updates on docs

docs/src/examples/delta_competition_example.md

@@ -38,11 +38,11 @@ gplot(g, collect(1:nodes), collect(1:nodes))
 
 ## Defining competition processes
 We propose that any individual have a constant birth rate, and competes with all the individuals present in the same patch. Assume there are ``N_t`` individuals at time ``t``.
-Let ``i \in \{ 1,2,\dots,N_t\}``. ``x_{i,t} \in \{1,2,\dots,9\}`` denotes the position of the ``i``-th individual at time ``t``.
+Let ``i \in \{ 1,2,\dots,N_t\}``. ``x_{i} \in \{1,2,\dots,9\}`` denotes the position of the ``i``-th individual.
 The competition pressure experienced by individual ``i`` is such that
 
 ```math
-d(x_{i,t}) = \sum_j^{N(t)} \delta(x_{i,t}-x_{j,t})
+d(x_{i},t) = \sum_j^{N(t)} \delta(x_{i}-x_{j})
 ```
 where ``\delta`` is the dirac function.
 

docs/src/manual/gillepsie.md

@@ -16,7 +16,7 @@ A particular event, birth or death, is chosen at random with a probability equal
 ### Time steps
 An event is exponentiallly distributed in time, with parameter ``\lambda = U(t)``. This makes events memoryless, meaning that the probability of having a birth or death event is always the same, no matter when (``P(X > s_t | X > t) = P(X > s) ``.
 
-!!! tip "Inversion method"
+<!-- !!! tip "Inversion method"
     Let ``B(t) = \sum_i b_i(t)`` and  ``D(t) = \sum_i d_i(t)``. Let ``T_b, T_d`` the time for a birth or death event to occur. Then we have ``P(T_b < T_d) = \frac{B(t)}{B(t) + D(t)}``  (competing exponentials).
 
     Let ``U`` be an ``\mathcal{U}_{(0,1)}``-distributed random variable and ``F \colon \R \to [0,1]`` be a distribution function. Then we have
@@ -29,7 +29,7 @@ An event is exponentiallly distributed in time, with parameter ``\lambda = U(t)`
 
     ```math
         dt(\omega) = -\frac{\log(U(\omega))}{R(t)} \iff X(\omega) = \exp(-U(t)dt(\omega))
-    ```
+    ``` -->
 
 ```@autodocs
 Modules = [ABMEv]

src/ABMEv_world.jl

@@ -91,3 +91,14 @@ function get_xarray(world::World,geotrait::Bool=false)
     return xarray
 end
 @deprecate get_xarray(world,geotrait=false) get_x(world,Colon())
+
+"""
+    function give_birth(mum_idx::Int,w::World)
+Copies agent within index `mum_idx`, and increment it by dx.
+Return new agent (offspring).
+"""
+function give_birth(mum_idx::Int,w::World)
+    new_a = copyxt(w[mum_idx])
+    increment_x!(new_a,space(w),parameters(w),time(w))
+    return new_a
+end

src/algo/ABMEv_Gillepsie.jl

@@ -5,15 +5,6 @@ $(TYPEDEF)
 """
 struct Gillepsie <: AbstractAlg end
 export Gillepsie
-"""
-    function give_birth(a::Agent,t,p::Dict)
-Used for Gillepsie setting
-"""
-function give_birth(mum_idx::Int,w::World)
-    new_a = copyxt(w[mum_idx])
-    increment_x!(new_a,space(w),parameters(w),time(w))
-    return new_a
-end
 
 function updateBirthEvent!(w::World,::Gillepsie,mum_idx::Int,b,d)
     # updating competition only the two columns corresponding to agent idx