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If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Lesser General Public License instead of this License. But first, please read . diff --git a/README.md b/README.md new file mode 100644 index 0000000..138215d --- /dev/null +++ b/README.md @@ -0,0 +1,12 @@ +# simple-bushfire-model + +A simple model of a bushfire spreading across a landscape represented as a 2D +grid. The model takes into account many factors, such as the amount and type of +fuel available, the slope of the land, the direction of the wind, and the +combustibility of the landscape, though only to a very limited extent and depth. +This model is then used to determine the optimal area to conduct a prescribed +burn to increase the chance that a town is not caught in the bushfire. + +This project is based on an assignment for COMP10001, a subject at The +University of Melbourne. The assignment specification can be found +[here](docs/SPECIFICATION.md). diff --git a/bf0.dat b/data/bushfire-0.txt similarity index 100% rename from bf0.dat rename to data/bushfire-0.txt diff --git a/bf.dat b/data/bushfire-1.txt similarity index 100% rename from bf.dat rename to data/bushfire-1.txt diff --git a/docs/SPECIFICATION.md b/docs/SPECIFICATION.md new file mode 100644 index 0000000..79bbc7c --- /dev/null +++ b/docs/SPECIFICATION.md @@ -0,0 +1,469 @@ +# Assignment Specification + +Below is the assignment specification, in full, slightly edited for context and +appearence. + +## Introduction + +Computers can be used to build models of complex real world systems such as the +weather, traffic and stockmarkets. Computer models can help us to understand the +dynamics of these real world systems, and to make decisions about them. For +example, a model that can predict Saturday's weather could help us decid +whether to go to the beach or not. A traffic model could help us plan where to +build a new road to reduce traffic jams. A model of the stockmarket could help +us decide when to buy and sell shares. + +In this project, you will build a simple model of a bushfire spreading across a +landscape represented as a two-dimensional grid. The speed and direction that a +bushfire will spread in is affected by many factors, including the amount and +type of fuel (trees) available, the slope of the land, and the direction of the +wind. Your model will help forecast how much damage (number of grid squares +burnt) a fire will do before it burns out. + +Models like this (but much more complicated!) are used to help predict which way +a fire might spread, to assess where high risk fires are most likely to occur, +and help understand how the damage cause by fires can be reduced via management +practices. See Phoenix rapid fire for an example of a much more complex model +(developed at the University of Melbourne). + +In this project we will look at three different problems related to a bushfire + +- How to build a bushfire model from a data file. +- How to determine if a cell in a specific location will ignite. +- How to model the spread of a bushfire. + +You will also need to write and submit a set of test cases for evaluating +the model. + +### The bushfire model + +We model a bushfire as occurring in a square grid made up of M by M cells. The +cell (i, j) refers to the cell in the ith row and the jth column of the grid. +Each cell typically has eight adjacent cells (horizontally, vertically and +diagonally). Cells on the edge of the grid are adjacent to only five other +cells; cells in the corners of the grid are adjacent to only three other cells. +For convenience, we take the top of the grid to be North, the right side to +East, the bottom to be South and the left side to be West. See +[images/bushfire_model.png](../images/bushfire_model.png) for reference. + +Each cell in the M by M grid has several attributes: + +- **fuel load**: the amount of combustible material (trees, leaf litter, etc) in + that cell. The fuel load of a cell is represented as a non-negative integer, + where 0 equates to no combustible material. +- **height**: the elevation of the cell. Height is represented as a positive + integer (a cell with height 3 is higher than a cell with height 2, which is in + turn higher than a cell with height 1, and so on). Fires will tend to spread + more rapidly uphill, and more slowly downhill, compared to flat ground. +- **burning**: a Boolean value indicating whether the cell is