sunwen/Aurora
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Add index to min and max.

Browse Source
This commit is contained in:
Krad
2023-04-24 16:02:15 +08:00
parent a895785319
commit 37ffe9b51b
3 changed files with 67 additions and 28 deletions
Download Patch File Download Diff File Expand all files Collapse all files

62
src/Function2D.cpp
View File

@@ -131,7 +131,7 @@ Matrix Aurora::std(const Matrix &aMatrix) {
return Matrix::New(std,1,aMatrix.getDimSize(1), aMatrix.getDimSize(2));
}
Matrix Aurora::min(const Matrix &aMatrix, FunctionDirection direction) {
Matrix Aurora::min(const Matrix &aMatrix, FunctionDirection direction, long& rowIdx, long& colIdx) {
if (aMatrix.getDimSize(2)>1 || aMatrix.isComplex()) {
std::cerr
<< (aMatrix.getDimSize(2) > 1 ? "min() not support 3D data!" : "min() not support complex value type!")
@@ -140,33 +140,49 @@ Matrix Aurora::min(const Matrix &aMatrix, FunctionDirection direction) {
}
switch (direction)
{
case All:
{
Eigen::Map<Eigen::VectorXd> retV(aMatrix.getData(),aMatrix.getDataSize());
double * ret = malloc(1);
ret[0] = retV.array().minCoeff();
return Matrix::New(ret,1);
case All: {
Eigen::Map<Eigen::MatrixXd> retV(aMatrix.getData(), aMatrix.getDimSize(0), aMatrix.getDimSize(1));
double *ret = malloc(1);
ret[0] = retV.array().minCoeff(&rowIdx, &colIdx);
return Matrix::New(ret, 1);
}
case Row:
{
Eigen::Map<Eigen::MatrixXd> srcMatrix(aMatrix.getData(),aMatrix.getDimSize(0),aMatrix.getDimSize(1));
double * ret = malloc(aMatrix.getDimSize(0));
if (aMatrix.getDimSize(0) == 1){
ret[0] = srcMatrix.topRows(0).minCoeff(&rowIdx, &colIdx);
}
else{
Eigen::Map<Eigen::MatrixXd> retMatrix(ret,aMatrix.getDimSize(0),1);
retMatrix = srcMatrix.rowwise().minCoeff();
}
return Matrix::New(ret,aMatrix.getDimSize(0),1);
}
case Column:
default:
{
Eigen::Map<Eigen::MatrixXd> srcMatrix(aMatrix.getData(),aMatrix.getDimSize(0),aMatrix.getDimSize(1));
double * ret = malloc(aMatrix.getDimSize(0));
double * ret = malloc(aMatrix.getDimSize(1));
if (aMatrix.getDimSize(1) == 1){
ret[0] = srcMatrix.col(0).minCoeff(&rowIdx, &colIdx);
}
else {
Eigen::Map<Eigen::MatrixXd> retMatrix(ret,1,aMatrix.getDimSize(1));
retMatrix = srcMatrix.colwise().minCoeff();
}
return Matrix::New(ret,1,aMatrix.getDimSize(1));
}
}
}
Matrix Aurora::min(const Matrix &aMatrix, FunctionDirection direction) {
long a,b;
return min(aMatrix,direction,a,b);
}
Matrix Aurora::min(const Matrix &aMatrix, const Matrix &aOther) {
if (aMatrix.getDimSize(2)>1 || aMatrix.isComplex()) {
std::cerr
@@ -221,6 +237,11 @@ Matrix Aurora::min(const Matrix &aMatrix, const Matrix &aOther) {
}
Matrix Aurora::max(const Matrix &aMatrix, FunctionDirection direction) {
long a,b;
return max(aMatrix,direction,a,b);
}
Matrix Aurora::max(const Matrix &aMatrix, FunctionDirection direction, long& rowIdx, long& colIdx) {
if (aMatrix.getDimSize(2)>1 || aMatrix.isComplex()) {
std::cerr
<< (aMatrix.getDimSize(2) > 1 ? "max() not support 3D data!" : "max() not support complex value type!")
@@ -231,17 +252,22 @@ Matrix Aurora::max(const Matrix &aMatrix, FunctionDirection direction) {
{
case All:
{
Eigen::Map<Eigen::VectorXd> retV(aMatrix.getData(),aMatrix.getDataSize());
double * ret = malloc(1);
ret[0] = retV.array().maxCoeff();
Eigen::Map<Eigen::MatrixXd> retV(aMatrix.getData(), aMatrix.getDimSize(0), aMatrix.getDimSize(1));
double *ret = malloc(1);
ret[0] = retV.array().maxCoeff(&rowIdx, &colIdx);
return Matrix::New(ret,1);
}
case Row:
{
Eigen::Map<Eigen::MatrixXd> srcMatrix(aMatrix.getData(),aMatrix.getDimSize(0),aMatrix.getDimSize(1));
double * ret = malloc(aMatrix.getDimSize(0));
if (aMatrix.getDimSize(0) == 1){
ret[0] = srcMatrix.topRows(0).maxCoeff(&rowIdx, &colIdx);
}
else{
Eigen::Map<Eigen::MatrixXd> retMatrix(ret,aMatrix.getDimSize(0),1);
retMatrix = srcMatrix.rowwise().maxCoeff();
}
return Matrix::New(ret,aMatrix.getDimSize(0),1);
}
case Column:
@@ -249,8 +275,13 @@ Matrix Aurora::max(const Matrix &aMatrix, FunctionDirection direction) {
{
Eigen::Map<Eigen::MatrixXd> srcMatrix(aMatrix.getData(),aMatrix.getDimSize(0),aMatrix.getDimSize(1));
double * ret = malloc(aMatrix.getDimSize(0));
if (aMatrix.getDimSize(1) == 1){
ret[0] = srcMatrix.col(0).maxCoeff(&rowIdx, &colIdx);
}
else {
Eigen::Map<Eigen::MatrixXd> retMatrix(ret,1,aMatrix.getDimSize(1));
retMatrix = srcMatrix.colwise().maxCoeff();
}
return Matrix::New(ret,1,aMatrix.getDimSize(1));
}
}
@@ -292,15 +323,6 @@ Matrix Aurora::sum(const Matrix &aMatrix, FunctionDirection direction) {
}
}
void excludeNan(double * aInput, int aInputSize,double* aOutput,int& aOutputSize){
aOutputSize = 0;
for (int i = 0; i < aInputSize; ++i) {
if (std::isnan(aInput[i])) continue;
aOutput[aOutputSize]=aInput[i];
aOutputSize++;
}
}
Matrix Aurora::mean(const Matrix &aMatrix, FunctionDirection direction, bool aIncludeNan) {
if (aMatrix.getDimSize(2)>1 || aMatrix.isComplex()) {
std::cerr

