You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: README.md
+12-12Lines changed: 12 additions & 12 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -33,7 +33,7 @@ This module assumes familiarity with basic programming concepts such as floating
33
33
### Accessing the Module
34
34
### **On MATLAB Online:**
35
35
36
-
Use the [<imgsrc="Images/OpenInMO.png"width="136"alt="OpenInMO.png">](https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Numerical-Methods-with-Applications&project=NumericalMethods.prj) link to download the module. You will be prompted to log in or create a MathWorks account. The project will be loaded, and you will see an app with several navigation options to get you started.
36
+
Use the [<imgsrc="Images/OpenInMO.png"width="136"alt="OpenInMO.png">](https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Numerical-Methods-with-Applications&project=NumericalMethods.prj&file=README.mlx) link to download the module. You will be prompted to log in or create a MathWorks account. The project will be loaded, and you will see an app with several navigation options to get you started.
37
37
38
38
### **On Desktop:**
39
39
@@ -57,26 +57,26 @@ MATLAB® is used throughout. Tools from the Symbolic Math Toolbox™ are used fr
| <imgsrc="Images/NoisyDerivative.png"width="171"alt="NoisyDerivative.png"> <br> |**In this script, students will...** <br> <br> - determine numerical derivative approximations formulas <br>- use Taylor's theorem to calculate the order of the error for a numerical approximation to a derivative <br> - demonstrate how numerical derivatives can magnify approximation errors <br> |**Applications** <br>- Numerical solutions to differential equations <br> |
| <imgsrc="Images/BakerLakeSR.png"width="171"alt="BakerLakeSR.png"> <br> |**In this script, students will...** <br> <br> - implement Euler's method, Gaussian 2\-point approximations, and Simpson's rule for numerical integration <br> - explain why higher\-order approximations may not be appropriate in applications <br> |**Applications** <br> - Measure the area of a lake <br><br> **Scaffolded Template Scripts** <br> [<samp>eulerMethod.m</samp>](./FunctionLibrary/eulerMethod.m) <br> [<samp>gauss2pt.m</samp>](./FunctionLibrary/gauss2pt.m) <br> [<samp>simpsonsRule.m</samp>](./FunctionLibrary/simpsonsRule.m) <br> |
| <img src="Images/BakerLakeSR.png" width="171" alt="BakerLakeSR.png"> <br> | **In this script, students will...** <br> <br> - implement Euler's method, Gaussian 2\-point approximations, and Simpson's rule for numerical integration <br> - explain why higher\-order approximations may not be appropriate in applications <br> | **Applications** <br> - Measure the area of a lake <br><br> **Scaffolded Template Scripts** <br> [<samp>eulerMethod.m</samp>](https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Numerical-Methods-with-Applications&project=NumericalMethods.prj&file=FunctionLibrary/eulerMethod.m) <br> [<samp>gauss2pt.m</samp>](https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Numerical-Methods-with-Applications&project=NumericalMethods.prj&file=FunctionLibrary/gauss2pt.m) <br> [<samp>simpsonsRule.m</samp>](https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Numerical-Methods-with-Applications&project=NumericalMethods.prj&file=FunctionLibrary/simpsonsRule.m) <br> |
| <imgsrc="Images/heatSoln.gif"width="171"alt="heatSoln.gif"> <br> |**In this script, students will...** <br> <br> - identify errors from discretizing the problem and from discretizing the method and choose appropriate parameters to minimize overall error <br> - explain the importance of stability when choosing a numerical method <br> - implement explicit, implicit, and Crank\-Nicolson methods to solve a 1\-D heat equation <br> |**Applications** <br> - Solve a heat equation <br><br> **Scaffolded Template Scripts** <br> [<samp>explicitPDE.m</samp>](./FunctionLibrary/explicitPDE.m) <br> [<samp>implicitPDE.m</samp>](./FunctionLibrary/implicitPDE.m) <br> [<samp>cnPDE.m</samp>](./FunctionLibrary/cnPDE.m) <br> |
| <img src="Images/heatSoln.gif" width="171" alt="heatSoln.gif"> <br> | **In this script, students will...** <br> <br> - identify errors from discretizing the problem and from discretizing the method and choose appropriate parameters to minimize overall error <br> - explain the importance of stability when choosing a numerical method <br> - implement explicit, implicit, and Crank\-Nicolson methods to solve a 1\-D heat equation <br> | **Applications** <br> - Solve a heat equation <br><br> **Scaffolded Template Scripts** <br> [<samp>explicitPDE.m</samp>](https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Numerical-Methods-with-Applications&project=NumericalMethods.prj&file=FunctionLibrary/explicitPDE.m) <br> [<samp>implicitPDE.m</samp>](https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Numerical-Methods-with-Applications&project=NumericalMethods.prj&file=FunctionLibrary/implicitPDE.m) <br> [<samp>cnPDE.m</samp>](https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Numerical-Methods-with-Applications&project=NumericalMethods.prj&file=FunctionLibrary/cnPDE.m) <br> |
0 commit comments