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Add vecnorm and vecnorm's unittest.

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Add norm function with complex support.
This commit is contained in:
sunwen
2023-04-26 11:17:15 +08:00
parent d1389df8a4
commit 7693ce9f9e
3 changed files with 98 additions and 5 deletions
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41
src/Function1D.cpp
View File

@@ -1,4 +1,5 @@
#include "Function1D.h"
#include "Function2D.h"
#include "Function.h"
//必须在Eigen之前
@@ -420,12 +421,16 @@ Matrix Aurora::conj(const Matrix& aMatrix)
double Aurora::norm(const Matrix& aMatrix, NormMethod aNormMethod)
{
if(aMatrix.isComplex() || aMatrix.isNull())
if(aMatrix.isNull())
{
return NAN;
}
size_t size = aMatrix.getDataSize();
if(aMatrix.isComplex())
{
size*=2;
}
int column = aMatrix.getDimSize(1);
int row = aMatrix.getDimSize(0);
if (aNormMethod == NormMethod::Norm1)
@@ -433,7 +438,7 @@ double Aurora::norm(const Matrix& aMatrix, NormMethod aNormMethod)
double value = 0;
for(int i=0; i<column; ++i)
{
double temp = cblas_dasum(row, aMatrix($,i,$).toMatrix().getData(), 1);
double temp = Aurora::sum(abs(aMatrix($,i,$).toMatrix())).getData()[0];
if(temp > value)
{
value = temp;
@@ -450,9 +455,18 @@ double Aurora::norm(const Matrix& aMatrix, NormMethod aNormMethod)
//columns > 1
if(aMatrix.getDimSize(1) > 1)
{
Eigen::Map<Eigen::MatrixXd> eMatrix(aMatrix.getData(),aMatrix.getDimSize(0),aMatrix.getDimSize(1));
Eigen::JacobiSVD<Eigen::MatrixXd> svd(eMatrix, Eigen::ComputeThinU | Eigen::ComputeThinV);
return svd.singularValues()(0);
if(aMatrix.isComplex())
{
Eigen::Map<Eigen::MatrixXcd> eMatrix((MKL_Complex16*)aMatrix.getData(), row, column);
Eigen::JacobiSVD<Eigen::MatrixXcd> svd(eMatrix, Eigen::ComputeThinU | Eigen::ComputeThinV);
return svd.singularValues()(0);
}
else
{
Eigen::Map<Eigen::MatrixXd> eMatrix(aMatrix.getData(), row, column);
Eigen::JacobiSVD<Eigen::MatrixXd> svd(eMatrix, Eigen::ComputeThinU | Eigen::ComputeThinV);
return svd.singularValues()(0);
}
}
else
{
@@ -507,3 +521,20 @@ Matrix Aurora::horzcat(const Matrix& aMatrix1, const Matrix& aMatrix2)
return Matrix::New(resultData, row, column1+column2, 1, aMatrix1.getValueType());
}
Matrix Aurora::vecnorm(const Matrix& aMatrix, NormMethod aNormMethod, int aDim)
{
//only surpport aDim = 1 for now.
if(aDim != 1 || aNormMethod == NormMethod::NormF || aMatrix.isNull())
{
return Matrix();
}
int column = aMatrix.getDimSize(1);
double* resultData = Aurora::malloc(column);
for(int i=0; i<column; ++i)
{
resultData[i] = norm(aMatrix($,i,$).toMatrix(), aNormMethod);
}
return Matrix::New(resultData,column);
}

2
src/Function1D.h
View File

@@ -70,6 +70,8 @@ namespace Aurora {
Matrix horzcat(const Matrix& aMatrix1, const Matrix& aMatrix2);
Matrix vecnorm(const Matrix& aMatrix, NormMethod aNormMethod, int aDim);
/**
* 多项式计算
* @brief 例如p[1 0 1],x[3 2 5],代表对多项式 y = x^2 + 1 求(x=3, x=2, x=5)时所有的y

