see the attachments

This page contains animations drawn using Sage. One can create an animation (.gif) in Sage from a list of graphics objects using the animate command. Currently, to export an animation in .gif format, you might need to install the ImageMagick command line tools package (the convert command). See the documentation for more information:

sage: animate?

Animated

The witch of Maria Agnesi

witch.gif

by Marshall Hampton

xtreme = 4.1
myaxes = line([[-xtreme,0],[xtreme,0]],rgbcolor = (0,0,0))
myaxes = myaxes + line([[0,-1],[0,2.1]],rgbcolor = (0,0,0))
a = 1.0
t = var('t')
npi = RDF(pi)
def agnesi(theta):
    mac = circle((0,a),a,rgbcolor = (0,0,0))
    maL = line([[-xtreme,2*a],[xtreme,2*a]])
    maL2 = line([[0,0],[2*a*cot(theta),2*a]])
    p1 = [2*a*cot(theta),2*a*sin(theta)^2]
    p2 = [2*a*cot(theta)-cot(theta)*(2*a-2*a*sin(theta)^2),2*a*sin(theta)^2]
    maL3 = line([p2,p1,[2*a*cot(theta),2*a]], rgbcolor = (1,0,0))
    map1 = point(p1)
    map2 = point(p2)
    am = line([[-.05,a],[.05,a]], rgbcolor = (0,0,0))
    at = text('a',[-.1,a], rgbcolor = (0,0,0))
    yt = text('y',[0,2.2], rgbcolor = (0,0,0))
    xt = text('x',[xtreme + .1,-.1], rgbcolor = (0,0,0))
    matext = at+yt+xt
    ma = mac+myaxes+maL+am+matext+maL2+map1+maL3+map2
    return ma

def witchy(theta):
    ma = agnesi(theta)
    agplot = parametric_plot([2*a*cot(t),2*a*sin(t)^2],[t,.001,theta], rgbcolor = (1,0,1))
    return ma+agplot

a2 = animate([witchy(i) for i in srange(.1,npi-.1,npi/60)]+[witchy(i) for i in srange(npi-.1,.1,-npi/60)], xmin = -3, xmax = 3, ymin = 0, ymax = 2.3, figsize = [6,2.3], axes = False)

a2.show()

A simpler hypotrochoid

The following animates a hypotrochoid

import operator

# The colors for various elements of the plot:
class color:
    stylus = (1, 0, 0)
    outer  = (.8, .8, .8)
    inner  = (0, 0, 1)
    plot   = (0, 0, 0)
    center = (0, 0, 0)
    tip    = (1, 0, 0)
# and the corresponding line weights:
class weight:
    stylus = 1
    outer  = 1
    inner  = 1
    plot   = 1
    center = 5
    tip    = 5

scale = 1            # The scale of the image
animation_delay = .1 # The delay between frames, in seconds

# Starting and ending t values
t_i = 0
t_f = 2*pi
# The t values of the animation frames
tvals = srange(t_i, t_f, (t_f-t_i)/60)

r_o = 8 # Outer circle radius
r_i = 2 # Inner circle radius
r_s = 3 # Stylus radius

# Coordinates of the center of the inner circle
x_c = lambda t: (r_o - r_i)*cos(t)
y_c = lambda t: (r_o - r_i)*sin(t)

# Parametric coordinates for the plot
x = lambda t: x_c(t) + r_s*cos(t*(r_o/r_i))
y = lambda t: y_c(t) - r_s*sin(t*(r_o/r_i))

