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attractor_blender_2_6.py
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attractor_blender_2_6.py
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# Attractor.py - Blender add-on that generates various strange attractors
# Copyright (C) 2014 Mike Tyka
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import bpy
import math
from bpy.props import BoolProperty
from bpy.props import FloatProperty
from bpy.props import FloatVectorProperty
from bpy.props import IntProperty
bl_info = {
"author": "[email protected]",
"blender": (2, 6, 0),
"category": "Add Curve",
"description": "Creates a strange attractor curve",
"location": "View3D > Add > Curve > Attractors",
"name": "Strange Attractors",
"version": (0, 1),
"warning": "",
"wiki_url": ""
}
def get_prop(cls, name, default):
return bpy.props.FloatProperty(attr=cls + "_" + name,
name=name,
description="",
default=default)
def get_int_prop(cls, name, default):
return bpy.props.IntProperty(attr=cls + "_" + name,
name=name,
description="",
default=default)
def get_npoints(default=10000):
return IntProperty(attr="npoints",
name="Vertices",
description="",
min=1, soft_min=1, default=default)
class Attractor(bpy.types.Operator):
view_align = BoolProperty(name="Align to View",default=False)
location = FloatVectorProperty(name="Location",subtype="TRANSLATION")
rotation = FloatVectorProperty(name="Rotation",subtype="EULER")
def draw(self, context):
layout = self.layout
row = layout.row()
row.prop(self, "npoints", text="Vertices")
col = layout.column(align=True)
for param in self.params:
col.prop(self, param, text=param)
col2 = layout.column(align=True)
col2.prop(self, "x", text="x")
col2.prop(self, "y", text="y")
col2.prop(self, "z", text="z")
col2.prop(self, "dt", text="dt")
def execute(self, context):
curvedata = bpy.data.curves.new(name="Curve", type="CURVE")
curvedata.dimensions = "3D"
objectdata = bpy.data.objects.new("ObjCurve", curvedata)
objectdata.location = (0,0,0)
bpy.context.scene.objects.link(objectdata)
polyline = curvedata.splines.new("POLY")
polyline.points.add(self.npoints-1)
x = self.x
y = self.y
z = self.z
n = 0
while n < self.npoints:
dx, dy, dz = self.iterate(x, y, z)
x = x + self.dt * dx
y = y + self.dt * dy
z = z + self.dt * dz
polyline.points[n].co = (x,y,z,math.sqrt(dx*dx+dy*dy+dz*dz))
n += 1
return {"FINISHED"}
class CoulletAttractor(Attractor):
bl_idname = "curve.coullet_attractor_add"
bl_label = "Coullet Attractor"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c"]
a = get_prop("coullet", "a", 0.80)
b = get_prop("coullet", "b", -1.10)
c = get_prop("coullet", "c", -0.45)
d = get_prop("coullet", "d", -1.00)
x = get_prop("coullet", "x", 0.10)
y = get_prop("coullet", "y", 0.00)
z = get_prop("coullet", "z", 0.00)
dt = get_prop("coullet", "dt", 0.01)
def iterate(self, x, y, z):
dx = y
dy = z
dz = self.a*x + self.b*y + self.c*z + self.d*x**3
return (dx, dy, dz)
class LorenzAttractor(Attractor):
bl_idname = "curve.lorenz_attractor_add"
bl_label = "Lorenz Attractor"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c"]
a = get_prop("lorenz", "a", 10.00)
b = get_prop("lorenz", "b", 28.00)
c = get_prop("lorenz", "c", (8/3))
x = get_prop("lorenz", "x", 0.10)
y = get_prop("lorenz", "y", 0.00)
z = get_prop("lorenz", "z", 0.00)
