Narrower inbounds annotations in generic LinearAlgebra functions

stdlib/LinearAlgebra/src/generic.jl

@@ -709,14 +709,12 @@ function opnorm1(A::AbstractMatrix{T}) where T
     Tnorm = typeof(float(real(zero(T))))
     Tsum = promote_type(Float64, Tnorm)
     nrm::Tsum = 0
-    @inbounds begin
-        for j = axes(A,2)
-            nrmj::Tsum = 0
-            for i = axes(A,1)
-                nrmj += norm(A[i,j])
-            end
-            nrm = max(nrm,nrmj)
+    for j = axes(A,2)
+        nrmj::Tsum = 0
+        for i = axes(A,1)
+            nrmj += norm(@inbounds A[i,j])
         end
+        nrm = max(nrm,nrmj)
     end
     return convert(Tnorm, nrm)
 end
@@ -736,14 +734,12 @@ function opnormInf(A::AbstractMatrix{T}) where T
     Tnorm = typeof(float(real(zero(T))))
     Tsum = promote_type(Float64, Tnorm)
     nrm::Tsum = 0
-    @inbounds begin
-        for i = axes(A,1)
-            nrmi::Tsum = 0
-            for j = axes(A,2)
-                nrmi += norm(A[i,j])
-            end
-            nrm = max(nrm,nrmi)
+    for i = axes(A,1)
+        nrmi::Tsum = 0
+        for j = axes(A,2)
+            nrmi += norm(@inbounds A[i,j])
         end
+        nrm = max(nrm,nrmi)
     end
     return convert(Tnorm, nrm)
 end
@@ -938,7 +934,7 @@ function dot(x::AbstractArray, y::AbstractArray)
     end
     s = zero(dot(first(x), first(y)))
     for (Ix, Iy) in zip(eachindex(x), eachindex(y))
-        @inbounds s += dot(x[Ix], y[Iy])
+        s += dot(@inbounds(x[Ix]), @inbounds(y[Iy]))
     end
     s
 end
@@ -979,11 +975,11 @@ function dot(x::AbstractVector, A::AbstractMatrix, y::AbstractVector)
     s = zero(T)
     i₁ = first(eachindex(x))
     x₁ = first(x)
-    @inbounds for j in eachindex(y)
-        yj = y[j]
+    for j in eachindex(y)
+        yj = @inbounds y[j]
         if !iszero(yj)
-            temp = zero(adjoint(A[i₁,j]) * x₁)
-            @simd for i in eachindex(x)
+            temp = zero(adjoint(@inbounds A[i₁,j]) * x₁)
+            @inbounds @simd for i in eachindex(x)
                 temp += adjoint(A[i,j]) * x[i]
             end
             s += dot(temp, yj)
@@ -1596,10 +1592,12 @@ function rotate!(x::AbstractVector, y::AbstractVector, c, s)
     if n != length(y)
         throw(DimensionMismatch(lazy"x has length $(length(x)), but y has length $(length(y))"))
     end
-    @inbounds for i = eachindex(x,y)
-        xi, yi = x[i], y[i]
-        x[i] =       c *xi + s*yi
-        y[i] = -conj(s)*xi + c*yi
+    for i = eachindex(x,y)
+        @inbounds begin
+            xi, yi = x[i], y[i]
+            x[i] =       c *xi + s*yi
+            y[i] = -conj(s)*xi + c*yi
+        end
     end
     return x, y
 end
@@ -1619,10 +1617,12 @@ function reflect!(x::AbstractVector, y::AbstractVector, c, s)
     if n != length(y)
         throw(DimensionMismatch(lazy"x has length $(length(x)), but y has length $(length(y))"))
     end
-    @inbounds for i = eachindex(x,y)
-        xi, yi = x[i], y[i]
-        x[i] =      c *xi + s*yi
-        y[i] = conj(s)*xi - c*yi
+    for i = eachindex(x,y)
+        @inbounds begin
+            xi, yi = x[i], y[i]
+            x[i] =      c *xi + s*yi
+            y[i] = conj(s)*xi - c*yi
+        end
     end
     return x, y
 end
@@ -1633,18 +1633,16 @@ end
     require_one_based_indexing(x)
     n = length(x)
     n == 0 && return zero(eltype(x))
-    @inbounds begin
-        ξ1 = x[1]
-        normu = norm(x)
-        if iszero(normu)
-            return zero(ξ1/normu)
-        end
-        ν = T(copysign(normu, real(ξ1)))
-        ξ1 += ν
-        x[1] = -ν
-        for i = 2:n
-            x[i] /= ξ1
-        end
+    ξ1 = @inbounds x[1]
+    normu = norm(x)
+    if iszero(normu)
+        return zero(ξ1/normu)
+    end
+    ν = T(copysign(normu, real(ξ1)))
+    ξ1 += ν
+    @inbounds x[1] = -ν
+    for i = 2:n
+        @inbounds x[i] /= ξ1
     end
     ξ1/ν
 end
@@ -1661,10 +1659,10 @@ Multiplies `A` in-place by a Householder reflection on the left. It is equivalen
         throw(DimensionMismatch(lazy"reflector has length $(length(x)), which must match the first dimension of matrix A, $m"))
     end
     m == 0 && return A
-    @inbounds for j = axes(A,2)
-        Aj, xj = view(A, 2:m, j), view(x, 2:m)
-        vAj = conj(τ)*(A[1, j] + dot(xj, Aj))
-        A[1, j] -= vAj
+    for j = axes(A,2)
+        Aj, xj = @inbounds view(A, 2:m, j), view(x, 2:m)
+        vAj = conj(τ)*(@inbounds(A[1, j]) + dot(xj, Aj))
+        @inbounds A[1, j] -= vAj
         axpy!(-vAj, xj, Aj)
     end
     return A