{
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    "Root-finding Without Derivatives\n",
    "================================"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**References:**\n",
    "\n",
    "- Section 1.5.1 *Secant Method and variants* in [Sauer](../references.html#Sauer)\n",
    "- Section 2.3 *Newton's Method and it Extensions* in [Burden&Faires](../references.html#Burden-Faires);\n",
    "just the later sub-sections, on *The Secant Method* and *The Method of False Position*)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "We have already seen one method for solving $f(x) = 0$ without needing to know any derivatives of $f$:\n",
    "the [Bisection Method](root-finding-by-interval-halving-python.ipynb), a.k.a. *Interval Halving*.\n",
    "However, we have also seen that that method is far slower then Newton's Method.\n",
    "\n",
    "Here we explore methods that are almost the best of both worlds:\n",
    "about as fast as Newton's method but not needing derivatives.\n",
    "\n",
    "The first of these is the Secant Method.\n",
    "Later in this course we will see how this has been merged with the Bisection Method and\n",
    "[Polynomial Interpolation](polynomial-collocation+approximation-python.ipynb)\n",
    "to produce the current state-of-the-art approach;\n",
    "only perfected in the 1960's."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
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   "source": [
    "# We will often need resources from the modules numpy and pyplot:\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "# We can also import items from a module individually, so they can be used by \"first name only\";\n",
    "from numpy import abs, cos\n",
    "\n",
    "# Since we do a lot of graphics in this section, some more short-hands:\n",
    "from matplotlib.pyplot import figure, title, plot, xlabel, ylabel, grid, legend, show\n",
    "from numpy import linspace\n",
    "\n",
    "# Also, some from the module for this book:\n",
    "from numerical_methods_module import newton"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using Linear Approximation Without Derivatives\n",
    "\n",
    "One quirk of the [Bisection Method](root-finding-by-interval-halving-python.ipynb) is that it only used the sign of the values $f(a)$ and $f(b)$, not their magnitudes.\n",
    "If one of these is far smaller than the other, one might guess that the root is closer to that end of the interval.\n",
    "This leads to the idea of:\n",
    "- starting with an interval $[a, b]$ known to contain a zero of $f$,\n",
    "- connecting the two points $(a, f(a))$ and $(b, f(b))$ with a straight line, and\n",
    "- finding the $x$-value $c$ where this line crosses the $x$-axis.\n",
    "In the words, aproximating the function by a *secant line*, in place of the *tangent line* used in Newton's Method."
   ]
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   "source": [
    "<a name=\"method-of-false-position\"></a>\n",
    "### First Attempt: The Method of False Position\n",
    "\n",
    "The next step requires some care.\n",
    "The first idea (from almost a millenium ago) was to use this new approximation $c$ as done with bisection:\n",
    "check which of the intervals $[a, c]$ and $[c,b]$ has the sign change and use it as the new interval $[a, b]$;\n",
    "this is called *The Method of False Position* (or *Regula Falsi*, since the academic world used latin in those days.)\n",
    "\n",
    "The secant line between $(a, f(a))$ and $(b, f(b))$ is\n",
    "\n",
    "$$\n",
    "L(x) = \\frac{f(a)(b-x) + f(b)(x-a)}{b-a}\n",
    "$$\n",
    "\n",
    "and its zero is at\n",
    "\n",
    "$$\n",
    "c = \\frac{a f(b) - f(a) b}{f(b) - f(a)}\n",
    "$$\n",
    "\n",
    "This is easy to implement, and an example will show that it sort of works, but with a weakness that hampers it a bit:"
   ]
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  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def false_position(f, a, b, errorTolerance=1e-15, maxIterations=15, demoMode=False):\n",
    "    \"\"\"Solve f(x)=0 in the interval [a, b] by the Method of False Position.\n",
    "    This code also illustrates a few ideas that I encourage, such as:\n",
    "    - Avoiding infinite loops, by using for loops sand break\n",
