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* Bug 1452 - Decouple math functionality to 'com.jogamp.math' to be toolkit ↵Sven Gothel2023-09-201-2153/+0
| | | | | | | | | | | | | | | | | | | | agnostic (PMVMatrix, Matrix4f, Vec4f, ..) Math functionality (PMVMatrix, Matrix4f, Vec4f, ..) - shall be used toolkit agnostic, e.g. independent from OpenGL - shall be reused within our upcoming Vulkan implementation - may also move outside of JOGL, i.e. GlueGen or within its own package to be reused for other purposed. The 'com.jogamp.opengl.util.PMVMatrix' currently also used to feed in GLUniformData via the toolkit agnostic SyncAction and SyncBuffer shall also be split to a toolkit agnostic variant. An OpenGL PMVMatrix specialization implementing GLMatrixFunc can still exist, being derived from the toolkit agnostic base implementation. +++ Initial commit .. compile clean, passing most unit tests.
* FloatUtil.isEqual(..): Rename raw {isEqual->isEqualRaw}(a,b) varianr w/o ↵Sven Gothel2023-09-031-2/+2
| | | | | | EPSILON; Add isEqual(a,b) w/ default EPSILON; Use it where applicable Also add isEqual2(a,b) w/o corner cases (NaN, Inf) used for comparison in Graph Outline, OutlineShape and later GraphUI Shape.
* [PMV]Matrix[4f]: Clarify 'mulVec[34]f' in-place arg properties, add pure ↵Sven Gothel2023-04-281-2/+35
| | | | in-place variant and use it in PMVMatrix dropping temporary
* Matrix4f.mapWin*(): Drop unused temp matrices, map*() returns false on ↵Sven Gothel2023-04-091-14/+90
| | | | | | | | | | | | | | | | | | | | | | | | invPMv null; PMVMatrix: Make Mvi, Mvit optional at ctor, add user PMv and PMvi - used at gluUnProject() .. Matrix4f.mapWin*() variants w/ invPMv don't need temp matrices, they also shall handle null invPMv -> return false to streamline usage w/ PMVMatrix if inversion failed. PMVMatrix adds user space common premultiplies Pmv and Pmvi on demand like Frustum. These are commonly required for e.g. gluUnProject(..)/mapWinToObj(..) and might benefit from caching if stack is maintained and no modification occured. PMVMatrix now has the shader related Mvi and Mvit optional at construction(!), so its backing buffers. This reduces footprint for other use cases. The 2nd temp matrix is also on-demand, to reduce footprint for certain use cases. Removed public access to temporary storage. +++ While these additional matrices are on demand and/or at request @ ctor, general memory footprint is reduced per default and hence deemed acceptable while still having PMVMatrix acting as a core flexible matrix provider.
* PMVMatrix rewrite using Matrix4f, providing SyncMatrix4f* for GLUniformData; ↵Sven Gothel2023-04-071-77/+155
| | | | | | | | | | | | | | | | | Utilize Vec3f, Recti, .. throughout API (Matrix4f, AABBox, .. Graph*) Big Easter Cleanup - Net -214 lines of code, despite new classes. - GLUniformData buffer can be synced w/ underlying data via SyncAction/SyncBuffer, e.g. SyncMatrix4f + SyncMatrices4f - PMVMatrix rewrite using Matrix4f and providing SyncMatrix4f/Matrices4f to sync w/ GLUniformData - Additional SyncMatrix4f16 + SyncMatrices4f16 covering Matrix4f sync w/ GLUniformData w/o PMVMatrix - Utilize Vec3f, Recti, .. throughout API (Matrix4f, AABBox, .. Graph*) - Moved FloatUtil -> Matrix4f, kept a few basic matrix ops for ProjectFloat - Most, if not all, float[] and int[] should have been moved to proper classes - int[] -> Recti for viewport rectangle - Matrix4f and PMVMatrix is covered by math unit tests (as was FloatUtil before) -> save Passed all unit tests on AMD64 GNU/Linux
