Lab 02 update (#9)

Author: nmheim

src/Lab02Ecosystem.jl renamed to docs/src/lecture_02/Lab02Ecosystem.jl

@@ -96,6 +96,26 @@ food_prob(a::Animal) = a.food_prob
 energy!(a::Animal, e) = a.energy = e
 incr_energy!(a::Animal, Δe) = energy!(a, energy(a)+Δe)
 
+function Base.show(io::IO, g::Grass)
+    x = size(g)/max_size(g) * 100
+    print(io,"🌿 #$(id(g)) $(round(Int,x))% grown")
+end
+function Base.show(io::IO, w::Wolf)
+    e = energy(w)
+    d = Δenergy(w)
+    pr = reprprob(w)
+    pf = foodprob(w)
+    print(io,"🐺 #$(id(w)) E=$e ΔE=$d pr=$pr pf=$pf")
+end
+function Base.show(io::IO, s::Sheep)
+    e = energy(s)
+    d = Δenergy(s)
+    pr = reprprob(s)
+    pf = foodprob(s)
+    print(io,"🐑 #$(id(s)) E=$e ΔE=$d pr=$pr pf=$pf")
+end
+
+
 function eat!(a::Sheep, b::Grass, w::World)
     incr_energy!(a, size(b)*Δenergy(a))
     kill_agent!(b,w)

docs/src/lecture_02/hw.md

@@ -2,11 +2,11 @@
 
 In this lab you will continue working on your agent simulation. If you did not
 manage to finish the homework, do not worry, you can use [this
-script](https://github.com/JuliaTeachingCTU/Scientific-Programming-in-Julia/blob/master/src/Lab02Ecosystem.jl)
+script](https://github.com/JuliaTeachingCTU/Scientific-Programming-in-Julia/blob/master/docs/src/lecture_02/Lab02Ecosystem.jl)
 which contains all the functionality we developed in the lab.
 ```@setup hw02
 projdir = dirname(Base.active_project())
-include(joinpath(projdir,"..","src","Lab02Ecosystem.jl"))
+include(joinpath(projdir,"src","lecture_02","Lab02Ecosystem.jl"))
 ```
 
 ## How to submit?

docs/src/lecture_02/lab.md

@@ -15,14 +15,22 @@ In this lab we will first define what our agent simulation does on a high level.
 Then you will write the core methods for finding food (`find_food`),
 to specify what an animal eats (`eat!`), and how it reproduces (`reproduce!`).
 
+### High level-description
 In an agent simulation we assume that we have a bunch of agents (in our case
 grass, sheep, and wolves) that act in some environment (we will call it a
 *world*). At every iteration of the simulation each agent will perform a *step* in which it
 performs some of the actions that it can take. For example, a *grass* agent will grow
 a little at every step. A *sheep* agent will try to find some grass and
 reproduce.
 
-To get started we need a type hierarchy. The first abstract type `Agent` that
+In short:
+* Wolves, sheep, and grass exist in a one dimensional world `Dict(1=>🐺, 2=>🐑, 3=>🌿, 4=>🌿, ...)`
+  and are identified by a unique ID
+* Each agent can perform certain actions (eating, growing, reproducing, dying...)
+* In one iteration of the simulation each agent performs its actions
+
+### Code skeleton
+To get started we need a type hierarchy. The first abstract type `Agent`
 acts as the root of our tree.  All animals and plants will be subtypes of `Agent`.
 There are different kinds of animals and plants so it makes sense to create an
 `Animal` type which will be the supertype of all animals. The same is
@@ -154,6 +162,12 @@ nothing # hide
 The constructor for grass with random growth countdown:
 ```@example non_parametric_agents
 Grass(id,m) = Grass(id, rand(1:m), m)
+
+# optional: overload show function for Grass
+function Base.show(io::IO, g::Grass)
+    x = size(g)/max_size(g) * 100
+    print(io,"🌿 #$(id(g)) $(round(Int,x))% grown")
+end
 nothing # hide
 ```
 Creation of a world with a few grass agents:
@@ -196,6 +210,15 @@ foodprob(a::Animal) = a.foodprob
 # set field values
 energy!(a::Animal, e) = a.energy = e
 incr_energy!(a::Animal, Δe) = energy!(a, energy(a)+Δe)
+
+# optional: overload the show method for Sheep
+function Base.show(io::IO, s::Sheep)
+    e = energy(s)
+    d = Δenergy(s)
+    pr = reprprob(s)
+    pf = foodprob(s)
+    print(io,"🐑 #$(id(s)) E=$e ΔE=$d pr=$pr pf=$pf")
+end
 nothing # hide
 ```
 
@@ -285,6 +308,15 @@ function eat!(wolf::Wolf, sheep::Sheep, w::World)
 end
 
 kill_agent!(a::Animal, w::World) = delete!(w.agents, id(a))
+
+# optional: overload the show method for Wolf
+function Base.show(io::IO, w::Wolf)
+    e = energy(w)
+    d = Δenergy(w)
+    pr = reprprob(w)
+    pf = foodprob(w)
+    print(io,"🐺 #$(id(w)) E=$e ΔE=$d pr=$pr pf=$pf")
+end
 nothing # hide
 ```
 ```@raw html