diff --git a/HW2/README.md b/HW2/README.md
deleted file mode 100644
index f74173b..0000000
--- a/HW2/README.md
+++ /dev/null
@@ -1,36 +0,0 @@
-# Homework #2
-## due 2/3/17
-
-1. Now that you have created your own repository, 'homework_1', that has a README.md file.
-Create a new file in this repository called `setdefaults.m`. This file is a matlab/octave
-script that will set default plotting parameters. In this file, add the following lines:
-
- ```matlab
- set(0, 'defaultAxesFontSize', 16)
- set(0,'defaultTextFontSize',14)
- set(0,'defaultLineLineWidth',3)
- ```
-
- Commit the changes to your repository.
-
- ![projectile(v_mag,theta) predicts the height of the projectile based upon initial
-velocity and position, as see in the Figure](projectile.png)
-
-2. Clone your 'homework_1' repository to your own computer. Now, we want to create a
-function that uses kinematic formulas to predict the path of a projectile. The dimensions
-are taken from official dart board dimensions
-[darts](http://dartbrokers.com/dartboard-height.html). Create a function,
-`projectile.m` that will calculate the location of an object with an initial velocity. The
-function inputs are v_mag (initial speed), theta (initial angle). The output is the height
-of the object 2.37 m from its starting position. Assume g=9.81 m/s^2 and its initial
-height is 1.72 m.
-
- ```matlab
- >> h=projectile(v_mag,theta)
-
- h= 1
- ```
-
- In addition to the output of `h`-height at 2.37 m-plot the path of the object from its
- initial position to its position at 2.37 m away from the start. *Note: use your
- `setdefaults.m` to set the plot defaults before outputting the result.*
diff --git a/HW2/projectile.png b/HW2/projectile.png
deleted file mode 100644
index f544224..0000000
Binary files a/HW2/projectile.png and /dev/null differ
diff --git a/HW2/projectile.svg b/HW2/projectile.svg
deleted file mode 100644
index dc73374..0000000
--- a/HW2/projectile.svg
+++ /dev/null
@@ -1,334 +0,0 @@
-
-
-
-
diff --git a/README.md b/README.md
index 8059993..ca1565e 100644
--- a/README.md
+++ b/README.md
@@ -22,21 +22,14 @@ matlab/octave functions and programming best practices.
**Office hours**: Mon 2:30-4:30pm and Thur 11am-1pm in Engineering II room 315
## Teaching Assistants:
-- Graduate: Peiyu Zhang
-- Office hours: Friday 9:00-11:00am in Engineering II room 315
+- Graduate: **TBD**
+- Office hours: 2 hours / week in office **TBD**
-## Course Information
**Prerequisite:** CE 3110, MATH 2410Q
**Textbook:** Chapra, Steven, *Applied Numerical Methods with MATLAB for Engineers and
Scientists* 3rd edition.
-**Tools used:** [Matlab](https://www.mathworks.com/products/matlab.html),
-[Octave](https://www.gnu.org/software/octave/) , [Github](https://github.com).
-
-**Recommended tools:** Github Desktop, git, Atom (text editor), Vim (text editor),
-Jupiter notebook (with matlab or octave kernel)
-
## Grading
| Item | Percent | Requirement |
diff --git a/lecture_03/file.txt b/lecture_03/file.txt
deleted file mode 100644
index 0fb2c92..0000000
--- a/lecture_03/file.txt
+++ /dev/null
@@ -1,5 +0,0 @@
-computational mechanics
-the dog had 4 legs and weighed 10.0 lbs
-are you awake?computational mechanics
-the dog had 4 legs and weighed 10.0 lbs
-are you awake?
\ No newline at end of file
diff --git a/lecture_03/lecture_03.ipynb b/lecture_03/lecture_03.ipynb
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--- a/lecture_03/lecture_03.ipynb
+++ /dev/null
@@ -1,6077 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Matlab basic use\n",
- "## 1- the environment, path and working directory"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Matlab environment can be called by:\n",
- "1. Starting the matlab executable (the gui)\n",
- "2. Starting a jupyter notebook with Matlab kernel\n",
- "3. Starting matlab with command-line interface (no gui)\n",
- "\n",
- "The main requirement is that matlab kernel (main matlab program) is running and accepting commands\n",
- "\n",
- "When you start, you can call matlab built-in functions or anything you write that is in your `MATLABPATH` or working directory (`pwd`)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "MATLABPATH\n",
- "\n",
- "\t/usr/local/lib/python2.7/dist-packages/matlab_kernel/toolbox\n",
- "\t/usr/local/lib/python2.7/dist-packages/pymatbridge/matlab\n",
- "\t/usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/usrprog\n",
- "\t/usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/util\n",
- "\t/usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/util/json_v0.2.2\n",
- "\t/usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/util/json_v0.2.2/json\n",
- "\t/usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/util/json_v0.2.2/json/java\n",
- "\t/usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/util/json_v0.2.2/test\n",
- "\t/home/ryan/Documents/MATLAB\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/strfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/datatypes\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/elfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/ops\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/timefun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/elmat\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/datafun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/iofun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/mvm\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/randfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/funfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/general\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/polyfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/matfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/lang\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/specfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/sparfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/images\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/testframework/performance\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/testframework/parallel\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/optimfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/testframework/ext\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/guide\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/testframework/measurement\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/icons\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/demos\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/helptools\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/winfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/winfun/NET\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/datamanager\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/verctrl\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/graph2d\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/graph3d\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/graphics\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/graphics/obsolete\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/plottools\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/scribe\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/scribe/obsolete\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/specgraph\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/uitools\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/uitools/obsolete\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/hdlcoder/matlabhdlcoder/matlabhdlcoder\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/hdlcoder/matlabhdlcoder\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/testframework/core\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/testframework/obsolete\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/hardware/stubs\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/local\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/datastoreio\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/codetools\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/codetools/embeddedoutputs\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/graphfun\n",
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- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/mapreduceio\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/findfiles\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/rtw/targets/asap2/asap2/dataclasses\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/rtw/targets/asap2/asap2\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/rtw/targets/asap2/asap2/user\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/rtw/targets/common/can/blocks/dataclasses\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/rtw/targets/common/can/blocks\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/rtw/targets/common/can/blocks/tlc_c\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/rtw/targets/common/tgtcommon\n",
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- "\t/usr/local/MATLAB/R2016a/toolbox/rtw/rtwdemos/rsimdemos\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/simfeatures\n",
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- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/sysarch/sysarch\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/simgeneral\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/slde/examples\n",
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- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simulink/modeladvisor\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simulink/modeladvisor/fixpt\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/automotive/fuelsys\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/components\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/dee\n",
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- "\t/usr/local/MATLAB/R2016a/toolbox/simulinktest/core/simharness/simharness\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simulink/frameedit\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/industrial\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/automotive\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/blocks/library\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/blocks/library/simulinkcoder\n",
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- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simdemos\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/blocks\n",
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- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simulink\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/simulink/simulink/MPlayIO\n",
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- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnnetfun\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnnetinput\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnnetwork\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnperformance\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnplot\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnprocess\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnsearch\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nntopology\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nntrain\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nntransfer\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnweight\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnguis\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnobsolete\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/nnet/nnutils\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/matlab/addons_product\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/shared/tracking/trackinglib\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/shared/simulink/sysarch/sysarch\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/shared/slreportgen/reportexplorer\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/coder/embeddedcoder_templates\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/coder/wizard\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/physmod/sm/core/m\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/ros\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/ros/helpers\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotalgs\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotalgs/helpers\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotcore\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotcore/helpers\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotsimulink\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotsimulink/helpers\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/shared/controllib/engine\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/shared/controllib/engine/numerics\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/shared/controllib/engine/options\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/shared/controllib/engine/optim\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/shared/controllib/engine/blocks\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/dsp/filterdesign\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/finance/findemos\n",
- "\t/usr/local/MATLAB/R2016a/toolbox/physmod/powersys/facts/facts\n"
- ]
- }
- ],
- "source": [
- "path"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- "/home/ryan/Documents/UConn/ME3255/me3255_S2017/lecture_03\n"
- ]
- }
- ],
- "source": [
- "pwd"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "\n",
- "path"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Assignments (`=`-operator)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Matlab is interpreted language so each line of code (either saved text file or command-line) is executed as a standalone command\n",
- "\n",
- "These are reffered to \"scripts\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 40\n"
- ]
- }
- ],
- "source": [
- "a=10; % line one assigns a to 10\n",
- "b=a*3; % line two assigns b to 10 times 3 by calling 'a' from line one\n",
- "a+b % line three does not assign anything directly, but leaving off the \";\" prints the result\n",
- " % ans"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Matlab has a number of \"objects\" that you can assign to variables\n",
- "1. arrays (vectors and matrices `[`...`]`) \n",
- "2. strings (text `\"`...`\"` )\n",
- "3. cells (combination of strings, text, even function calls `{`...`}`)\n",
- "3. functions (both built-in, defined or developed)\n",
- "4. and more... (classes defined by `classdef` - you can create your own object to help organize data)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### 1- Arrays"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Default in matlab is that when you assign a value to a variable, it is stored as an array\n",
- "\n",
- "arrays are N x M x ... values of integers or floating point numbers or complex integers/floating point numbers\n",
- "\n",
- "Use the parantheses to access values in an array `...(n,m)`"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 1\n"
- ]
- }
- ],
- "source": [
- "a=10; % a is 1x1 array where a(1,1)==10\n",
- "a(1,1)==10\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\u001b[0;31mIndex exceeds matrix dimensions.\n",
- "\u001b[0m"
- ]
- }
- ],
- "source": [
- "a(2)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "A =\n",
- "\n",
- " 1 2 3\n",
- " 4 5 6\n",
- " 7 8 9\n",
- " 10 11 12\n",
- "\n",
- "size of A is 4 x 3\n",
- "\n",
- "ans =\n",
- "\n",
- " 7\n",
- "\n",
- "\n",
- "ans =\n",
- "\n",
- " 5\n"
- ]
- }
- ],
- "source": [
- "A = [1 2 3;4,5,6;7,8,9;10,11,12]\n",
- "fprintf('size of A is %i x %i\\n',size(A))\n",
- "A(3,1)\n",
- "A(6)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "vectors are either 1xN or Nx1 arrays for row and column"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "v_row =\n",
- "\n",
- " 1 2 3\n",
- "\n",
- "\n",
- "v_column =\n",
- "\n",
- " 1\n",
- " 2\n",
- " 3\n"
- ]
- }
- ],
- "source": [
- "v_row = [1,2,3] %row vector\n",
- "v_column = [1;2;3] %column vector\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Matrices are MxN arrays\n",
- "the `:`-symbol can substitute for a counting"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 1 2 3\n"
- ]
- }
- ],
- "source": [
- "A(1,:) % the colon assumes you want the first value, 1, counting up by 1 to the last value, 4"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "You can also use every 2nd value or any other integer up to `end` which is the largest value of that row or column of the array"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 1\n",
- " 7\n"
- ]
- }
- ],
- "source": [
- "A(1:2:end,1) % you can also use `end` "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 1\n",
- " 4\n",
- " 7\n",
- " 10\n",
- " 2\n",
- " 5\n",
- " 8\n",
- " 11\n",
- " 3\n",
- " 6\n",
- " 9\n",
- " 12\n"
- ]
- }
- ],
- "source": [
- "A(:)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "In general, arrays can be any size \n",
- "\n",
- "take rolling 4 die and determining the sum of the components"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "A_6666 = zeros(6,6,6,6); %make a 6 x 6 x 6 x 6 array (1296 different values)\n",