dt = get_prop("lorenz", "dt", 0.01)
def iterate(self, x, y, z):
dx = self.a * (y - x)
dy = (x * (self.b - z) - y)
dz = (x * y - self.c * z)
return (dx, dy, dz)
class RoesslerAttractor(Attractor):
## Herrmann, Dietmar: Algorithmen für Fraktale und Chaostheorie
## Addison Wesley, 1994 ISBN 3-89319-633-1
bl_idname = "curve.roessler_attractor_add"
bl_label = "RoesslerAttractor"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c"]
a = get_prop("roessler", "a", 0.2)
b = get_prop("roessler", "b", 0.2)
c = get_prop("roessler", "c", 5.7)
x = get_prop("roessler", "x", 1.00)
y = get_prop("roessler", "y", 1.00)
z = get_prop("roessler", "z", 1.00)
dt = get_prop("roessler", "dt", 0.01)
def iterate(self, x, y, z):
dx=-(y+z);
dy=x+self.a*y;
dz=self.b+z*(x-self.c);
return (dx, dy, dz)
class AizawaAttractor(Attractor):
bl_idname = "curve.aizawa_attractor_add"
bl_label = "Aizawa Attractor"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c", "d", "e", "f"]
a = get_prop("aizawa", "a", 0.95)
b = get_prop("aizawa", "b", 0.7 )
c = get_prop("aizawa", "c", 0.6 )
d = get_prop("aizawa", "d", 3.5 )
e = get_prop("aizawa", "e", 0.25)
f = get_prop("aizawa", "f", 0.1 )
x = get_prop("aizawa", "x", 0.1 )
y = get_prop("aizawa", "y", 0.00)
z = get_prop("aizawa", "z", 0.00)
dt = get_prop("aizawa", "dt", 0.01)
def iterate(self, x, y, z):
dx = (z-self.b)*x-self.d*y
dy = self.d*x+(z-self.b)*y
dz = self.c+self.a*z-(pow(z,3)/3)-(pow(x,2)+pow(y,2))*(1+self.e*z)+self.f*z*pow(x,3)
return (dx, dy, dz)
class ActAttractor(Attractor):
bl_idname = "curve.act_attractor_add"
bl_label = "act"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "d", "m"]
a = get_prop("act", "a", 1.8)
b = get_prop("act", "b", -0.07)
d = get_prop("act", "d", 1.5)
m = get_prop("act", "m", 0.02)
x = get_prop("act", "x", 0.5)
y = get_prop("act", "y", 0.0)
z = get_prop("act", "z", 0.0)
dt = get_prop("act", "dt", 0.02)
def iterate(self, x, y, z):
xn = self.a*(x-y)
yn = -4*self.a*y+x*z+self.m*pow(x,3)
zn = -self.d*self.a*z+x*y+self.b*z*z
return xn, yn, zn
class ThreeCellsCNNAttractor(Attractor):
bl_idname = "curve.threecellscnn_attractor_add"
bl_label = "ThreeCellsCNN Attractor"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["p1", "p2", "r", "s"]
p1 = get_prop("ThreeCellsCNN", "p1", 1.24)
p2 = get_prop("ThreeCellsCNN", "p2", 1.1)
r = get_prop("ThreeCellsCNN", "r", 4.4)
s = get_prop("ThreeCellsCNN", "s", 3.21)
x = get_prop("ThreeCellsCNN", "x", 0.1)
y = get_prop("ThreeCellsCNN", "y", 0.1)
z = get_prop("ThreeCellsCNN", "z", 0.1)
dt = get_prop("ThreeCellsCNN", "dt", 0.01)
def iterate(self, x, y, z):
h1 = 0.5*(abs(x+1)-abs(x-1))
h2 = 0.5*(abs(y+1)-abs(y-1))
h3 = 0.5*(abs(z+1)-abs(z-1))
xn = -x+self.p1*h1-self.s*h2-self.s*h3
yn = -y-self.s*h1+self.p2*h2-self.r*h3
zn = -z-self.s*h1+self.r*h2+h3
return xn, yn, zn
class ArneodoAttractor(Attractor):
bl_idname = "curve.arneodo_attractor_add"
bl_label = "Arneodo"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c"]
a = get_prop("Arneodo", "a", -5.5)
b = get_prop("Arneodo", "b", 3.5)
c = get_prop("Arneodo", "c", -1)
x = get_prop("Arneodo", "x", 0.1)
y = get_prop("Arneodo", "y", 0.0)
z = get_prop("Arneodo", "z", 0.0)
dt = get_prop("Arneodo", "dt", 0.009)
def iterate(self, x, y, z):
xn = y
yn = z
zn = -self.a*x-self.b*y-z+self.c*pow(x,3)
return xn, yn, zn
class AnishenkoAstakhovAttractor(Attractor):
