srenblad/nalgebra
1
0
Fork 0
forked from M-Labs/nalgebra
Code Pull Requests Activity

clippy: fix or_fun_call warnings

Browse Source
This commit is contained in:
Philippe Renon 2020-11-16 15:17:10 +01:00
parent 6caa277ebd
commit 726b8eeecf
3 changed files with 6 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
src/base/construction.rs
View File

@ -238,7 +238,7 @@ where
SB: Storage<N, R>,
{
assert!(!columns.is_empty(), "At least one column must be given.");
let ncols = C::try_to_usize().unwrap_or(columns.len());
let ncols = C::try_to_usize().unwrap_or_else(|| columns.len());
let nrows = columns[0].len();
assert!(
columns.len() == ncols,

2
src/base/interpolation.rs
View File

@ -81,7 +81,7 @@ impl<N: RealField, D: Dim, S: Storage<N, D>> Unit<Vector<N, D, S>> {
{
// TODO: the result is wrong when self and rhs are collinear with opposite direction.
self.try_slerp(rhs, t, N::default_epsilon())
.unwrap_or(Unit::new_unchecked(self.clone_owned()))
.unwrap_or_else(|| Unit::new_unchecked(self.clone_owned()))
}
/// Computes the spherical linear interpolation between two unit vectors.

8
src/base/min_max.rs
View File

@ -57,7 +57,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
N: SimdPartialOrd + Zero,
{
self.fold_with(
|e| e.map(|e| e.inlined_clone()).unwrap_or(N::zero()),
|e| e.map(|e| e.inlined_clone()).unwrap_or_else(N::zero),
|a, b| a.simd_max(b.inlined_clone()),
)
}
@ -75,7 +75,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
N: Zero + SimdPartialOrd + SimdSigned,
{
self.fold_with(
|e| e.map(|e| e.simd_abs()).unwrap_or(N::zero()),
|e| e.map(|e| e.simd_abs()).unwrap_or_else(N::zero),
|a, b| a.simd_min(b.simd_abs()),
)
}
@ -97,7 +97,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
self.fold_with(
|e| {
e.map(|e| e.simd_norm1())
.unwrap_or(N::SimdRealField::zero())
.unwrap_or_else(N::SimdRealField::zero)
},
|a, b| a.simd_min(b.simd_norm1()),
)
@ -117,7 +117,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
N: SimdPartialOrd + Zero,
{
self.fold_with(
|e| e.map(|e| e.inlined_clone()).unwrap_or(N::zero()),
|e| e.map(|e| e.inlined_clone()).unwrap_or_else(N::zero),
|a, b| a.simd_min(b.inlined_clone()),
)
}