- "for i=1:6\n",
- " for j=1:6\n",
- " for k=1:6\n",
- " for l=1:6\n",
- " A_6666(i,j,k,l)=i+j+k+l; % each value is the sum of the indices\n",
- " end\n",
- " end\n",
- " end\n",
- "end\n",
- " "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 14\n",
- "\n",
- "\n",
- "ans =\n",
- "\n",
- " 3.4170\n"
- ]
- }
- ],
- "source": [
- "mean(A_6666(:))\n",
- "std(A_6666(:))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 12\n"
- ]
- }
- ],
- "source": [
- "A_6666(1,4,2,5)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Cells combine different size arrays and text\n",
- "### but, you cannot use math operators 'binary operators'"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "C={};\n",
- "C{1}=linspace(0,1,10);\n",
- "C{2}=linspace(0,1,3);\n",
- "C{'z'}='holy cow';"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 3.5185\n"
- ]
- }
- ],
- "source": [
- "C{1}*C{1}'"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Strings can be combined and printed"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- "computational mechanics\n"
- ]
- }
- ],
- "source": [
- "string1 = 'computational'; string2 = 'mechanics';\n",
- "[string1, ' ', string2]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "use `fprintf` to format strings and numbers for output and `sprintf` to save variables\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 32,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "computational mechanics\n",
- "\n",
- "\n",
- "string =\n",
- "\n",
- "the dog had 4 legs and weighed 10.0 lbs\n"
- ]
- }
- ],
- "source": [
- "fprintf([string1,' ',string2,'\\n\\n'])\n",
- "string = sprintf('the dog had %i legs and weighed %1.1f lbs',4,10.0)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "the `\\` signifies a special character e.g. `\\n` = newline, `\\t` = tab\n",
- "\n",
- "to actually print the \"\\\", use `\\\\`"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 33,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\\\n"
- ]
- }
- ],
- "source": [
- "fprintf('\\\\')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## This is helpful to create reports of computed data"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 36,
- "metadata": {
- "collapsed": false,
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 23\n",
- "\n",
- "\n",
- "ans =\n",
- "\n",
- " 1\n",
- "\n",
- "\n",
- "ans =\n",
- "\n",
- " 39\n",
- "\n",
- "\n",
- "ans =\n",
- "\n",
- " 1\n",
- "\n",
- "\n",
- "ans =\n",
- "\n",
- " 14\n"
- ]
- }
- ],
- "source": [
- "%fid = fopen('file.txt','w');\n",
- "fprintf(fid,[string1, ' ', string2])\n",
- "fprintf(fid,'\\n')\n",
- "fprintf(fid,string)\n",
- "fprintf(fid,'\\n')\n",
- "fprintf(fid,'are you awake?')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Math operators (=, +, -, /, *, ^)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Because matlab assumes all variables are matrices, then all operators are matrix operations"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans = 20\r\n"
- ]
- }
- ],
- "source": [
- "a+a % add two 1x1 arrays"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 2 4 6\n",
- " 8 10 12\n",
- " 14 16 18\n",
- " 20 22 24\n",
- "\n"
- ]
- }
- ],
- "source": [
- "A+A % add two 4 x 3 arrays"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 37,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 14 32 50 68\n",
- " 32 77 122 167\n",
- " 50 122 194 266\n",
- " 68 167 266 365\n"
- ]
- }
- ],
- "source": [
- "A*A'"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 39,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 1 4 9\n",
- " 16 25 36\n",
- " 49 64 81\n",
- " 100 121 144\n"
- ]
- }
- ],
- "source": [
- "A.^2"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 40,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 1 4 9\n",
- " 16 25 36\n",
- " 49 64 81\n",
- " 100 121 144\n"
- ]
- }
- ],
- "source": [
- "A.*A"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 44,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "[\b> In pymat_eval (line 31)\n",
- " In matlabserver (line 24)]\b \n",
- "[\bWarning: Rank deficient, rank = 2, tol = 1.696862e-14.]\b \n",
- "\n",
- "ans =\n",
- "\n",
- " 1.0000 0 0 -0.0000\n",
- " 0.6667 0 0 0.3333\n",
- " 0.3333 0 0 0.6667\n",
- " 0.0000 0 0 1.0000\n"
- ]
- }
- ],
- "source": [
- "A/A"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 45,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "/ Slash or right matrix divide.\n",
- " A/B is the matrix division of B into A, which is roughly the\n",
- " same as A*INV(B) , except it is computed in a different way.\n",
- " More precisely, A/B = (B'\\A')'. See MLDIVIDE for details.\n",
- " \n",
- " C = MRDIVIDE(A,B) is called for the syntax 'A / B' when A or B is an\n",
- " object.\n",
- " \n",
- " See also MLDIVIDE, RDIVIDE, LDIVIDE.\n",
- "\n",
- " Reference page in Doc Center\n",
- " doc mrdivide\n",
- "\n",
- " Other functions named mrdivide\n",
- "\n",
- " codistributed/mrdivide gf/mrdivide laurpoly/mrdivide\n",
- " duration/mrdivide gpuArray/mrdivide StaticModel/mrdivide\n",
- " DynamicSystem/mrdivide LagOp/mrdivide timeseries/mrdivide\n",
- " fints/mrdivide\n"
- ]
- }
- ],
- "source": [
- "help /"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "To accomplish one-by-one operations, need to include a `.`"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 1 1 1\n",
- " 1 1 1\n",
- " 1 1 1\n",
- " 1 1 1\n",
- "\n"
- ]
- }
- ],
- "source": [
- "A./A"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "But, for 1x1 arrays, these are considered scalars and you get a free-pass"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 10 20 30\n",
- " 40 50 60\n",
- " 70 80 90\n",
- " 100 110 120\n",
- "\n"
- ]
- }
- ],
- "source": [
- "a*A % where a=10 and A is 1:12 in a 3 x 4 matrix"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Some built in Matlab functions (e.g. the reasons to run Matlab)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 49,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "t_linear =\n",
- "\n",
- " Columns 1 through 7\n",
- "\n",
- " 0 0.1000 0.2000 0.3000 0.4000 0.5000 0.6000\n",
- "\n",
- " Columns 8 through 11\n",
- "\n",
- " 0.7000 0.8000 0.9000 1.0000\n"
- ]
- }
- ],
- "source": [
- "t_linear=linspace(0,1,11)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 46,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "t_log =\n",
- "\n",
- " 1 10 100\n"
- ]
- }
- ],
- "source": [
- "t_log = logspace(0,2,3) % log interval from 10^0 to 10^2 split into 3 values"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "'logspace' is a function from the file /usr/share/octave/4.0.0/m/general/logspace.m\n",
- "\n",
- " -- Function File: logspace (A, B)\n",
- " -- Function File: logspace (A, B, N)\n",
- " -- Function File: logspace (A, pi, N)\n",
- " Return a row vector with N elements logarithmically spaced from\n",
- " 10^A to 10^B.\n",
- "\n",
- " If N is unspecified it defaults to 50.\n",
- "\n",
- " If B is equal to pi, the points are between 10^A and pi, _not_ 10^A\n",
- " and 10^pi, in order to be compatible with the corresponding MATLAB\n",
- " function.\n",
- "\n",
- " Also for compatibility with MATLAB, return the second argument B if\n",
- " fewer than two values are requested.\n",
- "\n",
- " See also: linspace.\n",
- "\n",
- "Additional help for built-in functions and operators is\n",
- "available in the online version of the manual. Use the command\n",
- "'doc ' to search the manual index.\n",
- "\n",
- "Help and information about Octave is also available on the WWW\n",
- "at http://www.octave.org and via the help@octave.org\n",
- "mailing list.\n"
- ]
- }
- ],
- "source": [
- "help logspace"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## When using the command prompt, anything in your path or working directory can be run either as a script, function or class (to define objects)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "%myscript"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 31,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "%plot --format svg"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "When using the GUI, your command history is saved, but it is better to save your work either as a script or a function or combination of both\n",
- "\n",
- "Creating a default graph script:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 50,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "set(0, 'defaultAxesFontSize', 16)\n",
- "set(0,'defaultTextFontSize',14)\n",
- "set(0,'defaultLineLineWidth',3)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 51,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
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IsrIy41QFAGB+mMzbxFi8GCsSiWJjYwkhfn5+hYWFpaWlUVFR9vb27u7uGsfd8Xi88+fP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\ncAICCQAAOAGBBAAAnPD/AHltgbQ+BHrdAAAAAElFTkSuQmCC\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot(t_linear,t_linear.^2)\n",
- "xlabel('time (s)')\n",
- "ylabel('displacement (m)')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "#EOL"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Graphics can be produced with a number of functions"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "2-D plots, 3-D plots, contour plots, 3D contour plots ... "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 57,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Z =\n",
- "\n",
- " Columns 1 through 8:\n",
- "\n",
- " 0.00000 0.17100 0.28800 0.35700 0.38400 0.37500 0.33600 0.27300\n",
- " -0.17100 0.00000 0.12240 0.20160 0.24300 0.25200 0.23400 0.19440\n",
- " -0.28800 -0.12240 0.00000 0.08400 0.13440 0.15600 0.15360 0.13200\n",
- " -0.35700 -0.20160 -0.08400 0.00000 0.05460 0.08400 0.09240 0.08400\n",
- " -0.38400 -0.24300 -0.13440 -0.05460 0.00000 0.03300 0.04800 0.04860\n",
- " -0.37500 -0.25200 -0.15600 -0.08400 -0.03300 0.00000 0.01800 0.02400\n",
- " -0.33600 -0.23400 -0.15360 -0.09240 -0.04800 -0.01800 0.00000 0.00840\n",
- " -0.27300 -0.19440 -0.13200 -0.08400 -0.04860 -0.02400 -0.00840 0.00000\n",
- " -0.19200 -0.13860 -0.09600 -0.06300 -0.03840 -0.02100 -0.00960 -0.00300\n",
- " -0.09900 -0.07200 -0.05040 -0.03360 -0.02100 -0.01200 -0.00600 -0.00240\n",
- " 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000\n",
- " 0.09900 0.07200 0.05040 0.03360 0.02100 0.01200 0.00600 0.00240\n",
- " 0.19200 0.13860 0.09600 0.06300 0.03840 0.02100 0.00960 0.00300\n",
- " 0.27300 0.19440 0.13200 0.08400 0.04860 0.02400 0.00840 -0.00000\n",
- " 0.33600 0.23400 0.15360 0.09240 0.04800 0.01800 -0.00000 -0.00840\n",
- " 0.37500 0.25200 0.15600 0.08400 0.03300 0.00000 -0.01800 -0.02400\n",
- " 0.38400 0.24300 0.13440 0.05460 -0.00000 -0.03300 -0.04800 -0.04860\n",
- " 0.35700 0.20160 0.08400 -0.00000 -0.05460 -0.08400 -0.09240 -0.08400\n",
- " 0.28800 0.12240 0.00000 -0.08400 -0.13440 -0.15600 -0.15360 -0.13200\n",
- " 0.17100 -0.00000 -0.12240 -0.20160 -0.24300 -0.25200 -0.23400 -0.19440\n",
- " 0.00000 -0.17100 -0.28800 -0.35700 -0.38400 -0.37500 -0.33600 -0.27300\n",
- "\n",
- " Columns 9 through 16:\n",
- "\n",
- " 0.19200 0.09900 0.00000 -0.09900 -0.19200 -0.27300 -0.33600 -0.37500\n",
- " 0.13860 0.07200 0.00000 -0.07200 -0.13860 -0.19440 -0.23400 -0.25200\n",
- " 0.09600 0.05040 0.00000 -0.05040 -0.09600 -0.13200 -0.15360 -0.15600\n",
- " 0.06300 0.03360 0.00000 -0.03360 -0.06300 -0.08400 -0.09240 -0.08400\n",
- " 0.03840 0.02100 0.00000 -0.02100 -0.03840 -0.04860 -0.04800 -0.03300\n",
- " 0.02100 0.01200 0.00000 -0.01200 -0.02100 -0.02400 -0.01800 0.00000\n",
- " 0.00960 0.00600 0.00000 -0.00600 -0.00960 -0.00840 0.00000 0.01800\n",
- " 0.00300 0.00240 0.00000 -0.00240 -0.00300 0.00000 0.00840 0.02400\n",
- " 0.00000 0.00060 0.00000 -0.00060 0.00000 0.00300 0.00960 0.02100\n",
- " -0.00060 0.00000 0.00000 0.00000 0.00060 0.00240 0.00600 0.01200\n",
- " 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000\n",
- " 0.00060 -0.00000 0.00000 0.00000 -0.00060 -0.00240 -0.00600 -0.01200\n",
- " -0.00000 -0.00060 0.00000 0.00060 0.00000 -0.00300 -0.00960 -0.02100\n",
- " -0.00300 -0.00240 0.00000 0.00240 0.00300 0.00000 -0.00840 -0.02400\n",
- " -0.00960 -0.00600 0.00000 0.00600 0.00960 0.00840 0.00000 -0.01800\n",
- " -0.02100 -0.01200 0.00000 0.01200 0.02100 0.02400 0.01800 0.00000\n",
- " -0.03840 -0.02100 0.00000 0.02100 0.03840 0.04860 0.04800 0.03300\n",
- " -0.06300 -0.03360 0.00000 0.03360 0.06300 0.08400 0.09240 0.08400\n",
- " -0.09600 -0.05040 0.00000 0.05040 0.09600 0.13200 0.15360 0.15600\n",
- " -0.13860 -0.07200 0.00000 0.07200 0.13860 0.19440 0.23400 0.25200\n",
- " -0.19200 -0.09900 0.00000 0.09900 0.19200 0.27300 0.33600 0.37500\n",
- "\n",
- " Columns 17 through 21:\n",
- "\n",
- " -0.38400 -0.35700 -0.28800 -0.17100 0.00000\n",
- " -0.24300 -0.20160 -0.12240 0.00000 0.17100\n",
- " -0.13440 -0.08400 0.00000 0.12240 0.28800\n",
- " -0.05460 0.00000 0.08400 0.20160 0.35700\n",
- " 0.00000 0.05460 0.13440 0.24300 0.38400\n",
- " 0.03300 0.08400 0.15600 0.25200 0.37500\n",
- " 0.04800 0.09240 0.15360 0.23400 0.33600\n",
- " 0.04860 0.08400 0.13200 0.19440 0.27300\n",
- " 0.03840 0.06300 0.09600 0.13860 0.19200\n",
- " 0.02100 0.03360 0.05040 0.07200 0.09900\n",
- " 0.00000 0.00000 0.00000 0.00000 0.00000\n",
- " -0.02100 -0.03360 -0.05040 -0.07200 -0.09900\n",
- " -0.03840 -0.06300 -0.09600 -0.13860 -0.19200\n",
- " -0.04860 -0.08400 -0.13200 -0.19440 -0.27300\n",
- " -0.04800 -0.09240 -0.15360 -0.23400 -0.33600\n",
- " -0.03300 -0.08400 -0.15600 -0.25200 -0.37500\n",
- " 0.00000 -0.05460 -0.13440 -0.24300 -0.38400\n",
- " 0.05460 0.00000 -0.08400 -0.20160 -0.35700\n",
- " 0.13440 0.08400 0.00000 -0.12240 -0.28800\n",
- " 0.24300 0.20160 0.12240 0.00000 -0.17100\n",
- " 0.38400 0.35700 0.28800 0.17100 0.00000\n",
- "\n"
- ]
- }
- ],
- "source": [
- "x=linspace(-1,1,21); y=linspace(-1,1,21);\n",
- "[X,Y]=meshgrid(x,y);\n",
- "Z=(X.*Y.^3-X.^3.*Y)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 58,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/svg+xml": [
- ""
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "contour(X,Y,Z)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 59,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/svg+xml": [
- ""
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "mesh(X,Y,Z)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 60,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/svg+xml": [
- ""
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "pcolor(X,Y,Z)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## "
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Matlab",
- "language": "matlab",
- "name": "matlab"
- },
- "language_info": {
- "codemirror_mode": "octave",
- "file_extension": ".m",
- "help_links": [
- {
- "text": "MetaKernel Magics",
- "url": "https://github.com/calysto/metakernel/blob/master/metakernel/magics/README.md"
- }
- ],
- "mimetype": "text/x-octave",
- "name": "matlab",
- "version": "0.11.0"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/lecture_03/lecture_03.md b/lecture_03/lecture_03.md
deleted file mode 100644
index ce76e7f..0000000
--- a/lecture_03/lecture_03.md
+++ /dev/null
@@ -1,1447 +0,0 @@
-
-# Matlab basic use
-## 1- the environment, path and working directory
-
-Matlab environment can be called by:
-1. Starting the matlab executable (the gui)
-2. Starting a jupyter notebook with Matlab kernel
-3. Starting matlab with command-line interface (no gui)
-
-The main requirement is that matlab kernel (main matlab program) is running and accepting commands
-
-When you start, you can call matlab built-in functions or anything you write that is in your `MATLABPATH` or working directory (`pwd`)
-
-
-```matlab
-path
-```
-
- MATLABPATH
-
- /usr/local/lib/python2.7/dist-packages/matlab_kernel/toolbox
- /usr/local/lib/python2.7/dist-packages/pymatbridge/matlab
- /usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/usrprog
- /usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/util
- /usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/util/json_v0.2.2
- /usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/util/json_v0.2.2/json
- /usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/util/json_v0.2.2/json/java
- /usr/local/lib/python2.7/dist-packages/pymatbridge/matlab/util/json_v0.2.2/test
- /home/ryan/Documents/MATLAB
- /usr/local/MATLAB/R2016a/toolbox/matlab/strfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/datatypes
- /usr/local/MATLAB/R2016a/toolbox/matlab/elfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/ops
- /usr/local/MATLAB/R2016a/toolbox/matlab/timefun
- /usr/local/MATLAB/R2016a/toolbox/matlab/elmat
- /usr/local/MATLAB/R2016a/toolbox/matlab/datafun
- /usr/local/MATLAB/R2016a/toolbox/matlab/iofun
- /usr/local/MATLAB/R2016a/toolbox/matlab/mvm
- /usr/local/MATLAB/R2016a/toolbox/matlab/randfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/funfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/general
- /usr/local/MATLAB/R2016a/toolbox/matlab/polyfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/matfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/lang
- /usr/local/MATLAB/R2016a/toolbox/matlab/specfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/sparfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/images