* Matrix4f Perf: Enhance invert(), Drop (test) load on Matrix4f.mul(Matrix4f) ↵Sven Gothel2023-04-051-53/+141
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | for fair and realistic numbers - Both mul() ops faster than FloatUtil Enhanced invert() of Matrix4f* and FloatUtil: Use 1f/det factor for burst scale. Enhanced Matrix4f.invert(..): Use factored-out mulScale() to deliver the scale, giving a good 10% advantage on aarch64 and amd64. Brings Matrix4f.invert(..) on par w/ FloatUtil, on aarch64 even a 14% advantage. +++ TestMatrix4f02MulNOUI added an additional Matrix4f.load() to the mul(Matrix4f) loop test, which surely is an extra burden and not realistic as the mul(Matrix4f, Matrix4f) and FloatUtil pendants also don't count loading a value. Matrix4f.mul(Matrix4f) shall be used to utilize an already stored value anyways. Matrix4f.mul(Matrix4f) didn't really exist in FloatUtil. Same is true for Matrix4f.invert(), re-grouped order, i.e. pushing the non-arg variant last. +++ Revised performance numbers from commit 15e60161787224e85172685f74dc0ac195969b51 AMD64 + OpenJDK17 - FloatUtil.multMatrix(a, a_off, b, b_off, dest) is considerable slower than all - Matrix4f.mul(a, b) roughly ~10% faster than FloatUtil.multMatrix(a, b, dest) - Matrix4f.mul(b) roughly ~18% faster than FloatUtil.multMatrix(a, b, dest) (*) - Matrix4f.invert(a) roughly ~ 2% faster than FloatUtil.invertMatrix(..) - Matrix4f.invert() roughly ~ 4% slower than FloatUtil.invertMatrix(..) (*) - Launched: nice -19 scripts/tests-x64.sh RaspberryPi 4b aarch64 + OpenJDK17 - FloatUtil.multMatrix(a, a_off, b, b_off, dest) is considerable slower than all - Matrix4f.mul(a, b) roughly ~ 9% faster than FloatUtil.multMatrix(a, b, dest) - Matrix4f.mul(b) roughly ~14% faster than FloatUtil.multMatrix(a, b, dest) (*) - Matrix4f.invert(a) roughly ~14% faster than FloatUtil.invertMatrix(..) - Matrix4f.invert() roughly ~12% faster than FloatUtil.invertMatrix(..) (*) - Launched: nice -19 scripts/tests-linux-aarch64.sh (*) not a true comparison in feature, as operating on 'this' matrix values for one argument, unavailable to FloatUtil. Conclusion - Matrix4f.mul(..) is considerable faster! - Matrix4f.invert(..) faster, esp on aarch64 And additional Matrix4fb tests using float[16] similar to FloatUtil also demonstrates less performance compared to Matrix4f using dedicated float fields.
* Math: Complete Matrix4f w/ Vec[234]f and adopt it throughout Quaternion, ↵Sven Gothel2023-04-051-0/+1878
Ray, AABBox, Frustum, Stereo*, ... adding hook to PMVMatrix Motivation was to simplify matrix + vector math usage, ease review and avoid usage bugs. Matrix4f implementation uses dedicated float fields instead of an array. Performance didn't increase much, as JVM >= 11(?) has some optimizations to drop the array bounds check. AMD64 + OpenJDK17 - Matrix4f.mul(a, b) got a roughly ~10% enhancement over FloatUtil.multMatrix(a, b, dest) - Matrix4f.mul(b) roughly ~3% slower than FloatUtil.multMatrix(a, b, dest) - FloatUtil.multMatrix(a, a_off, b, b_off, dest) is considerable slower than all - Matrix4f.invert(..) roughly ~3% slower than FloatUtil.invertMatrix(..) RaspberryPi 4b aarch64 + OpenJDK17 - Matrix4f.mul(a, b) got a roughly ~10% enhancement over FloatUtil.multMatrix(a, b, dest) - Matrix4f.mul(b) roughly ~20% slower than FloatUtil.multMatrix(a, b) - FloatUtil.multMatrix(a, a_off, b, b_off, dest) is considerable slower than all - Matrix4f.invert(..) roughly ~4% slower than FloatUtil.invertMatrix(..) Conclusion - Matrix4f.mul(b) needs to be revised (esp for aarch64) - Matrix4f.invert(..) should also not be slower ..
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