5 unstable releases
0.3.1 | Aug 24, 2024 |
---|---|
0.3.0 | Sep 18, 2023 |
0.2.0 | Jun 20, 2022 |
0.1.1 | Jun 19, 2022 |
0.1.0 | May 7, 2022 |
#479 in Math
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quaternion-wrapper
This is a wrapper for the quaternion-core crate.
Provides quaternion operations and interconversion with several attitude representations.
Operator overloading allows implementation similar to mathematical expressions.
Usage
Add this to your Cargo.toml
:
[dependencies]
quaternion-wrapper = "0.3"
For use in a no_std
environment:
[dependencies.quaternion-wrapper]
version = "0.3"
default-features = false
features = ["libm"]
Operator Overloading
Operator overloading allows operations between QuaternionWrapper
, Vector3Wrapper
, and ScalarWrapper
.
The supported operations are listed in the table below:
Left↓ / Right→ | QuaternionWrapper | Vector3Wrapper | ScalarWrapper |
---|---|---|---|
QuaternionWrapper | + , - , * , += , -= , *= |
+ , - , * |
+ , - , * , / |
Vector3Wrapper | + , - , * |
+ , - , * , += , -= |
+ , - , * , / |
ScalarWrapper | + , - , * |
+ , - , * |
+ , - , * , / , += , -= , *= , /= |
To prevent implementation errors by users, the operation with T
(f32
or f64
) is
intentionally not implemented.
That is, ScalarWrapper<f64> * QuaternionWrapper<f64>
can be calculated,
but f64 * QuaternionWrapper<f64>
cannot.
Features
fma
When this feature is enabled, the
mul_add
method will be used internally as much as possible.
That is, (s * a) + b
will be expanded as s.mul_add(a, b)
at compile time.
This crate uses the mul_add
method mainly to improve calculation speed, but if the CPU does
not support the FMA
(Fused Multiply-Add) instruction or if the libm
feature is
enabled, then the calculation is performed by the software implementation.
In this case, it may be rather slower than if the fma
feature is not enabled.
libm
If you set default-features=false
(do not import std
), you must enable this feature.
In this case, mathematical functions (e.g. sin
, cos
, sqrt
...) are provided by
libm crate.
norm-sqrt
By default, the a.norm()
method is implemented in such a way that overflow and
underflow are less likely to occur than with dot(a, a).sqrt()
. However, if extremely
large values are not input and underflow is not that much of a concern,
dot(a, a).sqrt()
is sufficient (and dot(a, a).sqrt()
is faster than the default implementation in most cases).
Example
src/main.rs
:
use quaternion_wrapper::{QuaternionWrapper, Vector3Wrapper};
const PI: f64 = std::f64::consts::PI;
const EPSILON: f64 = 1e-12;
fn main() {
// Generates a quaternion representing the
// rotation of π/2[rad] around the y-axis.
let q = QuaternionWrapper::from_axis_angle([0.0, 1.0, 0.0], PI/2.0);
// Point
let v = Vector3Wrapper([2.0, 2.0, 0.0]);
let result = (q * v * q.conj()).get_vector_part();
//let result = q.point_rotation(v); // <--- It could be written like this
// Check if the calculation is correct.
let true_val = Vector3Wrapper([0.0, 2.0, -2.0]);
let diff: [f64; 3] = (true_val - result).unwrap();
for val in diff {
assert!(val.abs() < EPSILON);
}
}
License
Licensed under either of Apache License, Version 2.0 or MIT License at your option.
Contribution
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.
Dependencies
~170–285KB