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Two distinct uniformly distributed points on a sphere from one uniform distribut

Two distinct uniformly distributed points on a sphere from one uniform distribut
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2021-01-18 02:11
VectorSolid GeometryOptimizationGeometric Construction
This example demonstrates how to generate two different points on a sphere from a single uniform random parameter, aiming for uniformity and good spherical coverage using a geometry-driven construction based on a biscribed/truncated icosahedron model (V=60). It combines sphere geometry with vector-based distance/angle measures to control how the two points relate, and uses constrained search via max/min logic to select valid candidates and verify extremal test quantities. Key math concepts include: solid/solid-like spherical geometry (Sphere, Circle), vectors and angular relationships (Vector, Angle), and optimization-style feasibility selection (Max/Min) guided by region tests (PointIn). In GeoGebra, the construction leverages commands such as Polygon to build the polyhedral partition/structure, Sphere and Circle for the underlying spherical geometry, PointIn and If for membership testing in candidate regions, Vector/Angle/Length for geometric relations, and Textfield/TableText with auxiliary text (e.g., RotateText) for parameter control and numerical verification (e.g., Zmin/Zmax, fmin/fmax). Suitable for advanced high-school enrichment and undergraduate courses on geometric construction, spherical sampling, and computational math experimentation.

GeoGebra Commands & Parameters

  1. Polygon({((-π), ((-π)) / 2), ((-π), π / 2), (π, π / 2), (π, ((-π)) / 2)}) → q_2
  2. PointIn(q_2) → Atest_2
  3. Function(f01, (-π), π, ((-π)) / 2, π / 2) → f0
  4. Zip((x(a), y(a), f0(a)), a, Zmin_2) → fmin3D
  5. Zip((x(a), y(a), f0(a)), a, Zmax_2) → fmax3D
  6. Vector((1.3 * Z3), (1.5 * Z3)) → AVZ3r
  7. Vector((1.3 * Z3), (1.3 * Z3) + UnitVector[Sum[Zip[UnitVector[a - Z3], a, lP]]]) → AVZ3
  8. Vector((1.3 * Z2), (1.5 * Z2)) → AVZ2r
  9. Vector((1.3 * Z2), (1.3 * Z2) + UnitVector[Sum[Zip[UnitVector[a - Z2], a, lP]]]) → AVZ2
  10. Vector((1.3 * Z1), (1.5 * Z1)) → AVZ1r
  11. Vector((1.3 * Z1), (1.3 * Z1) + UnitVector[Sum[Zip[UnitVector[a - Z1], a, lP]]]) → AVZ1
  12. Vector((1.3 * Atest_R), (1.3 * Atest_R) + UnitVector[Sum[Zip[UnitVector[a - Atest_R], a, lP]]]) → AVtest
  13. Vector((1.3 * Atest_R), (1.5 * Atest_R)) → AVtestr
  14. Sphere(O, R) → sphera
  15. Circle(O, R, xOyPlane) → c
  16. PointIn(q_2) → RZ1_2
  17. PointIn(q_2) → RZ2_2
  18. Angle(AVtest, AVtestr) → αA
  19. Angle(AVZ1, AVZ1r) → αZ1
  20. Angle(AVZ2, AVZ2r) → αZ2
  21. Zip(Segment[Atest_R, p], p, lP) → seg
  22. Sum(seg) → sum_seg
  23. PolyLine({((-π), ((-π)) / 2), ((-π), π / 2), (π, π / 2), (π, ((-π)) / 2), ((-π), ((-π)) / 2)}) → q1
  24. Flatten(Sequence[Sequence[((-π) + ((2 * π / na) * i), ((-π)) / 2 + (π / na * j)), j, 1, na], i, 1, na]) → ltest_2
  25. Zip((R; x(a); y(a)), a, ltest_2) → ltest_3
  26. Length(lZmax') → lälZmax'
  27. Textfield(n) → InputBox11
  28. alfa(R, lP, lZsad') → αsad
  29. If(αZ1 > 100°, 180° - αZ1, αZ1) → αZ1'
  30. Textfield(m_1) → InputBox12
  31. Textfield(t) → InputBox13
  32. Textfield(m_2) → InputBox14
  33. PointIn(q_2) → RZ3_2
  34. Sum(Zip[1 / Length[p - Z3], p, lP]) → ZahZ3