    "    - Avoiding repeated evaluation of the same quantity\n",
    "    - Use of descriptive variable names\n",
    "    - Use of \"camelCase\" to turn descriptive phrases into valid Python variable names\n",
    "    - An optional \"demonstration mode\" to display intermediate results.\n",
    "    \"\"\"\n",
    "    if demoMode: print(f\"Solving by the Method of False Position.\")\n",
    "    fa = f(a)\n",
    "    fb = f(b)\n",
    "    for iteration in range(maxIterations):\n",
    "        if demoMode: print(f\"\\nIteration {iteration}:\")\n",
    "        c = (a * fb - fa * b)/(fb - fa)\n",
    "        fc = f(c)\n",
    "        if fa * fc < 0:\n",
    "            b = c\n",
    "            fb = fc  # N.B. When b is updated, so must be fb = f(b)\n",
    "        else:\n",
    "            a = c\n",
    "            fa = fc\n",
    "        errorBound = b - a\n",
    "        if demoMode:\n",
    "            print(f\"The root is in interval [{a}, {b}]\")\n",
    "            print(f\"The new approximation is {c}, with error bound {errorBound:0.4}, backward error {abs(fc):0.4}\")\n",
    "        if errorBound < errorTolerance:\n",
    "            break\n",
    "    # Whether we got here due to accuracy of running out of iterations,\n",
    "    # return the information we have, including an error bound:\n",
    "    root = c  # the newest value is probably the most accurate\n",
    "    return (root, errorBound)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note:** For a more concise presentation, you could omit the above `def` and instead import this function with\n",
    "\n",
    "    from numerical_methods_module import false_position"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def f(x): return x - cos(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solving by the Method of False Position.\n",
      "\n",
      "Iteration 0:\n",
      "The root is in interval [0.5403023058681398, 1]\n",
      "The new approximation is 0.5403023058681398, with error bound 0.4597, backward error 0.3173\n",
      "\n",
      "Iteration 1:\n",
      "The root is in interval [0.7280103614676172, 1]\n",
      "The new approximation is 0.7280103614676172, with error bound 0.272, backward error 0.01849\n",
      "\n",
      "Iteration 2:\n",
      "The root is in interval [0.7385270062423998, 1]\n",
      "The new approximation is 0.7385270062423998, with error bound 0.2615, backward error 0.000934\n",
      "\n",
      "Iteration 3:\n",
      "The root is in interval [0.7390571666782676, 1]\n",
      "The new approximation is 0.7390571666782676, with error bound 0.2609, backward error 4.68e-05\n",
      "\n",
      "Iteration 4:\n",
      "The root is in interval [0.7390837322783136, 1]\n",
      "The new approximation is 0.7390837322783136, with error bound 0.2609, backward error 2.345e-06\n",
      "\n",
      "Iteration 5:\n",
      "The root is in interval [0.7390850630385933, 1]\n",
      "The new approximation is 0.7390850630385933, with error bound 0.2609, backward error 1.174e-07\n",
      "\n",
      "Iteration 6:\n",
      "The root is in interval [0.7390851296998365, 1]\n",
      "The new approximation is 0.7390851296998365, with error bound 0.2609, backward error 5.883e-09\n",
      "\n",
      "Iteration 7:\n",
      "The root is in interval [0.7390851330390691, 1]\n",
      "The new approximation is 0.7390851330390691, with error bound 0.2609, backward error 2.947e-10\n",
      "\n",
      "Iteration 8:\n",
      "The root is in interval [0.7390851332063397, 1]\n",
      "The new approximation is 0.7390851332063397, with error bound 0.2609, backward error 1.476e-11\n",
      "\n",
      "Iteration 9:\n",
      "The root is in interval [0.7390851332147188, 1]\n",
      "The new approximation is 0.7390851332147188, with error bound 0.2609, backward error 7.394e-13\n",
      "\n",
      "Iteration 10:\n",
      "The root is in interval [0.7390851332151385, 1]\n",
      "The new approximation is 0.7390851332151385, with error bound 0.2609, backward error 3.708e-14\n",
      "\n",
      "Iteration 11:\n",
      "The root is in interval [0.7390851332151596, 1]\n",
      "The new approximation is 0.7390851332151596, with error bound 0.2609, backward error 1.776e-15\n",
      "\n",
      "Iteration 12:\n",
      "The root is in interval [0.7390851332151606, 1]\n",
