18417
Comment:

18327
fixing geodesics interact ...

Deletions are marked like this.  Additions are marked like this. 
Line 12:  Line 12: 
p12 = p1.union(p2)  p12 = p1.convex_hull(p2) 
Line 15:  Line 15: 
p34 = p3.union(p4)  p34 = p3.convex_hull(p4) 
Line 18:  Line 18: 
p56 = p5.union(p6)  p56 = p5.convex_hull(p6) 
Line 21:  Line 21: 
p78 = p7.union(p8)  p78 = p7.convex_hull(p8) 
Line 85:  Line 85: 
by Antonio Valdés and Pablo Angulo. A first interact allows the user to introduce a parametric surface, and draws it. Then a second interact draws a geodesic within the surface. The separation is so that after the first interact, the geodesic equations are "compiled", and then the second interact is faster. {{{#!sagecell u, v, t = var('u v t') 
by Antonio Valdés and Pablo Angulo. This example was originally composed of two interacts:  the first allowing the user to introduce a parametric surface, and draw it.  the second drawing a geodesic within the surface. The separation was so that after the first interact, the geodesic equations were "compiled", thus making the second interact faster. This still looks as a good idea to me, so please read the original code at https://malabares.cancamusa.net/home/pub/14/ But the following is fixed so that there is only one interact, and sagecell works. There might be another way yto {{{#!sagecell from scipy.integrate import odeint u, v, t, du, dv = var('u v t du dv') def fading_line3d(points, rgbcolor1, rgbcolor2, *args, **kwds): L = len(points) vcolor1 = vector(RDF, rgbcolor1) vcolor2 = vector(RDF, rgbcolor2) return sum(line3d(points[j:j+2], rgbcolor = tuple( ((Lj)/L)*vcolor1 + (j/L)*vcolor2 ), *args, **kwds) for j in srange(L1)) steps = 100 
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_int_u = input_grid(1, 2, default = [[0,pi]], label = 'u interval'), _int_v = input_grid(1, 2, default = [[pi,pi]], label = 'v interval')): global F, Fu, Fv, func, S_plot, int_u, int_v int_u = _int_u[0] int_v = _int_v[0] 
int_u = input_grid(1, 2, default = [[0,pi]], label = 'u interval'), int_v = input_grid(1, 2, default = [[pi,pi]], label = 'v interval'), init_point = input_grid(1, 2, default = [[pi/4,pi/8]], label = 'coordinates of \ninitial point'), init_vector = input_grid(1, 2, default = [[1,0]], label = 'coordinates of \ninitial vector'), int_s = slider(0, 10, 1/10, default = pi/2, label = 'geodesic interval'), sliding_color = checkbox(True,'change color along the geodesic')): int_u = int_u[0] int_v = int_v[0] u_0, v_0 = init_point[0] V_u, V_v = init_vector[0] 
Line 104:  Line 132: 
S_plot.show(aspect_ratio = [1, 1, 1]) 