currently burning + or not. A cell can only be burning if it's fuel load is greater than 0. + +In addition, the entire grid is characterised by three further attributes: + +- **ignition threshold**: how combustible the landscape is (for instance, a dry + landscape would be more combustible than a wet landscape, and have a lower + ignition threshold). The ignition threshold is represented by an integer + greater than 0. A non-burning cell will start burning if its ignition + factor (explained below) is greater than or equal to the ignition threshold. +- **ignition factor**: the intensity of fire around a particular non-burning + cell at a given point in time that, in combination with the ignition threshold + described above, will be used to determine whether a cell will start burning. + The ignition factor is floating point number; details of how to calculate the + ignition factor are provided in the following sections. +- **wind direction**: if a wind is blowing, it can carry embers that allow a + fire to spread more rapidly in a particular direction. Wind may blow from one + fire to directions: North, Northeast, East, Southeast, South, Southwest, West + or Northwest (abbreviated N, NE, E, SE, S, SW, W, NW) or there may be no wind. + How the wind affects ignition will be explained further. + +## Part 1 - Parse a bushfire scenario file + +Your task is to write a function `parse_scenario(filename)` that parses a file +with the structure described below, validates the contents and returns either a +dictionary containing all values required to specify a model scenario if the +contents are valid, or `None` if any of the contents are invalid. + +The structure of the file is as follows: + +- an integer specifying the width and height (M) of the square landscape grid; +- M lines, each containing M integer values (separated by commas), defining the + initial fuel load of the landscape (a visual representation of the M by + M grid); +- M lines, each containing M integer values (separated by commas), defining the + height of the landscape (again, a visual representation of the M by M grid); +- an integer specifying the ignition threshold for this scenario; +- a one or two character string specifying the wind direction for this scenario + (or `None` if there is no wind); and +- one or more lines, each containing the (i, j) coordinates (row number, column + number) of a cell which is burning at the start of the simulation. + +For example, the file [bushfire-0.txt](../data/bushfire-0.txt) specifies a 2 by +2 landscape: + +- there is an initial fuel load of 2 in three of the four cells, with a fuel + load of 0 in the cell (1, 0); +- the height of all cells in the first column (j = 0) is 1, while the height of + all cells in the second column (j = 1) is 2 (i.e., the landscape slopes up + toward the East); +- the dimensions of the grid are a positive integer; +- the ignition threshold is a positive integer not greater than eight; +- the wind direction is valid; and +- the coordinates of the burning cells are (a) located on the landscape, and (b) + have non-zero initial fuel load. + +If all values are valid, your function should return a dictionary with key/value +pairs as follows: + +- `f_grid`: a list of lists (of dimensions M by M); +- `h_grid`: a list of lists (of dimensions M by M); +- `i_threshold`: an integer; +- `w_direction`: a string or `None`; and +- `burn_seeds`: a list of tuples. + +If there is no wind, `w_direction` can be either an empty string `''` or `None`. +If any values are invalid, your function should return `None`. + +For example: + + >>> parse_scenario('data/bushfire-0.txt') + + {'f_grid': [[2, 2], [0, 2]], 'h_grid': [[1, 2], [1, 2]], 'i_threshold': 1, 'w_direction': 'N', 'burn_seeds': [(0, 0)]} + + >>> parse_scenario('data/bushfire-1.txt') + + {'f_grid': [[1, 2, 1], [0, 1, 2], [0, 0, 1]], 'h_grid': [[1, 1, 1], [2, 1, 2], [3, 2, 2]], 'i_threshold': 1, 'w_direction': 'N', 'burn_seeds': [(1, 1)]} + +## Updating the model + +The state of the bushfire model is defined by the attributes (fuel load, height, +burning, ignition threshold and wind direction) described in a previous section. +Of these, fuel load and burning status may change over time as the bushfire +spreads. Height, ignition threshold and wind direction are fixed and never +change. + +The state of the model is updated in discrete timesteps, t = 0, 1, 2, ..., +and at each timestep, the following things happen: + +- If a cell is currently burning, it's fuel load will be reduced by one in the + following timestep. If this will result in its fuel load reaching zero, it + will stop burning in the following timestep. +- If a cell is not currently burning, it may start burning, depending on its + proximity to other cells which are burning in this timestep. The rules + describing how to determine if a cell catches fire are described in the + next section. + +Note, the future state of each cell in time t + 1 is determined on the basis of +the current state of the grid at time t. We stop updating the model when no +cells are burning, as the state will not change after this point. + +### Determining when a cell catches fire (simple) + +To determine whether a cell (i, j) catches fire, we calculate its ignition +factor and compare this to the landscape's ignition threshold. As stated above, +a cell will catch fire if its ignition factor is greater than or equal to the +ignition threshold. A cell must be currently not burning and have a fuel load +greater than 0 in order to catch fire. + +We will start by considering the simplest case: a flat landscape with no wind in +which cell (i, j) is not currently burning. In this case, each cell adjacent to +(i, j) that is burning contributes 1 point to (i, j)'s ignition factor. Thus, if +the ignition threshold is 1, (i, j) will start burning if it is adjacent to at +least one burning cell. If the ignition threshold is 2, (i, j) will start +burning only if it is adjacent to at least two burning cells. + +Consider the sequence of landscape states shown in +[simple_bushfire_model.png](../images/simple_bushfire_model.png), in +which all cells are of the same height, there is no wind, and the ignition +threshold is 1. At the first timestep (t = 0), the two cells (0, 0) and (0, 1) +are burning. During this timestep, the fuel load of each of these two cells will +decrease by one (causing the fire in (0, 0) to stop burning in the next time +step, t = 1). If we then consider at the surrounding cells, (1, 0) has a fuel +load of 0, so it cannot catch fire. Cells (0, 2), (1, 1) and (1, 2) each have a +fuel load greater than 0 and are adjacent to one of the currently burning cells, +(0, 1), therefore they will start burning in the next time step (t = 1). + +The example in +[simple_bushfire_model_2.png](../images/simple_bushfire_model_2.png) is +identical to that in the previous example, but the ignition threshold is now 2, +meaning that each non-burning cell needs to be adjacent to two or more burning +cells in order to start burning. Therefore, cells (0, 2) and cells (1, 2) will +not start burning at t = 1, as they were only adjacent to a single burning cell +at t = 0. + +Only cells that are located within the bounds of the landscape grid can +contribute to a cell's ignition factor. Thus, a cell located in the corner of a +grid will, in this simple case, only have three adjacent cells that may cause it +to start burning. + +### Determining when a cell catches fire (height included) + +Height and wind modify can modify the calculation of the basic ignition factor +described in the previous section. The effect of landscape height is described +in this section. + +On a flat landscape, where neighbouring cells are of the same height, each +burning cell contributes 1 point to an adjacent non-burning cell's +ignition factor. + +However, bushfires tend to spread more rapidly uphill, therefore if a cell +(i, j) has height that is greater than that of an adjacent burning cell, that +cell will contribute twice as much (i.e., 2 points) to (i, j)'s ignition factor. +Conversely, bushfires tend to spread more slowly downhill, therefore an adjacent +burning cell with height greater than (i, j)'s height will contribute only half +as much (i.e., 0.5 points) to (i, j)'s ignition factor. + +In the sequence shown in +[height_bushfire_model.png](../images/height_bushfire_model.png), the height of +each cell is indicated by a small blue number. No wind is blowing and the +ignition threshold of the landscape is 2. At the first timestep (t = 0), a +single cell (0, 0) is burning. The cell to the South of it (1, 0) has a fuel +load of 0 and hence cannot catch fire. On a flat landscape, the other two +adjacent cells (0, 1) and (1, 1) would not catch fire either, as their ignition +factor would only be 1 (from the single burning cell (0, 0)), below the ignition +threshold of 2. However, in