bl_idname = "curve.anishenko_astakhov_attractor_add"
bl_label = "AnishenkoAstakhov"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["m", "n"]
m = get_prop("AnishenkoAstakov", "m", 1.2)
n = get_prop("AnishenkoAstakov", "n", 0.5)
x = get_prop("AnishenkoAstakov", "x", 1)
y = get_prop("AnishenkoAstakov", "y", 0.0)
z = get_prop("AnishenkoAstakov", "z", 0.0)
dt = get_prop("AnishenkoAstakov", "dt", 0.01)
def iterate(self, x, y, z):
i = 1.0 if x > 0 else 0.0
xn = self.m*x + y - x*z
yn = -x
zn = -self.n*z + self.n*i*x*x
return xn, yn, zn
class BoualiAttractor(Attractor):
bl_idname = "curve.bouali_attractor_add"
bl_label = "Bouali"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "g"]
a = get_prop("Bouali", "a", 0.2)
b = get_prop("Bouali", "b", 0.05)
g = get_prop("Bouali", "g", 1.0)
x = get_prop("Bouali", "x", 1)
y = get_prop("Bouali", "y", 0.0)
z = get_prop("Bouali", "z", 0.0)
dt = get_prop("Bouali", "dt", 0.005)
def iterate(self, x, y, z):
xn = 0.02*y + 0.4*x*(0.2 - y*y)
yn = -x + self.a*z
zn = 10.0*x - 0.1*y
return xn, yn, zn
class BurkeShawAttractor(Attractor):
bl_idname = "curve.burkeshaw_attractor_add"
bl_label = "BurkeShaw"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["s", "v"]
s = get_prop("BurkeShaw", "s", 10)
v = get_prop("BurkeShaw", "v", 4.272)
x = get_prop("BurkeShaw", "x", 1)
y = get_prop("BurkeShaw", "y", 0.0)
z = get_prop("BurkeShaw", "z", 0.0)
dt = get_prop("BurkeShaw", "dt", 0.005)
def iterate(self, x, y, z):
xn = -self.s*(x+y)
yn = -y-self.s*x*z
zn = self.s*x*y+self.v
return xn, yn, zn
class ChenAttractor(Attractor):
## Professor Tetsushi Ueta
## Center for Advanced Information Technology, Tokushima University
bl_idname = "curve.chen_attractor_add"
bl_label = "Chen"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c"]
a = get_prop("Chen", "a", 35)
b = get_prop("Chen", "b", 8/3.0)
c = get_prop("Chen", "c", 20)
x = get_prop("Chen", "x", -3)
y = get_prop("Chen", "y", 2)
z = get_prop("Chen", "z", 20)
dt = get_prop("Chen", "dt", 0.002)
def iterate(self, x, y, z):
xn = self.a*(y-x)
yn = (self.c-self.a)*x-(x*z)+(self.c*y)
zn = (x*y)-(self.b*z)
return xn, yn, zn
class LotkaVolterraAttractor(Attractor):
## John S. Costello
## Synchronisation of Chaos in a Generalized Lotka-Volterra Atractor
## The Nonlinear Journal Vol. 1, 1999 pp 11-17
bl_idname = "curve.lotka_volterra_attractor_add"
bl_label = "LotkaVolterra"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints(30000)
params = ["a", "b", "c"]
a = get_prop("LotkaVolterra", "a", 2.9851)
b = get_prop("LotkaVolterra", "b", 3.0)
c = get_prop("LotkaVolterra", "c", 2)
x = get_prop("LotkaVolterra", "x", 1.0)
y = get_prop("LotkaVolterra", "y", 1.0)
z = get_prop("LotkaVolterra", "z", 1.0)
dt = get_prop("LotkaVolterra", "dt", 0.01)
def iterate(self, x, y, z):
xn = x - x*y + self.c*x*x - self.a*z*x*x
yn = -y + x*y
zn = -self.b*z + self.a*z*x*x
return xn, yn, zn
class MooreSpiegelAttractor(Attractor):
## L. A. Smith, C. Ziehmann und K. Fraedrich
## Uncertainty Dynamics and Predictability in Chaotic Systems
## (1999) Quart. J. Royal Meteorological Soc. 125, 2855-2886
## http://www.lse.ac.uk/collections/cats/abstracts/UncertaintyDynamics.htm
bl_idname = "curve.moorespiegel_attractor_add"
bl_label = "MooreSpiegel"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b"]