Line 143:  Line 170: 
# second interact from scipy.integrate import odeint def fading_line3d(points, rgbcolor1, rgbcolor2, *args, **kwds): L = len(points) vcolor1 = vector(RDF, rgbcolor1) vcolor2 = vector(RDF, rgbcolor2) return sum(line3d(points[j:j+2], rgbcolor = tuple( ((Lj)/L)*vcolor1 + (j/L)*vcolor2 ), *args, **kwds) for j in srange(L1)) steps = 100 @interact def _(u_0 = slider(int_u[0], int_u[1], (int_u[1]  int_u[0])/100, default = (int_u[0] + int_u[1])/2, label = 'u_0'), v_0 = slider(int_v[0], int_v[1], (int_v[1]  int_v[0])/100, default = (int_v[0] + int_v[1])/2, label = 'v_0'), V_u = slider(10, 10, 1/10, default = 1, label = 'V_u'), V_v = slider(10, 10, 1/10, default = 0, label = 'V_v'), int_s = slider(0, 10, 1/10, default = (int_u[1]  int_u[0])/2, label = 'geodesic interval'), sliding_color = checkbox(True,'change color along the geodesic')): du, dv, u, v = var('du dv u v') Point = [u_0, v_0] velocity = [V_u, V_v] Point = map(float, Point) velocity = map(float, velocity) geo2D_aux = odeint(func, y0 = [velocity[0], velocity[1], Point[0], Point[1]], t = srange(0, int_s, 0.01)) geo3D = [F(u=l,v=r) for [j, k, l, r] in geo2D_aux] if sliding_color: g_plot = fading_line3d(geo3D, rgbcolor1 = (1, 0, 0), rgbcolor2 = (0, 1, 0), thickness=4) else: g_plot = line3d(geo3D, rgbcolor=(0, 1, 0), thickness=4) P = F(u=Point[0], v=Point[1]) P_plot = point3d((P[0], P[1], P[2]), rgbcolor = (0, 0, 0), pointsize = 30) V = velocity[0] * Fu(u = Point[0], v = Point[1]) + \ velocity[1] * Fv(u= Point[0], v = Point[1]) V_plot = arrow3d(P, P + V, color = 'black') show(g_plot + S_plot + V_plot + P_plot,aspect_ratio = [1, 1, 1]) 
Point = [u_0, v_0] velocity = [V_u, V_v] Point = map(float, Point) velocity = map(float, velocity) geo2D_aux = odeint(func, y0 = [velocity[0], velocity[1], Point[0], Point[1]], t = srange(0, int_s, 0.01)) geo3D = [F(u=l,v=r) for [j, k, l, r] in geo2D_aux] if sliding_color: g_plot = fading_line3d(geo3D, rgbcolor1 = (1, 0, 0), rgbcolor2 = (0, 1, 0), thickness=4) else: g_plot = line3d(geo3D, rgbcolor=(0, 1, 0), thickness=4) P = F(u=Point[0], v=Point[1]) P_plot = point3d((P[0], P[1], P[2]), rgbcolor = (0, 0, 0), pointsize = 30) V = velocity[0] * Fu(u = Point[0], v = Point[1]) + \ velocity[1] * Fv(u= Point[0], v = Point[1]) V_plot = arrow3d(P, P + V, color = 'black') show(g_plot + S_plot + V_plot + P_plot,aspect_ratio = [1, 1, 1]) 
Sage Interactions  Geometry
goto interact main page
Contents
Intersecting tetrahedral reflections FIXME
by Marshall Hampton. Inspired by a question from Hans Schepker of Glass Geometry.
Evolutes
by Pablo Angulo. Computes the evolute of a plane curve given in parametric coordinates. The curve must be parametrized from the interval [0,2pi].
Geodesics on a parametric surface
by Antonio Valdés and Pablo Angulo. This example was originally composed of two interacts:
  the first allowing the user to introduce a parametric surface, and draw it.  the second drawing a geodesic within the surface.
The separation was so that after the first interact, the geodesic equations were "compiled", thus making the second interact faster.
This still looks as a good idea to me, so please read the original code at https://malabares.cancamusa.net/home/pub/14/ But the following is fixed so that there is only one interact, and sagecell works. There might be another way yto
Dimensional Explorer
By Eviatar Bach
Renders 2D images (perspective or springlayout) and 3D models of 010 dimensional hypercubes. It also displays number of edges and vertices.
Crofton's formula
by Pablo Angulo. Illustrates Crofton's formula by throwing some random lines and computing the intersection number with a given curve. May use either solve for exact computation of the intersections, or may also approximate the curve by straight segments (this is the default).
BanchoffPohl area
by Pablo Angulo. Computes the BanchoffPohl "area enclosed by a spatial curve", by throwing some random lines and computing the linking number with the given curve. Lines not linked to the given curve are displayed in red, linked lines are displayed in green.