this landscape, cells (0, 1) and (1, 1) are higher +than cell (0, 0), therefore its contribution to their ignition factor is doubled +to 2 points, high enough to equal the landscape's ignition threshold and cause +them to start burning in the following timestep (t = 1). + +In constrast, the top-right cell (0, 2) will escape being burnt in timestep +t = 2 (and beyond) as it is lower than the surrounding cells, hence they each +contribute only 0.5 points to its ignition factor. Thus, even when all three +surrounding cells are burning, (0, 2)'s ignition factor is only 1.5, below the +landscape ignition threshold of 2. + +### Determining when a cell catches fire (wind included) + +Wind can carry burning embers that allow a fire to spread more rapidly in a +particular direction. If a wind is blowing, up to three additional cells are +considered to be adjacent to (i, j) for the purpose of calculating its +ignition factor. + +For example, as shown in [wind_example.png](../images/wind_example.png), if a +wind is blowing from the North, the cell two cells above (i, j) and the cells +immediately to the left and right of this cell are considered adjacent to (i, j) +(i.e., cells (i − 2, j − 1), (i − 2, j) and (i − 2, j + 1)). If any of these +additional cells are burning, they will also contribute when calculating +(i, j)'s ignition factor. + +If a wind is blowing from the Southwest, the cell two cells below and to the +left of (i, j) and the cells immediately above and to the right of this cell are +considered adjacent to (i, j). That is, cells (i + 1, j − 2), (i + 2, j − 2) and +(i + 2, j − 1). Of course, these additional cells must be within the bounds of +the landscape in order to have any effect, as in the simple case in the previous +section. + +The sequence shown in +[wind_bushfire_model.png](../images/wind_bushfire_model.png) is identical to the +simple example shown in the previous section (on a flat landscape, with ignition +threshold of 2) except that the wind is now blowing from the Northwest. As a +consequence, cell (0, 0) is considered adjacent to (1, 2), which therefore has +an ignition factor of 2 (as (0, 1) is also adjacent and burning) and hence will +start burning at t = 1. In addition, (0, 0) and (0, 1) are also both considered +adjacent to (2, 2), which will also start burning at t = 1. Bushfires spread +much more rapidly when the wind is blowing! + +When considering the joint effects of height and wind, you should compare the +heights of (i, j) and each of its adjacent cells on a pairwise basis, +disregarding the heights of any other surrounding cells. For example, if (0, 0) +was higher than (2, 2) and (0, 1) was lower than (2, 2) then they would +contribute 0.5 points and 2 points respectively to (2, 2)'s ignition factor, +irrespective of the heights of the intervening cells (e.g., (1, 1)). + +## Part 2 - Determine if a cell starts burning + +Based on the rules described earlier, your task is to write a function +`check_ignition(b_grid, f_grid, h_grid, i_threshold, w_direction, i, j)` that +takes as arguments the burning state `b_grid` (at time t), current fuel load +`f_grid` (at time t), height `h_grid`, ignition threshold `i_threshold`, wind +direction `w_direction` and coordinates `i` and `j` of a cell, and returns +`True` if that cell will catch fire at time t + 1 and `False` otherwise. + +The arguments are of the following types: + +- `b_grid`: a list of lists of Boolean values (of dimensions M by M) +- `f_grid`: a list of lists of integers (of dimensions M by M) +- `h_grid`: a list of lists of integers (of dimensions M by M) +- `i_threshold`: an integer +- `w_direction`: a string (if wind is blowing), otherwise `None` (if no wind + is blowing) +- `i` and `j`: integers (i, j < M) + +You may assume that all arguments are valid, as defined in Part 1. + +For example: + + >>> check_ignition([[True, False], [False, False]], [[2, 2], [2, 2]], [[1, 1], [1, 1]], 1, 'N', 0, 1) + + True + + >>> check_ignition([[True, False], [False, False]], [[2, 0], [2, 2]], [[1, 1], [1, 1]], 1, 'N', 1, 0) + + True + + >>> check_ignition([[True, True, False], [False, False, False], [False, False, False]], [[1, 1, 1], [1, 1, 1], [1, 0, 0]], [[2, 2, 1], [2, 3, 1], [1, 1, 1]], 1, None, 0, 2) + + False + + >>> check_ignition([[True, True, False], [False, False, False], [False, False, False]], [[1, 1, 1], [1, 1, 1], [1, 0, 0]], [[2, 2, 1], [2, 3, 1], [1, 1, 1]], 2, None, 1, 1) + + True + +## Part 3 - Run the model + +Your task is to write a function `run_model(f_grid, h_grid, i_threshold, +w_direction, burn_seeds)` that takes as arguments the initial fuel load `f_grid` +(i.e., at time t = 0), height `h_grid`, ignition threshold `i_threshold`, wind +direction `w_direction` and a list of cells `burn_seeds` that are burning at +time t = 0, and returns a tuple containing (a) the final state of the landscape +once the fire has stopped burning, and (b) the total number of cells that have +been burnt by the fire (including any initially burning cells in `burn_seeds`). + +The arguments are of the following types: + +- `f_grid`: a list of lists (of dimensions M by M) +- `h_grid`: a list of lists (of dimensions M by M) +- `i_threshold`: an integer +- `w_direction`: a string +- `burn_seeds`: a list of integer tuples (i, j) where i, j < M + +You may assume that all arguments are valid, as defined in previous parts. + +You may find it helpful to define one or more additional functions that carry +out a single step of the model run, determining the new burning state and fuel +load at time t + 1 on the basis of the model state at time t. + +For example: + + >>> run_model([[2, 2], [2, 2]], [[1, 1], [1, 1]], 1, 'N', [(0, 0)]) + + ([[0, 0], [0, 0]], 4) + + >>> run_model([[2, 0], [0, 2]], [[1, 1], [1, 1]], 2, 'S', [(0, 0)]) + + ([[0, 0], [0, 2]], 1) + +## Part 4 - Test cases + +In addition to implementing your solutions, you are also required to submit a +set of test cases that can be used to test your Part 3 `run_model` function. + +You should aim to make your test cases as complete as possible. That is, they +should be sufficient to pick up incorrect implementations of the model. + +Your set of test cases may assume that the input passed to your function will be +of the correct types and will be well-formed. + +Your test cases suite will be evaluated by running it on several known incorrect +implementations, in which it should detect incorrect behaviour; i.e., returning +an incorrect final state of the landscape and/or number of cells burnt. + +You should specify your test cases as a series of calls to the function +`test_run_model(run_model, input_args, expected_return_value)`, where the first +argument `run_model` is the model you created in Part 3, the second argument, +`input_args` contains a list of `f_grid`, `h_grid`, `i_threshold`, +`w_direction`, `burn_seeds` representing the call to the function `run_model` +(described in Part 3) and `expected_return_value` is the expected return from +the function `run_model`, namely a list containing the final state of the +landscape once the fire has stopped burning, and the total number of cells that +have been burnt by the fire as in Part 3). + +`test_run_model` will return `True` if the model successfully passes the test, +and `False` otherwise. + +For example, using the first two examples from Part 2: + + >>> test_run_model(run_model, [[[2, 2], [2, 2]], [[1, 1], [1, 1]], 1, 'N', [(0, 0)]], + [[[0, 0], [0, 0]], 4]) + + True + + >>> test_run_model(run_model, [[[2, 0], [0, 2]], [[1, 1], [1, 1]], 2, 'S', [(0, 0)]], + [[[0, 0], [0, 2]], 1]) + + True + +## Part 5 - Bonus + +The final part is for bonus marks, and is deliberately quite a bit harder than +the four basic questions (and the number of marks on offer is deliberately not +commensurate with the amount of effort required — bonus marks aren't meant to be +easy to get!). Only attempt this is you have completed the earlier questions, +and are up for a challenge! + +In this question, you will use the bushfire model to determine the optimal cell +or cells in a landscape in which to conduct a prescribed burn in order to best +protect a town from a future bushfire of unknown timing and origin. + +For this question, we modify our original definition of a landscape to include a +town cell, containing a town. The town cell has a non-zero fuel load; that is, +the town can catch fire. + +### Prescribed burns + +A prescribed burn is a controlled fire used as part of forest management in +order to reduce the risk of future uncontrolled fires. + +In our simulation model, the rules of a prescribed burn are that it will only +occur on a day with no wind, and will commence on a single prescribed burn cell +with a non-zero fuel load. A prescribed burn will not be conducted on the cell +containing the town. + +A prescribed burn spreads just like a normal bushfire; however, due to the +controlled