a = get_prop("MoreSpiegel", "a", 100.0)
b = get_prop("MoreSpiegel", "b", 26.0)
x = get_prop("MoreSpiegel", "x", 1.0)
y = get_prop("MoreSpiegel", "y", 0.0)
z = get_prop("MoreSpiegel", "z", 0.0)
dt = get_prop("MoreSpiegel", "dt", 0.002)
def iterate(self, x, y, z):
xn=y
yn=z
zn=(-z-(self.b-self.a+self.a*x*x)*y-self.b*x)
return xn, yn, zn
class RikitakeAttractor(Attractor):
## Tyler McMillen
## The Shape and Dynamics of the Rikitake Atractor
## The Nonlinear Journal Vol. 1, 1999 pp 1-10
bl_idname = "curve.rikitake_attractor_add"
bl_label = "Rikitake"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b"]
a = get_prop("Rikitake", "a", 5.0)
b = get_prop("Rikitake", "b", 2.0)
x = get_prop("Rikitake", "x", 1.0)
y = get_prop("Rikitake", "y", 1.0)
z = get_prop("Rikitake", "z", 1.0)
dt = get_prop("Rikitake", "dt", 0.01)
def iterate(self, x, y, z):
xn=-self.b*x+z*y
yn=-self.b*y+(z-self.a)*x
zn=1.0-x*y
return xn, yn, zn
class RabinovichFabrikantAttractor(Attractor):
## Rabinovich Fabrikant Attraktor: Robert Doerner
## http://www.robert-doerner.de/Glossar/glossar.html#rabinovich
bl_idname = "curve.rabinovichfabrikant_attractor_add"
bl_label = "RabinovichFabrikant"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints(25000)
params = ["a", "b"]
a = get_prop("RabinovichFabrikant", "a", 1.1)
b = get_prop("RabinovichFabrikant", "b", 0.87)
x = get_prop("RabinovichFabrikant", "x", -1.05)
y = get_prop("RabinovichFabrikant", "y", 0.9)
z = get_prop("RabinovichFabrikant", "z", 1.01)
dt = get_prop("RabinovichFabrikant", "dt", 0.001)
def iterate(self, x, y, z):
xn=y*(z-1.0+x*x)+self.b*x
yn=x*(3.0*z+1.0-x*x)+self.b*y
zn=-2.0*z*(self.a+x*y)
return xn, yn, zn
class ThreeLayerAttractor(Attractor):
## Tianshou Zhou, Guanrong Chen A Simple Smooth Chaotic System with a 3-Layer Attractor
bl_idname = "curve.threelayer_attractor_add"
bl_label = "ThreeLayer"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints(15000)
params = ["a1","a2","a3","c1","c2","c3","d"]
a1 = get_prop("ThreeLayer", "a1",-4.1)
a2 = get_prop("ThreeLayer", "a2", 1.2)
a3 = get_prop("ThreeLayer", "a3",13.45)
c1 = get_prop("ThreeLayer", "c1", 2.76)
c2 = get_prop("ThreeLayer", "c2", 0.6)
c3 = get_prop("ThreeLayer", "c3", 13.13)
d = get_prop("ThreeLayer", "d", 1.8)
x = get_prop("ThreeLayer", "x", 0.0)
y = get_prop("ThreeLayer", "y", -15.0)
z = get_prop("ThreeLayer", "z", 0.0)
dt = get_prop("ThreeLayer", "dt", 0.04 )
def iterate(self, x, y, z):
b=((self.d*self.a2*self.a2*self.c3*self.c3)/(32*self.a3*self.a3*self.c2*self.c2))*math.sqrt((-self.a3*self.c2)/(self.a1*self.c1))
c=((self.a2*self.a2*self.c3*self.c3)/(4*self.a3*self.c2) - (self.a3*self.c1 + self.a1*self.c2)*b/self.d)/self.a2
xn=self.a1*x - self.a2*y + self.a3*z
yn=-self.d*x*z + b
zn=self.c1*x*y + self.c2*y*z + self.c3*z + c
return xn, yn, zn
class ChuaAttractor(Attractor):
## http://haides.caltech.edu/~mcc/chaos_new/Chua.html
## http://www.science.gmu.edu/~rcastro/chualink.html
bl_idname = "curve.chua_attractor_add"
bl_label = "Chua"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a","b","c","d","e"]
a = get_prop("Chua", "a", 15.6)
b = get_prop("Chua", "b", 1.0)
c = get_prop("Chua", "c", 25.58)
d = get_prop("Chua", "d", -1)
e = get_prop("Chua", "e", 0)
x = get_prop("Chua", "x", 1.0)
y = get_prop("Chua", "y", 1.0)
z = get_prop("Chua", "z", 1.0)
dt = get_prop("Chua", "dt", 0.01)
