- Define the satisfaction thresholds u1 and u2 for populations 1 and 2, respectively.
- Calculate the number of neighbours of each type surrounding each cell.
- Move unsatisfied occupants to empty cells until all occupants are satisfied or no more moves can be made.
how to set up two different populations in a segregation model code?
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I have a general code for the segregation model like the following:
%% n = grid_size;
grid_size = 50;
n = grid_size;
n2 = n^2;
grids = zeros(n);
emp = round((percent_empty/100)*n2);
two = round((percent_two/100)*n2);
tot = emp + two;
rand_loc = randperm(n2);
init_emp = rand_loc(1:emp);
init_two = rand_loc(emp+1:tot);
init_one = rand_loc(tot+1:end);
grids(init_emp) = 3;
grids(init_two) = 2;
grids(init_one) = 1;
figure, imagesc(grids), colorbar, axis([1 n 1 n]);
% frame = getframe;
% writeVideo(writerObj,frame);
how could I insert two populations in this code, that is population 1 are unsatis ed with their location if the number of their neighbours that are from population 2 is u1 or higher, and population 2 occupants are unsatis ed with their location if the number of their neighbours that are from population 1 is u2 or higher. Beside this, p1+p2 is less than 100; the rest can be empty.
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Answers (1)
Abhinaya Kennedy
on 15 Feb 2024
Hi,
To modify the existing code to include two populations with specific satisfaction conditions, you would need to add functionality to:
Here's an outline of how you can modify the code to include these steps:
% Define the grid size and the percentages for each population
grid_size = 50;
percent_empty = 10; % You can set this value as needed
percent_one = 45; % Population 1 percentage
percent_two = 45; % Population 2 percentage
% Define satisfaction thresholds
u1 = 3; % Threshold for population 1
u2 = 3; % Threshold for population 2
% Initialize the grid
n = grid_size;
n2 = n^2;
grids = zeros(n);
% Calculate the number of each type
emp = round((percent_empty/100)*n2);
one = round((percent_one/100)*n2);
two = round((percent_two/100)*n2);
% Randomly assign initial locations
rand_loc = randperm(n2);
init_emp = rand_loc(1:emp);
init_one = rand_loc(emp+1:emp+one);
init_two = rand_loc(emp+one+1:end);
% Fill the grid with populations and empty spaces
grids(init_emp) = 0; % Empty cells
grids(init_one) = 1; % Population 1
grids(init_two) = 2; % Population 2
% Display the initial grid
figure, imagesc(grids), colorbar, axis square;
% Main loop to move unsatisfied occupants
max_iterations = 1000; % Set a maximum number of iterations to prevent infinite loop
iteration = 0;
while iteration < max_iterations
iteration = iteration + 1;
moved = false;
for x = 1:n
for y = 1:n
if ~check_satisfaction(grids, x, y, u1, u2)
% Find an empty cell to move to
empty_cells = find(grids == 0);
if ~isempty(empty_cells)
new_loc = empty_cells(randi(length(empty_cells)));
grids(new_loc) = grids(x, y); % Move occupant to the new location
grids(x, y) = 0; % Set old location to empty
moved = true;
end
end
end
end
% Update the display
figure, imagesc(grids), colorbar, axis square;
% If no one moved in this iteration, everyone is satisfied
if ~moved
break;
end
end
% Display the final grid
figure, imagesc(grids), colorbar, axis square;
% Function definitions must appear at the end of the file
% Function to calculate the number of neighbors of a given type
function count = count_neighbors(grids, x, y, neighbor_type)
[rows, cols] = size(grids);
count = 0;
for i = -1:1
for j = -1:1
if ~(i == 0 && j == 0) && x+i > 0 && x+i <= rows && y+j > 0 && y+j <= cols
if grids(x+i, y+j) == neighbor_type
count = count + 1;
end
end
end
end
end
% Function to determine if an occupant is satisfied
function is_satisfied = check_satisfaction(grids, x, y, u1, u2)
if grids(x, y) == 1
is_satisfied = count_neighbors(grids, x, y, 2) < u1;
elseif grids(x, y) == 2
is_satisfied = count_neighbors(grids, x, y, 1) < u2;
else
is_satisfied = true;
end
end
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