- /usr/local/MATLAB/R2016a/toolbox/matlab/testframework/performance
- /usr/local/MATLAB/R2016a/toolbox/matlab/testframework/parallel
- /usr/local/MATLAB/R2016a/toolbox/matlab/optimfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/testframework/ext
- /usr/local/MATLAB/R2016a/toolbox/matlab/guide
- /usr/local/MATLAB/R2016a/toolbox/matlab/testframework/measurement
- /usr/local/MATLAB/R2016a/toolbox/matlab/icons
- /usr/local/MATLAB/R2016a/toolbox/matlab/demos
- /usr/local/MATLAB/R2016a/toolbox/matlab/helptools
- /usr/local/MATLAB/R2016a/toolbox/matlab/winfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/winfun/NET
- /usr/local/MATLAB/R2016a/toolbox/matlab/datamanager
- /usr/local/MATLAB/R2016a/toolbox/matlab/verctrl
- /usr/local/MATLAB/R2016a/toolbox/matlab/graph2d
- /usr/local/MATLAB/R2016a/toolbox/matlab/graph3d
- /usr/local/MATLAB/R2016a/toolbox/matlab/graphics
- /usr/local/MATLAB/R2016a/toolbox/matlab/graphics/obsolete
- /usr/local/MATLAB/R2016a/toolbox/matlab/plottools
- /usr/local/MATLAB/R2016a/toolbox/matlab/scribe
- /usr/local/MATLAB/R2016a/toolbox/matlab/scribe/obsolete
- /usr/local/MATLAB/R2016a/toolbox/matlab/specgraph
- /usr/local/MATLAB/R2016a/toolbox/matlab/uitools
- /usr/local/MATLAB/R2016a/toolbox/matlab/uitools/obsolete
- /usr/local/MATLAB/R2016a/toolbox/hdlcoder/matlabhdlcoder/matlabhdlcoder
- /usr/local/MATLAB/R2016a/toolbox/hdlcoder/matlabhdlcoder
- /usr/local/MATLAB/R2016a/toolbox/matlab/testframework/core
- /usr/local/MATLAB/R2016a/toolbox/matlab/testframework/obsolete
- /usr/local/MATLAB/R2016a/toolbox/matlab/hardware/stubs
- /usr/local/MATLAB/R2016a/toolbox/local
- /usr/local/MATLAB/R2016a/toolbox/matlab/datastoreio
- /usr/local/MATLAB/R2016a/toolbox/matlab/codetools
- /usr/local/MATLAB/R2016a/toolbox/matlab/codetools/embeddedoutputs
- /usr/local/MATLAB/R2016a/toolbox/matlab/graphfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/depfun
- /usr/local/MATLAB/R2016a/toolbox/matlab/mapreduceio
- /usr/local/MATLAB/R2016a/toolbox/matlab/findfiles
- /usr/local/MATLAB/R2016a/toolbox/rtw/targets/asap2/asap2/dataclasses
- /usr/local/MATLAB/R2016a/toolbox/rtw/targets/asap2/asap2
- /usr/local/MATLAB/R2016a/toolbox/rtw/targets/asap2/asap2/user
- /usr/local/MATLAB/R2016a/toolbox/rtw/targets/common/can/blocks/dataclasses
- /usr/local/MATLAB/R2016a/toolbox/rtw/targets/common/can/blocks
- /usr/local/MATLAB/R2016a/toolbox/rtw/targets/common/can/blocks/tlc_c
- /usr/local/MATLAB/R2016a/toolbox/rtw/targets/common/tgtcommon
- /usr/local/MATLAB/R2016a/toolbox/coder/simulinkcoder/cgv/API
- /usr/local/MATLAB/R2016a/toolbox/rtw/rtw/misra
- /usr/local/MATLAB/R2016a/toolbox/coder/simulinkcoder
- /usr/local/MATLAB/R2016a/toolbox/coder/simulinkcoder/templates
- /usr/local/MATLAB/R2016a/toolbox/coder/simulinkcoder/targets
- /usr/local/MATLAB/R2016a/toolbox/rtw/targets/pil
- /usr/local/MATLAB/R2016a/toolbox/rtw/targets/AUTOSAR/AUTOSAR/dataclasses
- /usr/local/MATLAB/R2016a/toolbox/rtw/targets/AUTOSAR/AUTOSAR
- /usr/local/MATLAB/R2016a/toolbox/rtw/accel
- /usr/local/MATLAB/R2016a/toolbox/coder/simulinkcoder_core
- /usr/local/MATLAB/R2016a/toolbox/rtw/rtwdemos
- /usr/local/MATLAB/R2016a/toolbox/rtw/rtwdemos/rsimdemos
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/simfeatures
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/simfeatures/modelreference
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/simfeatures/datadictionary
- /usr/local/MATLAB/R2016a/toolbox/simulink/sysarch/sysarch
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/simgeneral
- /usr/local/MATLAB/R2016a/toolbox/slde/examples
- /usr/local/MATLAB/R2016a/toolbox/coder/advisor
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink/modeladvisor
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink/modeladvisor/fixpt
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/automotive/fuelsys
- /usr/local/MATLAB/R2016a/toolbox/simulink/components
- /usr/local/MATLAB/R2016a/toolbox/simulink/dee
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/aerospace
- /usr/local/MATLAB/R2016a/toolbox/simulinktest/core/simharness/simharness
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink/frameedit
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/industrial
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/automotive
- /usr/local/MATLAB/R2016a/toolbox/simulink/blocks/library
- /usr/local/MATLAB/R2016a/toolbox/simulink/blocks/library/simulinkcoder
- /usr/local/MATLAB/R2016a/toolbox/simulink/blocks/obsolete
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/dataclasses
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos
- /usr/local/MATLAB/R2016a/toolbox/simulink/blocks
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink/dataclasses
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink/MPlayIO
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink/dataobjectwizard
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink/slresolve
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink/units
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink/resources
- /usr/local/MATLAB/R2016a/toolbox/simulink/sdi
- /usr/local/MATLAB/R2016a/toolbox/simulink/simulink/core_templates
- /usr/local/MATLAB/R2016a/toolbox/simulinktest/core/testsequence/testsequence
- /usr/local/MATLAB/R2016a/toolbox/simulink/simdemos/automotive/powerwindow
- /usr/local/MATLAB/R2016a/toolbox/simulink/sldependency
- /usr/local/MATLAB/R2016a/toolbox/simulink/hmi
- /usr/local/MATLAB/R2016a/toolbox/coder/objectives
- /usr/local/MATLAB/R2016a/toolbox/slde/slde
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- /usr/local/MATLAB/R2016a/toolbox/stateflow/stateflow
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- /usr/local/MATLAB/R2016a/toolbox/stateflow/sfdemos
- /usr/local/MATLAB/R2016a/toolbox/stateflow/sftemplates
- /usr/local/MATLAB/R2016a/toolbox/shared/testmeaslib/general
- /usr/local/MATLAB/R2016a/toolbox/simulink/blocks/sb2sl
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- /usr/local/MATLAB/R2016a/toolbox/shared/controllib/graphics/utils
- /usr/local/MATLAB/R2016a/toolbox/shared/controllib/graphics/plotoptions
- /usr/local/MATLAB/R2016a/toolbox/simulink/sledittimecheck
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- /usr/local/MATLAB/R2016a/toolbox/distcomp/cluster
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- /usr/local/MATLAB/R2016a/toolbox/distcomp/array
- /usr/local/MATLAB/R2016a/toolbox/target/codertarget
- /usr/local/MATLAB/R2016a/toolbox/target/codertarget/rtw
- /usr/local/MATLAB/R2016a/toolbox/target/codertarget/matlabcoder
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- /usr/local/MATLAB/R2016a/toolbox/target/extensions/processor/tic5000/tic5000demos
- /usr/local/MATLAB/R2016a/toolbox/physmod/common/gl/sli/m
- /usr/local/MATLAB/R2016a/toolbox/shared/system/simulink
- /usr/local/MATLAB/R2016a/toolbox/images/colorspaces
- /usr/local/MATLAB/R2016a/toolbox/images/images
- /usr/local/MATLAB/R2016a/toolbox/images/imdata
- /usr/local/MATLAB/R2016a/toolbox/images/imuitools
- /usr/local/MATLAB/R2016a/toolbox/images/iptformats
- /usr/local/MATLAB/R2016a/toolbox/images/iptutils
- /usr/local/MATLAB/R2016a/toolbox/target/extensions/processor/tic6000
- /usr/local/MATLAB/R2016a/toolbox/target/extensions/processor/tic6000/rtw
- /usr/local/MATLAB/R2016a/toolbox/target/extensions/processor/tic6000/tfl
- /usr/local/MATLAB/R2016a/toolbox/target/extensions/processor/tic6000/utils
- /usr/local/MATLAB/R2016a/toolbox/target/extensions/processor/tic6000/blks/sysobj_mex
- /usr/local/MATLAB/R2016a/toolbox/target/extensions/processor/tic6000/blks/mex
- /usr/local/MATLAB/R2016a/toolbox/distcomp/pctdemos
- /usr/local/MATLAB/R2016a/toolbox/matlab/appdesigner/appdesigner
- /usr/local/MATLAB/R2016a/toolbox/shared/mlreportgen/ppt
- /usr/local/MATLAB/R2016a/toolbox/shared/mlreportgen/ppt/ppt
- /usr/local/MATLAB/R2016a/toolbox/shared/mlreportgen/ppt/ppt/help
- /usr/local/MATLAB/R2016a/toolbox/coder/matlabcoder
- /usr/local/MATLAB/R2016a/toolbox/coder/matlabcoder/templates
- /usr/local/MATLAB/R2016a/toolbox/dsp/templates
- /usr/local/MATLAB/R2016a/toolbox/globaloptim
- /usr/local/MATLAB/R2016a/toolbox/globaloptim/globaloptim
- /usr/local/MATLAB/R2016a/toolbox/shared/appdes/services
- /usr/local/MATLAB/R2016a/toolbox/coder/emlcodermex
- /usr/local/MATLAB/R2016a/toolbox/physmod/powersys/powerdemo/power_electronics
- /usr/local/MATLAB/R2016a/toolbox/pde/pdedemos
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- /usr/local/MATLAB/R2016a/toolbox/shared/etargets/etargets
- /usr/local/MATLAB/R2016a/toolbox/shared/etargets/etargets/demoutils
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- /usr/local/MATLAB/R2016a/toolbox/robust/rctobsolete/lmi
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- /usr/local/MATLAB/R2016a/toolbox/control/ctrldesign
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- /usr/local/MATLAB/R2016a/toolbox/fixpoint/fpca
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- /usr/local/MATLAB/R2016a/toolbox/shared/hotpluglib
- /usr/local/MATLAB/R2016a/toolbox/shared/multimedia
- /usr/local/MATLAB/R2016a/toolbox/shared/testmeaslib/graphics
- /usr/local/MATLAB/R2016a/toolbox/matlab/addons_toolbox
- /usr/local/MATLAB/R2016a/toolbox/shared/imageslib
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- /usr/local/MATLAB/R2016a/toolbox/ident/ident
- /usr/local/MATLAB/R2016a/toolbox/ident/nlident
- /usr/local/MATLAB/R2016a/toolbox/ident/idobsolete
- /usr/local/MATLAB/R2016a/toolbox/ident/idguis
- /usr/local/MATLAB/R2016a/toolbox/ident/idutils
- /usr/local/MATLAB/R2016a/toolbox/ident/idrecursive
- /usr/local/MATLAB/R2016a/toolbox/ident/idhelp
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- /usr/local/MATLAB/R2016a/toolbox/idelink/foundation/xmakefile
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- /usr/local/MATLAB/R2016a/toolbox/physmod/simscape/compiler/mli/m
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- /usr/local/MATLAB/R2016a/toolbox/physmod/pe/utils/m
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- /usr/local/MATLAB/R2016a/toolbox/coder/foundation
- /usr/local/MATLAB/R2016a/toolbox/coder/foundation/build
- /usr/local/MATLAB/R2016a/toolbox/coder/foundation/build/tools/registry
- /usr/local/MATLAB/R2016a/toolbox/coder/foundation/tfl
- /usr/local/MATLAB/R2016a/toolbox/coder/foundation/tfl/AUTOSAR/AUTOSAR4p0/IFX
- /usr/local/MATLAB/R2016a/toolbox/coder/foundation/tfl/AUTOSAR/AUTOSAR4p0/IFL
- /usr/local/MATLAB/R2016a/toolbox/coder/foundation/tfl/gui
- /usr/local/MATLAB/R2016a/toolbox/coder/foundation/templates
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- /usr/local/MATLAB/R2016a/toolbox/fininst/fininstdemos
- /usr/local/MATLAB/R2016a/toolbox/nnet
- /usr/local/MATLAB/R2016a/toolbox/nnet/nncontrol
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnadapt
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nndatafun
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnderivative
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- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nninitnetwork
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nninitweight
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnlearn
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnnetfun
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnnetinput
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnnetwork
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnperformance
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnplot
- /usr/local/MATLAB/R2016a/toolbox/nnet/nnet/nnprocess
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- /usr/local/MATLAB/R2016a/toolbox/nnet/nnutils
- /usr/local/MATLAB/R2016a/toolbox/matlab/addons_product
- /usr/local/MATLAB/R2016a/toolbox/shared/tracking/trackinglib
- /usr/local/MATLAB/R2016a/toolbox/shared/simulink/sysarch/sysarch
- /usr/local/MATLAB/R2016a/toolbox/shared/slreportgen/reportexplorer
- /usr/local/MATLAB/R2016a/toolbox/coder/embeddedcoder_templates
- /usr/local/MATLAB/R2016a/toolbox/coder/wizard
- /usr/local/MATLAB/R2016a/toolbox/physmod/sm/core/m
- /usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples
- /usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/ros
- /usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/ros/helpers
- /usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotalgs
- /usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotalgs/helpers
- /usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotcore
- /usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotcore/helpers
- /usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotsimulink
- /usr/local/MATLAB/R2016a/toolbox/robotics/robotexamples/robotsimulink/helpers
- /usr/local/MATLAB/R2016a/toolbox/shared/controllib/engine
- /usr/local/MATLAB/R2016a/toolbox/shared/controllib/engine/numerics
- /usr/local/MATLAB/R2016a/toolbox/shared/controllib/engine/options
- /usr/local/MATLAB/R2016a/toolbox/shared/controllib/engine/optim
- /usr/local/MATLAB/R2016a/toolbox/shared/controllib/engine/blocks
- /usr/local/MATLAB/R2016a/toolbox/dsp/filterdesign
- /usr/local/MATLAB/R2016a/toolbox/finance/findemos
- /usr/local/MATLAB/R2016a/toolbox/physmod/powersys/facts/facts
-
-
-
-```matlab
-pwd
-```
-
- ans =
-
- /home/ryan/Documents/UConn/ME3255/me3255_S2017/lecture_03
-
-
-
-path
-
-## Assignments (`=`-operator)
-
-Matlab is interpreted language so each line of code (either saved text file or command-line) is executed as a standalone command
-
-These are reffered to "scripts"
-
-
-```matlab
-a=10; % line one assigns a to 10
-b=a*3; % line two assigns b to 10 times 3 by calling 'a' from line one
-a+b % line three does not assign anything directly, but leaving off the ";" prints the result
- % ans
-```
-
- ans =
-
- 40
-
-
-Matlab has a number of "objects" that you can assign to variables
-1. arrays (vectors and matrices `[`...`]`)
-2. strings (text `"`...`"` )
-3. cells (combination of strings, text, even function calls `{`...`}`)
-3. functions (both built-in, defined or developed)
-4. and more... (classes defined by `classdef` - you can create your own object to help organize data)
-
-### 1- Arrays
-
-Default in matlab is that when you assign a value to a variable, it is stored as an array
-
-arrays are N x M x ... values of integers or floating point numbers or complex integers/floating point numbers
-
-Use the parantheses to access values in an array `...(n,m)`
-
-
-```matlab
-a=10; % a is 1x1 array where a(1,1)==10
-a(1,1)==10
-
-```
-
- ans =
-
- 1
-
-
-
-```matlab
-a(2)
-```
-
- [0;31mIndex exceeds matrix dimensions.
- [0m
-
-
-```matlab
-A = [1 2 3;4,5,6;7,8,9;10,11,12]
-fprintf('size of A is %i x %i\n',size(A))
-A(3,1)
-A(6)
-```
-
- A =
-
- 1 2 3
- 4 5 6
- 7 8 9
- 10 11 12
-
- size of A is 4 x 3
-
- ans =
-
- 7
-
-
- ans =
-
- 5
-
-
-vectors are either 1xN or Nx1 arrays for row and column
-
-
-```matlab
-v_row = [1,2,3] %row vector
-v_column = [1;2;3] %column vector
-
-```
-
- v_row =
-
- 1 2 3
-
-
- v_column =
-
- 1
- 2
- 3
-
-
-Matrices are MxN arrays
-the `:`-symbol can substitute for a counting
-
-
-```matlab
-A(1,:) % the colon assumes you want the first value, 1, counting up by 1 to the last value, 4
-```
-
- ans =
-
- 1 2 3
-
-
-You can also use every 2nd value or any other integer up to `end` which is the largest value of that row or column of the array
-
-
-```matlab
-A(1:2:end,1) % you can also use `end`
-```
-
- ans =
-
- 1
- 7
-
-
-
-```matlab
-A(:)
-```
-
- ans =
-
- 1
- 4
- 7
- 10
- 2
- 5
- 8
- 11
- 3
- 6
- 9
- 12
-
-
-In general, arrays can be any size
-
-take rolling 4 die and determining the sum of the components
-
-
-```matlab
-A_6666 = zeros(6,6,6,6); %make a 6 x 6 x 6 x 6 array (1296 different values)
-for i=1:6
- for j=1:6
- for k=1:6
- for l=1:6
- A_6666(i,j,k,l)=i+j+k+l; % each value is the sum of the indices
- end
- end
- end
-end
-
-```
-
-
-```matlab
-mean(A_6666(:))
-std(A_6666(:))
-```
-
- ans =
-
- 14
-
-
- ans =
-
- 3.4170
-
-
-
-```matlab
-A_6666(1,4,2,5)
-```
-
- ans =
-
- 12
-
-
-## Cells combine different size arrays and text
-### but, you cannot use math operators 'binary operators'
-
-
-```matlab
-C={};
-C{1}=linspace(0,1,10);
-C{2}=linspace(0,1,3);
-C{'z'}='holy cow';
-```
-
-
-```matlab
-C{1}*C{1}'
-```
-
- ans =
-
- 3.5185
-
-
-## Strings can be combined and printed
-
-
-```matlab
-string1 = 'computational'; string2 = 'mechanics';
-[string1, ' ', string2]
-```
-
- ans =
-
- computational mechanics
-
-
-use `fprintf` to format strings and numbers for output and `sprintf` to save variables
-
-
-
-```matlab
-fprintf([string1,' ',string2,'\n\n'])
-string = sprintf('the dog had %i legs and weighed %1.1f lbs',4,10.0)
-```
-
- computational mechanics
-
-
- string =
-
- the dog had 4 legs and weighed 10.0 lbs
-
-
-the `\` signifies a special character e.g. `\n` = newline, `\t` = tab
-
-to actually print the "\", use `\\`
-
-
-```matlab
-fprintf('\\')
-```
-
- \
-
-
-## This is helpful to create reports of computed data
-
-
-```matlab
-%fid = fopen('file.txt','w');
-fprintf(fid,[string1, ' ', string2])
-fprintf(fid,'\n')
-fprintf(fid,string)
-fprintf(fid,'\n')
-fprintf(fid,'are you awake?')
