Collision Detection and Spatial Analysis with Python
Collision Detection and Spatial Analysis with Python Data Science Project
Fun and Puzzles

Collision Detection and Spatial Analysis with Python

Particle Collision Detection and Spatial Analysis are very common applications in Game Development, Scientific programming and simulations. In this project, you'll need to use Python (pandas, optionally) to generate thousands of random particles, and matplotlib to visualize them in the plane.
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Collision Detection and Spatial Analysis with PythonCollision Detection and Spatial Analysis with Python
Project Created by

Santiago Basulto

Project Activities

All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.

All our activities include solutions with explanations on how they work and why we chose them.

codevalidated

Write a function that generates a random particle

Write the function generate_particle that generates a particle according to the previous definition. The function accepts three parameters max_x, max_y, max_r which by default take the constants above and returns a tuple with (x, y, r).

Example:

>>> generate_particle()
(391.8484862104256, 92.86444985326192, 0.7227983373572378)

>>> generate_particle(10, 10, 1)
(5.184593462659739, 3.5388971902026602, 0.8641652792107458)
codevalidated

Generate 1,000 random particles using `random.seed(10)`

Generate a list of 1,000 random particles with the default values for max_x, max_y and max_r, and store them in the particles variable.

IMPORTANT: We'll validate your program by comparing it with the expected result of the same generation with random.seed(10), so make sure you're using setting the correct seed before generating the particles.

codevalidated

Store your particles in a CSV file

Store the data from particles in a CSV file named particles.csv, with the header x,y,r. You can use any method, including Pandas, manual CSV handling, etc. Here's an example header of the particles.csv file:

x,y,r
399.98181628293946,214.4445273375573,2.890456505672352
144.2687624976512,406.66062567866004,4.117944362667227
457.43077373082303,80.11477825940983,2.603346798199623
codevalidated

Plot your particles in a matplotlib plane

Plot your particles in a dot-plot, each particle centered in x, y and with a marker size of r.

Warning! don't change the fig, or ax variables or the figsize defined.

It should look something like this:

codevalidated

Write the function `calculate_particle_position`

The function calculate_particle_position receives two tuples, with the particle's and area's x, y, r parameters and it should return the position of the particle (either completely contained, partially contained, or outside) in the form of an Enum as its defined below:

from enum import Enum

class ParticlePosition(Enum):
    PARTIALLY_CONTAINED = 1
    COMPLETELY_CONTAINED = 2
    OUTSIDE = 3
codevalidated

Plot the particles according to their position

Read the particles from particles.csv and plot them using special colors depending if the particle is fully contained, partially contained or not contained at all in the area A (325, 225, 50)

If the particle is fully contained, it should be colored green, if it's partially contained, it should be colored red, while if it's outside, it should be black.

Your plot should look something like:

Collision Detection and Spatial Analysis with PythonCollision Detection and Spatial Analysis with Python
Project Created by

Santiago Basulto

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