Homework 1: Extending polynomial
the other way
Extend the original polynomial function to the case where x
is a square matrix. Create a function called circlemat
, that returns nxn
matrix $A(n)$ with the following elements
\[\left[A(n)\right]_{ij} = \begin{cases} 1 &\text{if } (i = j-1 \land j > 1) \lor (i = n \land j=1) \\ 1 &\text{if } (i = j+1 \land j < n) \lor (i = 1 \land j=n) \\ 0 & \text{ otherwise} \end{cases}\]
and evaluate the polynomial
\[f(A) = I + A + A^2 + A^3.\]
, at point $A = A(10)$.
HINTS for matrix definition: You can try one of these options:
- create matrix with all zeros with
zeros(n,n)
, use two nested for loops going in ranges1:n
and if condition with logical or||
, and&&
- employ array comprehension with nested loops
[expression for i in 1:n, j in 1:n]
and ternary operatorcondition ? true branch : false
HINTS for polynomial
extension:
- extend the original example (one with for-loop) to initialize the
accumulator
variable with matrix of proper size (usesize
function to get the dimension), using argument typing forx
is preferred to distinguish individual implementations<: AbstractMatrix
or
- test later defined
polynomial
methods, that may work out of the box
Solution:
Nothing to see here.
Install GraphRecipes
and Plots
packages into the environment defined during the lecture and figure out, how to plot the graph defined by adjacency matrix A
from the homework.
HINTS:
- There is help command inside the the pkg mod of the REPL. Type
? add
to find out how to install a package. Note that both pkgs are registered. - Follow a guide in the
Plots
pkg's documentation, which is accessible throughdocs
icon on top of the README in the GitHub repository. Direct link.
Solution:
Activate the environment in pkg mode, if it is not currently active.
pkg> activate .
Installing pkgs is achieved using the add
command. Running ] ? add
returns a short piece of documentation for this command:
pkg> ? add
[...]
Examples
pkg> add Example # most commonly used for registered pkgs (installs usually the latest release)
pkg> add Example@0.5 # install with some specific version (realized through git tags)
pkg> add Example#master # install from master branch directly
pkg> add Example#c37b675 # install from specific git commit
pkg> add https://github.com/JuliaLang/Example.jl#master # install from specific remote repository (when pkg is not registered)
pkg> add git@github.com:JuliaLang/Example.jl.git # same as above but using the ssh protocol
pkg> add Example=7876af07-990d-54b4-ab0e-23690620f79a # when there are multiple pkgs with the same name
As the both Plots
and GraphRecipes
are registered and we don't have any version requirements, we will use the first option.
pkg> add Plots
pkg> add GraphRecipes
This process downloads the pkgs and triggers some build steps, if for example some binary dependencies are needed. The process duration depends on the "freshness" of Julia installation and the size of each pkg. With Plots
being quite dependency heavy, expect few minutes. After the installation is complete we can check the updated environment with the status
command.
pkg> status
The plotting itself as easy as calling the graphplot
function on our adjacency matrix.
julia> using GraphRecipes, Plots
julia> graphplot(A)
Plot{Plots.GRBackend() n=21} Captured extra kwargs: Series{1}: num_edges_nodes: (10, 10) Series{2}: num_edges_nodes: (10, 10) Series{3}: num_edges_nodes: (10, 10) Series{4}: num_edges_nodes: (10, 10) Series{5}: num_edges_nodes: (10, 10) Series{6}: num_edges_nodes: (10, 10) Series{7}: num_edges_nodes: (10, 10) Series{8}: num_edges_nodes: (10, 10) Series{9}: num_edges_nodes: (10, 10) Series{10}: num_edges_nodes: (10, 10)
How to submit?
Isolate the code of the compulsory task into a script named hw.jl
alongside with the Project.toml
and Manifest.toml
of the environment. Create a zipfile of the folder and send it to the lab instructor, who has assigned the task, via email (contact emails are located on the homepage of the course).