// // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions // are met: // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above copyright // notice, this list of conditions and the following disclaimer in the // documentation and/or other materials provided with the distribution. // * Neither the name of NVIDIA CORPORATION nor the names of its // contributors may be used to endorse or promote products derived // from this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY // EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR // PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR // CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, // EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY // OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Copyright (c) 2008-2018 NVIDIA Corporation. All rights reserved. // Copyright (c) 2004-2008 AGEIA Technologies, Inc. All rights reserved. // Copyright (c) 2001-2004 NovodeX AG. All rights reserved. #include "PsIntrinsics.h" #include "PsUserAllocated.h" #include "GuSerialize.h" #include "GuBigConvexData2.h" #include "GuCubeIndex.h" #include "PsIntrinsics.h" #include "CmUtils.h" #include "PsUtilities.h" #include "PsAllocator.h" using namespace physx; using namespace Gu; BigConvexData::BigConvexData() : mVBuffer(NULL) { mData.mSubdiv = 0; mData.mNbSamples = 0; mData.mSamples = NULL; ////// mData.mNbVerts = 0; mData.mNbAdjVerts = 0; mData.mValencies = NULL; mData.mAdjacentVerts = NULL; } BigConvexData::~BigConvexData() { PX_FREE(mData.mSamples); /////////// if(mVBuffer) { PX_FREE(mVBuffer); } else { // Allocated from somewhere else!! PX_FREE(mData.mValencies); PX_FREE(mData.mAdjacentVerts); } } void BigConvexData::CreateOffsets() { // Create offsets (radix style) mData.mValencies[0].mOffset = 0; for(PxU32 i=1;i(mVBuffer); mData.mAdjacentVerts = (reinterpret_cast(mVBuffer)) + sizeof(Gu::Valency)*numVerts; PX_ASSERT(0 == (size_t(mData.mAdjacentVerts) & 0xf)); PX_ASSERT(Version==2); { PxU16* temp = reinterpret_cast(mData.mValencies); PxU32 MaxIndex = readDword(Mismatch, stream); ReadIndices(Ps::to16(MaxIndex), mData.mNbVerts, temp, stream, Mismatch); // We transform from: // // |5555|4444|3333|2222|1111|----|----|----|----|----| // // to: // // |5555|4444|4444|2222|3333|----|2222|----|1111|----| // for(PxU32 i=0;i(PX_ALLOC(sizeof(PxU8)*mData.mNbSamples*2, "BigConvex Samples Data")); // These byte buffers shouldn't need converting stream.read(mData.mSamples, sizeof(PxU8)*mData.mNbSamples*2); //load the valencies return VLoad(stream); } // PX_SERIALIZATION void BigConvexData::exportExtraData(PxSerializationContext& stream) { if(mData.mSamples) { stream.alignData(PX_SERIAL_ALIGN); stream.writeData(mData.mSamples, sizeof(PxU8)*mData.mNbSamples*2); } if(mData.mValencies) { stream.alignData(PX_SERIAL_ALIGN); PxU32 numVerts = (mData.mNbVerts+3)&~3; const PxU32 TotalSize = sizeof(Gu::Valency)*numVerts + sizeof(PxU8)*mData.mNbAdjVerts; stream.writeData(mData.mValencies, TotalSize); } } void BigConvexData::importExtraData(PxDeserializationContext& context) { if(mData.mSamples) mData.mSamples = context.readExtraData(PxU32(mData.mNbSamples*2)); if(mData.mValencies) { context.alignExtraData(); PxU32 numVerts = (mData.mNbVerts+3)&~3; mData.mValencies = context.readExtraData(numVerts); mData.mAdjacentVerts = context.readExtraData(mData.mNbAdjVerts); } } //~PX_SERIALIZATION