-```
-
- ans =
-
- 23
-
-
- ans =
-
- 1
-
-
- ans =
-
- 39
-
-
- ans =
-
- 1
-
-
- ans =
-
- 14
-
-
-## Math operators (=, +, -, /, *, ^)
-
-Because matlab assumes all variables are matrices, then all operators are matrix operations
-
-
-```matlab
-a+a % add two 1x1 arrays
-```
-
- ans = 20
-
-
-
-```matlab
-A+A % add two 4 x 3 arrays
-```
-
- ans =
-
- 2 4 6
- 8 10 12
- 14 16 18
- 20 22 24
-
-
-
-
-```matlab
-A*A'
-```
-
- ans =
-
- 14 32 50 68
- 32 77 122 167
- 50 122 194 266
- 68 167 266 365
-
-
-
-```matlab
-A.^2
-```
-
- ans =
-
- 1 4 9
- 16 25 36
- 49 64 81
- 100 121 144
-
-
-
-```matlab
-A.*A
-```
-
- ans =
-
- 1 4 9
- 16 25 36
- 49 64 81
- 100 121 144
-
-
-
-```matlab
-A/A
-```
-
- [> In pymat_eval (line 31)
- In matlabserver (line 24)]
- [Warning: Rank deficient, rank = 2, tol = 1.696862e-14.]
-
- ans =
-
- 1.0000 0 0 -0.0000
- 0.6667 0 0 0.3333
- 0.3333 0 0 0.6667
- 0.0000 0 0 1.0000
-
-
-
-```matlab
-help /
-```
-
- / Slash or right matrix divide.
- A/B is the matrix division of B into A, which is roughly the
- same as A*INV(B) , except it is computed in a different way.
- More precisely, A/B = (B'\A')'. See MLDIVIDE for details.
-
- C = MRDIVIDE(A,B) is called for the syntax 'A / B' when A or B is an
- object.
-
- See also MLDIVIDE, RDIVIDE, LDIVIDE.
-
- Reference page in Doc Center
- doc mrdivide
-
- Other functions named mrdivide
-
- codistributed/mrdivide gf/mrdivide laurpoly/mrdivide
- duration/mrdivide gpuArray/mrdivide StaticModel/mrdivide
- DynamicSystem/mrdivide LagOp/mrdivide timeseries/mrdivide
- fints/mrdivide
-
-
-To accomplish one-by-one operations, need to include a `.`
-
-
-```matlab
-A./A
-```
-
- ans =
-
- 1 1 1
- 1 1 1
- 1 1 1
- 1 1 1
-
-
-
-But, for 1x1 arrays, these are considered scalars and you get a free-pass
-
-
-```matlab
-a*A % where a=10 and A is 1:12 in a 3 x 4 matrix
-```
-
- ans =
-
- 10 20 30
- 40 50 60
- 70 80 90
- 100 110 120
-
-
-
-Some built in Matlab functions (e.g. the reasons to run Matlab)
-
-
-```matlab
-t_linear=linspace(0,1,11)
-```
-
- t_linear =
-
- Columns 1 through 7
-
- 0 0.1000 0.2000 0.3000 0.4000 0.5000 0.6000
-
- Columns 8 through 11
-
- 0.7000 0.8000 0.9000 1.0000
-
-
-
-```matlab
-t_log = logspace(0,2,3) % log interval from 10^0 to 10^2 split into 3 values
-```
-
- t_log =
-
- 1 10 100
-
-
-
-```matlab
-help logspace
-```
-
- 'logspace' is a function from the file /usr/share/octave/4.0.0/m/general/logspace.m
-
- -- Function File: logspace (A, B)
- -- Function File: logspace (A, B, N)
- -- Function File: logspace (A, pi, N)
- Return a row vector with N elements logarithmically spaced from
- 10^A to 10^B.
-
- If N is unspecified it defaults to 50.
-
- If B is equal to pi, the points are between 10^A and pi, _not_ 10^A
- and 10^pi, in order to be compatible with the corresponding MATLAB
- function.
-
- Also for compatibility with MATLAB, return the second argument B if
- fewer than two values are requested.
-
- See also: linspace.
-
- Additional help for built-in functions and operators is
- available in the online version of the manual. Use the command
- 'doc ' to search the manual index.
-
- Help and information about Octave is also available on the WWW
- at http://www.octave.org and via the help@octave.org
- mailing list.
-
-
-## When using the command prompt, anything in your path or working directory can be run either as a script, function or class (to define objects)
-
-
-```matlab
-%myscript
-```
-
-
-```matlab
-%plot --format svg
-```
-
-When using the GUI, your command history is saved, but it is better to save your work either as a script or a function or combination of both
-
-Creating a default graph script:
-
-
-```matlab
-set(0, 'defaultAxesFontSize', 16)
-set(0,'defaultTextFontSize',14)
-set(0,'defaultLineLineWidth',3)
-```
-
-
-```matlab
-plot(t_linear,t_linear.^2)
-xlabel('time (s)')
-ylabel('displacement (m)')
-```
-
-
-![png](output_58_0.png)
-
-
-#EOL
-
-## Graphics can be produced with a number of functions
-
-2-D plots, 3-D plots, contour plots, 3D contour plots ...
-
-
-```matlab
-x=linspace(-1,1,21); y=linspace(-1,1,21);
-[X,Y]=meshgrid(x,y);
-Z=(X.*Y.^3-X.^3.*Y)
-```
-
- Z =
-
- Columns 1 through 8:
-
- 0.00000 0.17100 0.28800 0.35700 0.38400 0.37500 0.33600 0.27300
- -0.17100 0.00000 0.12240 0.20160 0.24300 0.25200 0.23400 0.19440
- -0.28800 -0.12240 0.00000 0.08400 0.13440 0.15600 0.15360 0.13200
- -0.35700 -0.20160 -0.08400 0.00000 0.05460 0.08400 0.09240 0.08400
- -0.38400 -0.24300 -0.13440 -0.05460 0.00000 0.03300 0.04800 0.04860
- -0.37500 -0.25200 -0.15600 -0.08400 -0.03300 0.00000 0.01800 0.02400
- -0.33600 -0.23400 -0.15360 -0.09240 -0.04800 -0.01800 0.00000 0.00840
- -0.27300 -0.19440 -0.13200 -0.08400 -0.04860 -0.02400 -0.00840 0.00000
- -0.19200 -0.13860 -0.09600 -0.06300 -0.03840 -0.02100 -0.00960 -0.00300
- -0.09900 -0.07200 -0.05040 -0.03360 -0.02100 -0.01200 -0.00600 -0.00240
- 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
- 0.09900 0.07200 0.05040 0.03360 0.02100 0.01200 0.00600 0.00240
- 0.19200 0.13860 0.09600 0.06300 0.03840 0.02100 0.00960 0.00300
- 0.27300 0.19440 0.13200 0.08400 0.04860 0.02400 0.00840 -0.00000
- 0.33600 0.23400 0.15360 0.09240 0.04800 0.01800 -0.00000 -0.00840
- 0.37500 0.25200 0.15600 0.08400 0.03300 0.00000 -0.01800 -0.02400
- 0.38400 0.24300 0.13440 0.05460 -0.00000 -0.03300 -0.04800 -0.04860
- 0.35700 0.20160 0.08400 -0.00000 -0.05460 -0.08400 -0.09240 -0.08400
- 0.28800 0.12240 0.00000 -0.08400 -0.13440 -0.15600 -0.15360 -0.13200
- 0.17100 -0.00000 -0.12240 -0.20160 -0.24300 -0.25200 -0.23400 -0.19440
- 0.00000 -0.17100 -0.28800 -0.35700 -0.38400 -0.37500 -0.33600 -0.27300
-
- Columns 9 through 16:
-
- 0.19200 0.09900 0.00000 -0.09900 -0.19200 -0.27300 -0.33600 -0.37500
- 0.13860 0.07200 0.00000 -0.07200 -0.13860 -0.19440 -0.23400 -0.25200
- 0.09600 0.05040 0.00000 -0.05040 -0.09600 -0.13200 -0.15360 -0.15600
- 0.06300 0.03360 0.00000 -0.03360 -0.06300 -0.08400 -0.09240 -0.08400
- 0.03840 0.02100 0.00000 -0.02100 -0.03840 -0.04860 -0.04800 -0.03300
- 0.02100 0.01200 0.00000 -0.01200 -0.02100 -0.02400 -0.01800 0.00000
- 0.00960 0.00600 0.00000 -0.00600 -0.00960 -0.00840 0.00000 0.01800
- 0.00300 0.00240 0.00000 -0.00240 -0.00300 0.00000 0.00840 0.02400
- 0.00000 0.00060 0.00000 -0.00060 0.00000 0.00300 0.00960 0.02100
- -0.00060 0.00000 0.00000 0.00000 0.00060 0.00240 0.00600 0.01200
- 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
- 0.00060 -0.00000 0.00000 0.00000 -0.00060 -0.00240 -0.00600 -0.01200
- -0.00000 -0.00060 0.00000 0.00060 0.00000 -0.00300 -0.00960 -0.02100
- -0.00300 -0.00240 0.00000 0.00240 0.00300 0.00000 -0.00840 -0.02400
- -0.00960 -0.00600 0.00000 0.00600 0.00960 0.00840 0.00000 -0.01800
- -0.02100 -0.01200 0.00000 0.01200 0.02100 0.02400 0.01800 0.00000
- -0.03840 -0.02100 0.00000 0.02100 0.03840 0.04860 0.04800 0.03300
- -0.06300 -0.03360 0.00000 0.03360 0.06300 0.08400 0.09240 0.08400
- -0.09600 -0.05040 0.00000 0.05040 0.09600 0.13200 0.15360 0.15600
- -0.13860 -0.07200 0.00000 0.07200 0.13860 0.19440 0.23400 0.25200
- -0.19200 -0.09900 0.00000 0.09900 0.19200 0.27300 0.33600 0.37500
-
- Columns 17 through 21:
-
- -0.38400 -0.35700 -0.28800 -0.17100 0.00000
- -0.24300 -0.20160 -0.12240 0.00000 0.17100
- -0.13440 -0.08400 0.00000 0.12240 0.28800
- -0.05460 0.00000 0.08400 0.20160 0.35700
- 0.00000 0.05460 0.13440 0.24300 0.38400
- 0.03300 0.08400 0.15600 0.25200 0.37500
- 0.04800 0.09240 0.15360 0.23400 0.33600
- 0.04860 0.08400 0.13200 0.19440 0.27300
- 0.03840 0.06300 0.09600 0.13860 0.19200
- 0.02100 0.03360 0.05040 0.07200 0.09900
- 0.00000 0.00000 0.00000 0.00000 0.00000
- -0.02100 -0.03360 -0.05040 -0.07200 -0.09900
- -0.03840 -0.06300 -0.09600 -0.13860 -0.19200
- -0.04860 -0.08400 -0.13200 -0.19440 -0.27300
- -0.04800 -0.09240 -0.15360 -0.23400 -0.33600
- -0.03300 -0.08400 -0.15600 -0.25200 -0.37500
- 0.00000 -0.05460 -0.13440 -0.24300 -0.38400
- 0.05460 0.00000 -0.08400 -0.20160 -0.35700
- 0.13440 0.08400 0.00000 -0.12240 -0.28800
- 0.24300 0.20160 0.12240 0.00000 -0.17100
- 0.38400 0.35700 0.28800 0.17100 0.00000
-
-
-
-
-```matlab
-contour(X,Y,Z)
-```
-
-
-![svg](output_63_0.svg)
-
-
-
-```matlab
-mesh(X,Y,Z)
-```
-
-
-![svg](output_64_0.svg)
-
-
-
-```matlab
-pcolor(X,Y,Z)
-```
-
-
-![svg](output_65_0.svg)
-
-
-##
diff --git a/lecture_03/octave-workspace b/lecture_03/octave-workspace
deleted file mode 100644
index 4a1464b..0000000
Binary files a/lecture_03/octave-workspace and /dev/null differ
diff --git a/lecture_03/output_58_0.png b/lecture_03/output_58_0.png
deleted file mode 100644
index 1737c76..0000000
Binary files a/lecture_03/output_58_0.png and /dev/null differ
diff --git a/lecture_03/output_63_0.svg b/lecture_03/output_63_0.svg
deleted file mode 100644
index 3ed45d2..0000000
--- a/lecture_03/output_63_0.svg
+++ /dev/null
@@ -1,270 +0,0 @@
-
\ No newline at end of file
diff --git a/lecture_03/output_64_0.svg b/lecture_03/output_64_0.svg
deleted file mode 100644
index 509634c..0000000
--- a/lecture_03/output_64_0.svg
+++ /dev/null
@@ -1,1632 +0,0 @@
-
\ No newline at end of file
diff --git a/lecture_03/output_65_0.svg b/lecture_03/output_65_0.svg
deleted file mode 100644
index 5ce036b..0000000
--- a/lecture_03/output_65_0.svg
+++ /dev/null
@@ -1,2146 +0,0 @@
-
\ No newline at end of file
diff --git a/lecture_04/lecture_4.md b/lecture_04/lecture_4.md
deleted file mode 100644
index dd549aa..0000000
--- a/lecture_04/lecture_4.md
+++ /dev/null
@@ -1,339 +0,0 @@
-
-## When using the command prompt, anything in your path or working directory can be run either as a script, function or class (to define objects)
-
-Questions from last class:
-- I downloaded GitHub to my desktop but I cannot sign into my UConn account like I can online.
-- I checked my grades on HuskyCt recently and I received a 0 / 100 for Homework 1.
-- It is very hard to tell if what I'm doing on github is right or wrong.
-- How often will be using our laptops during the lecture?
-- How many frogs would it take to move a car that is stuck in the snow? And what would be the approximate cost to do so
-
-$m_{frog}$=22.7 g (https://en.wikipedia.org/wiki/Common_frog)
-
-$v_{frog}$=17 kph = 4.72 m/s (http://purelyfacts.com/question/14/is-a-toad-faster-than-a-frog?DDA=113&DDB=40)
-
-$m_{car}$=1000 kg (reasonable guess)
-
-conservation of momentum:
-
-$mv_{1} +mv_{2} = mv_{1}'+mv_{2}' = m_{total}v_{2}'$
-
-
-```matlab
-number_of_frogs = 1;
-v2=0;
-while v2 < 1 % 1 m/s
- m_frogs=number_of_frogs*22.7e-3;
- number_of_frogs=number_of_frogs+1;
- p1=(m_frogs)*4.72; % momentum 1
- v2=p1/(m_frogs+1000); % p2=p1, so v2=p1/m_total
-end
-number_of_frogs
-
-```
-
- number_of_frogs =
-
- 11844
-
-
-
-```matlab
-%myscript
-```
-
-
-```matlab
-%plot --format svg
-```
-
-When using the GUI, your command history is saved, but it is better to save your work either as a script or a function or combination of both
-
-Creating a default graph script: `setdefaults.m`
-
-```matlab
-set(0, 'defaultAxesFontSize', 16)
-set(0,'defaultTextFontSize',14)
-set(0,'defaultLineLineWidth',3)
-```
-
-
-```matlab
-set(0, 'defaultAxesFontSize', 16)
-set(0,'defaultTextFontSize',14)
-set(0,'defaultLineLineWidth',3)
-```
-
-
-```matlab
-t_linear=linspace(0,10,100);
-plot(t_linear,t_linear.^2)
-xlabel('time (s)')
-ylabel('displacement (m)')
-```
-
-
-![png](lecture_4_files/lecture_4_7_0.png)
-
-
-#EOL
-
-## Graphics can be produced with a number of functions
-
-2-D plots, 3-D plots, contour plots, 3D contour plots ...