4
src/Function2D.h
View File

@@ -26,6 +26,8 @@ namespace Aurora {
*/
Matrix min(const Matrix& aMatrix,FunctionDirection direction = Column);
Matrix min(const Matrix& aMatrix,FunctionDirection direction, long& rowIdx, long& colIdx);
/**
* 求矩阵最小值，可按行、列、单元, 目前不支持三维，不支持复数
* @param aMatrix 矩阵
@@ -34,6 +36,8 @@ namespace Aurora {
*/
Matrix max(const Matrix& aMatrix,FunctionDirection direction = Column);
Matrix max(const Matrix& aMatrix,FunctionDirection direction , long& rowIdx, long& colIdx);
/**
* 比较两个矩阵，求对应位置的最小值，不支持三维
* @attention 矩阵形状不一样时，如A为[MxN],则B应为标量或[1xN]的行向量

13
test/Function2D_Test.cpp
View File

@@ -96,6 +96,12 @@ TEST_F(Function2D_Test, min) {
EXPECT_DOUBLE_EQ(2, ret.getData()[0]);
EXPECT_DOUBLE_EQ(2, ret.getData()[1]);
EXPECT_DOUBLE_EQ(-1, ret.getData()[2]);
long r,c;
ret = Aurora::min(A, Aurora::Column,r,c);
EXPECT_DOUBLE_EQ(1, ret.getDataSize());
EXPECT_DOUBLE_EQ(1, ret.getData()[0]);
EXPECT_EQ(0, r);
EXPECT_EQ(0, c);
ret = Aurora::min(A, C);
EXPECT_DOUBLE_EQ(3, ret.getDataSize());
EXPECT_DOUBLE_EQ(1, ret.getData()[0]);
@@ -129,6 +135,12 @@ TEST_F(Function2D_Test, max) {
EXPECT_DOUBLE_EQ(3, ret.getData()[0]);
EXPECT_DOUBLE_EQ(3, ret.getData()[1]);
EXPECT_DOUBLE_EQ(3, ret.getData()[2]);
long r,c;
ret = Aurora::max(A, Aurora::Column,r,c);
EXPECT_DOUBLE_EQ(1, ret.getDataSize());
EXPECT_DOUBLE_EQ(3, ret.getData()[0]);
EXPECT_EQ(2, r);
EXPECT_EQ(0, c);
}
TEST_F(Function2D_Test, sum) {
@@ -153,6 +165,7 @@ TEST_F(Function2D_Test, sum) {
}
TEST_F(Function2D_Test, mean) {
{
double *dataB = new double[16]{1.1, 2.6, 3.8, 6.2,
4.3, 5.7, 6.9, 10.6,