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About

The Bagula Double-V is a self-similar fractal constructed by recursive subdivision of line segments into a symmetric double-V motif. Each iteration replaces a single segment with 5 scaled copies arranged at alternating angles ยฑฮฑ, producing a branching structure whose Hausdorff dimension D depends on the scaling ratio r and the number of copies N. Misconfiguring the angle or depth yields either a degenerate line or an unresolvable cloud of points. This tool computes the fractal geometry in real time for depths up to 15 iterations, which can exceed 315 = 14,348,907 line segments. Heavy iterations are offloaded to a Web Worker to keep the interface responsive.

The fractal belongs to the broader family of IFS attractors studied in computational geometry. The rendering uses exact trigonometric transformations rather than pixel-based approximation. Note: at depths beyond 12, visual detail saturates at typical screen resolutions. The tool approximates continuous-limit geometry within the discrete pixel grid of your display.

fractal bagula double-v iterated function system IFS geometry mathematics recursion self-similarity

Formulas

The Bagula Double-V fractal replaces each line segment with N = 5 scaled and rotated copies. The Hausdorff dimension is computed from the self-similarity relation:

D = ln(N)ln(1 รท r) = ln(5)ln(3) 1.465

Each recursive step applies 5 affine transformations. Given endpoints (x0, y0) and (x1, y1), the segment direction vector is:

dx = x1 โˆ’ x0 , dy = y1 โˆ’ y0

The five child segments connect through intermediate points computed by rotating sub-vectors by ยฑฮฑ (default ฮฑ = 60ยฐ):

xโ€ฒ = x โ‹… cos(ฮฑ) โˆ’ y โ‹… sin(ฮฑ)
yโ€ฒ = x โ‹… sin(ฮฑ) + y โ‹… cos(ฮฑ)

Where N = number of self-similar copies, r = scaling ratio (1/3), D = Hausdorff (fractal) dimension, ฮฑ = rotation angle per V-branch.

Reference Data

DepthSegmentsScale FactorApprox. Hausdorff Dim.Render Complexity
150.3331.465Trivial
2250.1111.465Trivial
31250.0371.465Low
46250.0121.465Low
53,1250.0041.465Moderate
615,6250.0011.465Moderate
778,125 - 1.465High
8390,625 - 1.465High
91,953,125 - 1.465Very High
109,765,625 - 1.465Extreme
1148,828,125 - 1.465Extreme
12244,140,625 - 1.465Pixel-saturated

Frequently Asked Questions

At depths beyond 10-12, the individual line segments become smaller than a single pixel on most displays. The fractal's Hausdorff dimension D โ‰ˆ 1.465 means it fills more space than a line but less than an area. When segment length drops below 1 pixel, anti-aliasing blends them into a continuous mass. Reduce depth or zoom into a sub-region for detail.
The angle ฮฑ controls the deflection of the V-branches. However, the Hausdorff dimension D = ln(N)/ln(1/r) depends only on the number of copies N and the scaling ratio r, not on angle directly. Changing ฮฑ alters the visual appearance and overlap behavior but not the theoretical dimension - unless the angle causes sub-segments to overlap perfectly, which effectively reduces N.
Depth 12 produces approximately 244 million segments. Most browsers can handle rendering up to depth 9-10 smoothly (under 10 million segments). Beyond depth 10, the Web Worker may take several seconds. The tool caps at 15 but recommends staying at 8-10 for interactive use. At depth 15 you would need over 30 billion segment computations.
The classic Bagula Double-V uses r = 1/3 with 5 copies, yielding D โ‰ˆ 1.465. This tool allows adjusting the scaling ratio. Note that if r ร— N > 1, the IFS segments overlap, producing a filled region rather than a fractal curve. If r is too small, the structure collapses to isolated points. The mathematically interesting range is roughly 0.2 โ‰ค r โ‰ค 0.45.
This tool uses deterministic recursive subdivision: every segment is computed explicitly and drawn as a line. The chaos game plots random orbits of the IFS and approximates the attractor statistically. Deterministic rendering is exact but O(N^depth) in time and memory. The chaos game is O(iterations) regardless of fractal complexity, but requires millions of points to fill in detail. For the Double-V at low depths, deterministic rendering is superior.