r)^n - 1 \\right)$$\n",
+    "\n",
+    "$A$ is the total amount after n payments\n",
+    "\n",
+    "$P$ is the incremental payment\n",
+    "\n",
+    "$r$ is the interest rate per payment period\n",
+    "\n",
+    "$n$ is the number of payments\n",
+    "\n",
+    "\n",
+    "\n",
+    "Note that these can all be functions of $r$, $n$, and time"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hide_input": true,
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
+   "source": [
+    "What is the minimum interest rate $r$ required to accrue \\$1M over 20 years saving \\\\$1000 per month?\n",
+    "\n",
+    "$$\n",
+    "A = \\frac{P}{r} \\left((1+r)^n - 1 \\right)\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
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+    "jupyter": {
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+   },
+   "outputs": [],
+   "source": [
+    "def A(P, r, n):\n",
+    "    return P / r * ((1 + r)**n - 1)\n",
+    "\n",
+    "P = 1000.\n",
+    "years = numpy.linspace(0,20,241)\n",
+    "n = 12*years\n",
+    "target = 1.e6"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
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+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# find the root using scipy's brentq method\n",
+    "from scipy.optimize import brentq\n",
+    "n_max = n[-1]\n",
+    "f = lambda r : target - A(P,r/12., n_max)\n",
+    "r_target = brentq(f,0.1,0.15)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
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+     "slide_type": "fragment"
+    }
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+   "outputs": [],
+   "source": [
+    "fig = plt.figure(figsize=(8,6))\n",
+    "fig.set_figwidth(fig.get_figwidth() * 2)\n",
+    "\n",
+    "axes = fig.add_subplot(1, 2, 1)\n",
+    "for r in [0.02, 0.05, 0.08, 0.1, 0.12, 0.15]:\n",
+    "    axes.plot(years, A(P, r/12., n),label='r = {}'.format(r))\n",
+    "axes.plot(years, numpy.ones(years.shape) * target, 'k--',linewidth=2,label=\"Target\")\n",
+    "axes.legend(loc='best')\n",
+    "axes.set_xlabel(\"Years\",fontsize=18)\n",
+    "axes.set_ylabel(\"Annuity Value (Dollars)\",fontsize=18)\n",
+    "axes.set_title(\"The Forward Problem $A(P,r,n)$\",fontsize=20)\n",
+    "axes.grid()\n",
+    "\n",
+    "axes = fig.add_subplot(1, 2, 2)\n",
+    "r = numpy.linspace(1.e-6,0.15,100)\n",
+    "target = 1.e6\n",
+    "axes.plot(A(P,r/12.,n_max),r,linewidth=2)\n",
+    "axes.plot(numpy.ones(r.shape) * target, r,'k--',linewidth=2)\n",
+    "axes.scatter(A(P,r_target/12,n_max),r_target,s=100,c='r')\n",
+    "axes.set_xlabel('Annuity Value (Dollars)',fontsize=18)\n",
+    "axes.set_title('The Inverse Problem $r(A,P,n)$, $r\\geq$ {:.3f}'.format(r_target),fontsize=20)\n",
+    "axes.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "This is a rootfinding problem for a function of a single variable"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "### Another Example:  Boat race (numerical quadrature of arc length)\n",
+    "Given a river with coordinates $(x,f(x))$ find the total length actually rowed over a given interval $x\\in [0,X]$\n",
+    "\n",
+    "Example:  a sinusoidal river $$f(x) = A \\sin x$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "hide_input": true,
+    "slideshow": {
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+    }
+   },
+   "outputs": [],
+   "source": [
+    "A=.5\n",
+    "fig = plt.figure(figsize=(8,6))\n",
+    "x = numpy.linspace(0,10,100)\n",
+    "plt.plot(x,A*numpy.sin(x),'r',linewidth=2,)\n",
+    "plt.xlabel('distance (km)')\n",
+    "plt.grid()\n",
+    "plt.title('The Boat Race: $f(x)=A\\sin(x)')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
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+    }
+   },
+   "source": [
+    "We need to calculate the function $f(x)$'s arc-length from $[0, X]$ e.g.\n",
+    "\n",
+    "\\begin{align}\n",
+    "    L(X) &= \\int_0^{X} \\sqrt{1 + |f'(x)|^2} dx\\\\\n",
+    "         &= \\int_0^{X} \\sqrt{1 + A^2\\cos^2(x)} dx\\\\\n",
+    "\\end{align}\n",
+    "\n",
+    "In general the value of this integral cannot be solved analytically (the answer is actually an elliptic integral). We usually need to approximate the integral using a numerical quadrature."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hide_input": true,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "## Why is this exciting?\n",
+    "\n",
+    "Computers have revolutionized our ability to explore...\n",
+    "\n",
+    "[Top 10 Algorithms of the 20th Century](http://www.siam.org/pdf/news/637.pdf?t=1&cn=ZmxleGlibGVfcmVjcw%3D%3D&refsrc=email&iid=658bdab6af614c83a8df1f8e02035eae&uid=755271476&nid=244+285282312)\n",
+    "\n",
+    "...and there is more to come!"
+   ]
+  }
+ ],
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