      "The new approximation is 0.7390851332151606, with error bound 0.2609, backward error 1.11e-16\n",
      "\n",
      "Iteration 13:\n",
      "The root is in interval [0.7390851332151607, 1]\n",
      "The new approximation is 0.7390851332151607, with error bound 0.2609, backward error 0.0\n",
      "\n",
      "Iteration 14:\n",
      "The root is in interval [0.7390851332151607, 1]\n",
      "The new approximation is 0.7390851332151607, with error bound 0.2609, backward error 0.0\n",
      "\n",
      "The Method of False Position gave approximate root is 0.7390851332151607,\n",
      "with estimate error 0.2609, backward error 0.0\n"
     ]
    }
   ],
   "source": [
    "(root, errorBound) = false_position(f, a=-1, b=1, demoMode=True)\n",
    "print(f\"\\nThe Method of False Position gave approximate root is {root},\")\n",
    "print(f\"with estimate error {errorBound:0.4}, backward error {abs(f(root)):0.4}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The good news is that the approximations are approaching the zero reasonably fast — far faster than bisection —\n",
    "as indicated by the backward errors improving by a factor of better than ten at each iteration.\n",
    "\n",
    "The bad news is that one end gets \"stuck\", so the interval does not shrink on both sides, and the error bound stays large.\n",
    "\n",
    "This behavior is generic: with function $f$ of the same convexity on the interval $[a, b]$, the secant line will always cross on the same side of the zero, so that one end-point persists;\n",
    "in this case, the curve is concave up, so the secant line always crosses to the left of the root, as seen in the following graphs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def graph_false_position(f, a, b, maxIterations=3):\n",
    "    \"\"\"Graph a few iterations of the Method of False Position for solving f(x)=0 in the interval [a, b].\n",
    "    \"\"\"\n",
    "    fa = f(a)\n",
    "    fb = f(b)\n",
    "    for iteration in range(maxIterations):\n",
    "        c = (a * fb - fa * b)/(fb - fa)\n",
    "        fc = f(c)\n",
    "        abc = [a,b, c]\n",
    "        left = np.min(abc)\n",
    "        right = np.max(abc)\n",
    "        x = linspace(left, right)\n",
    "        figure(figsize=[16,6])\n",
    "        title(f\"Iteration {iteration+1}, Method of False Position\")\n",
    "        xlabel(\"$x$\")\n",
    "        plot(x, f(x))\n",
    "        plot([left, right], [f(left), f(right)])  # the secant line\n",
    "        plot([left, right], [0, 0], 'k')  # the x-axis line\n",
    "        plot(abc, f(abc), 'r*')\n",
    "        show()  # The Windows version of JupytLab might need this command; it is harmless anyway.\n",
    "        if fa * fc < 0:\n",
    "            b = c\n",
    "            fb = fc  # N.B. When b is updated, so must be fb = f(b)\n",
    "        else:\n",
    "            a = c\n",
    "            fa = fc"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph_false_position(f, a=-1, b=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Refinement: Alway Use the Two Most Recent Approximations — The Secant Method\n",
    "\n",
    "The basic solution is to always discard the oldest approximation — at the cost of not always having the zero surrounded!\n",
    "This gives the Secant Method.\n",
    "\n",
    "For a mathemacal description, one typically enumerates the successive approximations as $x_0$, $x_1$, etc.,\n",
    "so the notation above gets translated with $a \\to x_{k-2}$, $b \\to x_{k-1}$, $c \\to x_{k}$;\n",
    "then the formula becomes the recursive rule\n",
    "\n",
    "$$\n",
    "x_k = \\frac{x_{k-2} f(x_{k-1}) - f(x_{k-2}) x_{k-1}}{f(x_{k-1}) - f(x_{k-2})}\n",
    "$$\n",
    "\n",
    "Two difference from above:\n",
    "- previously we could assume that $a<b$, but now we do not know the order of the various $x_k$ values, and\n",
    "- the root is not necessarily bewtween the two most recent values, so we no longer have tht simple error bound.\n",
    "(In fact, we will see that the zero is typically surrounded two-thirds of the time!)\n",
    "\n",
    "Instead, we use the *magnitude* of $b-a$ which is now $|x_k - x_{k-1}|$, and this is only an *estimate* of the error.\n",