  35. Angle(AVZ3, AVZ3r) → αZ3
  36. Textfield(R) → InputBox1
  37. Textfield(na) → InputBox2
  38. Max(f(Zmax_2)) → max_f
  39. Min(f(Zmin_2)) → min_f
  40. Zip(Text["d_{" + (a) + "}", (Atest_R + Element[lP, a]) / 2], a, 1…n) → lPtxt
  41. Zip(Segment[F_o, p], p, lP) → seg0
  42. Sum(seg0) → sum_seg0
  43. RotateText(txt, 90°) → txt1
  44. Sum(lZ3sad) → sumlZ3sad
  45. Textfield(Points3D) → InputBox7
  46. Textfield(lZsad') → InputBox17
  47. Textfield(lZmin') → InputBox16
  48. Textfield(lZmax') → InputBox15
  49. Textfield(jmin) → InputBox18
  50. Textfield(jmax) → InputBox19
  51. Textfield(jsad) → InputBox20
  52. Zip(Text["" + (b), a - (0.1, 0.1)], a, Zmax_2, b, 1…Length[Zmax_2]) → l2maxtxt
  53. Zip(Text["" + (b), a - (0.1, 0.1)], a, Zmin_2, b, 1…Length[Zmin_2]) → l2mintxt
  54. Zip(Text["" + (b), a - (0.1, 0.1)], a, Zsad_2, b, 1…Length[Zsad_2]) → l2sadtxt
  55. Zip(Vector[r1, (1.153846154 * r1)], r1, (1.3 * Zip[(R * UnitVector[a]), a, lZmax'])) → lVmaxr
  56. Zip(Vector[r1, (1.153846154 * r1)], r1, (1.3 * Zip[(R * UnitVector[a]), a, lZmin'])) → lVminr
  57. Zip(Vector[r1, (1.153846154 * r1)], r1, (1.3 * Zip[(R * UnitVector[a]), a, lZsad'])) → lVsadr
  58. alfa(R, lP, lZmax') → αmax
  59. alfa(R, lP, lZmin') → αmin
  60. arrow(R, lP, lZmax') → lVmax
  61. arrow(R, lP, lZmin') → lVmin
  62. arrow(R, lP, lZsad') → lVsad
  63. CurveCartesian((-π) + ((2 * π) * a), ((-π)) / 2, f0((-π) + ((2 * π) * a), ((-π)) / 2), a, 0, 1) → par1
  64. CurveCartesian((-π) + ((2 * π) * a), π / 2, f0((-π) + ((2 * π) * a), π / 2), a, 0, 1) → par2
  65. CurveCartesian((-π), ((-π)) / 2 + (π * a), f0((-π), ((-π)) / 2 + (π * a)), a, 0, 1) → par3
  66. CurveCartesian(π, ((-π)) / 2 + (π * a), f0(π, ((-π)) / 2 + (π * a)), a, 0, 1) → par4
  67. Polygon({((-π), ((-π)) / 2), ((-π), π / 2), (π, π / 2), (π, ((-π)) / 2)}) → q_3
  68. Textfield(achs) → InputBox3
  69. Circle(Atest_2, 0.2) → ci
  70. TableText(Append["i", Sequence[Length[lZsad']]], Append["\frac{N°}{levels} ", msad], Append["P_{sad }", lZsad'], Append["(f'x,f'y)", lZf'xysad], Append[" Δα≟ π ", αsad], "v") → text2c
  71. TableText(Append["i", Sequence[Length[αmax]]], Append["\frac{N°}{levels} ", mmax], Append["P_{Max }", lZmax'], Append["(f'x,f'y)", lZf'xymax], Append[" Δα≟ π ", αmax], "v") → text2a
  72. TableText(Append["i", Sequence[Length[αmin]]], Append["\frac{N°}{levels} ", mmin], Append["P_{Min }", lZmin'], Append["(f'x,f'y)", lZf'xymin], Append[" Δα≟ π ", αmin], "v") → text2b
  73. Zip((x(a), y(a), f0(a)), a, Zsad_2) → fsad3D
  74. Zip(Atest_2 + (r_c; ((2 * π / n_c) * k)), k, 0…(n_c - 1)) → l0r
  75. Sum(Sequence[If[sum00_r(i) ≠ sum00_r(i + 1), 1, 0], i, 1, Length[sum00_r] - 1]) → sum01_r
  76. Sum(Unique[sgn(f(Atest_2) - f(l0r))]) → sum_r

AI Drawing Prompt Reference

Draw a sphere and randomly select two different points on the sphere to ensure uniform distribution on the spherical surface. First, construct a truncated icosahedron model, then randomly select a point on the sphere as the starting point, and generate another point using vector and angle relationships to ensure the distance and angle between the two points meet the uniform distribution requirement. Finally, use point-in-region testing to verify that the generated points satisfy the conditions.
The prompt above was compiled from the original drawing commands and is for reference only.