93 lines
3.4 KiB
Python
93 lines
3.4 KiB
Python
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# Title: Project 2 - Run the model
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# Author: Rory Healy
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# Date created - 9th May 2019
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# Create global variables to be accessed in multiple functions.
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times_iterated = 0
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current_state = []
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previous_state = []
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b_grid_initial = []
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def create_b_grid(f_grid, burn_seeds):
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'''Creates a matrix of size M, b_grid, which indicates whether a cell is
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currently burning or not.'''
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b_grid = []
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for row in range(len(f_grid)):
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b_grid.append([])
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for column in range(len(f_grid)):
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b_grid[row].append([])
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for cell in burn_seeds:
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for row in range(len(b_grid)):
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for column in range(len(b_grid)):
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if (row, column) == cell:
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b_grid[row].remove([])
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b_grid[row].append(True)
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else:
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b_grid[row].remove([])
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b_grid[row].append(False)
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return b_grid
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def iterate_time(f_grid, h_grid, i_threshold, w_direction, b_grid):
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'''Takes the conditions of the current state and iterates the grid so that
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exactly 1 unit of time passes. Returns a list of the updated f_grid and
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burn_seeds.'''
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global current_state
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# Creates a new b_grid and f_grid to be returned. Updates b_grid_new and
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# f_grid_new to match the changes in the next timestep.
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b_grid_new = b_grid
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f_grid_new = f_grid
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for cell in f_grid:
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i = cell[0]
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j = cell[1]
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if check_ignition(b_grid, f_grid, h_grid, i_threshold, w_direction, i,
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j) is True:
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f_grid_new[cell] -= 1
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for row in b_grid_new:
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for column in b_grid_new:
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b_grid_new[row][column] = True
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current_state = [f_grid_new, b_grid_new]
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return current_state
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def run_model(f_grid, h_grid, i_threshold, w_direction, burn_seeds):
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'''Takes the initial conditions as given above and returns a tuple
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containing the final state of the grid once the fire has gone out, and the
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total number of cells that were burned.'''
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global times_iterated
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global current_state
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global previous_state
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global b_grid_initial
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# Calls iterate_time for the first time in order to generate a new value
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# for current_state to be compared to the previous state.
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if times_iterated == 0:
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b_grid = create_b_grid(f_grid, burn_seeds)
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b_grid_initial = create_b_grid(f_grid, burn_seeds)
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current_state = [f_grid, b_grid]
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times_iterated = 1
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previous_state = current_state
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current_state = iterate_time(f_grid, h_grid, i_threshold, w_direction,
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b_grid)
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# Either returns the final state and total burned cells, or continues to
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# the next timestep and calls run_model again, repeating until the states
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# aren't changing anymore.
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elif current_state == previous_state:
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total_burned_cells = len(burn_seeds)
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for row in b_grid_initial:
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for cell in b_grid_initial:
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if cell == b_grid[row][cell]:
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total_burned_cells += 1
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return (current_state, total_burned_cells)
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else:
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times_iterated += 1
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previous_state = current_state
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current_state = iterate_time(f_grid, h_grid, i_threshold, w_direction,
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b_grid)
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run_model(f_grid, h_grid, i_threshold, w_direction, burn_seeds)
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