# Maximum x and y values of the plot
x_max = r_o - r_i + r_s
y_max = find_maximum_on_interval(y, t_i, t_f)[0]

# The plots of the individual elements. Order is important; plots
# are stacked from bottom to top as they appear.
elements = (
    # The outer circle
    lambda t_f: circle((0, 0),               r_o, rgbcolor=color.outer, thickness=weight.outer),
    # The plot itself
    lambda t_f: parametric_plot((x, y), t_i, t_f, rgbcolor=color.plot,  thickness=weight.plot),
    # The inner circle
    lambda t_f: circle((x_c(t_f), y_c(t_f)), r_i, rgbcolor=color.inner, thickness=weight.inner),
    # The inner circle's center
    lambda t_f: point((x_c(t_f), y_c(t_f)),       rgbcolor=color.center,pointsize=weight.center),
    # The stylus
    lambda t_f: line([(x_c(t_f), y_c(t_f)), (x(t_f), y(t_f))], rgbcolor=color.stylus, thickness=weight.stylus),
    # The stylus' tip
    lambda t_f: point((x_c(t_f), y_c(t_f)),       rgbcolor=color.tip,   pointsize=weight.tip),
)

# Create the plots and animate them. The animate function renders an
# animated gif from the frames provided as its first argument.
# Though avid python programmers will find the syntax clear, an
# explanation is provided for novices.
animation = animate([sum(f(t) for f in elements)
                     for t in tvals],
                    xmin=-x_max, xmax=x_max,
                    ymin=-y_max, ymax=y_max,
                    figsize=(x_max*scale, y_max*scale * y_max/x_max))

animation.show(delay=animation_delay)

# The previous could be expressed more pedagogically as follows:
#
#   Evaluate each function in the elements array for the provided t
#   value:
#
#     plots = lambda t: f(t) for f in elements
#
#   Join a group of plots together to form a single plot:
#
#     def join_plots(plots):
#         result = plots[0]
#         for plot in plots[1:]:
#             result += plot
#         return result
#
#   or
#
#     join_plots = sum
#
#   Create an array of plots, one for each provided t value:
#
#     frames = [join_plots(plots(t)) for t in tvals]
#
#   Finally, animate the frames:
#
#     animation = animate(frames)

The Towers of Hanoi

hanoi.gif

by Pablo Angulo

def plot_towers(towers):
    '''Returns a plot of the towers of Hanoi
    
    Uses matrix_plot
    '''
    K=max(max(l) for l in towers if l)+1
    M=matrix(ZZ,K,6*K+7)
    #first tower
    for t in range(len(towers[0])):
        j = t
        k=towers[0][t]-1
        for l in range(K+1-k,K+2+k):
            M[K-1-j,l]=1
    #second tower
    for t in range(len(towers[1])):
        j = t
        k=towers[1][t]-1
        for l in range(3*K+3-k,3*K+4+k):
            M[K-1-j,l]=1
    #third tower
    for t in range(len(towers[2])):
        j = t
        k=towers[2][t]-1
        for l in range(5*K+5-k,5*K+6+k):
            M[K-1-j,l]=1

    return matrix_plot(M, axes=False)

def animate_towers(towers,a=0,b=1,c=2,k=-1):
    '''Move last k discs from column a into column b
    
    Assumes that the last k discs of column a are all smaller 
    than the discs in columns b and c
    '''
    if k==0:  return
    if k==-1: k=len(towers[a])
    for t in animate_towers(towers,a,c,b,k-1):
        yield t
    disc = towers[a].pop()
    towers[b].append(disc)
    yield plot_towers(towers)
    for t in animate_towers(towers,c,b,a,k-1):
        yield t

towers = (range(4,0,-1),[],[])
initial = plot_towers(towers)
frame_list=[initial]+list(animate_towers(towers))
animate(frame_list, axes=False).show(delay=80)

Fibonacci Tiles

fibotile.gif

by Sébastien Labbé

sage: path_op = dict(rgbcolor='red', thickness=1)
sage: fill_op = dict(rgbcolor='blue', alpha=0.3)
sage: options = dict(pathoptions=path_op, filloptions=fill_op, endarrow=False, startpoint=False)
sage: G = [words.fibonacci_tile(i).plot(**options) for i in range(7)]
sage: a = animate(G)
sage: a.show(delay=150)

Pencil of conics

by Pablo Angulo pencil.gif

puntos = [(0,0),(0,1),(1,3),(2,1)]
K = len(puntos)

var('x y')
coefs = matrix(QQ, K, 6)
for j in range(K):
    x0, y0 = puntos[j]
    coefs[j,:] = vector([x0^2, y0^2, x0*y0, x0, y0, 1])
    
