PART IV: Modelling, Simulation And Analysis With Python Flashcards
What are the two main types of filters?
Boxcar filtering
Gaussian filtering
Boxcar filtering
Equal weights assigned to each sample in a set
Gaussian filtering
Weights that form the shape of a bell curve
What’s universal for filtering data about weights?
Weights must be normalized
Sum of all weights =1 to get back data that looks like original data
Filtering data: endpoints
They require separate treatments to smooth them out and prevent noise
Tapered filter sums weights in data range to help with this
What are some ways that filters can affect an image?
Blur Sharpen Edge-detect Calculate gradients Curvature Shift Rotate More lol
Common features of simulations
- principle set of physical laws, typically in DE form
- initial and boundary conditions specified
- derive observable/measurable quantities
- test for conservation and convergence
- want to compare with anakytic solutions where possible
Main steps for simple simulations
- identify initial and boundary conditions
- determine path of object (bouncing ball, ray tracing etc)
- identify intersection point between path of object and boundary
- calculate interaction at intersection point (ex. Reflection is calculating reflected angle)
- repeat determine path until calc interaction in a loop which redefines ICs and proceeds to continue the path after first intersection point
Particle based simulations
For complex models
Look at each object as a discrete particle
Particle based simulations: what should we keep in mind?
All particles must have ICs
All particles must evolve through time
To speed up calcs, group/categorize them into shells or grid cells so all particles within group are affected equally
Sorted algorithms help determine interactions between one particle/group and nearest neighbours