2023-02-06 03:52:42 +00:00
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use anyhow::Result;
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use nalgebra::{Matrix3, Vector3};
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use ordered_float::NotNan;
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/// Finds the minimum of an iterator of f64s, ignoring any NaN values
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pub fn min_f64<I>(i: I) -> Option<f64>
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where
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I: Iterator<Item = f64>,
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{
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i.filter_map(|i| NotNan::new(i).ok())
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.min()
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.map(|i| i.into_inner())
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}
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/// Finds the minimum of an iterator of f64s using the given predicate, ignoring
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/// any NaN values
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pub fn min_f64_by_key<I, F>(i: I, f: F) -> Option<f64>
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where
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I: Iterator<Item = f64>,
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F: FnMut(&NotNan<f64>),
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{
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i.filter_map(|i| NotNan::new(i).ok())
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.min_by_key(f)
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.map(|i| i.into_inner())
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}
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/// Calculate the rotation matrix between the 2 given vectors
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2023-02-13 05:46:54 +00:00
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///
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/// Based on the method given [here][1].
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///
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/// [1]: https://math.stackexchange.com/a/897677
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2023-02-06 03:52:42 +00:00
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pub fn compute_rotation_matrix(
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a: Vector3<f64>,
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b: Vector3<f64>,
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) -> Result<Matrix3<f64>> {
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// Special case: if a and b are in the same direction, just return the identity matrix
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if a.normalize() == b.normalize() {
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return Ok(Matrix3::identity())
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}
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let cos_t = a.dot(&b);
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let sin_t = a.cross(&b).norm();
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let g = Matrix3::new(cos_t, -sin_t, 0.0, sin_t, cos_t, 0.0, 0.0, 0.0, 1.0);
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// New basis vectors
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let u = a;
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let v = (b - a.dot(&b) * a).normalize();
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let w = b.cross(&a);
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// Not sure if this is required to be invertible?
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let f_inverse = Matrix3::from_columns(&[u, v, w]);
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let f = match f_inverse.try_inverse() {
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Some(v) => v,
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None => {
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// So I ran into this case trying to compute the rotation matrix where one
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// of the vector endpoints was (0, 0, 0). I'm pretty sure this case makes
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// no sense in reality, so going to just error out here and screw
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// recovering.
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//
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// println!("Failed to compute inverse matrix.");
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// println!("- Initial: a = {a}, b = {b}");
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// println!("- cos(t) = {cos_t}, sin(t) = {sin_t}");
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// println!("- Basis: u = {u}, v = {v}, w = {w}");
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bail!("Failed to compute inverse matrix of {f_inverse}\na = {a}\nb = {b}")
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}
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};
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// if (f_inverse * g * f).norm() != 1.0 {
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// bail!("WTF {}", (f_inverse * g * f).norm());
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// }
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Ok(f_inverse * g * f)
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}
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