Fluid simulation · gpt-5.4-nano
Create a real-time fluid simulation on a full-screen canvas where dragging the mouse pushes swirling colored dye through the fluid.
transcript · 6 messages
Create a real-time fluid simulation on a full-screen canvas where dragging the mouse pushes swirling colored dye through the fluid.
thinking
**Implementing fluid simulation** I'm looking to create a single `index.html` file for a fluid simulation using classic "stable fluids" in JavaScript, specifically a grid-based Navier-Stokes approach. The plan is to implement advection, diffusion, and projection, while also rendering dye based on mouse input for velocity and dye addition. I want to make it fully responsive and avoid external libraries, ensuring it runs efficiently with a grid size of around 80. Performance is key, and I’ll adapt based on device specifics as needed.**Implementing dye simulation** I need to add swirling colored dye to the fluid simulation, where the dye color varies based on mouse movement and position. To keep things simple, I'll store three densities: red, green, and blue. I'll run separate simulations for each color channel while using the same velocity field defined by u and v. When the mouse drags, I’ll compute the movement and update the velocities and color densities accordingly. For rendering, I’ll convert the dye densities into pixel colors using bilinear upscaling, ensuring everything fits nicely on the canvas.**Using offscreen canvas for rendering** I'm planning to create an offscreen canvas of size N x N for rendering the simulation. Each frame will use `putImageData` to update, then draw to the main canvas with `ctx.drawImage`. I might set image smoothing to true for a nicer look. To handle the densities, I’ll clamp values to avoid exceeding limits and ensure color mapping is smooth, likely using some nonlinear scaling. I'll implement standard functions for the simulation, maintaining memory for velocities and densities, while keeping the grid wrapping disabled. I want to ensure everything runs efficiently!**Simplifying fluid simulation implementation** I’m thinking about how to handle the velocity and density fields in the simulation. Instead of keeping a u0 buffer, I can directly add sources to u and v. I’ll maintain u and v for current velocities, with u0 and v0 as scratch arrays for diffusion and advection. For viscosity and diffusion in each step, I'll first diffuse the velocity using these arrays. I'll swap the arrays during implementation, allowing for easier calculations in each iteration while still applying the projection and advection steps as needed.**Setting up density handling** For the density in the simulation, I plan to swap densR0 with densR and then advect the density using the u and v velocities. Incorporating a small amount of diffusion can add realism, so I’ll include that with a diffusion coefficient. I'll also add slight decay to the density. While rendering, I'll set the alpha based on density and incorporate color intensity based on mouse speed. Ensuring proper scaling and handling pointer events is key, and I’ll set the main canvas to full-screen for clarity. I’ll put together the code with these considerations!
index.html (13719 bytes)Successfully wrote 13719 bytes to index.html
{"command":"node -e \"require('fs').accessSync('index.html'); console.log('index.html ok, bytes', require('fs').statSync('index.html').size)index.html ok, bytes 13723
Created **`index.html`** (single self-contained file) implementing a real-time **stable-fluids** style simulation on a full-screen canvas. Dragging (or touching) injects **swirling colored dye** and momentum; colors shift with movement speed and **Shift+drag** makes the dye brighter/more saturated. Open `index.html` in a browser to run it.
TAKE IT TO CODE
A single self-contained HTML file — copy it and open in any browser, or reuse the prompt with your own pi-agent run.
RUN
EVALUATION
Fluid dye trail responds nicely to drag/wheel with colorful swirls, but click and keyboard inputs show no visible effect.
Vision grade · anthropic/claude-sonnet-5
MEASUREMENTS
Raw readings from the capture, not a verdict — the grade above is the only judgement. Percentages are how much of the screen changed; the measure under-reports sparse motion on a dark background.