K = coefs.right_kernel()
v1 = K.basis()[0]
v2 = K.basis()[1]

graficas = []
for t in srange(0,2*pi,0.3):
    c1, c2 = sin(t), cos(t)
    a,b,c,d,e,f = c1*v1 + c2*v2
    curva = a*x^2 + b*y^2 + c*x*y + d*x + e*y + f
    graficas.append( point2d(puntos,color=(1,0,0),pointsize=30) + 
                     implicit_plot(curva,(x,-1,4),(y,-1,4)) )
a = animate(graficas)

a.show(delay=10)

Pictures drawn by Sage

These pictures and images were drawn by Sage.

Everywhere continuous, nowhere differentiable function

p = Graphics()
for n in range(1,20):
  f = lambda x: sum([sin(x*3^i)/(2^i) for i in range(1,n)])
  p += plot(f,0,float(pi/3),plot_points=2000,rgbcolor=hue(n/20))

p.show(xmin=0, ymin=0,dpi=250)

cool pic 1

Mirrored balls in tachyon

t = Tachyon(camera_center=(8.5,5,5.5), look_at=(2,0,0), raydepth=6, xres=1500, yres=1500)
t.light((10,3,4), 1, (1,1,1))
t.texture('mirror', ambient=0.05, diffuse=0.05, specular=.9, opacity=0.9, color=(.8,.8,.8))
t.texture('grey', color=(.8,.8,.8), texfunc=7) ## try other values of texfunc too!
t.plane((0,0,0),(0,0,1),'grey')
t.sphere((4,-1,1), 1, 'mirror')
t.sphere((0,-1,1), 1, 'mirror')
t.sphere((2,-1,1), 0.5, 'mirror')
t.sphere((2,1,1), 0.5, 'mirror')
show(t)

cool ray tracing pic

Math art by Tom Boothby

# Author: Tom Boothby
# This is a remake of an old art piece I made in POVRay


t = Tachyon(xres=1000,yres=600, camera_center=(1,0,5), antialiasing=3)
t.light((4,3,2), 0.2, (1,1,1))
t.texture('t0', ambient=0.1, diffuse=0.9, specular=0.5, opacity=1.0, color=(1.0,1,1))
t.texture('t1', ambient=0.5, diffuse=0.5, specular=0.0, opacity=1.0, color=(0,0,0))
t.texture('t2', ambient=0.2, diffuse=0.7, specular=0, opacity=0.7, color=(.5,.5,.5))
t.texture('t3', ambient=.9, diffuse=5, specular=0,opacity=.1, color=(1,0,0))
t.sphere((1,0,0), 30, 't2')



k=0
for i in srange(-pi*10,0,.01):
  k += 1
  t.sphere((cos(i/10)-.1, sin(i/10)*cos(i), sin(i/10)*sin(i)), 0.1, 't0')
  t.sphere((cos(i/10) + 2.1, sin(i/10)*cos(i), sin(i/10)*sin(i)), 0.1, 't1')

t.show(verbose=1)

cool pic 2

Twisted cubic in tachyon

t = Tachyon(xres=512,yres=512, camera_center=(5,0,0))
t.light((4,3,2), 0.2, (1,1,1))
t.texture('t0', ambient=0.1, diffuse=0.9, specular=0.5, opacity=1.0, color=(1.0,0,0))
t.texture('t1', ambient=0.1, diffuse=0.9, specular=0.3, opacity=1.0, color=(0,1.0,0))
t.texture('t2', ambient=0.2, diffuse=0.7, specular=0.5, opacity=0.7, color=(0,0,1.0))
k=0
for i in srange(-5,1.5,0.1):
    k += 1
    t.sphere((i,i^2-0.5,i^3), 0.1, 't%s'%(k%3))

t.show()

