About The Project

Coordinate Distance Calculator is an interactive notebook which calculates the distance and optimal path from a set of Cartesian coordinates. The Python functions enable users to find the closest point from the starting coordinate, calculate the distance between multiple coordinates, and determine the best path.

• Simple and modular Python code which can be repurposed
• Can calculate distance between multiple Cartesian coordinates
• Determines the best path based on the shortest overrall distance required
• Can graphically represent optimised path

Guide

To use the Coordinate Distance Calculator, input your desired values into the distance, find_closest, path_distance and or best_path function.

Distance

# Insert desired coordinates, P1/P2 being 1 set and P3/P4 being another set of coordinates.

distance((P1, P2), (P3, P4))

Find Closest

# The first coordinate is considered the starting point, the function will find the closest coordinate to that point.

find_closest((StartingP1, StartingP2), [(P1, P2), (P3, P4), (P5, P6), (P7, P8)])

Path Distance

# Insert desired coordinates into P1/P2, etc.

path_distance([(P1, P2), (P3, P4), (P5, P6)])

Best Path

# Insert desired coordinates into P1/P2, etc.

points = [(P1, P2), (P3, P4), (P5, P6), (P7, P8), (P9, P10)]

path = best_path(points)
print(path)

Graphical Representation

# This will graphically represent the best path, you can replace "path" with another function to see that function.

matplotlib.pyplot.plot(*zip(*path))

If values are null the function will not produce a result. Do not alter the function which is being called, as the calculations may not function as intended. The explanation behind each function is featured in the notebook.

Planned Features

• Move from a Jupyter-based interactive notebook to a designed user interface
• Integrate Dijkstra's algorithm and A* Search algorithm for the best path function
• Build a front-end platform for user input

(Back to top)