Parametric and Algorithmic Design with Grasshopper

Lesson 1 • Grasshopper Interface and Navigation

Covers the canvas, component panels, and Rhino viewport link. Provides the spatial literacy needed to build and read definitions efficiently.

Lesson 2 • Parametric Design Concepts and Workflow

Establishes the shift from static to parameter-driven modeling. Connects design intent to computational logic as the chapter's conceptual backbone.

Lesson 3 • Basic Geometry Components

Covers point, line, plane, and curve primitives within Grasshopper. Builds the geometric vocabulary used throughout all subsequent chapters.

Lesson 4 • Components, Wires, and Data Flow

Explains how components receive, process, and output data through wires. Students trace data flow to debug simple connection errors.

Lesson 1 • List Operations and Manipulation

Covers splitting, shifting, and combining lists to reshape data sets. Enables precise control over which geometry receives which parameter values.

Lesson 2 • Tree Manipulation Components

Teaches Flatten, Graft, Simplify, and Flip Matrix to reshape trees. Students restructure mismatched trees to resolve common data mismatch errors.

Lesson 3 • Introduction to Data Trees

Introduces branched data structures and path notation. Students read tree previews and understand why trees arise from surface and grid operations.

Lesson 4 • Understanding Lists in Grasshopper

Explains how Grasshopper stores multiple values as ordered lists. Establishes list indexing as the foundation for all data manipulation techniques.

Lesson 1 • NURBS Curve Fundamentals

Covers degree, control points, knots, and weights of NURBS curves. Connects mathematical properties to visual behaviour for informed curve design.

Lesson 2 • Surface Analysis and UV Space

Explains UV parameterisation, surface normals, and curvature analysis. Students use UV coordinates to place geometry precisely on surfaces.

Lesson 3 • Brep Operations and Boolean Logic

Covers Brep construction, Boolean union, difference, and intersection. Students build complex solids by combining and subtracting parametric volumes.

Lesson 4 • Surface Generation Methods

Introduces Loft, Extrude, Sweep, and Revolve surface creation methods. Students select the appropriate method based on design geometry requirements.

Lesson 1 • Rationalisation for Fabrication

Groups similar panels by geometry to minimise unique part counts. Students apply clustering and labelling to prepare panel sets for production.

Lesson 2 • Custom Panel Geometry Mapping

Maps custom 2D panel profiles onto surface cells using surface frames. Students create varied panel designs driven by attractor logic.

Lesson 3 • Planar Panel Extraction

Extracts and tests panels for planarity using deviation analysis. Students identify non-planar panels and apply correction strategies.

Lesson 4 • Grid Systems on Surfaces

Generates rectangular, triangular, and diamond grids mapped to UV space. Establishes the grid logic that underpins all panelisation workflows.

Lesson 1 • Graph Mapper and Value Remapping

Controls the nonlinear relationship between distance and output using Graph Mapper. Students tune response curves to achieve precise visual effects.

Lesson 2 • Gradient Patterns and Responsive Facades

Combines attractor logic with panelisation to produce responsive facade systems. Students integrate all attractor techniques into a complete facade definition.

Lesson 3 • Curve and Surface Attractors

Extends attractor logic to curves and surfaces using closest-point distance. Students create gradient effects that follow linear or surface features.

Lesson 4 • Point Attractor Fundamentals

Maps distance from attractor points to parameter values driving geometry. Introduces the core attractor pattern used in all field-based workflows.

Lesson 1 • RhinoCommon Geometry in Scripts

Uses RhinoCommon classes to create and manipulate geometry inside scripts. Students generate curves, surfaces, and transforms programmatically.

Lesson 2 • Packaging Scripts as Reusable Components

Wraps scripts into cluster-like components with icons and documentation. Students build a personal component library for repeated use across projects.

Lesson 3 • Introduction to the Script Component

Introduces the GhPython and C# Script components, their editors, and I/O ports. Students write and run their first custom script inside a definition.

Lesson 4 • Python Syntax for Grasshopper

Covers Python data types, loops, conditionals, and functions in the GH context. Students translate native component logic into equivalent Python code.

Lesson 1 • Structural Analysis with Karamba3D

Introduces Karamba3D components for finite element structural analysis within GH. Students assess beam and shell structures and read stress output.

Lesson 2 • Form Finding with Kangaroo

Uses Kangaroo physics solver for tension, compression, and equilibrium form finding. Students generate structurally informed shapes through live simulation.

Lesson 3 • Closing the Analysis-Design Loop

Feeds analysis results back into geometry parameters to automate design iteration. Students build a definition where performance metrics directly drive form.

Lesson 4 • Daylight and Thermal Analysis with Honeybee

Connects Honeybee to Radiance and EnergyPlus for daylight and thermal simulation. Students evaluate room performance and adjust geometry to meet targets.

Lesson 1 • Machine Learning Assistance in Optimisation

Introduces surrogate modelling and ML-assisted search to accelerate optimisation. Students use trained models to predict fitness without full simulation runs.

Lesson 2 • Multi-Objective Optimisation with Octopus

Uses Octopus to explore Pareto fronts across competing design objectives. Students visualise trade-offs and select solutions from the Pareto set.

Lesson 3 • Galapagos Evolutionary Solver

Configures Galapagos for single-objective optimisation using genetic algorithms. Students tune population size, mutation rate, and termination criteria.

Lesson 4 • Optimisation Fundamentals in Design

Defines fitness functions, design variables, and constraints in a parametric context. Students frame a design problem as a solvable optimisation task.