-
-
-```matlab
-x=linspace(-1,1,21); y=linspace(-1,1,21);
-[X,Y]=meshgrid(x,y);
-Z=(X.*Y.^3-X.^3.*Y)
-```
-
- Z =
-
- Columns 1 through 7
-
- 0 0.1710 0.2880 0.3570 0.3840 0.3750 0.3360
- -0.1710 0 0.1224 0.2016 0.2430 0.2520 0.2340
- -0.2880 -0.1224 0 0.0840 0.1344 0.1560 0.1536
- -0.3570 -0.2016 -0.0840 0 0.0546 0.0840 0.0924
- -0.3840 -0.2430 -0.1344 -0.0546 0 0.0330 0.0480
- -0.3750 -0.2520 -0.1560 -0.0840 -0.0330 0 0.0180
- -0.3360 -0.2340 -0.1536 -0.0924 -0.0480 -0.0180 0
- -0.2730 -0.1944 -0.1320 -0.0840 -0.0486 -0.0240 -0.0084
- -0.1920 -0.1386 -0.0960 -0.0630 -0.0384 -0.0210 -0.0096
- -0.0990 -0.0720 -0.0504 -0.0336 -0.0210 -0.0120 -0.0060
- 0 0 0 0 0 0 0
- 0.0990 0.0720 0.0504 0.0336 0.0210 0.0120 0.0060
- 0.1920 0.1386 0.0960 0.0630 0.0384 0.0210 0.0096
- 0.2730 0.1944 0.1320 0.0840 0.0486 0.0240 0.0084
- 0.3360 0.2340 0.1536 0.0924 0.0480 0.0180 0.0000
- 0.3750 0.2520 0.1560 0.0840 0.0330 0 -0.0180
- 0.3840 0.2430 0.1344 0.0546 -0.0000 -0.0330 -0.0480
- 0.3570 0.2016 0.0840 0 -0.0546 -0.0840 -0.0924
- 0.2880 0.1224 0 -0.0840 -0.1344 -0.1560 -0.1536
- 0.1710 0.0000 -0.1224 -0.2016 -0.2430 -0.2520 -0.2340
- 0 -0.1710 -0.2880 -0.3570 -0.3840 -0.3750 -0.3360
-
- Columns 8 through 14
-
- 0.2730 0.1920 0.0990 0 -0.0990 -0.1920 -0.2730
- 0.1944 0.1386 0.0720 0 -0.0720 -0.1386 -0.1944
- 0.1320 0.0960 0.0504 0 -0.0504 -0.0960 -0.1320
- 0.0840 0.0630 0.0336 0 -0.0336 -0.0630 -0.0840
- 0.0486 0.0384 0.0210 0 -0.0210 -0.0384 -0.0486
- 0.0240 0.0210 0.0120 0 -0.0120 -0.0210 -0.0240
- 0.0084 0.0096 0.0060 0 -0.0060 -0.0096 -0.0084
- 0 0.0030 0.0024 0 -0.0024 -0.0030 0
- -0.0030 0 0.0006 0 -0.0006 0 0.0030
- -0.0024 -0.0006 0 0 0.0000 0.0006 0.0024
- 0 0 0 0 0 0 0
- 0.0024 0.0006 -0.0000 0 0 -0.0006 -0.0024
- 0.0030 0 -0.0006 0 0.0006 0 -0.0030
- 0 -0.0030 -0.0024 0 0.0024 0.0030 0
- -0.0084 -0.0096 -0.0060 0 0.0060 0.0096 0.0084
- -0.0240 -0.0210 -0.0120 0 0.0120 0.0210 0.0240
- -0.0486 -0.0384 -0.0210 0 0.0210 0.0384 0.0486
- -0.0840 -0.0630 -0.0336 0 0.0336 0.0630 0.0840
- -0.1320 -0.0960 -0.0504 0 0.0504 0.0960 0.1320
- -0.1944 -0.1386 -0.0720 0 0.0720 0.1386 0.1944
- -0.2730 -0.1920 -0.0990 0 0.0990 0.1920 0.2730
-
- Columns 15 through 21
-
- -0.3360 -0.3750 -0.3840 -0.3570 -0.2880 -0.1710 0
- -0.2340 -0.2520 -0.2430 -0.2016 -0.1224 -0.0000 0.1710
- -0.1536 -0.1560 -0.1344 -0.0840 0 0.1224 0.2880
- -0.0924 -0.0840 -0.0546 0 0.0840 0.2016 0.3570
- -0.0480 -0.0330 0.0000 0.0546 0.1344 0.2430 0.3840
- -0.0180 0 0.0330 0.0840 0.1560 0.2520 0.3750
- -0.0000 0.0180 0.0480 0.0924 0.1536 0.2340 0.3360
- 0.0084 0.0240 0.0486 0.0840 0.1320 0.1944 0.2730
- 0.0096 0.0210 0.0384 0.0630 0.0960 0.1386 0.1920
- 0.0060 0.0120 0.0210 0.0336 0.0504 0.0720 0.0990
- 0 0 0 0 0 0 0
- -0.0060 -0.0120 -0.0210 -0.0336 -0.0504 -0.0720 -0.0990
- -0.0096 -0.0210 -0.0384 -0.0630 -0.0960 -0.1386 -0.1920
- -0.0084 -0.0240 -0.0486 -0.0840 -0.1320 -0.1944 -0.2730
- 0 -0.0180 -0.0480 -0.0924 -0.1536 -0.2340 -0.3360
- 0.0180 0 -0.0330 -0.0840 -0.1560 -0.2520 -0.3750
- 0.0480 0.0330 0 -0.0546 -0.1344 -0.2430 -0.3840
- 0.0924 0.0840 0.0546 0 -0.0840 -0.2016 -0.3570
- 0.1536 0.1560 0.1344 0.0840 0 -0.1224 -0.2880
- 0.2340 0.2520 0.2430 0.2016 0.1224 0 -0.1710
- 0.3360 0.3750 0.3840 0.3570 0.2880 0.1710 0
-
-
-
-```matlab
-contour(X,Y,Z)
-```
-
-
-![png](lecture_4_files/lecture_4_12_0.png)
-
-
-
-```matlab
-mesh(X,Y,Z)
-```
-
-
-![png](lecture_4_files/lecture_4_13_0.png)
-
-
-
-```matlab
-pcolor(X,Y,Z)
-```
-
-
-![png](lecture_4_files/lecture_4_14_0.png)
-
-
-## Functions
-
-So far, everything has been executed as a script, or calling a built-in function. Now we begin building our own functions.
-
-Functions are saved in memory (or better yet) in a folder in your path or current directory
-
-Example of storing function in memory
-
-$f(x,y) = (xy^{3}-x^{3}y)$
-
-
-```matlab
-f= @(x,y) (x.*y.^3-x.^3.*y)
-```
-
- f =
-
- @(x,y)(x.*y.^3-x.^3.*y)
-
-
-
-```matlab
-f(0.1,-0.5)
-```
-
- ans =
-
- -0.0120
-
-
-Here we will save a function called `my_function` as `my_function.m`
-
-```matlab
-function [vx,vy] = my_function(x,y,t)
- % Help documentation of "my_function"
- % This function computes the velocity in the x- and y-directions given
- % three vectors of position in x- and y-directions as a function of time
- % x = x-position
- % y = y-position
- % t = time
- % output
- % vx = velocity in x-direction
- % vy = velocity in y-direction
-
- vx=zeros(length(t),1);
- vy=zeros(length(t),1);
-
- vx(1:end-1) = diff(x)./diff(t); % calculate vx as delta x/delta t
- vy(1:end-1) = diff(y)./diff(t); % calculate vy as delta y/delta t
-
- vx(end) = vx(end-1);
- vy(end) = vy(end-1);
-
-end
-```
-
-
-```matlab
-help my_function
-```
-
- Help documentation of "my_function"
- This function computes the velocity in the x- and y-directions given
- three vectors of position in x- and y-directions as a function of time
- x = x-position
- y = y-position
- t = time
- output
- vx = velocity in x-direction
- vy = velocity in y-direction
-
-
-
-```matlab
-t=linspace(0,10,100)';
-x=t.^3; % vx = 3*t^2
-y=t.^2/2; % vy = t
-[vx,vy]=my_function(x,y,t);
-```
-
-
-```matlab
-yyaxis left
-plot(t(1:10:end),vx(1:10:end),'o',t,3*t.^2)
-ylabel('v_{x}')
-yyaxis right
-plot(t(1:10:end),vy(1:10:end),'s',t, t)
-ylabel('v_{y}')
-xlabel('time')
-```
-
-
-![png](lecture_4_files/lecture_4_22_0.png)
-
-
-Now, create a new function that calls 'my_function' called, `my_caller.m`
-
-
-```matlab
-help my_caller
-```
-
- Help documentation of "my_caller"
- This function computes the acceleration in the x- and y-directions given
- three vectors of position in x- and y-directions as a function of time
- x = x-position
- y = y-position
- t = time
- output
- ax = velocity in x-direction
- ay = velocity in y-direction
-
-
-
-```matlab
-[ax,ay]=my_caller(x,y,t);
-```
-
-
-```matlab
-yyaxis left
-plot(t(1:10:end),ax(1:10:end),'o',t,6*t)
-ylabel('a_{x}')
-yyaxis right
-plot(t(1:10:end),ay(1:10:end),'s',t, 1*t./t)
-ylabel('a_{x}')
-xlabel('time')
-axis([0,10,0,3])
-```
-
-
-![png](lecture_4_files/lecture_4_26_0.png)
-
-
-
-```matlab
-diff_match_dims(x,t)
-```
-
- [0;31mUndefined function 'diff_match_dims' for input arguments of type 'double'.
- [0m
-
-
-```matlab
-
-```
diff --git a/lecture_04/lecture_4.pdf b/lecture_04/lecture_4.pdf
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diff --git a/lecture_04/lecture_4_files/lecture_4_7_0.png b/lecture_04/lecture_4_files/lecture_4_7_0.png
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diff --git a/lecture_04/myscript.m b/lecture_04/myscript.m
deleted file mode 100644
index 4488e0f..0000000
--- a/lecture_04/myscript.m
+++ /dev/null
@@ -1,11 +0,0 @@
-f=100;
-
-for i=1:10
- g=i^2;
- if f==g
- fprintf('we made it\n')
- else
- fprintf('not yet\n')
- end
-end
-
diff --git a/lecture_05/.ipynb_checkpoints/lecture_05-checkpoint.ipynb b/lecture_05/.ipynb_checkpoints/lecture_05-checkpoint.ipynb
deleted file mode 100644
index 2fd6442..0000000
--- a/lecture_05/.ipynb_checkpoints/lecture_05-checkpoint.ipynb
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "cells": [],
- "metadata": {},
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/lecture_05/gp_image_01.png b/lecture_05/gp_image_01.png
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diff --git a/lecture_05/lecture_05.ipynb b/lecture_05/lecture_05.ipynb
deleted file mode 100644
index 66fcbe9..0000000
--- a/lecture_05/lecture_05.ipynb
+++ /dev/null
@@ -1,559 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "%plot --format svg"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Questions from last class"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "When you execute the given function \n",
- "\n",
- "my_function.m:\n",
- "\n",
- "```matlab\n",
- "function [x,y] = my_function(max_time)\n",
- " N=100;\n",
- " t=linspace(0,max_time,N);\n",
- " x=t.^2;\n",
- " y=2*t;\n",
- "end\n",
- "```\n",
- "\n",
- "as \n",
- "\n",
- "```>> [x,y] = my_function(20);```\n",
- "\n",
- "What variables are saved to your workspace?\n",
- "\n",
- "![responses](q1.png)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "How do you write a help description for a function?\n",
- "\n",
- "![responses to question 2](q2.png)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- " \n",
- "How to keep our forked ME3255S page up to date with the original\n",
- "pretty tired this morning\n",
- "\n",
- "How do I use the Github Desktop?\n",
- "\n",
- "whats your favorite football team?\n",
- "\n",
- "Will UConn's github get updated to the newest version of github?\n",
- "As u said in class trail and error is the best way of learning.\n",
- "\n",
- "I believe the % is the same as matlab where it de-links your code into text\n",
- "\n",
- "Does the @ symbol designate a pointer? \n",
- "\n",
- "Given the change of air pressure as altitude increases, how fast would a frisbee have to travel (and spin) to hit an airplane?\n",
- "\n",
- "What is a gui?\n",
- "\n",
- "\n",
- "could you go over a nested for loop example\n",
- "\n",
- "Can't seem to get this function to produce any graph and am not sure why\n",
- "\n",
- "When are these google forms due?\n",
- "\n",
- "how do I create a new function using Github on my desktop?\n",
- "\n",
- "Can you explain the first question more in class?\n",
- "\n",
- "What is the meaning of life?\n",
- "\n",
- "Should I just know how or what these topics are or will we learn them in the future?\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "f = \n",
- "\n",
- " @(x)x.^2\n"
- ]
- }
- ],
- "source": [
- "f =@(x) x.^2\n",
- "\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans =\n",
- "\n",
- " 1 9 25 49 81\n",
- "\n",
- "\n",
- "ans =\n",
- "\n",
- " 16\n"
- ]
- }
- ],
- "source": [
- "f([1:2:10])\n",
- "f(4)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "i=1 and j=1\n",
- "i=1 and j=2\n",
- "i=1 and j=3\n",
- "i=2 and j=1\n",
- "i=2 and j=2\n",
- "i=2 and j=3\n",
- "i=3 and j=1\n",
- "i=3 and j=2\n",
- "i=3 and j=3\n",
- "i=4 and j=1\n",
- "i=4 and j=2\n",
- "i=4 and j=3\n",
- "i=5 and j=1\n",
- "i=5 and j=2\n",
- "i=5 and j=3\n",
- "i=6 and j=1\n",
- "i=6 and j=2\n",
- "i=6 and j=3\n"
- ]
- }
- ],
- "source": [
- "% nested for loop example\n",
- "for i = [1:6]\n",
- " for j = [1:3]\n",
- " fprintf('i=%i and j=%i\\n',i,j)\n",
- " end\n",
- "end\n",
- " "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# From last class "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Help documentation of \"my_function\"\n",
- " This function computes the velocity in the x- and y-directions given\n",
- " three vectors of position in x- and y-directions as a function of time\n",
- " x = x-position\n",
- " y = y-position\n",
- " t = time\n",
- " output\n",
- " vx = velocity in x-direction\n",
- " vy = velocity in y-direction\n"
- ]
- }
- ],
- "source": [
- "help my_function"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Help documentation of \"my_caller\"\n",
- " This function computes the acceleration in the x- and y-directions given\n",
- " three vectors of position in x- and y-directions as a function of time\n",
- " x = x-position\n",
- " y = y-position\n",
- " t = time\n",
- " output\n",
- " ax = acceleration in x-direction\n",
- " ay = acceleration in y-direction\n"
- ]
- }
- ],
- "source": [
- "help my_caller"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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8H8sNnMXS2dF+qcrSZiAivnhQ64lD5x+fIJ547y0v/YOcmJCqGgy3vXXE0GHO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\nDyUkAADgMp/IugAAwH1ISAAAwAlISAAAwAlISAA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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "t=linspace(0,10,100)'; \n",
- "x=t.^3; % vx = 3*t^2\n",
- "y=t.^2/2; % vy = t\n",
- "[vx,vy]=my_function(x,y,t);\n",
- "[ax,ay]=my_caller(x,y,t);\n",
- "yyaxis left\n",
- "plot(t(1:10:end),ax(1:10:end),'o',t,6*t)\n",
- "ylabel('a_{x}')\n",
- "yyaxis right\n",
- "plot(t(1:10:end),ay(1:10:end),'s',t, 1*t./t)\n",
- "ylabel('a_{y}')\n",
- "xlabel('time')\n",
- "axis([0,10,0,3])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\u001b[0;31mUndefined function 'diff_match_dims' for input arguments of type 'double'.\n",
- "\u001b[0m"
- ]
- }
- ],
- "source": [
- "diff_match_dims(x,t)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Good coding habits\n",