nature of the fire, any burning cell contributes only half as many +points to the ignition factor of adjacent cells as it ordinarily would (taking +slope into account). That is, if it would normally contribute 0.5, 1 or 2 +points, it will now only contribute 0.25, 0.5, or 1 points. This reduction +applies both to the original prescribed burn cell and to any cell that +subsequently catches fire during the prescribed burn. As with a normal bushfire, +a prescribed burn will continue until no cells remain on fire. + +### Scoring prescribed burn cells + +We filter out invalid prescribed burn cells and score the remaining valid +prescribed burn cells as follows: + +- Any prescribed burn cell that results in the the town cell catching fire is + deemed invalid. +- Following the completion of a prescribed burn, we will consider scenarios in + which potential bushfires start in any (single) seed cell with a non-zero fuel + load (after the prescribed burn), except for the town cell, on a day with any + possible wind conditions. Thus, for a landscape of dimensions M, we will + consider up to 9 × (M^2 − 2) bushfire scenarios. 2 is subtracted because we + don't seed a bushfire on the town cell or cells with zero fuel load, of which + there is at least one, being the cell in which the prescribed burn was + conducted. For each seed cell there are 9 possible wind directions to + consider, including no wind. +- Valid prescribed burn cells are scored according to the proportion of + scenarios in which the town cell caught fire. + +The optimal cell or cells for prescribed burning are those with the lowest +score; that is, that have been more effective at protecting the town. + +In the first example below, there are 4 cells with a non-zero fuel load, one of +which (1, 1) is the town cell. Therefore there are three cells in which a +prescribed burn can be conducted. None of these will result in the town being +burnt, therefore they are all valid. When we test the 18 possible bushfire +scenarios, we find that for one valid prescribed burn cell (0, 1), all +subsequent bushfires will result in the town catching fire. For the other two +prescribed burn cells ((0, 0) and (1, 0)), only half of the subsequent bushfires +will result in the town catching fire; thus, either of these would be the +optimal location in which to carry out a prescribed burn in this landscape. + +Your task is to write a function `plan_burn(f_grid, h_grid, i_threshold, +town_cell)` that determines the optimal prescribed burn cell or cells. `f_grid`, +`h_grid` and `i_threshold` are all as defined in Parts 2 and 3. `town_cell` is a +tuple containing the coordinates of the town cell. + +Your function should return a sorted list containing the coordinates of the +optimal prescribed burn cell or cells, as defined above. If there are no valid +prescribed burn cells, this list will be empty. + +For example: + + >>> plan_burn([[2, 2], [1, 2]], [[1, 2], [1, 2]], 2, (1, 1)) + + [(0, 0), (1, 0)] + + >>> plan_burn([[0, 0, 0, 0, 0], [0, 2, 2, 0, 0], [0, 0, 0, 1, 0], [0, 0, 0, 1, 0], [1, 0, 0, 0, 0]], [[2, 2, 2, 2, 2], [2, 1, 2, 2, 2], [2, 2, 2, 2, 2], [2, 2, 2, 1, 2], [2, 2, 2, 2, 2]], 2, (3, 3)) + + [(1, 1), (1, 2), (2, 3)] diff --git a/bushfire_model.png b/images/bushfire_model.png similarity index 100% rename from bushfire_model.png rename to images/bushfire_model.png diff --git a/height_bushfire_model.png b/images/height_bushfire_model.png similarity index 100% rename from height_bushfire_model.png rename to images/height_bushfire_model.png diff --git a/simple_bushfire_model.png b/images/simple_bushfire_model.png similarity index 100% rename from simple_bushfire_model.png rename to images/simple_bushfire_model.png diff --git a/simple_bushfire_model_2.png b/images/simple_bushfire_model_2.png similarity index 100% rename from simple_bushfire_model_2.png rename to images/simple_bushfire_model_2.png diff --git a/wind_bushfire_model.png b/images/wind_bushfire_model.png similarity index 100% rename from wind_bushfire_model.png rename to images/wind_bushfire_model.png diff --git a/wind_example.png b/images/wind_example.png similarity index 100% rename from wind_example.png rename to images/wind_example.png diff --git a/old/bf.dat b/old/bf.dat new file mode 100644 index 0000000..8b1dfab --- /dev/null +++ b/old/bf.dat @@ -0,0 +1,10 @@ +3 +1,2,1 +0,1,2 +0,0,1 +1,1,1 +2,1,2 +3,2,2 +1 +N +1,1 diff --git a/old/bf0.dat b/old/bf0.dat new file mode 