200 lines
5.8 KiB
Org Mode
200 lines
5.8 KiB
Org Mode
#+TITLE: Homework 6
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#+AUTHOR: Elizabeth Hunt
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#+LATEX_HEADER: \notindent \notag \usepackage{amsmath} \usepackage[a4paper,margin=1in,portrait]{geometry}
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#+LATEX: \setlength\parindent{0pt}
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#+OPTIONS: toc:nil
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* Question One
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For $g(x) = x + f(x)$ then we know $g'(x) = 1 + 2x - 5$ and thus $|g'(x)| \lt 1$ is only true
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on the interval $(1.5, 2.5)$, and for $g(x) = x - f(x)$ then we know $g'(x) = 1 - (2x - 5)$
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and thus $|g'(x)| < 1$ is only true on the interval $(2.5, 3.5)$.
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Because we know the roots of $f$ are $2, 3$ ($f(x) = (x-2)(x-3)$) then we can only be
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certain that $g(x) = x + f(x)$ will converge to the root $2$ if we pick an initial
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guess between $(1.5, 2.5)$, and likewise for $g(x) = x - f(x)$, $3$:
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#+BEGIN_SRC c
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// tests/roots.t.c
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UTEST(root, fixed_point_iteration_method) {
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// x^2 - 5x + 6 = (x - 3)(x - 2)
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double expect_x1 = 3.0;
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double expect_x2 = 2.0;
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double tolerance = 0.001;
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uint64_t max_iterations = 10;
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double x_0 = 1.55; // 1.5 < 1.55 < 2.5
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// g1(x) = x + f(x)
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double root1 =
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fixed_point_iteration_method(&f2, &g1, x_0, tolerance, max_iterations);
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EXPECT_NEAR(root1, expect_x2, tolerance);
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// g2(x) = x - f(x)
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x_0 = 3.4; // 2.5 < 3.4 < 3.5
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double root2 =
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fixed_point_iteration_method(&f2, &g2, x_0, tolerance, max_iterations);
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EXPECT_NEAR(root2, expect_x1, tolerance);
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}
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#+END_SRC
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And by this method passing in ~tests/roots.t.c~ we know they converged within ~tolerance~ before
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10 iterations.
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* Question Two
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Yes, we showed that for $\epsilon = 1$ in Question One, we can converge upon a root in the range $(2.5, 3.5)$, and
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when $\epsilon = -1$ we can converge upon a root in the range $(1.5, 2.5)$.
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See the above unit tests in Question One for each $\epsilon$.
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* Question Three
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See ~test/roots.t.c -> UTEST(root, bisection_with_error_assumption)~
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and the software manual entry ~bisect_find_root_with_error_assumption~.
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* Question Four
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See ~test/roots.t.c -> UTEST(root, fixed_point_newton_method)~
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and the software manual entry ~fixed_point_newton_method~.
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* Question Five
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See ~test/roots.t.c -> UTEST(root, fixed_point_secant_method)~
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and the software manual entry ~fixed_point_secant_method~.
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* Question Six
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See ~test/roots.t.c -> UTEST(root, fixed_point_bisection_secant_method)~
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and the software manual entry ~fixed_point_bisection_secant_method~.
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* Question Seven
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The existance of ~test/roots.t.c~'s compilation into ~dist/lizfcm.test~ via ~make~
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shows that the compiled ~lizfcm.a~ contains the root methods mentioned; a user
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could link the library and use them, as we do in Question Eight.
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* Question Eight
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The given ODE $\frac{dP}{dt} = \alpha P - \beta P$ has a trivial solution by separation:
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\begin{equation*}
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P(t) = C e^{t(\alpha - \beta)}
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\end{equation*}
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And
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\begin{equation*}
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P_0 = P(0) = C e^0 = C
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\end{equation*}
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So $P(t) = P_0 e^{t(\alpha - \beta)}$.
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We're trying to find $t$ such that $P(t) = P_\infty$, thus we're finding roots of $P(t) - P_\infty$.
