FluxRender

A high-performance, architecturally advanced engine for mathematical vector field and topological visualization.

FluxRender is not just a plotting library; it is a dynamic, Taichi-powered evaluation engine designed for physicists, mathematicians, and engineers. It bridges the gap between complex mathematical definitions and stunning, real-time visual analysis.

By combining an intelligent, zero-redundancy math engine with native HSL color interpolation and adaptive spatial grids, FluxRender allows you to explore chaotic attractors, fluid dynamics, and topological tensors interactively.

fluxrender_demo.mp4

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🔥 Core Architecture & Features

FluxRender is built around a philosophy of computational efficiency and seamless user experience:

• Massive Particle Dynamics: Effortlessly simulate, render, and track tens of thousands of particles simultaneously. The particles are driven natively by the underlying mathematical engine, allowing for real-time observation of fluid flows and chaotic systems.
• Advanced Field Rendering Modes: The arrow-based vector field is strictly engineered for topological analysis. It features five distinct rendering strategies (including SCREEN_FIXED, WORLD_FIXED, and ZOOM_DENSITY_ADAPTIVE). The grid dynamically recalculates and adapts to your camera's zoom level and local mathematical density, ensuring crisp, uncluttered visual flow regardless of the scale.
• Zero-Redundancy Math Engine: The engine evaluates your primary vector fields once per frame. When applying custom topological metrics (like divergence, curl, or kinetic energy) to your visual entities, the engine securely passes pre-calculated vector data to your functions, saving millions of redundant operations.
• Automatic Vectorization & Time Injection: Write your mathematical logic in pure Python or native NumPy. FluxRender dynamically inspects your function signatures, automatically injects simulation time (t) if requested, and falls back to safe vectorization for unoptimized scalar functions.
• Interactive Regions & Data Probes: Bridge the gap between the user and the math. Use CircularRegion or CursorRegion to define precise spatial boundaries. Attach them to your mouse to dynamically emit particles on click, or use them as DataProbes to sample and display local mathematical properties simply by hovering over the field.
• Total Visual Granularity: Every single visual component is fully exposed. Control the exact thickness, opacity, geometry, and anti-aliasing of vector arrows and grids. The built-in ColorMapper maps scalars directly through the HSL space (avoiding muddy RGB mid-tones) and allows you to inject custom mapping algorithms (scale_function) for absolute visual precision.
• Seamless UI Integration: Turn static simulations into interactive topological dashboards effortlessly. FluxRender provides a streamlined built-in UI system that allows you to instantly attach custom buttons and interaction listeners to your scene.

fluxrender_modes.mp4

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🚀 Quick Start

See the engine in action. This minimal setup creates a fully interactive, time-dependent swirling vortex, evaluated and colored dynamically based on its rotational velocity.

import FluxRender as fr
import numpy as np

# 1. Initialize the scene and coordinate system
coords = fr.CoordinateSystem((-4, 4), (-4, 4), 1200, 800, keep_aspect_ratio=True)
scene = fr.Scene("Swirling Vortex", coords)

# 2. Define the mathematical flow with time dependency
def swirling_vortex(x, y, t):
    vector_dx = np.sin(x) + np.sin(y) * np.sin(t)
    vector_dy = np.cos(x) + np.cos(y) * np.cos(t)
    return vector_dx, vector_dy

# 3. Configure a vibrant HSL Color Mapper for the velocity magnitude
velocity_mapper = fr.ColorMapper(
    min_hue=280, max_hue=180,       # Deep Purple to Neon Cyan
)

# 4. Create a vector field and particles
vector_field = fr.VectorField(
    vec_function=swirling_vortex,
    color_mapper=velocity_mapper,
    mode=fr.FieldMode.SCREEN_FIXED
)
particles = fr.ParticleSystem(
    vec_function=swirling_vortex,
    color_mapper=velocity_mapper,
    radius=1,
    count=15000
)

# 5. Create coordinate axes and grid
axes = fr.Axis()
grid = fr.Grid()

# 6. Attach to the rendering core and launch
scene.add(particles, vector_field, grid, axes)
scene.run()

📖 Documentation

Dive deeper into the architecture, explore the 5 advanced rendering modes, and learn how to attach interactive Particle Systems and Cursor Regions in the official documentation:

👉 Read the full API Reference & Guides here