- "## naming folders and files"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "[Stanford file naming best practices](https://library.stanford.edu/research/data-management-services/data-best-practices/best-practices-file-naming)\n",
- "\n",
- "1. Include information to distinguish file name e.g. project name, objective of function, name/initials, type of data, conditions, version of file, \n",
- "2. if using dates, use YYYYMMDD, so the computer organizes by year, then month, then day\n",
- "3. avoid special characters e.g. !, #, \\$, ...\n",
- "4. avoid using spaces if not necessary, some programs consider a space as a break in code use dashes `-` or underscores `_` or CamelCase"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Commenting your code"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Its important to comment your code to mention what a variable's units are, what the function is supposed to do, etc. \n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\u001b[0;31mError: Function definitions are not permitted in this context.\n",
- "\u001b[0m"
- ]
- }
- ],
- "source": [
- "function i=code(j)\n",
- " % Example of bad variable names and bad function name\n",
- " for w=1:j\n",
- " i(w)=w;\n",
- " end\n",
- "end"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "code not found.\n",
- "\n",
- "Use the Help browser search field to search the documentation, or\n",
- "type \"help help\" for help command options, such as help for methods.\n"
- ]
- }
- ],
- "source": [
- "help code"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Choose variable names that describe the variable"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "function count_vector=counting_function(max_value)\n",
- " % Good variable names and better help documentation\n",
- " % \n",
- " % counting function creates a vector from 1 to max_value where each index, i, is \n",
- " % stored in each vector spot\n",
- " for i=1:max_value\n",
- " count_vector(i)=i; % set each element in count_vector to i\n",
- " end\n",
- "end "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "'counting_function' is a command-line function\n",
- "\n",
- " Good variable names and better help documentation\n",
- " \n",
- " counting function creates a vector from 1 to max_value where each index, i, is \n",
- " stored in each vector spot\n",
- "\n",
- "\n",
- "Additional help for built-in functions and operators is\n",
- "available in the online version of the manual. Use the command\n",
- "'doc ' to search the manual index.\n",
- "\n",
- "Help and information about Octave is also available on the WWW\n",
- "at http://www.octave.org and via the help@octave.org\n",
- "mailing list.\n"
- ]
- }
- ],
- "source": [
- "help counting_function"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Putting it all together"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "1. Clone your homework_1 to your computer\n",
- "2. open Matlab (cli, jupyter or gui)\n",
- "3. Change working directory to homework_1 *e.g.* Windows:`cd('C:\\Users\\rcc02007\\Documents\\Github\\homework_1')`, Mac: `cd('/Users/rcc02007/Documents/Github/homework_1')`\n",
- "4. You have already created your first script `setdefaults.m` (if not see lecture_4)\n",
- "5. Run `>> setdefaults.m`\n",
- "6. Create a new m-file called nitrogen_pressure.m\n",
- "7. Create a function based upon the ideal gas law for nitrogen, Pv=RT\n",
- " 1. R=0.2968 kJ/(kg-K)\n",
- " 2. inputs to function are v (specific volume m^3/kg), and T, temperature (K)\n",
- " 3. output is P, pressure (kPa)\n",
- "8. Once the function works, commit the change to the repository (add a message, like 'added file nitrogen_pressure.m'\n",
- "9. After file is 'committed', 'push' the changes to your github account\n",
- "\n",
- "for the command-line git user, this is steps 8 and 9:\n",
- "1. `$ git add *`\n",
- "2. `$ git commit -m 'added file nitrogen_pressure.m'`\n",
- "3. `$ git push -u origin master\n",
- " Username for 'https://github.uconn.edu':rcc02007 \n",
- " Password for 'https://rcc02007@github.uconn.edu': `\n",
- " "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "Now, use this function to plot the range of pressures that a pressure vessel would experience if it is 1000 gallons (3.79 m^3) with 10-20 kg of Nitrogen and temperatures range from -10 to 35 degrees C. \n",
- "\n",
- "```matlab\n",
- "v=0.379/linspace(50,20,10);\n",
- "T=273.15+linspace(-10,35,10);\n",
- "[v_grid,T_grid]=meshgrid(v,T);\n",
- "P = nitrogen_pressure(v,T);\n",
- "pcolor(v_grid,T_grid,P)\n",
- "```"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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T4sWLN2zYwOVyhULhwYMHU1JSuukb+D8KApKZmdmwYcNevXqFEPr++++///57e3v73bt3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\nONp5CLqPAAAAAElFTkSuQmCC\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "setdefaults;\n",
- "v=3.79./linspace(10,20,10);\n",
- "T=273.15+linspace(-10,35,10);\n",
- "[v_grid,T_grid]=meshgrid(v,T);\n",
- "P = nitrogen_pressure(v_grid,T_grid);\n",
- "pcolor(v_grid,T_grid-273.15,P-100)\n",
- "xlabel('specific volume (m^3/kg)')\n",
- "ylabel('Temperature (C)')\n",
- "%zlabel('Pressure (kPa)')\n",
- "\n",
- "%colormap winter\n",
- "%colormap summer\n",
- "%colormap jet\n",
- "colorbar()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Octave",
- "language": "octave",
- "name": "octave"
- },
- "language_info": {
- "file_extension": ".m",
- "help_links": [
- {
- "text": "MetaKernel Magics",
- "url": "https://github.com/calysto/metakernel/blob/master/metakernel/magics/README.md"
- }
- ],
- "mimetype": "text/x-octave",
- "name": "octave",
- "version": "0.19.14"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/lecture_05/lecture_05.md b/lecture_05/lecture_05.md
deleted file mode 100644
index 11c2894..0000000
--- a/lecture_05/lecture_05.md
+++ /dev/null
@@ -1,325 +0,0 @@
-
-
-```octave
-%plot --format svg
-```
-
-## Questions from last class
-
-When you execute the given function
-
-my_function.m:
-
-```matlab
-function [x,y] = my_function(max_time)
- N=100;
- t=linspace(0,max_time,N);
- x=t.^2;
- y=2*t;
-end
-```
-
-as
-
-```>> [x,y] = my_function(20);```
-
-What variables are saved to your workspace?
-
-![responses](q1.png)
-
-How do you write a help description for a function?
-
-![responses to question 2](q2.png)
-
-
-How to keep our forked ME3255S page up to date with the original
-pretty tired this morning
-
-How do I use the Github Desktop?
-
-whats your favorite football team?
-
-Will UConn's github get updated to the newest version of github?
-As u said in class trail and error is the best way of learning.
-
-I believe the % is the same as matlab where it de-links your code into text
-
-Does the @ symbol designate a pointer?
-
-Given the change of air pressure as altitude increases, how fast would a frisbee have to travel (and spin) to hit an airplane?
-
-What is a gui?
-
-
-could you go over a nested for loop example
-
-Can't seem to get this function to produce any graph and am not sure why
-
-When are these google forms due?
-
-how do I create a new function using Github on my desktop?
-
-Can you explain the first question more in class?
-
-What is the meaning of life?
-
-Should I just know how or what these topics are or will we learn them in the future?
-
-
-
-```octave
-f =@(x) x.^2
-
-
-```
-
- f =
-
- @(x)x.^2
-
-
-
-```octave
-f([1:2:10])
-f(4)
-```
-
- ans =
-
- 1 9 25 49 81
-
-
- ans =
-
- 16
-
-
-
-```octave
-% nested for loop example
-for i = [1:6]
- for j = [1:3]
- fprintf('i=%i and j=%i\n',i,j)
- end
-end
-
-```
-
- i=1 and j=1
- i=1 and j=2
- i=1 and j=3
- i=2 and j=1
- i=2 and j=2
- i=2 and j=3
- i=3 and j=1
- i=3 and j=2
- i=3 and j=3
- i=4 and j=1
- i=4 and j=2
- i=4 and j=3
- i=5 and j=1
- i=5 and j=2
- i=5 and j=3
- i=6 and j=1
- i=6 and j=2
- i=6 and j=3
-
-
-# From last class
-
-
-```octave
-help my_function
-```
-
- Help documentation of "my_function"
- This function computes the velocity in the x- and y-directions given
- three vectors of position in x- and y-directions as a function of time
- x = x-position
- y = y-position
- t = time
- output
- vx = velocity in x-direction
- vy = velocity in y-direction
-
-
-
-```octave
-help my_caller
-```
-
- Help documentation of "my_caller"
- This function computes the acceleration in the x- and y-directions given
- three vectors of position in x- and y-directions as a function of time
- x = x-position
- y = y-position
- t = time
- output
- ax = acceleration in x-direction
- ay = acceleration in y-direction
-
-
-
-```octave
-t=linspace(0,10,100)';
-x=t.^3; % vx = 3*t^2
-y=t.^2/2; % vy = t
-[vx,vy]=my_function(x,y,t);
-[ax,ay]=my_caller(x,y,t);
-yyaxis left
-plot(t(1:10:end),ax(1:10:end),'o',t,6*t)
-ylabel('a_{x}')
-yyaxis right
-plot(t(1:10:end),ay(1:10:end),'s',t, 1*t./t)
-ylabel('a_{y}')
-xlabel('time')
-axis([0,10,0,3])
-```
-
-
-![png](lecture_05_files/lecture_05_11_0.png)
-
-
-
-```octave
-diff_match_dims(x,t)
-```
-
- [0;31mUndefined function 'diff_match_dims' for input arguments of type 'double'.
- [0m
-
-# Good coding habits
-## naming folders and files
-
-[Stanford file naming best practices](https://library.stanford.edu/research/data-management-services/data-best-practices/best-practices-file-naming)
-
-1. Include information to distinguish file name e.g. project name, objective of function, name/initials, type of data, conditions, version of file,
-2. if using dates, use YYYYMMDD, so the computer organizes by year, then month, then day
-3. avoid special characters e.g. !, #, \$, ...
-4. avoid using spaces if not necessary, some programs consider a space as a break in code use dashes `-` or underscores `_` or CamelCase
-
-## Commenting your code
-
-Its important to comment your code to mention what a variable's units are, what the function is supposed to do, etc.
-
-
-
-```octave
-function i=code(j)
- % Example of bad variable names and bad function name
- for w=1:j
- i(w)=w;
- end
-end
-```
-
- [0;31mError: Function definitions are not permitted in this context.
- [0m
-
-
-```octave
-help code
-```
-
- code not found.
-
- Use the Help browser search field to search the documentation, or
- type "help help" for help command options, such as help for methods.
-
-
-## Choose variable names that describe the variable
-
-
-```octave
-function count_vector=counting_function(max_value)
- % Good variable names and better help documentation
- %
- % counting function creates a vector from 1 to max_value where each index, i, is
- % stored in each vector spot
- for i=1:max_value
- count_vector(i)=i; % set each element in count_vector to i
- end
-end
-```
-
-
-```octave
-help counting_function
-```
-
- 'counting_function' is a command-line function
-
- Good variable names and better help documentation
-
- counting function creates a vector from 1 to max_value where each index, i, is
- stored in each vector spot
-
-
- Additional help for built-in functions and operators is
- available in the online version of the manual. Use the command
- 'doc ' to search the manual index.
-
- Help and information about Octave is also available on the WWW
- at http://www.octave.org and via the help@octave.org
- mailing list.
-
-
-## Putting it all together
-
-1. Clone your homework_1 to your computer
-2. open Matlab (cli, jupyter or gui)
-3. Change working directory to homework_1 *e.g.* Windows:`cd('C:\Users\rcc02007\Documents\Github\homework_1')`, Mac: `cd('/Users/rcc02007/Documents/Github/homework_1')`
-4. You have already created your first script `setdefaults.m` (if not see lecture_4)
-5. Run `>> setdefaults.m`
-6. Create a new m-file called nitrogen_pressure.m
-7. Create a function based upon the ideal gas law for nitrogen, Pv=RT
- 1. R=0.2968 kJ/(kg-K)
- 2. inputs to function are v (specific volume m^3/kg), and T, temperature (K)
- 3. output is P, pressure (kPa)
-8. Once the function works, commit the change to the repository (add a message, like 'added file nitrogen_pressure.m'
-9. After file is 'committed', 'push' the changes to your github account
-
-for the command-line git user, this is steps 8 and 9:
-1. `$ git add *`
-2. `$ git commit -m 'added file nitrogen_pressure.m'`
-3. `$ git push -u origin master
- Username for 'https://github.uconn.edu':rcc02007
- Password for 'https://rcc02007@github.uconn.edu': `
-
-
-Now, use this function to plot the range of pressures that a pressure vessel would experience if it is 1000 gallons (3.79 m^3) with 10-20 kg of Nitrogen and temperatures range from -10 to 35 degrees C.