cool pic 3

Reflections from four spheres in tachyon

t6 = Tachyon(camera_center=(0,-4,1), xres = 800, yres = 600, raydepth = 12, aspectratio=.75, antialiasing = True)
t6.light((0.02,0.012,0.001), 0.01, (1,0,0))
t6.light((0,0,10), 0.01, (0,0,1))
t6.texture('s', color = (.8,1,1), opacity = .9, specular = .95, diffuse = .3, ambient = 0.05)
t6.texture('p', color = (0,0,1), opacity = 1, specular = .2)
t6.sphere((-1,-.57735,-0.7071),1,'s')
t6.sphere((1,-.57735,-0.7071),1,'s')
t6.sphere((0,1.15465,-0.7071),1,'s')
t6.sphere((0,0,0.9259),1,'s')
t6.plane((0,0,-1.9259),(0,0,1),'p')
t6.show()

A cone inside a sphere

sage: u,v = var("u,v")
sage: p1 = parametric_plot3d([cos(u)*v, sin(u)*v, 3*v/2-1/3], (u, 0, 2*pi), (v, 0, 0.95),plot_points=[20,20])
sage: p2 = sphere((0,0,2/3), color='red', opacity=0.5, aspect_ratio=[1,1,1])
sage: show(p1+p2)

http://sage.math.washington.edu/home/wdj/art/cone-inside-sphere.jpg

A cylinder inside a cone

sage: u,v = var("u,v")
sage: p1 = parametric_plot3d([cos(u)*v, sin(u)*v, 3/2-3*v/2], (u, 0, 2*pi), (v, 0, 1.5), opacity = 0.5, plot_points=[20,20])
sage: p2 = parametric_plot3d([cos(u)/2, sin(u)/2, v-3/4], (u, 0, 2*pi), (v, 0, 3/2), plot_points=[20,20])
sage: show(p1+p2)

http://sage.math.washington.edu/home/wdj/art/cylinder-inside-cone.jpg

p-adic Seasons Greetings

http://sage.math.washington.edu/home/wdj/art/padic-seasons-greetings.png

This is the code:

sage: P1 = Zp(3).plot(rgbcolor=(0,1,0))
sage: P2 = Zp(7).plot(rgbcolor=(1,0,0))
sage: P3 = text("$Seasons$ $Greetings$ ",(0.0,1.8))
sage: P4 = text("$from$ $everyone$ $at$ sagemath.org!",(0.1,-1.6))
sage: (P1+P2+P3+P4).show(axes=False)

Lorentz butterfly

"""
Draws Loretz butterfly using matplotlib (2d) or jmol (3d).
Written by Matthew Miller and William Stein.

"""

def butterfly2d():
    """"
    EXAMPLE:
        sage: butterfly2d()
    """
    g = Graphics()
    x1, y1 = 0, 0
    from math import sin, cos, exp, pi
    for theta in srange( 0, 10*pi, 0.01 ):
        r = exp(cos(theta)) - 2*cos(4*theta) + sin(theta/12)^5
        x = r * cos(theta)  # Convert polar to rectangular coordinates
        y = r * sin(theta)
        xx = x*6 + 25       # Scale factors to enlarge and center the curve.
        yy = y*6 + 25
        if theta != 0:
            l = line( [(x1, y1), (xx, yy)], rgbcolor=hue(theta/7 + 4) )
            g = g + l
            x1, y1 = xx, yy
    g.show(dpi=100, axes=False)

def butterfly3d():
    """"
    EXAMPLE:
        sage: butterfly3d()
    """
    g = point3d((0,0,0))
    x1, y1 = 0, 0
    from math import sin, cos, exp, pi
    for theta in srange( 0, 10*pi, 0.05):
        r = exp(cos(theta)) - 2*cos(4*theta) + sin(theta/12)^5
        x = r * cos(theta)  # Convert polar to rectangular coordinates
        y = r * sin(theta)
        xx = x*6 + 25       # Scale factors to enlarge and center the curve.
        yy = y*6 + 25
        if theta != 0:
            l = line3d( [(x1, y1, theta), (xx, yy, theta)],
            rgbcolor=hue(theta/7 + 4) )
            g = g + l
            x1, y1 = xx, yy
    g.show(dpi=100, axes=False)

http://sage.math.washington.edu/home/wdj/art/butterfly2d.png

http://sage.math.washington.edu/home/wdj/art/butterfly3d.png

Feigenbaum diagram

Author: Pablo Angulo Posted to sage-devel 2008-09-13. See also https://sage.math.washington.edu:8101/home/pub/3 #Note: Mandelbrot set moved to interact/fractals