100644 index 0000000..f86d981 --- /dev/null +++ b/old/bf0.dat @@ -0,0 +1,8 @@ +2 +2,2 +0,2 +1,2 +1,2 +1 +N +0,0 diff --git a/old/bushfire_model.png b/old/bushfire_model.png new file mode 100644 index 0000000..1448153 Binary files /dev/null and b/old/bushfire_model.png differ diff --git a/old/height_bushfire_model.png b/old/height_bushfire_model.png new file mode 100644 index 0000000..b28b40e Binary files /dev/null and b/old/height_bushfire_model.png differ diff --git a/part1.py b/old/part1.py similarity index 100% rename from part1.py rename to old/part1.py diff --git a/part2.py b/old/part2.py similarity index 100% rename from part2.py rename to old/part2.py diff --git a/part3.py b/old/part3.py similarity index 100% rename from part3.py rename to old/part3.py diff --git a/part4.py b/old/part4.py similarity index 100% rename from part4.py rename to old/part4.py diff --git a/part5.py b/old/part5.py similarity index 100% rename from part5.py rename to old/part5.py diff --git a/project02 b/old/project02 similarity index 100% rename from project02 rename to old/project02 diff --git a/project02-rubric.pdf b/old/project02-rubric.pdf similarity index 100% rename from project02-rubric.pdf rename to old/project02-rubric.pdf diff --git a/project02-sample-solutions.py b/old/project02-sample-solutions.py similarity index 100% rename from project02-sample-solutions.py rename to old/project02-sample-solutions.py diff --git a/old/simple_bushfire_model.png b/old/simple_bushfire_model.png new file mode 100644 index 0000000..3e9e9fe Binary files /dev/null and b/old/simple_bushfire_model.png differ diff --git a/old/simple_bushfire_model_2.png b/old/simple_bushfire_model_2.png new file mode 100644 index 0000000..4174691 Binary files /dev/null and b/old/simple_bushfire_model_2.png differ diff --git a/old/wind_bushfire_model.png b/old/wind_bushfire_model.png new file mode 100644 index 0000000..b71e4e6 Binary files /dev/null and b/old/wind_bushfire_model.png differ diff --git a/old/wind_example.png b/old/wind_example.png new file mode 100644 index 0000000..f8c6f8b Binary files /dev/null and b/old/wind_example.png differ diff --git a/src/parse.py b/src/parse.py new file mode 100644 index 0000000..de4c6c6 --- /dev/null +++ b/src/parse.py @@ -0,0 +1,72 @@ +""" +Contains functions for parsing a file containing a bushfire scenario. +""" + +def make_grid(grid: list[str], format_tuples: bool=False) -> list[list[int]]: + """Makes a valid grid from the input. + + ### Parameters: + grid (list): Either a fuel load or height grid. + format_tuples (bool): To format the elements as tuples. Defaults to + False, meaning that the elements of the grid will be lists. + + ### Returns: + new_grid (list): The correctly formatted grid. + + ### Example: + >>> make_grid(['2,2', '0,2']) + [[2, 2], [0, 2]] + """ + + new_grid = [] + for row in grid: + cells = row.split(',') + new_row = [int(i.strip()) for i in cells] + if format_tuples: + new_grid.append(tuple(new_row)) + else: + new_grid.append(new_row) + return new_grid + +def parse_scenario(path: str) -> dict | None: + """Parses a bushfire scenario file. + + ### Parameters: + path (str): The path to the bushfire scenario file. + + ### Returns: + scanario (dict): The dictionary containing information describing the + bushfire scenario. Returns None if path was not valid or the file was + not formatted correctly. + + ### Examples: + >>> parse_scenario('../data/bushfire-0.txt') + {'f_grid': [[2, 2], [0, 2]], 'h_grid': [[1, 2], [1, 2]], 'i_threshold': 1, + 'w_direction': 'N', 'burn_seeds': [(0, 0)]} + + >>> parse_scenario('data/bushfire-1.txt') + {'f_grid': [[1, 2, 1], [0, 1, 2], [0, 0, 1]], + 'h_grid': [[1, 1, 1], [2, 1, 2], [3, 2, 2]], 'i_threshold': 1, + 'w_direction': 'N', 'burn_seeds': [(1, 1)]} + """ + + lines = [] + with open(path, 'r', encoding='utf-8') as file: + lines = [line[:-1] for line in file] + + if lines == []: + return None + + size = int(lines[0]) + f_grid = make_grid(lines[1 : 1 + size]) + h_grid = make_grid(lines[1 + size : 1 + size * 2]) + i_threshold = int(lines[1 + size * 2]) + w_direction = None if lines[2 + size * 2] == 'None' else lines[2 + size * 2] + burn_seeds = make_grid(lines[3 + size * 2:], format_tuples=True) + + return {'f_grid': f_grid, 'h_grid': h_grid, 'i_threshold': i_threshold, + 'w_direction': w_direction, 'burn_seeds': burn_seeds} + +print(parse_scenario('data/bushfire-0.txt')) +print() +print(parse_scenario('data/bushfire-1.txt'))