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 Python Tutorials : Physics Simulation and Swarm (back to the list of tutorials)

Newton's Law and Particles

Position, Velocity, Acceleration and Force

Implementing Particle Class

Using IParticle Class

Interaction between Particles

Agent to Apply Force to Particles

Agent to Bounce Particles

Creating Geometry on A Trace of Particles

Tension to Particles

Force Vector of Tension

Tension Agent Class

Tension Line

Using ITensionLine Class

Interaction of Particles with Tension

Tensile Line Network

Combining Tension and Other Forces

Tensile Line Network

Tensile Network from An Input File

Applying Force to Tensile Network

Tensile Network Parameters

Tensile Network with Custom Particle Class

Tensile Network with Custom Tension Class

Swarm Algorithm

Three Rules of Swarm Algorithm

Swarm Rule 1: Cohesion

Swarm Rule 2: Separation

Swarm Rule 3: Alignment

Combining 3 Rules into Swarm Class

Shorter Code of Swarm Class

Using IBoid Class

Tuning Swarm Parameters

Field Operation

Simple Field: Gravity and Attractor

Visualizing Field

Decay of Field from Defining Geometry

Field Defined by Points

Field Defined by Curves (Attractor, Tangent, Curl)

Multiple Summed Fields

Compound Field

Field Defined by Surfaces (Tangent, Normal, Slope)

Initialize Particles with Points

Initialize Particles with Points on Curves

Initialize Particles with Surfaces and Meshes

Making A Custom Agent (Particle Base)

Particle Based Agent

Random Walk Rule in Update Method

Attraction Force Rule in Interact Method

Adding A State Property

Other Agent Classes to Interact

Particle-based Branching Algorithm with Spring Force

Line Agent with Particle and Spring

Adding Branching Behavior

Collision Detection

Branching and Growth Angle Control

Setting Spring Length

Smoothing Branch Lines with Straightener

Bundling Close Branches

Applying More Force Field

Generative and Self-Optimizing Agents (Swarm-Generated Tensile Structure)

Swarm Formation by Force Fields

Swarm Formation and Force Field from Input Geometry

Self-Optimizing Physics Simulation Agents

Self-Optimizing Physics Simulation Agents for Bridging Structure

Branching Swarm Agents and Self-Optimizing Agents

Network Growth Agent

Reproduction Based Agent and Branching

Connecting Adjacent Existing Agents

Network Layout by Repulsion Force

Preferential Attachment

Reconstructing Network From File

Adding Geometry on Nodes and Links

Swarm and Network

Cell Division and Growth Algorithm 1

Cell Division and Growth by Particle and Repulsion

Division Control by Location

Division Control by Size

Division Control by Attractor

Division Control by Neighboring Cells

Cell Junction by Tensile Link

Cascading Activation Control on Division

Branching Activation Control on Division

Storing Links and Control Division by Link Count

Link Division and Closed Links

Cell Division and Growth Algorithm 2

Triangular Link for Surface Formation and Peripheral Edge Division

Visualization of Cell with Spherical Body

Building Polygon Mesh by Cell and Links

Interior Edge Division on Open Surface

Closed Surface Formation and Face Division

Interior Edge Division on Closed Surface

Finding Edges to Divide on Closed Surface

Division Control by Maximum Link Count

Maximum Link Count and Probabilistic Allowance of Extra Link

Cascading Activation Control on Division

Branching Activation Control on Division

Parent/Child Activation Behavior Control

Cell Division and Growth from Imported Mesh

Particle and Swarm Example

Particle Example 1

Swarm Example 1

Swarm Example 2

Tension Example 1

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TUTORIALS (Java / Python)