def iterate(self, x, y, z):
h = self.e*x+(self.d+self.e)*(abs(x+1)-abs(x-1));
xn = self.a * (y - x - h);
yn = self.b * (x - y + z);
zn = -self.c * y;
return xn, yn, zn
class ChuaMultiIAttractor(Attractor):
## W. Tang, G. Zhong, G. Chen und K. Man Generation of N-Scroll Attractors via Sine Function
bl_idname = "curve.chuamultii_attractor_add"
bl_label = "ChuaMultiI"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints(15000)
params = ["alpha","beta","a","b","c"]
alpha = get_prop("ChuaMultiI", "alpha", 10.814)
beta = get_prop("ChuaMultiI", "beta", 14.0)
a = get_prop("ChuaMultiI", "a", 1.3)
b = get_prop("ChuaMultiI", "b", 0.11)
c = get_int_prop("ChuaMultiI", "c", 2)
x = get_prop("ChuaMultiI", "x", 1.0)
y = get_prop("ChuaMultiI", "y", 0.0)
z = get_prop("ChuaMultiI", "z", 0.0)
dt = get_prop("ChuaMultiI", "dt", 0.01)
def iterate(self, x, y, z):
d=0
if self.c % 2 == 0: d=math.pi
h = 0
if x >= 2*self.a*self.c:
h=((self.b*math.pi)/(2*self.a))*(x - 2*self.a*self.c)
if x <= -2*self.a*self.c:
h=((self.b*math.pi)/(2*self.a))*(x + 2*self.a*self.c)
if x < 2*self.a*self.c and x > -2*self.a*self.c:
h=-self.b*math.sin((math.pi*x)/(2*self.a)+d)
xn = self.alpha * (y - h)
yn = x - y + z
zn = -self.beta * y
return xn, yn, zn
class ChuaMultiIIAttractor(Attractor):
## J.A.K. Suykens und J. Vandewalle
## The K.U. Leuven Competition Data: a Challenge for Advanced Neural Network Techniques
## http://www.dice.ucl.ac.be/Proceedings/esann/esannpdf/es2000-261.pdf
bl_idname = "curve.chuamultiii_attractor_add"
bl_label = "ChuaMultiII"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints(15000)
params = ["alpha","beta","a","b"]
alpha = get_prop("ChuaMultiII", "alpha", 10.814)
beta = get_prop("ChuaMultiII", "beta", 14.0)
a = get_prop("ChuaMultiII", "a", 1.3)
b = get_prop("ChuaMultiII", "b", 0.11)
x = get_prop("ChuaMultiII", "x", 1.0)
y = get_prop("ChuaMultiII", "y", 0.0)
z = get_prop("ChuaMultiII", "z", 0.0)
dt = get_prop("ChuaMultiII", "dt", 0.01)
m = [0.9/7.0, -3.0/7.0, 3.5/7.0, -2.7/7.0, 4.0/7.0, -2.4/7.0]
c = [0.0, 1.0, 2.15, 3.6, 6.2, 9.0]
def iterate(self, x, y, z):
sum=0
for k in range(1,6):
sum+=((self.m[k-1] - self.m[k])*(abs(x + self.c[k])-abs(x - self.c[k])))
h = self.m[5]*x+0.5*sum
xn = self.alpha * (y - h)
yn = x - y + z
zn = -self.beta * y
return xn, yn, zn
class ChenLeeAttractor(Attractor):
bl_idname = "curve.chenlee_attractor_add"
bl_label = "ChenLee"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c"]
a = get_prop("ChenLee", "a", 5)
b = get_prop("ChenLee", "b", -10)
c = get_prop("ChenLee", "c", -0.38)
x = get_prop("ChenLee", "x", 1)
y = get_prop("ChenLee", "y", 1)
z = get_prop("ChenLee", "z", 1)
dt = get_prop("ChenLee", "dt", 0.002)
def iterate(self, x, y, z):
xn = self.a*x - y*z
yn = self.b*y + x*z
zn = self.c*z + x*y/3.0
return xn, yn, zn
class FinanceAttractor(Attractor):
bl_idname = "curve.finance_attractor_add"
bl_label = "Finance"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c"]
a = get_prop("Finance", "a", 0.001)
b = get_prop("Finance", "b", 0.2)
c = get_prop("Finance", "c", 1.1)
x = get_prop("Finance", "x", 0.1)
y = get_prop("Finance", "y", 0.1)
z = get_prop("Finance", "z", 0.1)
dt = get_prop("Finance", "dt", 0.002)
def iterate(self, x, y, z):
xn = (1/self.b - self.a)*x + x*y + z
yn = -self.b*y - x*x
zn = -x-self.c*z
return xn, yn, zn