    "This is the same as used for Newton's Method; as there, it is still useful as a condition for ending the iterations and indeed tends to be pessimistic, so that we typically do one more iteration than needed — but it is not on its own a complete guarantee of having achieved the desired accuracy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pseduo-code for a Secant Method Algorithm\n",
    "\n",
    "Input function $f$, interval endpoints $x_0$ and $x_1$, an error tolerance $E_{tol}$, and an iteration limit $N$\n",
    "\n",
    "for k from 2 to N:\n",
    "<br>$\\quad$ $\\displaystyle x_k \\leftarrow \\frac{x_{k-2} f(x_{k-1}) - f(x_{k-2}) x_{k-1}}{f(x_{k-1}) - f(x_{k-2})}$\n",
    "<br>$\\quad$ Evaluate the error estimate $E_{est} \\leftarrow |x_k - x_{k-1}|$\n",
    "<br>$\\quad$ if $E_{est} \\leq E_{tol}$:\n",
    "<br>$\\quad\\quad$ End the iterations\n",
    "<br>$\\quad$ else:\n",
    "<br>$\\quad\\quad$ Go around another time\n",
    "<br>end for\n",
    "<br>Output the final $x_k$ as the approximate root and $E_{est}$ as an estimate of its absolute error."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Python Code for this Secant Method Algorithm\n",
    "\n",
    "We could write Python code that closely follows this notation, accumulating a list of the values $x_k$.\n",
    "\n",
    "However, since we only ever need the two most recent values to compute the new one, we can instead just store these three,\n",
    "in the same way that we recylced the variables `a`, `b` and `c`.\n",
    "Here I use more descriptive names though:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def secant_method(f, a, b, errorTolerance=1e-15, maxIterations=15, demoMode=False):\n",
    "    \"\"\"Solve f(x)=0 in the interval [a, b] by the Secant Method.\"\"\"\n",
    "    if demoMode:\n",
    "        print(f\"Solving by the Secant Method.\")        \n",
    "    # Some more descriptive names\n",
    "    x_older = a\n",
    "    x_more_recent = b\n",
    "    f_x_older = f(x_older)\n",
    "    f_x_more_recent = f(x_more_recent)\n",
    "    for iteration in range(maxIterations):\n",
    "        if demoMode: print(f\"\\nIteration {iteration}:\")\n",
    "        x_new = (x_older * f_x_more_recent - f_x_older * x_more_recent)/(f_x_more_recent - f_x_older)\n",
    "        f_x_new = f(x_new)\n",
    "        (x_older, x_more_recent) = (x_more_recent, x_new)\n",
    "        (f_x_older, f_x_more_recent) = (f_x_more_recent, f_x_new)\n",
    "        errorEstimate = abs(x_older - x_more_recent)\n",
    "        if demoMode:\n",
    "            print(f\"The latest pair of approximations are {x_older} and {x_more_recent},\")\n",
    "            print(f\"where the function's values are {f_x_older:0.4} and {f_x_more_recent:0.4} respectively.\")\n",
    "            print(f\"The new approximation is {x_new}, with estimated error {errorEstimate:0.4}, backward error {abs(f_x_new):0.4}\")\n",
    "        if errorEstimate < errorTolerance:\n",
    "            break\n",
    "    # Whether we got here due to accuracy of running out of iterations,\n",
    "    # return the information we have, including an error estimate:\n",
    "    return (x_new, errorEstimate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note:** As above, you could omit the above `def` and instead import this function with\n",
    "\n",
    "    from numerical_methods_module import secant_method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solving by the Secant Method.\n",
      "\n",
      "Iteration 0:\n",
      "The latest pair of approximations are 1 and 0.5403023058681398,\n",
      "where the function's values are 0.4597 and -0.3173 respectively.\n",
      "The new approximation is 0.5403023058681398, with estimated error 0.4597, backward error 0.3173\n",
      "\n",
      "Iteration 1:\n",
      "The latest pair of approximations are 0.5403023058681398 and 0.7280103614676172,\n",
      "where the function's values are -0.3173 and -0.01849 respectively.\n",
      "The new approximation is 0.7280103614676172, with estimated error 0.1877, backward error 0.01849\n",
      "\n",
      "Iteration 2:\n",
      "The latest pair of approximations are 0.7280103614676172 and 0.7396270126307336,\n",
      "where the function's values are -0.01849 and 0.000907 respectively.\n",
      "The new approximation is 0.7396270126307336, with estimated error 0.01162, backward error 0.000907\n",
      "\n",
      "Iteration 3:\n",
      "The latest pair of approximations are 0.7396270126307336 and 0.7390838007832722,\n",