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The following code (in ~homeworks/hw_6_p_8.c~) produces this output:
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\begin{verbatim}
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$ gcc -I../inc/ -Wall hw_6_p_8.c ../lib/lizfcm.a -lm -o hw_6_p_8 && ./hw_6_p_8
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a ~ 27.269515; P(27.269515) - P_infty = -0.000000
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b ~ 40.957816; P(40.957816) - P_infty = -0.000000
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c ~ 40.588827; P(40.588827) - P_infty = -0.000000
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d ~ 483.611967; P(483.611967) - P_infty = -0.000000
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e ~ 4.894274; P(4.894274) - P_infty = -0.000000
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\end{verbatim}
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#+BEGIN_SRC c
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// compile & test w/
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// \--> gcc -I../inc/ -Wall hw_6_p_8.c ../lib/lizfcm.a -lm -o hw_6_p_8
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// \--> ./hw_6_p_8
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#include "lizfcm.h"
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#include <math.h>
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#include <stdio.h>
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double a(double t) {
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double alpha = 0.1;
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double beta = 0.001;
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double p_0 = 2;
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double p_infty = 29.75;
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return p_0 * exp(t * (alpha - beta)) - p_infty;
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}
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double b(double t) {
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double alpha = 0.1;
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double beta = 0.001;
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double p_0 = 2;
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double p_infty = 115.35;
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return p_0 * exp(t * (alpha - beta)) - p_infty;
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}
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double c(double t) {
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double alpha = 0.1;
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double beta = 0.0001;
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double p_0 = 2;
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double p_infty = 115.35;
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return p_0 * exp(t * (alpha - beta)) - p_infty;
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}
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double d(double t) {
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double alpha = 0.01;
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double beta = 0.001;
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double p_0 = 2;
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double p_infty = 155.346;
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return p_0 * exp(t * (alpha - beta)) - p_infty;
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}
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double e(double t) {
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double alpha = 0.1;
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double beta = 0.01;
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double p_0 = 100;
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double p_infty = 155.346;
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return p_0 * exp(t * (alpha - beta)) - p_infty;
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}
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int main() {
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uint64_t max_iterations = 1000;
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double tolerance = 0.0000001;
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Array_double *ivt_range = find_ivt_range(&a, -5.0, 3.0, 1000);
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double approx_a = fixed_point_secant_bisection_method(
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&a, ivt_range->data[0], ivt_range->data[1], tolerance, max_iterations);
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free_vector(ivt_range);
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ivt_range = find_ivt_range(&b, -5.0, 3.0, 1000);
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double approx_b = fixed_point_secant_bisection_method(
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&b, ivt_range->data[0], ivt_range->data[1], tolerance, max_iterations);
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free_vector(ivt_range);
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ivt_range = find_ivt_range(&c, -5.0, 3.0, 1000);
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double approx_c = fixed_point_secant_bisection_method(
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&c, ivt_range->data[0], ivt_range->data[1], tolerance, max_iterations);
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free_vector(ivt_range);
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ivt_range = find_ivt_range(&d, -5.0, 3.0, 1000);
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double approx_d = fixed_point_secant_bisection_method(
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&d, ivt_range->data[0], ivt_range->data[1], tolerance, max_iterations);
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free_vector(ivt_range);
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ivt_range = find_ivt_range(&e, -5.0, 3.0, 1000);
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double approx_e = fixed_point_secant_bisection_method(
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&e, ivt_range->data[0], ivt_range->data[1], tolerance, max_iterations);
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printf("a ~ %f; P(%f) = %f\n", approx_a, approx_a, a(approx_a));
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printf("b ~ %f; P(%f) = %f\n", approx_b, approx_b, b(approx_b));
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printf("c ~ %f; P(%f) = %f\n", approx_c, approx_c, c(approx_c));
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printf("d ~ %f; P(%f) = %f\n", approx_d, approx_d, d(approx_d));
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printf("e ~ %f; P(%f) = %f\n", approx_e, approx_e, e(approx_e));
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return 0;
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}
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#+END_SRC
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