class ChenCelikovskyAttractor(Attractor):
bl_idname = "curve.chencelikovsky_attractor_add"
bl_label = "ChenCelikovsky"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c"]
a = get_prop("ChenCelikovsky", "a", 36)
b = get_prop("ChenCelikovsky", "b", 3)
c = get_prop("ChenCelikovsky", "c", 20)
x = get_prop("ChenCelikovsky", "x", 1)
y = get_prop("ChenCelikovsky", "y", 1)
z = get_prop("ChenCelikovsky", "z", 1)
dt = get_prop("ChenCelikovsky", "dt", 0.002)
cnt = 0
t = 0
def iterate(self, x, y, z):
xn = self.a*(y-x)
yn = -(x*z)+(self.c*y)
zn = (x*y)-(self.b*z)
self.cnt += 1
if self.cnt >= 500: self.t = 1
return xn, yn, zn
class DadrasAttractor(Attractor):
bl_idname = "curve.dadras_attractor_add"
bl_label = "Dadras"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["p", "o", "r", "c", "e"]
p = get_prop("Dadras", "p", 3)
o = get_prop("Dadras", "o", 2.7)
r = get_prop("Dadras", "r", 1.7)
c = get_prop("Dadras", "c", 2)
e = get_prop("Dadras", "e", 9)
x = get_prop("Dadras", "x", 0.1)
y = get_prop("Dadras", "y", 0.03)
z = get_prop("Dadras", "z", 0.0)
dt = get_prop("Dadras", "dt", 0.008)
def iterate(self, x, y, z):
xn = y - self.p*x + self.o*y*z
yn = self.r*y - x*z + z
zn = self.c*x*y - self.e*z
return xn, yn, zn
class DequanLiAttractor(Attractor):
bl_idname = "curve.dequanli_attractor_add"
bl_label = "DequanLi"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints(20000)
params = ["a", "b", "d", "e", "p", "g"]
a = get_prop("DequanLi", "a", 40)
b = get_prop("DequanLi", "b", 11.0/6.0)
d = get_prop("DequanLi", "d", 0.16)
e = get_prop("DequanLi", "e", 0.65)
p = get_prop("DequanLi", "p", 55.0)
g = get_prop("DequanLi", "g", 20.0)
x = get_prop("DequanLi", "x", 0.01)
y = get_prop("DequanLi", "y", 0.0)
z = get_prop("DequanLi", "z", 0.0)
dt = get_prop("DequanLi", "dt", 0.0003)
def iterate(self, x, y, z):
xn = self.a*(y-x) + self.d*x*z
yn = self.p*x + self.g*y - x*z
zn = self.b*z + x*y - self.e*x*x
return xn, yn, zn
class YuWangAttractor(Attractor):
bl_idname = "curve.yuwang_attractor_add"
bl_label = "YuWang"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c", "d"]
a = get_prop("YuWang", "a", 10.0)
b = get_prop("YuWang", "b", 40.0)
c = get_prop("YuWang", "c", 2)
d = get_prop("YuWang", "d", 2.5)
x = get_prop("YuWang", "x", 0.1)
y = get_prop("YuWang", "y", 0.0)
z = get_prop("YuWang", "z", 15)
dt = get_prop("YuWang", "dt", 0.002)
def iterate(self, x, y, z):
xn = self.a*(y-x)
yn = self.b * x - self.c*x*z
zn = math.exp(x*y) - self.d*z
return xn, yn, zn
class HadleyAttractor(Attractor):
bl_idname = "curve.hadley_attractor_add"
bl_label = "Hadley"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "f", "g"]
a = get_prop("Hadley", "a", 0.2)
b = get_prop("Hadley", "b", 4)
f = get_prop("Hadley", "f", 8)
g = get_prop("Hadley", "g", 1)
x = get_prop("Hadley", "x", 0.0)
y = get_prop("Hadley", "y", 0.0)
z = get_prop("Hadley", "z", 1.3)
dt = get_prop("Hadley", "dt", 0.008)
def iterate(self, x, y, z):
xn = -y*y-z*z-self.a*x+self.a*self.f
yn = x*y-self.b*x*z-y+self.g
zn = self.b*x*y+x*z-z
return xn, yn, zn
class HalvorsenAttractor(Attractor):
bl_idname = "curve.halvorsen_attractor_add"
bl_label = "Halvorsen"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
param = ["a"]
a = get_prop("Halvorsen", "a", 1.4)
x = get_prop("Halvorsen", "x", -5)
y = get_prop("Halvorsen", "y", 0.0)