      "where the function's values are 0.000907 and -2.23e-06 respectively.\n",
      "The new approximation is 0.7390838007832722, with estimated error 0.0005432, backward error 2.23e-06\n",
      "\n",
      "Iteration 4:\n",
      "The latest pair of approximations are 0.7390838007832722 and 0.7390851330557805,\n",
      "where the function's values are -2.23e-06 and -2.667e-10 respectively.\n",
      "The new approximation is 0.7390851330557805, with estimated error 1.332e-06, backward error 2.667e-10\n",
      "\n",
      "Iteration 5:\n",
      "The latest pair of approximations are 0.7390851330557805 and 0.7390851332151607,\n",
      "where the function's values are -2.667e-10 and 0.0 respectively.\n",
      "The new approximation is 0.7390851332151607, with estimated error 1.594e-10, backward error 0.0\n",
      "\n",
      "Iteration 6:\n",
      "The latest pair of approximations are 0.7390851332151607 and 0.7390851332151607,\n",
      "where the function's values are 0.0 and 0.0 respectively.\n",
      "The new approximation is 0.7390851332151607, with estimated error 0.0, backward error 0.0\n",
      "\n",
      "The Secant Method gave approximate root is 0.7390851332151607,\n",
      "with estimated error 0.0, backward error 0.0\n"
     ]
    }
   ],
   "source": [
    "(root, errorEstimate) = secant_method(f, a=-1, b=1, demoMode=True)\n",
    "print(f\"\\nThe Secant Method gave approximate root is {root},\")\n",
    "print(f\"with estimated error {errorEstimate:0.4}, backward error {abs(f(root)):0.4}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def graph_secant_method(f, a, b, maxIterations=5):\n",
    "    \"\"\"Graph a few iterations of the Secant Method for solving f(x)=0 in the interval [a, b].\n",
    "    \"\"\"\n",
    "    x_older = a\n",
    "    x_more_recent = b\n",
    "    f_x_older = f(x_older)\n",
    "    f_x_more_recent = f(x_more_recent)\n",
    "    for iteration in range(maxIterations):\n",
    "        x_new = (x_older * f_x_more_recent - f_x_older * x_more_recent)/(f_x_more_recent - f_x_older)\n",
    "        f_x_new = f(x_new)\n",
    "        latest_three_x_values = [x_older, x_more_recent, x_new]\n",
    "        left = np.min(latest_three_x_values)\n",
    "        right = np.max(latest_three_x_values)\n",
    "        x = linspace(left, right)\n",
    "        figure(figsize=[16,6])\n",
    "        title(f\"Iteration {iteration+1}, Secant Method\")\n",
    "        xlabel(\"$x$\")\n",
    "        plot(x, f(x))\n",
    "        plot([left, right], [f(left), f(right)])  # the secant line\n",
    "        plot([left, right], [0, 0], 'k')  # the x-axis line\n",
    "        plot(latest_three_x_values, f(latest_three_x_values), 'r*')\n",
    "        show()  # The Windows version of JupytLab might need this command; it is harmless anyway.\n",
    "        (x_older, x_more_recent) = (x_more_recent, x_new)\n",
    "        (f_x_older, f_x_more_recent) = (f_x_more_recent, f_x_new)\n",
    "        errorEstimate = abs(x_older - x_more_recent)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph_secant_method(f, a=-1, b=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observations\n",
    "\n",
    "- This converges faster than the [Method of False Position](#method-of-false-position) (and far faster than Bisection).\n",
    "- The majority of iterations do have the root surrounded (sign-change in $f$), but every third one — the second and fifth — do not.\n",
    "- Comparing the error estimate to the backward error, the error estmte is in fact quite pessimistic (and so fairly trustworthy); in fact, it is typically of similar size to the backward error at the previous iteration.\n",
    "\n",
    "The last point is a quite common occurence: the available error estimates are often \"trailing indicators\",\n",
    "closer to the error in the previous approximation in an iteration.\n",
    "For example, recall that we saw the same thing with Newton's Method when we used $|x_k - x_{k-1}|$ to estimate the error $E_k := x_k - r$ and saw that it is in fact closer to the previous error, $E_{k-1}$."
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    "---\n",
    "This work is licensed under [Creative Commons Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/)"
   ]
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