-
-```matlab
-v=0.379/linspace(50,20,10);
-T=273.15+linspace(-10,35,10);
-[v_grid,T_grid]=meshgrid(v,T);
-P = nitrogen_pressure(v,T);
-pcolor(v_grid,T_grid,P)
-```
-
-
-```octave
-setdefaults;
-v=3.79./linspace(10,20,10);
-T=273.15+linspace(-10,35,10);
-[v_grid,T_grid]=meshgrid(v,T);
-P = nitrogen_pressure(v_grid,T_grid);
-pcolor(v_grid,T_grid-273.15,P-100)
-xlabel('specific volume (m^3/kg)')
-ylabel('Temperature (C)')
-%zlabel('Pressure (kPa)')
-
-%colormap winter
-%colormap summer
-%colormap jet
-colorbar()
-```
-
-
-![png](lecture_05_files/lecture_05_25_0.png)
-
-
-
-```octave
-
-```
diff --git a/lecture_05/lecture_05.pdf b/lecture_05/lecture_05.pdf
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diff --git a/lecture_05/my_caller.m b/lecture_05/my_caller.m
deleted file mode 100644
index f0cd536..0000000
--- a/lecture_05/my_caller.m
+++ /dev/null
@@ -1,23 +0,0 @@
-function [ax,ay]=my_caller(x,y,t)
- % Help documentation of "my_caller"
- % This function computes the acceleration in the x- and y-directions given
- % three vectors of position in x- and y-directions as a function of time
- % x = x-position
- % y = y-position
- % t = time
- % output
- % ax = acceleration in x-direction
- % ay = acceleration in y-direction
-
- function v=diff_match_dims(x,t)
- v=zeros(length(t),1);
- v(1:end-1)=diff(x)./diff(t);
- v(end)=v(end-1);
- end
-
- [vx,vy]=my_function(x,y,t);
-
- ax = diff_match_dims(vx,t);
- ay = diff_match_dims(vy,t);
-
-end
diff --git a/lecture_05/my_function.m b/lecture_05/my_function.m
deleted file mode 100644
index 5953061..0000000
--- a/lecture_05/my_function.m
+++ /dev/null
@@ -1,21 +0,0 @@
-function [vx,vy] = my_function(x,y,t)
- % Help documentation of "my_function"
- % This function computes the velocity in the x- and y-directions given
- % three vectors of position in x- and y-directions as a function of time
- % x = x-position
- % y = y-position
- % t = time
- % output
- % vx = velocity in x-direction
- % vy = velocity in y-direction
-
- vx=zeros(length(t),1);
- vy=zeros(length(t),1);
-
- vx(1:end-1) = diff(x)./diff(t); % calculate vx as delta x/delta t
- vy(1:end-1) = diff(y)./diff(t); % calculate vy as delta y/delta t
-
- vx(end) = vx(end-1);
- vy(end) = vy(end-1);
-
-end
diff --git a/lecture_05/nitrogen_pressure.m b/lecture_05/nitrogen_pressure.m
deleted file mode 100644
index a76abf3..0000000
--- a/lecture_05/nitrogen_pressure.m
+++ /dev/null
@@ -1,10 +0,0 @@
-function P=nitrogen_pressure(v,T)
- % function to calculate Pressure of Nitrogen using ideal gas law given the specific
- % volume, v (m^3/kg), and temperature, T (K)
- % Pv = RT
- % R=0.2968; % kJ/kg-K
- % P [in kPa] = nitrogen_pressure(v [in m^3/kg], T[in K])
- R=0.2968; % kJ/kg-K
- P=R*T./v;
-end
-
diff --git a/lecture_05/octave-workspace b/lecture_05/octave-workspace
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diff --git a/lecture_05/q1.png b/lecture_05/q1.png
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diff --git a/lecture_05/q2.png b/lecture_05/q2.png
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diff --git a/lecture_05/setdefaults.m b/lecture_05/setdefaults.m
deleted file mode 100644
index 8c3c5c8..0000000
--- a/lecture_05/setdefaults.m
+++ /dev/null
@@ -1,3 +0,0 @@
-set(0, 'defaultAxesFontSize', 16)
-set(0,'defaultTextFontSize',14)
-set(0,'defaultLineLineWidth',3)
diff --git a/lecture_06/bisect.m b/lecture_06/bisect.m
deleted file mode 100644
index c09ffbf..0000000
--- a/lecture_06/bisect.m
+++ /dev/null
@@ -1,37 +0,0 @@
-function [root,fx,ea,iter]=bisect(func,xl,xu,es,maxit,varargin)
-% bisect: root location zeroes
-% [root,fx,ea,iter]=bisect(func,xl,xu,es,maxit,p1,p2,...):
-% uses bisection method to find the root of func
-% input:
-% func = name of function
-% xl, xu = lower and upper guesses
-% es = desired relative error (default = 0.0001%)
-% maxit = maximum allowable iterations (default = 50)
-% p1,p2,... = additional parameters used by func
-% output:
-% root = real root
-% fx = function value at root
-% ea = approximate relative error (%)
-% iter = number of iterations
-if nargin<3,error('at least 3 input arguments required'),end
-test = func(xl,varargin{:})*func(xu,varargin{:});
-if test>0,error('no sign change'),end
-if nargin<4|isempty(es), es=0.0001;end
-if nargin<5|isempty(maxit), maxit=50;end
-iter = 0; xr = xl; ea = 100;
-while (1)
- xrold = xr;
- xr = (xl + xu)/2;
- iter = iter + 1;
- if xr ~= 0,ea = abs((xr - xrold)/xr) * 100;end
- test = func(xl,varargin{:})*func(xr,varargin{:});
- if test < 0
- xu = xr;
- elseif test > 0
- xl = xr;
- else
- ea = 0;
- end
- if ea <= es | iter >= maxit,break,end
-end
-root = xr; fx = func(xr, varargin{:});
\ No newline at end of file
diff --git a/lecture_06/falsepos.m b/lecture_06/falsepos.m
deleted file mode 100644
index 0a3477c..0000000
--- a/lecture_06/falsepos.m
+++ /dev/null
@@ -1,39 +0,0 @@
-function [root,fx,ea,iter]=bisect(func,xl,xu,es,maxit,varargin)
-% bisect: root location zeroes
-% [root,fx,ea,iter]=bisect(func,xl,xu,es,maxit,p1,p2,...):
-% uses bisection method to find the root of func
-% input:
-% func = name of function
-% xl, xu = lower and upper guesses
-% es = desired relative error (default = 0.0001%)
-% maxit = maximum allowable iterations (default = 50)
-% p1,p2,... = additional parameters used by func
-% output:
-% root = real root
-% fx = function value at root
-% ea = approximate relative error (%)
-% iter = number of iterations
-if nargin<3,error('at least 3 input arguments required'),end
-test = func(xl,varargin{:})*func(xu,varargin{:});
-if test>0,error('no sign change'),end
-if nargin<4|isempty(es), es=0.0001;end
-if nargin<5|isempty(maxit), maxit=50;end
-iter = 0; xr = xl; ea = 100;
-while (1)
- xrold = xr;
- xr = (xl + xu)/2;
- % xr = (xl + xu)/2; % bisect method
- xr=xu - (f_m(xu)*(xl-xu))/(f_m(xl)-f_m(xu)); % false position method
- iter = iter + 1;
- if xr ~= 0,ea = abs((xr - xrold)/xr) * 100;end
- test = func(xl,varargin{:})*func(xr,varargin{:});
- if test < 0
- xu = xr;
- elseif test > 0
- xl = xr;
- else
- ea = 0;
- end
- if ea <= es | iter >= maxit,break,end
-end
-root = xr; fx = func(xr, varargin{:});
diff --git a/lecture_06/incsearch.m b/lecture_06/incsearch.m
deleted file mode 100644
index bd82554..0000000
--- a/lecture_06/incsearch.m
+++ /dev/null
@@ -1,37 +0,0 @@
-function xb = incsearch(func,xmin,xmax,ns)
-% incsearch: incremental search root locator
-% xb = incsearch(func,xmin,xmax,ns):
-% finds brackets of x that contain sign changes
-% of a function on an interval
-% input:
-% func = name of function
-% xmin, xmax = endpoints of interval
-% ns = number of subintervals (default = 50)
-% output:
-% xb(k,1) is the lower bound of the kth sign change
-% xb(k,2) is the upper bound of the kth sign change
-% If no brackets found, xb = [].
-if nargin < 3, error('at least 3 arguments required'), end
-if nargin < 4, ns = 50; end %if ns blank set to 50
-% Incremental search
-x = linspace(xmin,xmax,ns);
-f = func(x);
-nb = 0; xb = []; %xb is null unless sign change detected
-%for k = 1:length(x)-1
-% if sign(f(k)) ~= sign(f(k+1)) %check for sign change
-% nb = nb + 1;
-% xb(nb,1) = x(k);
-% xb(nb,2) = x(k+1);
-% end
-%end
-sign_change = diff(sign(f));
-[~,i_change] = find(sign_change~=0);
-nb=length(i_change);
-xb=[x(i_change)',x(i_change+1)'];
-
-if isempty(xb) %display that no brackets were found
- fprintf('no brackets found\n')
- fprintf('check interval or increase ns\n')
-else
- fprintf('number of brackets: %i\n',nb) %display number of brackets
-end
diff --git a/lecture_06/lecture_06.ipynb b/lecture_06/lecture_06.ipynb
deleted file mode 100644
index f44f84c..0000000
--- a/lecture_06/lecture_06.ipynb
+++ /dev/null
@@ -1,834 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "%plot --format svg"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "my_caller.m\n",
- "```matlab\n",
- "function [vx,vy] = my_caller(max_time)\n",
- " N=100;\n",
- " t=linspace(0,max_time,N);\n",
- " [x,y]=my_function(max_time);\n",
- " vx=diff(x)./diff(t);\n",
- " vy=diff(y)./diff(t);\n",
- "end\n",
- "```\n",
- "\n",
- "my_function.m\n",
- "```matlab\n",
- "function [x,y] = my_function(max_time)\n",
- " N=100;\n",
- " t=linspace(0,max_time,N);\n",
- " x=t.^2;\n",
- " y=2*t;\n",
- "end\n",
- "```\n",
- "\n",
- "In order to use `my_caller.m` where does `my_function.m` need to be saved?\n",
- "![responses](q1.png)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "\n",
- "What cool personal projects are you working on?\n",
- "While we delve deeper into Matlab functions, could we review some of the basic logic\n",
- "operators it uses and command codes. \n",
- "\n",
- "I still dont know when these forms are technically due. \n",
- " \n",
- " -by the following lecture\n",
- "\n",
- "I'm having trouble interfacing Atom with GitHub. Is there a simple tutorial for this?\n",
- " \n",
- " -Mac? Seems there could be a bug that folks are working on\n",
- "\n",
- "What are the bear necessities of life? \n",
- "please go over how to \"submit\" the homeworks because it is still confusing\n",
- "\n",
- "Do you prefer Matlab or Octave?\n",
- " \n",
- " -octave is my preference, but Matlab has some benefits\n",
- "\n",
- "Would you consider a country to be open-source?\n",
- " \n",
- " -??\n",
- "\n",
- "Is there a way to download matlab for free?\n",
- " \n",
- " -not legally\n",
- "\n",
- "how do you add files to current folder in matlab?\n",
- " \n",
- " -you can do this either through a file browser or cli\n",
- "\n",
- "How should Homework 2 be submitted? By simply putting the function into the homework_1\n",
- "repository?\n",
- " \n",
- " -yes\n",
- " \n",
- "How can we tell that these forms are being received?\n",
- " \n",
- " -when you hit submit, the form says \"form received\"\n",
- " \n",
- "can you save scripted outputs from matlab/octave as an excel file?\n",
- " \n",
- " -yes, easy way is open a file with a .csv extension then fprintf and separate everything with commas, harder way is to use the `xlswrite`\n",
- " \n",
- "\n",
- "Also, can you update your notes to show what happens when these things are run, as you do\n",
- "in class?\"\n",
- " \n",
- " -I always update the lecture notes after class so they should display what we did in class\n",
- " \n",
- "I have a little difficulty following along in class on my laptop when you have programs\n",
- "pre-written. Maybe if you posted those codes on Github so I could copy them when you\n",
- "switch to different desktops I would be able to follow along better.\n",
- "\n",
- "Kirk or Picard?\n",
- " \n",
- " -Kirk\n",
- " \n",
- "Who is our TA?\n",
- " \n",
- " -Peiyu Zhang peiyu.zhang@uconn.edu\n",
- "\n",
- "Can we download libraries of data like thermodynamic tables into matlab?\n",
- " \n",
- "-YES! [Matlab Steam Tables](http://bit.ly/2kZygu8)\n",
- "\n",
- "Will we use the Simulink addition to Matlab? I found it interesting and useful for\n",
- "evaluating ODEs in Linear systems.\n",
- " \n",
- " -not in this class, everything in simulink has a matlab script/function that can be substituted, but many times its hidden by the gui. Here we want to look directly at our solvers\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Roots and Optimization\n",
- "## Bracketing ch. 5"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "When you are given a function, numerical or analytical, it's not always possible to solve directly for a given variable. \n",
- "\n",
- "Even for the freefall example we first explored, \n",
- "\n",
- "$v(t)=\\sqrt{\\frac{gm}{c_{d}}}\\tanh(\\sqrt{\\frac{gc_{d}}{m}}t)$\n",
- "\n",
- "There is no way to solve for m in terms of the other variables. \n",
- "\n",
- "Instead, we can solve the problem by creating a new function f(m) where\n",
- "\n",
- "$f(m)=\\sqrt{\\frac{gm}{c_{d}}}\\tanh(\\sqrt{\\frac{gc_{d}}{m}}t)-v(t)$. \n",
- "\n",
- "When f(m) = 0, we have solved for m in terms of the other variables (e.g. for a given time, velocity, drag coefficient and acceleration due to gravity)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/svg+xml": [
- ""
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "setdefaults\n",
- "g=9.81; % acceleration due to gravity\n",
- "m=linspace(50, 200,100); % possible values for mass 50 to 200 kg\n",
- "c_d=0.25; % drag coefficient\n",
- "t=4; % at time = 4 seconds\n",
- "v=36; % speed must be 36 m/s\n",
- "f_m = @(m) sqrt(g*m/c_d).*tanh(sqrt(g*c_d./m)*t)-v; % anonymous function f_m\n",
- "\n",
- "plot(m,f_m(m),m,zeros(length(m),1))\n",
- "axis([45 200 -5 1])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans = 0.045626\r\n"
- ]
- }
- ],
- "source": [
- "f_m(145)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Brute force method is plot f_m vs m and with smaller and smaller steps until f_m ~ 0\n",
- "\n",
- "Better methods are the \n",
- "1. Bracketing methods\n",
- "2. Open methods\n",
- "\n",
- "Both need an initial guess. \n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Incremental method (Brute force)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "You know that for one value, m_lower, f_m is negative and for another value, m_upper, f_m is positive. \n",
- "\n",
- "```matlab\n",
- "function xb = incsearch(func,xmin,xmax,ns)\n",
- "% incsearch: incremental search root locator\n",
- "% xb = incsearch(func,xmin,xmax,ns):\n",
- "% finds brackets of x that contain sign changes\n",
- "% of a function on an interval\n",
- "% input:\n",
- "% func = name of function\n",
- "% xmin, xmax = endpoints of interval\n",
- "% ns = number of subintervals (default = 50)\n",
- "% output:\n",
- "% xb(k,1) is the lower bound of the kth sign change\n",
- "% xb(k,2) is the upper bound of the kth sign change\n",
- "% If no brackets found, xb = [].\n",
- "if nargin < 3, error('at least 3 arguments required'), end\n",
- "if nargin < 4, ns = 50; end %if ns blank set to 50\n",
- "% Incremental search\n",
- "x = linspace(xmin,xmax,ns);\n",
- "f = func(x);\n",
- "nb = 0; xb = []; %xb is null unless sign change detected\n",
- "for k = 1:length(x)-1\n",
- " if sign(f(k)) ~= sign(f(k+1)) %check for sign change\n",
- " nb = nb + 1;\n",
- " xb(nb,1) = x(k);\n",
- " xb(nb,2) = x(k+1);\n",
- " end\n",
- "end\n",
- "if isempty(xb) %display that no brackets were found\n",
- " fprintf('no brackets found\\n')\n",
- " fprintf('check interval or increase ns\\n')\n",
- "else\n",
- " fprintf('number of brackets: %i\\n',nb) %display number of brackets\n",
- "end\n",
- "```"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "'incsearch' is a function from the file /home/ryan/Documents/UConn/ME3255/me3255_S2017/lecture_06/incsearch.m\n",
- "\n",
- " incsearch: incremental search root locator\n",
- " xb = incsearch(func,xmin,xmax,ns):\n",
- " finds brackets of x that contain sign changes\n",
- " of a function on an interval\n",
- " input:\n",
- " func = name of function\n",
- " xmin, xmax = endpoints of interval\n",
- " ns = number of subintervals (default = 50)\n",
- " output:\n",
- " xb(k,1) is the lower bound of the kth sign change\n",
- " xb(k,2) is the upper bound of the kth sign change\n",
- " If no brackets found, xb = [].\n",
- "\n",
- "\n",
- "Additional help for built-in functions and operators is\n",
- "available in the online version of the manual. Use the command\n",
- "'doc ' to search the manual index.\n",
- "\n",
- "Help and information about Octave is also available on the WWW\n",