z = get_prop("Halvorsen", "z", 0.0)
dt = get_prop("Halvorsen", "dt", 0.004)
def iterate(self, x, y, z):
xn = -self.a*x-4*y-4*z-y*y
yn = -self.a*y-4*z-4*x-z*z
zn = -self.a*z-4*x-4*y-x*x
return xn, yn, zn
class LinzSprottAttractor(Attractor):
bl_idname = "curve.linzsprott_attractor_add"
bl_label = "LinzSprott"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
param = []
x = get_prop("LinzSprott", "x", 0.1)
y = get_prop("LinzSprott", "y", 0.1)
z = get_prop("LinzSprott", "z", 0.1)
dt = get_prop("LinzSprott", "dt", 0.01)
def iterate(self, x, y, z):
xn = y
yn = -x+y*z
zn = 1-pow(y,2)
return xn, yn, zn
class LorenzMod1Attractor(Attractor):
bl_idname = "curve.lorenzmod1_attractor_add"
bl_label = "LorenzMod1"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c", "d"]
a = get_prop("LorenzMod1", "a", 0.1)
b = get_prop("LorenzMod1", "b", 4)
c = get_prop("LorenzMod1", "c", 14)
d = get_prop("LorenzMod1", "d", 0.08)
x = get_prop("LorenzMod1", "x", 0.0)
y = get_prop("LorenzMod1", "y", 1)
z = get_prop("LorenzMod1", "z", 0.0)
dt = get_prop("LorenzMod1", "dt", 0.005)
def iterate(self, x, y, z):
xn = -self.a*x+(y*y)-(z*z)+self.a*self.c
yn = x*(y-self.b*z)+self.d
zn = -z+x*(self.b*y+z)
return xn, yn, zn
class LorenzMod2Attractor(Attractor):
bl_idname = "curve.lorenzmod2_attractor_add"
bl_label = "LorenzMod2"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "c", "d"]
a = get_prop("LorenzMod2", "a", 0.9)
b = get_prop("LorenzMod2", "b", 5)
c = get_prop("LorenzMod2", "c", 9.9)
d = get_prop("LorenzMod2", "d", 1)
x = get_prop("LorenzMod2", "x", 5)
y = get_prop("LorenzMod2", "y", 5)
z = get_prop("LorenzMod2", "z", 5)
dt = get_prop("LorenzMod2", "dt", 0.003)
def iterate(self, x, y, z):
xn = -self.a*x+(y*y)-(z*z)+self.a*self.c
yn = x*(y-self.b*z)+self.d
zn = -z+x*(self.b*y+z)
return xn, yn, zn
class NewtonLeipnikAttractor(Attractor):
bl_idname = "curve.newtonleipnik_attractor_add"
bl_label = "NewtonLeipnik"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b"]
a = get_prop("NewtonLeipnik", "a", 0.4)
b = get_prop("NewtonLeipnik", "b", 0.175)
x = get_prop("NewtonLeipnik", "x", 0.349)
y = get_prop("NewtonLeipnik", "y", 0.0)
z = get_prop("NewtonLeipnik", "z", -0.16)
dt = get_prop("NewtonLeipnik", "dt", 0.03)
def iterate(self, x, y, z):
xn = -self.a*x+y+10*y*z
yn = -x-0.4*y+5*x*z
zn = self.b*z-5*x*y
return xn, yn, zn
class NoseHooverAttractor(Attractor):
bl_idname = "curve.nosehoover_attractor_add"
bl_label = "NoseHoover"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a"]
a = get_prop("NoseHoover", "a", 1.5)
x = get_prop("NoseHoover", "x", 1)
y = get_prop("NoseHoover", "y", 0.0)
z = get_prop("NoseHoover", "z", 0.0)
dt = get_prop("NoseHoover", "dt", 0.009)
def iterate(self, x, y, z):
xn = y
yn = -x+y*z
zn = self.a-(y*y)
return xn, yn, zn
class RayleighBenardAttractor(Attractor):
bl_idname = "curve.rayleighbenard_attractor_add"
bl_label = "RayleighBenard"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "r", "b"]
a = get_prop("RayleighBenard", "a", 9)
r = get_prop("RayleighBenard", "r", 12)
b = get_prop("RayleighBenard", "b", 5)
x = get_prop("RayleighBenard", "x", 0.1)
y = get_prop("RayleighBenard", "y", 0.0)
z = get_prop("RayleighBenard", "z", 0.0)
dt = get_prop("RayleighBenard", "dt", 0.05)
def iterate(self, x, y, z):
xn = -self.a*x+self.a*y
yn = self.r*x-y-x*z
zn = x*y-self.b*z
