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https://github.com/bevyengine/bevy
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# Objective Augment Bevy's random sampling capabilities by providing good tools for producing random directions and rotations. ## Solution The `rand` crate has a natural tool for providing `Distribution`s whose output is a type that doesn't require any additional data to sample values — namely, [`Standard`](https://docs.rs/rand/latest/rand/distributions/struct.Standard.html). Here, our existing `ShapeSample` implementations have been put to good use in providing these, resulting in patterns like the following: ```rust // Using thread-local rng let random_direction1: Dir3 = random(); // Using an explicit rng let random_direction2: Dir3 = rng.gen(); // Using an explicit rng coupled explicitly with Standard let random_directions: Vec<Dir3> = rng.sample_iter(Standard).take(5).collect(); ``` Furthermore, we have introduced a trait `FromRng` which provides sugar for `rng.gen()` that is more namespace-friendly (in this author's opinion): ```rust let random_direction = Dir3::from_rng(rng); ``` The types this has been implemented for are `Dir2`, `Dir3`, `Dir3A`, and `Quat`. Notably, `Quat` uses `glam`'s implementation rather than an in-house one, and as a result, `bevy_math`'s "rand" feature now enables that of `glam`. --- ## Changelog - Created `standard` submodule in `sampling` to hold implementations and other items related to the `Standard` distribution. - "rand" feature of `bevy_math` now enables that of `glam`. --- ## Discussion From a quick glance at `Quat`'s distribution implementation in `glam`, I am a bit suspicious, since it is simple and doesn't match any algorithm that I came across in my research. I will do a little more digging as a follow-up to this and see if it's actually uniform (maybe even using those tools I wrote — what a thrill). As an aside, I'd also like to say that I think [`Distribution`](https://docs.rs/rand/latest/rand/distributions/trait.Distribution.html) is really, really good. It integrates with distributions provided externally (e.g. in `rand` itself and its extensions) along with doing a good job of isolating the source of randomness, so that output can be reliably reproduced if need be. Finally, `Distribution::sample_iter` is quite good for ergonomically acquiring lots of random values. At one point I found myself writing traits to describe random sampling and essentially reinvented this one. I just think it's good, and I think it's worth centralizing around to a significant extent.
51 lines
1.7 KiB
TOML
51 lines
1.7 KiB
TOML
[package]
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name = "bevy_math"
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version = "0.14.0-dev"
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edition = "2021"
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description = "Provides math functionality for Bevy Engine"
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homepage = "https://bevyengine.org"
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repository = "https://github.com/bevyengine/bevy"
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license = "MIT OR Apache-2.0"
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keywords = ["bevy"]
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[dependencies]
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glam = { version = "0.25", features = ["bytemuck"] }
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thiserror = "1.0"
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serde = { version = "1", features = ["derive"], optional = true }
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libm = { version = "0.2", optional = true }
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approx = { version = "0.5", optional = true }
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rand = { version = "0.8", features = [
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"alloc",
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], default-features = false, optional = true }
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[dev-dependencies]
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approx = "0.5"
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# Supply rngs for examples and tests
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rand = "0.8"
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rand_chacha = "0.3"
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# Enable the approx feature when testing.
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bevy_math = { path = ".", version = "0.14.0-dev", features = ["approx"] }
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[features]
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default = ["rand"]
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serialize = ["dep:serde", "glam/serde"]
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# Enable approx for glam types to approximate floating point equality comparisons and assertions
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approx = ["dep:approx", "glam/approx"]
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# Enable interoperation of glam types with mint-compatible libraries
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mint = ["glam/mint"]
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# Enable libm mathematical functions for glam types to ensure consistent outputs
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# across platforms at the cost of losing hardware-level optimization using intrinsics
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libm = ["dep:libm", "glam/libm"]
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# Enable assertions to check the validity of parameters passed to glam
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glam_assert = ["glam/glam-assert"]
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# Enable assertions in debug builds to check the validity of parameters passed to glam
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debug_glam_assert = ["glam/debug-glam-assert"]
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# Enable the rand dependency for shape_sampling
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rand = ["dep:rand", "glam/rand"]
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[lints]
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workspace = true
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[package.metadata.docs.rs]
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rustdoc-args = ["-Zunstable-options", "--cfg", "docsrs"]
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all-features = true
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