60
test/Function1D_Test.cpp
View File

@@ -290,6 +290,7 @@ TEST_F(Function1D_Test, conj) {
}
TEST_F(Function1D_Test, norm) {
//1Dim
double *data = new double[3]{1,2,-3};
auto matrix = Aurora::Matrix::fromRawData(data, 3);
auto result = Aurora::norm(matrix,Aurora::NormMethod::Norm1);
@@ -299,6 +300,7 @@ TEST_F(Function1D_Test, norm) {
result = Aurora::norm(matrix,Aurora::NormMethod::NormF);
EXPECT_DOUBLE_AE(result,3.74166);
//2Dims
data = new double[8]{1,2,-3,6,7,9,22.3,-8.6};
matrix = Aurora::Matrix::fromRawData(data, 4,2);
result = Aurora::norm(matrix,Aurora::NormMethod::Norm1);
@@ -307,6 +309,26 @@ TEST_F(Function1D_Test, norm) {
EXPECT_DOUBLE_AE(result,26.7284);
result = Aurora::norm(matrix,Aurora::NormMethod::NormF);
EXPECT_DOUBLE_AE(result,27.4089);
//1Dim Complex
data = new double[6]{1,2,-3,4,5,-6};
matrix = Aurora::Matrix::fromRawData(data, 3,1,1,Aurora::Complex);
result = Aurora::norm(matrix,Aurora::NormMethod::Norm1);
EXPECT_DOUBLE_AE(result,15.0463);
result = Aurora::norm(matrix,Aurora::NormMethod::Norm2);
EXPECT_DOUBLE_AE(result,9.5394);
result = Aurora::norm(matrix,Aurora::NormMethod::NormF);
EXPECT_DOUBLE_AE(result,9.5394);
//2Dims Complex
data = new double[12]{1,2,-3,4,5,-6,7,8,9,22,24,25};
matrix = Aurora::Matrix::fromRawData(data, 3,2,1,Aurora::Complex);
result = Aurora::norm(matrix,Aurora::NormMethod::Norm1);
EXPECT_DOUBLE_AE(result,69.0553);
result = Aurora::norm(matrix,Aurora::NormMethod::Norm2);
EXPECT_DOUBLE_AE(result,43.5314);
result = Aurora::norm(matrix,Aurora::NormMethod::NormF);
EXPECT_DOUBLE_AE(result,44.3847);
}
TEST_F(Function1D_Test, transpose) {
@@ -368,3 +390,41 @@ TEST_F(Function1D_Test, horzcat) {
EXPECT_DOUBLE_EQ(result.getDimSize(0),3);
EXPECT_DOUBLE_EQ(result.getDimSize(1),2);
}
TEST_F(Function1D_Test, vecnrom) {
//1Dim
double *data = new double[3]{1,2,-3};
auto matrix = Aurora::Matrix::fromRawData(data, 3);
auto result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm1,1);
EXPECT_DOUBLE_AE(result.getData()[0],6);
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm2,1);
EXPECT_DOUBLE_AE(result.getData()[0],3.74166);
//2Dims
data = new double[8]{1,2,-3,6,7,9,22.3,-8.6};
matrix = Aurora::Matrix::fromRawData(data, 4,2);
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm1,1);
EXPECT_DOUBLE_AE(result.getData()[0],12);
EXPECT_DOUBLE_AE(result.getData()[1],46.9);
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm2,1);
EXPECT_DOUBLE_AE(result.getData()[0],7.0711);
EXPECT_DOUBLE_AE(result.getData()[1],26.4811);
//1Dim Complex
data = new double[6]{1,2,-3,4,5,-6};
matrix = Aurora::Matrix::fromRawData(data, 3,1,1,Aurora::Complex);
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm1,1);
EXPECT_DOUBLE_AE(result.getData()[0],15.0463);
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm2,1);
EXPECT_DOUBLE_AE(result.getData()[0],9.5394);
//2Dims Complex
data = new double[12]{1,2,-3,4,5,-6,7,8,9,22,24,25};
matrix = Aurora::Matrix::fromRawData(data, 3,2,1,Aurora::Complex);
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm1,1);
EXPECT_DOUBLE_AE(result.getData()[0],15.0463);
EXPECT_DOUBLE_AE(result.getData()[1],69.0553);
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm2,1);
EXPECT_DOUBLE_AE(result.getData()[0],9.5394);
EXPECT_DOUBLE_AE(result.getData()[1],43.3474);
}