return xn, yn, zn
class RucklidgeAttractor(Attractor):
bl_idname = "curve.rucklidge_attractor_add"
bl_label = "Rucklidge"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["k", "a"]
k = get_prop("Rucklidge", "k", 2)
a = get_prop("Rucklidge", "a", 6.7)
x = get_prop("Rucklidge", "x", -5)
y = get_prop("Rucklidge", "y", 0.0)
z = get_prop("Rucklidge", "z", 0.0)
dt = get_prop("Rucklidge", "dt", 0.008)
def iterate(self, x, y, z):
xn = -self.k*x+self.a*y-y*z
yn = x
zn = -z+y*y
return xn, yn, zn
class WangSunAttractor(Attractor):
bl_idname = "curve.wangsun_attractor_add"
bl_label = "WangSun"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints(30000)
params = ["a", "b", "c", "d", "e", "f"]
a = get_prop("WangSun", "a", 0.2)
b = get_prop("WangSun", "b", -0.01)
c = get_prop("WangSun", "c", 1.0)
d = get_prop("WangSun", "d", -0.4)
e = get_prop("WangSun", "e", -1.0)
f = get_prop("WangSun", "f", -1.0)
x = get_prop("WangSun", "x", 0.5)
y = get_prop("WangSun", "y", 0.1)
z = get_prop("WangSun", "z", 0.1)
dt = get_prop("WangSun", "dt", 0.02)
def iterate(self, x, y, z):
xn = self.a*x + self.c*y*z
yn = self.b*x + self.d*y - x*z
zn = self.e*z + self.f*x*y
return xn, yn, zn
class NewJerkAttractor(Attractor):
bl_idname = "curve.newjerk_attractor_add"
bl_label = "NewJerk"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["k", "a"]
a = get_prop("NewJerk", "a", 0.00000001)
b = get_prop("NewJerk", "b", 0.026)
x = get_prop("NewJerk", "x", 0.1)
y = get_prop("NewJerk", "y", 0.1)
z = get_prop("NewJerk", "z", 0.1)
dt = get_prop("NewJerk", "dt", 0.01)
def iterate(self, x, y, z):
xn = y
yn = z
zn = -z-x-self.a*(math.exp(y/self.b)-1.0)
return xn, yn, zn
class SakaryaAttractor(Attractor):
bl_idname = "curve.sakarya_attractor_add"
bl_label = "Sakarya"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b"]
a = get_prop("Sakarya", "a", 0.4)
b = get_prop("Sakarya", "b", 0.3)
x = get_prop("Sakarya", "x", 1)
y = get_prop("Sakarya", "y", -1)
z = get_prop("Sakarya", "z", 1)
dt = get_prop("Sakarya", "dt", 0.003)
def iterate(self, x, y, z):
xn = -x+y+(y*z)
yn = -x-y+self.a*(x*z)
zn = z-self.b*(x*y)
return xn, yn, zn
class Duffing(Attractor):
bl_idname = "curve.duffing_attractor_add"
bl_label = "Duffing"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b", "w"]
a = get_prop("Duffing", "a", 0.25)
b = get_prop("Duffing", "b", 0.3)
w = get_prop("Duffing", "w", 1.0)
x = get_prop("Duffing", "x", 0.1)
y = get_prop("Duffing", "y", 0.0)
z = get_prop("Duffing", "z", 0.0)
dt = get_prop("Duffing", "dt", 0.01)
t = 0.0
def iterate(self, x, y, z):
xn = y
yn = x-x**3-self.a*y+self.b*math.cos(self.t*self.w)
zn = 0
t += dt
return xn, yn, zn
class ShimizuMoriokaAttractor(Attractor):
bl_idname = "curve.shimizumorioka_attractor_add"
bl_label = "ShimizuMorioka"
bl_options = {"REGISTER", "UNDO"}
npoints = get_npoints()
params = ["a", "b"]
a = get_prop("ShimizuMorioka", "a", 0.75)
b = get_prop("ShimizuMorioka", "b", 0.45)
x = get_prop("ShimizuMorioka", "x", 0.1)
y = get_prop("ShimizuMorioka", "y", 0.0)
z = get_prop("ShimizuMorioka", "z", 0.0)
dt = get_prop("ShimizuMorioka", "dt", 0.01)
def iterate(self, x, y, z):
xn = y
yn = (1-z)*x-self.a*y
zn = (x*x)-self.b*z
return xn, yn, zn
class SprottDAttractor(Attractor):
bl_idname = "curve.sprottd_attractor_add"
bl_label = "SprottD"
bl_options = {"REGISTER", "UNDO"}