- "at http://www.octave.org and via the help@octave.org\n",
- "mailing list.\n"
- ]
- }
- ],
- "source": [
- "help incsearch"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 24,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "no brackets found\n",
- "check interval or increase ns\n",
- "ans = [](1x0)\n"
- ]
- }
- ],
- "source": [
- "incsearch(f_m,50, 200,55)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Bisection method"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Divide interval in half until error is reduced to some level\n",
- "\n",
- "in previous example of freefall, choose x_l=50, x_u=200\n",
- "\n",
- "x_r = (50+200)/2 = 125\n",
- "\n",
- "f_m(125) = -0.408\n",
- "\n",
- "x_r= (125+200)/2 = 162.5\n",
- "\n",
- "f_m(162.5) = 0.3594\n",
- "\n",
- "x_r = (125+162.5)/2=143.75\n",
- "\n",
- "f_m(143.75)= 0.0206"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ans = 0.020577\r\n"
- ]
- }
- ],
- "source": [
- "f_m(143.75)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Much better root locator, with 4 iterations, our function is already close to zero\n",
- "\n",
- "Automate this with a function:\n",
- "`bisect.m`\n",
- "\n",
- "```matlab\n",
- "function [root,fx,ea,iter]=bisect(func,xl,xu,es,maxit,varargin)\n",
- "% bisect: root location zeroes\n",
- "% [root,fx,ea,iter]=bisect(func,xl,xu,es,maxit,p1,p2,...):\n",
- "% uses bisection method to find the root of func\n",
- "% input:\n",
- "% func = name of function\n",
- "% xl, xu = lower and upper guesses\n",
- "% es = desired relative error (default = 0.0001%)\n",
- "% maxit = maximum allowable iterations (default = 50)\n",
- "% p1,p2,... = additional parameters used by func\n",
- "% output:\n",
- "% root = real root\n",
- "% fx = function value at root\n",
- "% ea = approximate relative error (%)\n",
- "% iter = number of iterations\n",
- "if nargin<3,error('at least 3 input arguments required'),end\n",
- "test = func(xl,varargin{:})*func(xu,varargin{:});\n",
- "if test>0,error('no sign change'),end\n",
- "if nargin<4|isempty(es), es=0.0001;end\n",
- "if nargin<5|isempty(maxit), maxit=50;end\n",
- "iter = 0; xr = xl; ea = 100;\n",
- "while (1)\n",
- " xrold = xr;\n",
- " xr = (xl + xu)/2;\n",
- " iter = iter + 1;\n",
- " if xr ~= 0,ea = abs((xr - xrold)/xr) * 100;end\n",
- " test = func(xl,varargin{:})*func(xr,varargin{:});\n",
- " if test < 0\n",
- " xu = xr;\n",
- " elseif test > 0\n",
- " xl = xr;\n",
- " else\n",
- " ea = 0;\n",
- " end\n",
- " if ea <= es | iter >= maxit,break,end\n",
- "end\n",
- "root = xr; fx = func(xr, varargin{:});\n",
- "```"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## False position (linear interpolation)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Rather than bisecting each bracket (1/2 each time) we can calculate the slope between the two points and update the xr position in this manner\n",
- "\n",
- "$ x_{r} = x_{u} - \\frac{f(x_{u})(x_{l}-x_{u})}{f(x_{l})-f(x_{u})}$"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/svg+xml": [
- ""
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "xl=50; xu=200; \n",
- "xr=xu - (f_m(xu)*(xl-xu))/(f_m(xl)-f_m(xu));\n",
- "\n",
- "plot(m,f_m(m),xl,f_m(xl),'s',xu,f_m(xu),'s',xr,0)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Much better root locator, with 4 iterations, our function is already close to zero\n",
- "\n",
- "Automate this with a function:\n",
- "`falsepos.m`\n",
- "\n",
- "```matlab\n",
- "function [root,fx,ea,iter]=falsepos(func,xl,xu,es,maxit,varargin)\n",
- "% falsepos: root location zeroes\n",
- "% [root,fx,ea,iter]=bisect(func,xl,xu,es,maxit,p1,p2,...):\n",
- "% uses false position method to find the root of func\n",
- "% input:\n",
- "% func = name of function\n",
- "% xl, xu = lower and upper guesses\n",
- "% es = desired relative error (default = 0.0001%)\n",
- "% maxit = maximum allowable iterations (default = 50)\n",
- "% p1,p2,... = additional parameters used by func\n",
- "% output:\n",
- "% root = real root\n",
- "% fx = function value at root\n",
- "% ea = approximate relative error (%)\n",
- "% iter = number of iterations\n",
- "if nargin<3,error('at least 3 input arguments required'),end\n",
- "test = func(xl,varargin{:})*func(xu,varargin{:});\n",
- "if test>0,error('no sign change'),end\n",
- "if nargin<4|isempty(es), es=0.0001;end\n",
- "if nargin<5|isempty(maxit), maxit=50;end\n",
- "iter = 0; xr = xl; ea = 100;\n",
- "while (1)\n",
- " xrold = xr;\n",
- " % xr = (xl + xu)/2; % bisect method\n",
- " xr=xu - (f_m(xu)*(xl-xu))/(f_m(xl)-f_m(xu)); % false position method\n",
- " iter = iter + 1;\n",
- " if xr ~= 0,ea = abs((xr - xrold)/xr) * 100;end\n",
- " test = func(xl,varargin{:})*func(xr,varargin{:});\n",
- " if test < 0\n",
- " xu = xr;\n",
- " elseif test > 0\n",
- " xl = xr;\n",
- " else\n",
- " ea = 0;\n",
- " end\n",
- " if ea <= es | iter >= maxit,break,end\n",
- "end\n",
- "root = xr; fx = func(xr, varargin{:});\n",
- "```"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Octave",
- "language": "octave",
- "name": "octave"
- },
- "language_info": {
- "file_extension": ".m",
- "help_links": [
- {
- "text": "MetaKernel Magics",
- "url": "https://github.com/calysto/metakernel/blob/master/metakernel/magics/README.md"
- }
- ],
- "mimetype": "text/x-octave",
- "name": "octave",
- "version": "0.19.14"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/lecture_06/lecture_06.md b/lecture_06/lecture_06.md
deleted file mode 100644
index b3d2266..0000000
--- a/lecture_06/lecture_06.md
+++ /dev/null
@@ -1,373 +0,0 @@
-
-
-```octave
-%plot --format svg
-```
-
-my_caller.m
-```matlab
-function [vx,vy] = my_caller(max_time)
- N=100;
- t=linspace(0,max_time,N);
- [x,y]=my_function(max_time);
- vx=diff(x)./diff(t);
- vy=diff(y)./diff(t);
-end
-```
-
-my_function.m
-```matlab
-function [x,y] = my_function(max_time)
- N=100;
- t=linspace(0,max_time,N);
- x=t.^2;
- y=2*t;
-end
-```
-
-In order to use `my_caller.m` where does `my_function.m` need to be saved?
-![responses](q1.png)
-
-
-What cool personal projects are you working on?
-While we delve deeper into Matlab functions, could we review some of the basic logic
-operators it uses and command codes.
-
-I still dont know when these forms are technically due.
-
- -by the following lecture
-
-I'm having trouble interfacing Atom with GitHub. Is there a simple tutorial for this?
-
- -Mac? Seems there could be a bug that folks are working on
-
-What are the bear necessities of life?
-please go over how to "submit" the homeworks because it is still confusing
-
-Do you prefer Matlab or Octave?
-
- -octave is my preference, but Matlab has some benefits
-
-Would you consider a country to be open-source?
-
- -??
-
-Is there a way to download matlab for free?
-
- -not legally
-
-how do you add files to current folder in matlab?
-
- -you can do this either through a file browser or cli
-
-How should Homework 2 be submitted? By simply putting the function into the homework_1
-repository?
-
- -yes
-
-How can we tell that these forms are being received?
-
- -when you hit submit, the form says "form received"
-
-can you save scripted outputs from matlab/octave as an excel file?
-
- -yes, easy way is open a file with a .csv extension then fprintf and separate everything with commas, harder way is to use the `xlswrite`
-
-
-Also, can you update your notes to show what happens when these things are run, as you do
-in class?"
-
- -I always update the lecture notes after class so they should display what we did in class
-
-I have a little difficulty following along in class on my laptop when you have programs
-pre-written. Maybe if you posted those codes on Github so I could copy them when you
-switch to different desktops I would be able to follow along better.
-
-Kirk or Picard?
-
- -Kirk
-
-Who is our TA?
-
- -Peiyu Zhang peiyu.zhang@uconn.edu
-
-Can we download libraries of data like thermodynamic tables into matlab?
-
--YES! [Matlab Steam Tables](http://bit.ly/2kZygu8)
-
-Will we use the Simulink addition to Matlab? I found it interesting and useful for
-evaluating ODEs in Linear systems.
-
- -not in this class, everything in simulink has a matlab script/function that can be substituted, but many times its hidden by the gui. Here we want to look directly at our solvers
-
-
-# Roots and Optimization
-## Bracketing ch. 5
-
-When you are given a function, numerical or analytical, it's not always possible to solve directly for a given variable.
-
-Even for the freefall example we first explored,
-
-$v(t)=\sqrt{\frac{gm}{c_{d}}}\tanh(\sqrt{\frac{gc_{d}}{m}}t)$
-
-There is no way to solve for m in terms of the other variables.
-
-Instead, we can solve the problem by creating a new function f(m) where
-
-$f(m)=\sqrt{\frac{gm}{c_{d}}}\tanh(\sqrt{\frac{gc_{d}}{m}}t)-v(t)$.
-
-When f(m) = 0, we have solved for m in terms of the other variables (e.g. for a given time, velocity, drag coefficient and acceleration due to gravity)
-
-
-```octave
-setdefaults
-g=9.81; % acceleration due to gravity
-m=linspace(50, 200,100); % possible values for mass 50 to 200 kg
-c_d=0.25; % drag coefficient
-t=4; % at time = 4 seconds
-v=36; % speed must be 36 m/s
-f_m = @(m) sqrt(g*m/c_d).*tanh(sqrt(g*c_d./m)*t)-v; % anonymous function f_m
-
-plot(m,f_m(m),m,zeros(length(m),1))
-axis([45 200 -5 1])
-```
-
-
-![svg](lecture_06_files/lecture_06_5_0.svg)
-
-
-
-```octave
-f_m(145)
-```
-
- ans = 0.045626
-
-
-Brute force method is plot f_m vs m and with smaller and smaller steps until f_m ~ 0
-
-Better methods are the
-1. Bracketing methods
-2. Open methods
-
-Both need an initial guess.
-
-
-## Incremental method (Brute force)
-
-You know that for one value, m_lower, f_m is negative and for another value, m_upper, f_m is positive.
-
-```matlab
-function xb = incsearch(func,xmin,xmax,ns)
-% incsearch: incremental search root locator
-% xb = incsearch(func,xmin,xmax,ns):
-% finds brackets of x that contain sign changes
-% of a function on an interval
-% input:
-% func = name of function
-% xmin, xmax = endpoints of interval
-% ns = number of subintervals (default = 50)
-% output:
-% xb(k,1) is the lower bound of the kth sign change
-% xb(k,2) is the upper bound of the kth sign change
-% If no brackets found, xb = [].
-if nargin < 3, error('at least 3 arguments required'), end
-if nargin < 4, ns = 50; end %if ns blank set to 50
-% Incremental search
-x = linspace(xmin,xmax,ns);
-f = func(x);
-nb = 0; xb = []; %xb is null unless sign change detected
-for k = 1:length(x)-1
- if sign(f(k)) ~= sign(f(k+1)) %check for sign change
- nb = nb + 1;
- xb(nb,1) = x(k);
- xb(nb,2) = x(k+1);
- end
-end
-if isempty(xb) %display that no brackets were found
- fprintf('no brackets found\n')
- fprintf('check interval or increase ns\n')
-else
- fprintf('number of brackets: %i\n',nb) %display number of brackets
-end
-```
-
-
-```octave
-help incsearch
-```
-
- 'incsearch' is a function from the file /home/ryan/Documents/UConn/ME3255/me3255_S2017/lecture_06/incsearch.m
-
- incsearch: incremental search root locator
- xb = incsearch(func,xmin,xmax,ns):
- finds brackets of x that contain sign changes
- of a function on an interval
- input:
- func = name of function
- xmin, xmax = endpoints of interval
- ns = number of subintervals (default = 50)
- output:
- xb(k,1) is the lower bound of the kth sign change
- xb(k,2) is the upper bound of the kth sign change
- If no brackets found, xb = [].
-
-
- Additional help for built-in functions and operators is
- available in the online version of the manual. Use the command
- 'doc ' to search the manual index.
-
- Help and information about Octave is also available on the WWW
- at http://www.octave.org and via the help@octave.org
- mailing list.
-
-
-
-```octave
-incsearch(f_m,50, 200,55)
-```
-
- no brackets found
- check interval or increase ns
- ans = [](1x0)
-
-
-## Bisection method
-
-Divide interval in half until error is reduced to some level
-
-in previous example of freefall, choose x_l=50, x_u=200
-
-x_r = (50+200)/2 = 125
-
-f_m(125) = -0.408
-
-x_r= (125+200)/2 = 162.5
-
-f_m(162.5) = 0.3594
-
-x_r = (125+162.5)/2=143.75
-
-f_m(143.75)= 0.0206
-
-
-```octave
-f_m(143.75)
-```
-
- ans = 0.020577
-
-
-Much better root locator, with 4 iterations, our function is already close to zero
-
-Automate this with a function:
-`bisect.m`
-
-```matlab
-function [root,fx,ea,iter]=bisect(func,xl,xu,es,maxit,varargin)
-% bisect: root location zeroes
-% [root,fx,ea,iter]=bisect(func,xl,xu,es,maxit,p1,p2,...):
-% uses bisection method to find the root of func
-% input:
-% func = name of function
-% xl, xu = lower and upper guesses
-% es = desired relative error (default = 0.0001%)
-% maxit = maximum allowable iterations (default = 50)
-% p1,p2,... = additional parameters used by func
-% output:
-% root = real root
-% fx = function value at root
-% ea = approximate relative error (%)
-% iter = number of iterations
-if nargin<3,error('at least 3 input arguments required'),end
-test = func(xl,varargin{:})*func(xu,varargin{:});
-if test>0,error('no sign change'),end
-if nargin<4|isempty(es), es=0.0001;end
-if nargin<5|isempty(maxit), maxit=50;end
-iter = 0; xr = xl; ea = 100;
-while (1)
- xrold = xr;
- xr = (xl + xu)/2;
- iter = iter + 1;
- if xr ~= 0,ea = abs((xr - xrold)/xr) * 100;end
- test = func(xl,varargin{:})*func(xr,varargin{:});
- if test < 0
- xu = xr;
- elseif test > 0
- xl = xr;
- else
- ea = 0;
- end
- if ea <= es | iter >= maxit,break,end
-end
-root = xr; fx = func(xr, varargin{:});
-```
-
-## False position (linear interpolation)
-
-Rather than bisecting each bracket (1/2 each time) we can calculate the slope between the two points and update the xr position in this manner
-
-$ x_{r} = x_{u} - \frac{f(x_{u})(x_{l}-x_{u})}{f(x_{l})-f(x_{u})}$
-
-
-```octave
-xl=50; xu=200;
-xr=xu - (f_m(xu)*(xl-xu))/(f_m(xl)-f_m(xu));
-
-plot(m,f_m(m),xl,f_m(xl),'s',xu,f_m(xu),'s',xr,0)
-```
-
-
-![svg](lecture_06_files/lecture_06_18_0.svg)
-
-
-Much better root locator, with 4 iterations, our function is already close to zero
-
-Automate this with a function:
-`falsepos.m`
-
-```matlab
-function [root,fx,ea,iter]=falsepos(func,xl,xu,es,maxit,varargin)
-% falsepos: root location zeroes
-% [root,fx,ea,iter]=bisect(func,xl,xu,es,maxit,p1,p2,...):
-% uses false position method to find the root of func
-% input:
-% func = name of function
-% xl, xu = lower and upper guesses
-% es = desired relative error (default = 0.0001%)
-% maxit = maximum allowable iterations (default = 50)
-% p1,p2,... = additional parameters used by func
-% output:
-% root = real root
-% fx = function value at root
-% ea = approximate relative error (%)
-% iter = number of iterations
-if nargin<3,error('at least 3 input arguments required'),end
-test = func(xl,varargin{:})*func(xu,varargin{:});
-if test>0,error('no sign change'),end
-if nargin<4|isempty(es), es=0.0001;end
-if nargin<5|isempty(maxit), maxit=50;end
-iter = 0; xr = xl; ea = 100;
-while (1)
- xrold = xr;
- % xr = (xl + xu)/2; % bisect method
- xr=xu - (f_m(xu)*(xl-xu))/(f_m(xl)-f_m(xu)); % false position method
- iter = iter + 1;
- if xr ~= 0,ea = abs((xr - xrold)/xr) * 100;end
- test = func(xl,varargin{:})*func(xr,varargin{:});
- if test < 0
- xu = xr;
- elseif test > 0
- xl = xr;
- else
- ea = 0;
- end
- if ea <= es | iter >= maxit,break,end
-end
-root = xr; fx = func(xr, varargin{:});
-```
-
-
-```octave
-
-```
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