Question

You are given a table of values that give the height of a terrain at different points in a square. Write a function def floodMap (heights, waterLevel) that prints out a flood map, showing which of the points in the terrain would be flooded if the water level was the given value. In the flood map, print a = for each flooded point and a space for each point that is not flooded.

Short answer

Write a function `floodMap` to compare terrain heights to `waterLevel`, printing `=` for flooded points and space otherwise.

Step-by-step solution

Understand the Problem

The task is to write a function `floodMap` that takes an array of heights and a waterLevel as input. It should output a map indicating flooded points with `=` and non-flooded points with a space.

Define the Function Signature

Define the function `floodMap(heights, waterLevel)` where `heights` is a 2D list representing terrain heights and `waterLevel` is a number representing the flood level.

Loop Over the Terrain

Use nested loops to iterate over each point in the `heights` table. For a 2D list, a double loop will allow access to each element in the matrix.

Evaluate Flood Condition

Within the loops, compare each height with `waterLevel`. If the height of a point is less than or equal to `waterLevel`, it is considered flooded.

Print Flood Map

While iterating, print `=` if the point is flooded or print ` ` (space) if not flooded. Make sure to handle new lines correctly for rows.

Complete the Function

Combine all previous steps into the `floodMap` function. The function reads the 2D list, checks conditions, and prints each element appropriately in a formatted flood map.

Key concepts

Flood Map

When considering the concept of a flood map in programming, it's essentially a visual representation of data, particularly terrain data, that shows which areas are submerged under a certain water level. This can be incredibly useful in practical situations, such as environmental science, urban planning, or even video game development.

The flood map is created by mapping each point in the terrain described by a 2D list of height values. When we set a water level, the map shows the flooding status of each point using simple symbols: an '=' symbol for flooded areas and a space for dry land. This type of representation helps quickly identify flood-prone regions in a visualization-friendly format.

• Symbols reflect the status of each grid point.
• Quick and intuitive visual cues aid interpretation.

Creating such a map challenges programmers to process multi-dimensional data effectively and demands a keen understanding of how to loop through data structures.

2D Lists

In Python, a 2D list is essentially a list of lists, forming a matrix-like structure where data is stored in rows and columns. This data structure is extremely versatile and is extensively used in applications ranging from scientific computations to image processing.

For the flood map task, a 2D list represents the terrain heights. Each sublist corresponds to a single row of terrain data, and the elements within represent the heights at specific points. This format closely mirrors real-world data sets, such as geographical maps, making it a perfect fit for the task.

• Structure: [[row1], [row2], ...]
• Allows easy access and manipulation of tabular data.
• Enables nested loops for thorough data processing.

Understanding how to navigate a 2D list allows programmers to efficiently handle tasks requiring multi-dimensional analysis.

Function Definition

Defining functions in Python is central to structuring your code in a modular, reusable, and organized manner. For the flood map, you define a function called `floodMap` that bundles all instructions into a single, easy-to-capture block of code.

The function takes two parameters: `heights`, the 2D list of terrain elevations, and `waterLevel`, the specified flood threshold. This allows for dynamic analysis of any given set of terrain data against any potential flood level. Function definitions in Python start with the `def` keyword and include:

• A clear, descriptive name.
• Parameters that specify expected inputs.
• Indented code block defining the function's operations.

This organization helps maintain clarity in large codebases and makes functions easy to test and debug. Moreover, encapsulating logic into functions promotes reusability across different projects.

Comparisons in Loops

Loops in Python, especially when paired with conditional statements, are powerful tools for iterating over data structures. For creating a flood map, nested loops are crucial as they allow you to traverse each element in a 2D list systematically.

In our task, two loops are used: the outer loop iterates over each row, and the inner loop processes each element within these rows. Within these loops, comparisons are made to determine if a point is flooded by checking if the height is less than or equal to the water level. If it is, you print '=', and if not, you print a space. Considerations include:

• Using `if` statements for comparisons.
• Efficiently moving through each grid point.
• Managing output formatting for proper flood map visualization.

These operations are fundamental in many programming tasks where multi-layered data needs processing and scrutinizing based on conditions.