#Plots Feigenbaum diagram: divides the parameter interval [2,4] for mu
#into N steps. For each value of the parameter, iterate the discrete
#dynamical system x->mu*x*(1-x), drop the first M1 points in the orbit
#and plot the next M2 points in a (mu,x) diagram

N=200
M1=200
M2=200
x0=0.509434

puntos=[]
for t in range(N):
   mu=2.0+2.0*t/N
   x=x0
   for i in range(M1):
       x=mu*x*(1-x)
   for i in range(M2):
       x=mu*x*(1-x)
       puntos.append((mu,x))
point(puntos,pointsize=1)

Sierpinski triangle

def sierpinski_seasons_greetings():
    """
    Code by Marshall Hampton.
    Colors by David Joyner.
    General depth by Rob Beezer.
    Copyright Marshall Hampton 2008, licensed
    creative commons, attribution share-alike.
    """
    depth = 7
    nsq = RR(3^(1/2))/2.0
    tlist_old = [[[-1/2.0,0.0],[1/2.0,0.0],[0.0,nsq]]]
    tlist_new = tlist_old[:]
    for ind in range(depth):
       for tri in tlist_old:
           for p in tri:
               new_tri = [[(p[0]+x[0])/2.0, (p[1]+x[1])/2.0] for x in tri]
               tlist_new.append(new_tri)
       tlist_old = tlist_new[:]
    T = tlist_old
    N  = 4^depth
    N1 = N - 3^depth
    q1 = sum([line(T[i]+[T[i][0]], rgbcolor = (0,1,0)) for i in range(N1)])
    q2 = sum([line(T[i]+[T[i][0]], rgbcolor = (1,0,0)) for i in range(N1,N)])
    show(q2+q1, figsize = [6,6*nsq], axes = False)

GIMP was used to add a Season's greetings message:

http://sage.math.washington.edu/home/wdj/art/sierpinski-seasons-greetings-from-sage.png

Also (thanks to Rob Beezer) available in poster form in pdf format: http://sage.math.washington.edu/home/wdj/art/seasons-greetings-sage.pdf, and in A4 size: http://sage.math.washington.edu/home/wdj/art/seasons-greetings-sage-a4.pdf.

Integral Curvature Apollonian Circle Packing

by Marshall Hampton and Carl Witty

def kfun(k1,k2,k3,k4):
    """
    The Descartes formula for the curvature of an inverted tangent circle.
    """
    return 2*k1+2*k2+2*k3-k4


colorlist = [(1,0,1),(0,1,0),(0,0,1),(1,0,0)]

def circfun(c1,c2,c3,c4):
    """
    Computes the inversion of circle 4 in the first three circles.
    """
    newk = kfun(c1[3],c2[3],c3[3],c4[3])
    newx = (2*c1[0]*c1[3]+2*c2[0]*c2[3]+2*c3[0]*c3[3]-c4[0]*c4[3])/newk
    newy = (2*c1[1]*c1[3]+2*c2[1]*c2[3]+2*c3[1]*c3[3]-c4[1]*c4[3])/newk
    newcolor = c4[4]
    if newk > 0:
        newr = 1/newk
    elif newk < 0:
        newr = -1/newk
    else:
        newr = Infinity
    return [newx, newy, newr, newk, newcolor]

