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authorDaniel Baumann <daniel.baumann@progress-linux.org>2024-05-15 03:35:49 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2024-05-15 03:35:49 +0000
commitd8bbc7858622b6d9c278469aab701ca0b609cddf (patch)
treeeff41dc61d9f714852212739e6b3738b82a2af87 /third_party/jpeg-xl/lib/jxl/dct_for_test.h
parentReleasing progress-linux version 125.0.3-1~progress7.99u1. (diff)
downloadfirefox-d8bbc7858622b6d9c278469aab701ca0b609cddf.tar.xz
firefox-d8bbc7858622b6d9c278469aab701ca0b609cddf.zip
Merging upstream version 126.0.
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'third_party/jpeg-xl/lib/jxl/dct_for_test.h')
-rw-r--r--third_party/jpeg-xl/lib/jxl/dct_for_test.h6
1 files changed, 3 insertions, 3 deletions
diff --git a/third_party/jpeg-xl/lib/jxl/dct_for_test.h b/third_party/jpeg-xl/lib/jxl/dct_for_test.h
index 58dd75e20e..b0cbffacad 100644
--- a/third_party/jpeg-xl/lib/jxl/dct_for_test.h
+++ b/third_party/jpeg-xl/lib/jxl/dct_for_test.h
@@ -22,7 +22,7 @@ static inline double alpha(int u) { return u == 0 ? 0.7071067811865475 : 1.0; }
// N-DCT on M columns, divided by sqrt(N). Matches the definition in the spec.
template <size_t N, size_t M>
-void DCT1D(double block[N * M], double out[N * M]) {
+void DCT1D(const double block[N * M], double out[N * M]) {
std::vector<double> matrix(N * N);
const double scale = std::sqrt(2.0) / N;
for (size_t y = 0; y < N; y++) {
@@ -43,7 +43,7 @@ void DCT1D(double block[N * M], double out[N * M]) {
// N-IDCT on M columns, multiplied by sqrt(N). Matches the definition in the
// spec.
template <size_t N, size_t M>
-void IDCT1D(double block[N * M], double out[N * M]) {
+void IDCT1D(const double block[N * M], double out[N * M]) {
std::vector<double> matrix(N * N);
const double scale = std::sqrt(2.0);
for (size_t y = 0; y < N; y++) {
@@ -63,7 +63,7 @@ void IDCT1D(double block[N * M], double out[N * M]) {
}
template <size_t N, size_t M>
-void TransposeBlock(double in[N * M], double out[M * N]) {
+void TransposeBlock(const double in[N * M], double out[M * N]) {
for (size_t x = 0; x < N; x++) {
for (size_t y = 0; y < M; y++) {
out[y * N + x] = in[x * M + y];