: Define a function and call on it for calculations. The Wednesday tutorial will involve using functions. Use of a `for` loop in code. Plotting several plots on the same axes, with legend and labels.
1.6
Dhruv: For the coding assignment for week 1.6, I believe the students should be brought up to speed with calculating the mean, root mean square (e2), obtaining the absolute value, maximum and minimum value inside an array (e_infinity) and creating a log log plot with a detailed legend. I believe that should be enough? They should be able to use these to write the small portion of code for calculating these errors and filling in the table?
**1.6**
Dhruv: For the coding assignment for week 1.6, I believe the students should be brought up to speed with calculating the mean, root mean square (e2), obtaining the absolute value, maximum and minimum value inside an array (e_infinity) and creating a log log plot with a detailed legend. I believe that should be enough? They should be able to use these to write the small portion of code for calculating these errors and filling in the table?
###Wed Tutorial
Justin: Curve fitting to a dataset. Part of the Friday project will also include producing a log-log plot and fitting a line to an array to find the coefficient.
1.5
### Wed Tutorial
1.6
**1.5**
Run left, right, midpoint Riemann sum of an integral. Derive by hand, use this to fill in notebook and determine integral estimates using different schemes.
**1.6**
Last year's archive is FD: 1D & 2D Diffusion using FD in python. Everything is provided and they can run and see the results. It's a read & understand assignment.
###Project
### Project
**1.5**
Derive Taylor series of an expression to 4 terms. Students transfer their discretization terms into pre-filled function and use this to start calculating values of Tayor estimate based on carrying 1-4 terms with a provided step-size. Plot the results along with the analytical solution of the expression. Comment on the results and their assessment of the situation.
1.5
Following this, use all four terms, but alter the step-size in the function and plot the results again, in comparison with the analytical result.
1.6
**1.6**
Derive the forward, backward schemes, and the Runge-Kutta (RK4) terms for a given expression. Use these terms in provided code to determine estimations of these methods compared to the analytical solution. Determine error values of numeric from analytic, and be able to assemble these in a list/array/table, plot a log-log plot, apply fit to estimate the exponent (dependent on order of discretization).