def mcircle(circdata, label = False, thick = 1/10, cutoff = 2000, color = ''):
    """
    Draws a circle from the data.  label = True
    """
    if color == '':
        color = colorlist[circdata[4]]
    if label==True and circdata[3] > 0 and circdata[2] > 1/cutoff:
        lab = text(str(circdata[3]),(circdata[0],circdata[1]), fontsize = \
500*(circdata[2])^(.95), vertical_alignment = 'center', horizontal_alignment \
= 'center', rgbcolor = (0,0,0),zorder=10)
    else:
        lab = Graphics()
    circ = circle((circdata[0],circdata[1]), circdata[2], rgbcolor = (0,0,0), \
thickness = thick)
    circ = circ + circle((circdata[0],circdata[1]), circdata[2], rgbcolor = color, \
thickness = thick, fill=True, alpha = .4, zorder=0)
    return lab+circ

def add_circs(c1, c2, c3, c4, cutoff = 300):
    """
    Find the inversion of c4 through c1,c2,c3.  Add the result to circlist,
    then (if the result is big enough) recurse.
    """
    newcirc = circfun(c1, c2, c3, c4)
    if newcirc[3] < cutoff:
        circlist.append(newcirc)
        add_circs(newcirc, c1, c2, c3, cutoff = cutoff)
        add_circs(newcirc, c2, c3, c1, cutoff = cutoff)
        add_circs(newcirc, c3, c1, c2, cutoff = cutoff)

zst1 = [0,0,1/2,-2,0]
zst2 = [1/6,0,1/3,3,1]
zst3 = [-1/3,0,1/6,6,2]
zst4 = [-3/14,2/7,1/7,7,3]

circlist = [zst1,zst2,zst3,zst4]
add_circs(zst1,zst2,zst3,zst4,cutoff = 500)
add_circs(zst2,zst3,zst4,zst1,cutoff = 500)
add_circs(zst3,zst4,zst1,zst2,cutoff = 500)
add_circs(zst4,zst1,zst2,zst3,cutoff = 500)

circs = sum([mcircle(q, label = True, thick = 1/2) for q in \
circlist[1:]])
circs = circs + mcircle(circlist[0],color=(1,1,1),thick=1)
circs.save('./Apollonian3.png',axes = False, figsize = [12,12], xmin = \
-1/2, xmax = 1/2, ymin = -1/2, ymax = 1/2)

Call graph of a recursive function

def grafo_llamadas(f):
    class G(object):
        def __init__(self, f):
            self.f=f
            self.stack = []
            self.g   = DiGraph()
        def __call__(self, *args):
            if self.stack:
                sargs = ','.join(str(a) for a in args)
                last  = ','.join(str(a) for a in self.stack[-1])
                if self.g.has_edge(last, sargs):
                    l = self.g.edge_label(last, sargs)
                    self.g.set_edge_label(last, sargs, l + 1)
                else:
                    self.g.add_edge(last, sargs, 1)
            else:
                self.g   = DiGraph()
            self.stack.append(args)
            v = self.f(*args)
            self.stack.pop()
            return v
        def grafo(self):
            return self.g
    return G(f)

@grafo_llamadas
def particiones(n, k):
    if k == n:
        return [[1]*n]
    if k == 1:
        return [[n]]
    if not(0 < k < n):
        return []
    ls1 = [p+[1] for p in particiones(n-1, k-1)]
    ls2 = [[parte+1 for parte in p] for p in particiones(n-k, k)]
    return ls1 + ls2

particiones(13,5)
g = particiones.grafo()
g.show(edge_labels=True, figsize=(6,6), vertex_size=500, color_by_label=True)

.

#D3js interactive version (just a screenshot here)
edge_partition = [
    [edge for edge in g.edges() if edge[-1]==el]
    for el in set(g.edge_labels())
    ]
g.show(method='js',
       edge_labels=True,
       vertex_labels=True,
       link_distance=90,
       charge=-400,
       link_strength=2,
       force_spring_layout=True,
       edge_partition=edge_partition)

Sage plotting

Here are some python plotting engines/libraries:

Sage's plotting functionality is built on top of matplotlib, which is a very extensive plotting library with a user interface that is very similiar to Matlab's plotting. The interface that Sage provides to matplotlib is very Mathematica like.

There are also several links to plotting/graphics/data visualization programs at the scipy wiki.

art (last edited 2017-02-03 20:19:02 by mrennekamp)