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Fast loadInverse() implementation for the common case

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Most matrices used by the UI toolkit are translation matrices, whose
inverses can be quickly computed by using the negated translation
vector.

Change-Id: I54a28a634a586085779bfc26f3a4160cd5ab2b22
This commit is contained in:
Romain Guy
2015-01-15 11:53:44 -08:00
parent a747d5e47b
commit e4998e1ea9
1 changed files with 32 additions and 4 deletions
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36
libs/hwui/Matrix.cpp
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@@ -203,6 +203,34 @@ void Matrix4::copyTo(SkMatrix& v) const {
}
void Matrix4::loadInverse(const Matrix4& v) {
// Fast case for common translation matrices
if (v.isPureTranslate()) {
// Reset the matrix
// Unnamed fields are never written to except by
// loadIdentity(), they don't need to be reset
data[kScaleX] = 1.0f;
data[kSkewX] = 0.0f;
data[kScaleY] = 1.0f;
data[kSkewY] = 0.0f;
data[kScaleZ] = 1.0f;
data[kPerspective0] = 0.0f;
data[kPerspective1] = 0.0f;
data[kPerspective2] = 1.0f;
// No need to deal with kTranslateZ because isPureTranslate()
// only returns true when the kTranslateZ component is 0
data[kTranslateX] = -v.data[kTranslateX];
data[kTranslateY] = -v.data[kTranslateY];
data[kTranslateZ] = 0.0f;
// A "pure translate" matrix can be identity or translation
mType = v.getType();
return;
}
double scale = 1.0 /
(v.data[kScaleX] * ((double) v.data[kScaleY] * v.data[kPerspective2] -
(double) v.data[kTranslateY] * v.data[kPerspective1]) +
@@ -212,18 +240,18 @@ void Matrix4::loadInverse(const Matrix4& v) {
(double) v.data[kScaleY] * v.data[kPerspective0]));
data[kScaleX] = (v.data[kScaleY] * v.data[kPerspective2] -
v.data[kTranslateY] * v.data[kPerspective1]) * scale;
v.data[kTranslateY] * v.data[kPerspective1]) * scale;
data[kSkewX] = (v.data[kTranslateX] * v.data[kPerspective1] -
v.data[kSkewX] * v.data[kPerspective2]) * scale;
data[kTranslateX] = (v.data[kSkewX] * v.data[kTranslateY] -
v.data[kTranslateX] * v.data[kScaleY]) * scale;
v.data[kTranslateX] * v.data[kScaleY]) * scale;
data[kSkewY] = (v.data[kTranslateY] * v.data[kPerspective0] -
v.data[kSkewY] * v.data[kPerspective2]) * scale;
data[kScaleY] = (v.data[kScaleX] * v.data[kPerspective2] -
v.data[kTranslateX] * v.data[kPerspective0]) * scale;
v.data[kTranslateX] * v.data[kPerspective0]) * scale;
data[kTranslateY] = (v.data[kTranslateX] * v.data[kSkewY] -
v.data[kScaleX] * v.data[kTranslateY]) * scale;
v.data[kScaleX] * v.data[kTranslateY]) * scale;
data[kPerspective0] = (v.data[kSkewY] * v.data[kPerspective1] -
v.data[kScaleY] * v.data[kPerspective0]) * scale;