Format

NDTensors/src/linearalgebra/linearalgebra.jl

@@ -412,13 +412,13 @@ function qr_positive(M::AbstractMatrix)
   Q = convert(Matrix, sparseQ)
   nc = size(Q, 2)
   for c in 1:nc
-    if R[c, c]!=0.0 #sign(0.0)==0.0 so we don't want to zero out a column of Q.
+    if R[c, c] != 0.0 #sign(0.0)==0.0 so we don't want to zero out a column of Q.
       sign_Rc = sign(R[c, c])
       if !isone(sign_Rc)
         R[c, c:end] *= conj(sign_Rc) #only fip non-zero portion of the row.
         Q[:, c] *= sign_Rc
       end
-  end
+    end
   end
   return (Q, R)
 end
@@ -437,13 +437,13 @@ function ql_positive(M::AbstractMatrix)
   nr, nc = size(L)
   dc = nc > nr ? nc - nr : 0 #diag is shifted over by dc if nc>nr
   for c in 1:(nc - dc)
-    if L[c, c + dc]!=0.0 #sign(0.0)==0.0 so we don't want to zero out a column of Q.
+    if L[c, c + dc] != 0.0 #sign(0.0)==0.0 so we don't want to zero out a column of Q.
       sign_Lc = sign(L[c, c + dc])
       if c <= nr && !isone(sign_Lc)
         L[c, 1:(c + dc)] *= sign_Lc #only fip non-zero portion of the column.
         Q[:, c] *= conj(sign_Lc)
       end
-  end
+    end
   end
   return (Q, L)
 end
@@ -452,9 +452,9 @@ end
 #  Lapack replaces A with Q & R carefully packed together.  So here we just copy a
 #  before letting lapack overwirte it. 
 #
-function ql(A::AbstractMatrix; kwargs...) 
+function ql(A::AbstractMatrix; kwargs...)
   Base.require_one_based_indexing(A)
-  T=eltype(A)
+  T = eltype(A)
   AA = similar(A, LinearAlgebra._qreltype(T), size(A))
   copyto!(AA, A)
   return ql!(AA; kwargs...)

NDTensors/test/linearalgebra.jl

@@ -20,7 +20,10 @@ end
   @test norm(U2 * U2' - Diagonal(fill(1.0, m))) < 1E-14
 end
 
-@testset "Dense $qx decomposition, elt=$elt, positve=$positive, singular=$singular" for qx in [qr, ql],
+@testset "Dense $qx decomposition, elt=$elt, positve=$positive, singular=$singular" for qx in
+                                                                                        [
+    qr, ql
+  ],
   elt in [Float64, ComplexF64, Float32, ComplexF32],
   positive in [false, true],
   singular in [false, true]
@@ -35,7 +38,7 @@ end
   # We want to test 0.0 on the diagonal.  We need make all roaw equal to gaurantee this with numerical roundoff.
   if singular
     for i in 2:n
-      A[i,:]=A[1,:]
+      A[i, :] = A[1, :]
     end
   end
   Q, X = qx(A; positive=positive) #X is R or L.
@@ -56,7 +59,7 @@ end
   # We want to test 0.0 on the diagonal.  We need make all rows equal to gaurantee this with numerical roundoff.
   if singular
     for i in 2:m
-      A[i,:]=A[1,:]
+      A[i, :] = A[1, :]
     end
   end
   Q, X = qx(A; positive=positive)