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experimental features","maintainers":[{"name":"pessimistress","email":"cxiaoji@gmail.com"},{"name":"ibgreen","email":"ib@unfolded.ai"},{"name":"felixpalmer","email":"felixpalmer+npm@gmail.com"},{"name":"belom88","email":"belom88@yandex.ru"},{"name":"donmccurdy","email":"dm@donmccurdy.com"},{"name":"kaapp","email":"KappCK@googlemail.com"},{"name":"chrisgervang","email":"chris@gervang.com"}],"readme":"# @luma.gl/experimental\n\nExperimental features for luma.gl.\n\n:::warning\nThese are experimental features that may change or be removed at any time. Use at your own risk.\n:::\n\nThe published package includes experimental data-parallel primitives such as scan, compaction,\nstable key/value sort, two-dimensional FFT, and spectral ocean simulation,\nenergy-conserving FFT aperture diffraction and photographic bloom,\norder-independent transparency renderers, composable cross-backend glass and reflective-material\nshader modules, packed pixel-format helpers, and WebGPU/WebGL WebXR session\nand frame helpers, with WebGL-only raw camera textures. See the\n[luma.gl API reference](https://luma.gl/docs/api-reference/experimental) for documentation.\n\n## FFT Convolution Bloom\n\n`GPUConvolutionBloom` performs physically motivated optical convolution on WebGPU. Area-weighted\nHDR extraction preserves subpixel emitters and centers the sampled image inside zero-padded guard\nbands, preventing diffraction from wrapping onto the opposite edge. Packed RGB fields share one\nforward and one inverse FFT schedule instead of six independent transforms. Each wavelength uses\nits own cached aperture spectrum, with configurable blade count, diffraction strength, anamorphic\nstretch, and spectral spread. Applications can provide either one nonnegative `Float32Array`\nkernel or independently measured `{red, green, blue}` kernels and replace them with\n`setPointSpreadFunction()`.\n\nSet `energyConserving: true` for thresholdless normalized scattering. Optional chromatic ghosts,\nradial halo, sampled dirt, and neighborhood-clamped temporal stabilization execute inside the\nexisting final compute dispatch. Supplying `exposureTexture` to `encode()` consumes GPU-resident\nadapted exposure directly and automatically compensates temporal history without CPU readback.\n\n```ts\nimport {Texture} from '@luma.gl/core';\nimport {GPUConvolutionBloom, getGPUConvolutionBloomSupport} from '@luma.gl/experimental';\n\nconst support = getGPUConvolutionBloomSupport(device, {width, height, resolutionScale: 0.25});\nif (!support.supported) {\n  throw new Error(support.reason);\n}\n\nconst outputTexture = device.createTexture({\n  width,\n  height,\n  format: 'rgba16float',\n  usage: Texture.STORAGE | Texture.SAMPLE\n});\nconst bloom = new GPUConvolutionBloom(device, {\n  width,\n  height,\n  resolutionScale: 0.25,\n  guardBand: 0.125,\n  apertureBlades: 6,\n  diffractionStrength: 0.3,\n  spectralSpread: 0.65,\n  temporalStability: 0.55,\n  lens: {ghostIntensity: 0.25, haloIntensity: 0.15}\n});\n\nconst encoder = device.createCommandEncoder();\nbloom.encode(encoder, {sourceTexture, outputTexture, exposure: 1});\ndevice.submit(encoder.finish());\n```\n\nThe caller owns source/output textures and command submission; the renderer owns reusable FFT\nbuffers, its cached RGB optical spectrum, and optional history. `bloom.stats` publishes exact\nsampled content bounds, transform dimensions, packed complex-buffer allocation, steady-state\ndispatch count, and one-time kernel initialization work. At 1920 x 1080 with quarter-resolution\nsampling and the default 12.5% guard band, the transform is 1024 x 512 and requires four packed RGB\nbuffers totaling 48 MiB, 45 steady-state dispatches, and 21 dispatches when the aperture changes.\nSetting `guardBand: 0` reduces that to a 512 x 512 transform, 24 MiB, and 43 dispatches, while\ntrading away explicit wraparound protection. The previous independent-channel path required 123\nsteady-state dispatches. On devices with `timestamp-query`, create the command encoder with a\n`timeProfilingQuerySet` to collect actual GPU timings for every FFT and optical compute pass.\n\nOptional algorithm entry points keep specialized workflows out of the default experimental bundle:\n\n- `@luma.gl/experimental/geospatial` provides graph-native spatial operations and distance kernels.\n- `@luma.gl/experimental/gpu-project` compiles arbitrary CPU coordinate transformations into\n  precision-preserving, GPU-evaluated local projection patches.\n- `@luma.gl/experimental/gpu-trace` keeps execution-trace scenes, process/thread interactions,\n  dependency focus, and timeline picking separate from generic command-graph primitives.\n","readmeFilename":"README.md"}