Design Scripting

This course introduces students to the history, theory, and applications of Design Scripting. Defined as low-level computer programming of executable actions, scripting offers designers a powerful tool to automate routines, investigate diverse ways to process solutions, and generate intelligent models. The course will focus on the fundamental concepts, strategic approaches, and cultural context necessary for a critical and effective use of scripts within the creative process of design.

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Reaction Diffusion systems are mathematical models which explain how the concentration of one or more substances distributed in space changes under the influence of two processes.

This script simulates an R/D system by growing points from a base geometry according to a number of generations. Voronoi cells are grown around the points to create a reactive pattern where geometries collide.

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Field Weathering Video Example of Scripts possible output

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Field Weathering Agents

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Crater Formation - Although, my original natural process was "Melting Icebergs" I found that as I was writing my script, the natural process of Crater Formations seemed more appropriate for the type of geometric configurations that were occurring. Crater Formations are interesting for this type of project, because no material is lost or gained; it is radically reformed in a displaced manner. *I couldn't get this script to work with multiple agents - if anyone would like to adjust the script to work with multiple agents - PLEASE DO! It'll be uploaded to box shortly. This script uses one agent and one Mesh.  

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#objectives

#to simulate water-surface tension via particles in gravity

#to deposit a series of surface tension particles in layers

#   forming 'stalagmites'/'stalactites' over time

import rhinoscriptsyntax as rs

import scriptcontext as sc

#calculate the vector influence 

def vectorInfluence(startPt, cloudPt, pointRange):

    vectors = []

    for i in range(len(cloudPt)):

        #measure the distance between the startPt and each cloudPt

        dist = rs.Distance(startPt, cloudPt[i])

        #if in range, add to a list

        if dist < pointRange:

            #test

            #rs.SelectObjects(cloudPt[i])

            #rs.AddLine(startPt, cloudPt[i])

            vec = rs.VectorCreate(cloudPt[i], startPt)

            vectors.append(vec)

    return vectors

#average the vectors in range (via mLeta, modified slightly)

def vectorAverage(vectors):

    #definition: averages a list of vectors, returns a vector average

    #inputs:

    #vectors - list of vectors

    #outputs:

    #1 averaged vector (if list length is 0, returns (0,0,0))

    if len(vectors) == 0:

        return (0,0,0)

    elif len(vectors) == 1:

        return vectors[0]

    else:

        for i in range (0,len(vectors)):

            if i == 0:

                v1 = vectors[i]

            elif i < len(vectors)-1:

                v1 = rs.VectorAdd(v1,vectors[i])

            else:

                v1 = rs.VectorAdd(v1,vectors[i])

                newLength = (rs.VectorLength(v1))/(len(vectors))

                averageVector = rs.VectorScale(rs.VectorUnitize(v1),newLength)

                return averageVector

#run the functions in order, in a loop of iterations

#test vectors to delete any extra points

def Main():

    startPt = rs.GetObject("select the starting point, please", rs.filter.point)

    cloudPt = rs.GetObjects("select the point cloud, please", rs.filter.point)

    pointRange = 10

    iterations = 100

    mag = -8

    directionInfl = [0, 0, mag]

         trailPts =[]

         #for j in range???? Multiple starting points????

         for i in range(iterations):

                 vectors = vectorInfluence(startPt, cloudPt, pointRange)

                 averageVector = vectorAverage(vectors)

                 averageVector = rs.VectorAdd(averageVector, directionInfl)

                 vectorLength = rs.VectorLength(averageVector)

                 if vectorLength < .01:

            vecPt = rs.MoveObject(startPt, directionInfl)

        elif vectorLength == 8:

            vecPt = rs.MoveObject(startPt, directionInfl)

        else:

            startPt = rs.CopyObject(startPt, averageVector)

                         sc.escape_test()

                 #trailPts.append(startPt)

        #rs.AddCurve(trailPts)

        #cloudPt.append(trailPts)

        #rs.DeleteObjects(trailPts)

         Main()

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Recursive Branching Script. crackMe

Braden Caldwell

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Generative Logic Proposal: Hierarchical Subdivision Network Recursive script that mimics a leaf’s vein structure and creates three distinct layers of subdivisions as it grows. The webbing is done using Matt’s curve network webbing script

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Final Requirements

For Friday, May 3rd (Worksession Tuesday, April 30):

Finalize

Finalize your Generative Logic Tool.

Document

Compile finalized documentation of your Generative Logic Tool (this should be high quality documentation - drawings in Illustrator, etc.) to include:

The logic of your script described through a sequence of diagrams.

A final Script Flow Chart. 

A series of images displaying the outcome of your script and its capacity to work with different inputs.

The Script itself.

Post 

Post the Final Documentation as a high quality PDF to Box.

Post the Script and an example file to Box.

Post individual pages/images from the documentation to Tumblr.

Extra Credit

Create and post a video of your script progress and/or result.

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Wcheng #CL12