isMatrixSymmetric

C++ Function Reference

1 Signature

bool BigDataStatMeth::isMatrixSymmetric(const Eigen::MatrixXd &X, int sample_size=100)

2 Description

Matrix symmetry detection.

3 Parameters

X (const Eigen::MatrixXd &)
sample_size (int)

4 Returns

Type: bool

5 Caller Graph

6 Source Code

Implementation

File: inst/include/hdf5Algebra/matrixEigenDecomposition.hpp • Lines 84-104

inline bool isMatrixSymmetric(const Eigen::MatrixXd& X, int sample_size = 100) {
        if (X.rows() != X.cols()) return false;
        int n = X.rows();
        if (n <= 3) return true;
        if (n <= 50) {
            double max_diff = (X - X.transpose()).cwiseAbs().maxCoeff();
            return max_diff <= 1e-12 * std::max(1.0, X.cwiseAbs().maxCoeff());
        }
        sample_size = std::min(sample_size, n * n / 4);
        Eigen::VectorXd diffs(sample_size);
        int count = 0;
        std::random_device rd;
        std::mt19937 gen(rd());
        std::uniform_int_distribution<> dis(0, n - 1);
        for (int s = 0; s < sample_size && count < sample_size; ++s) {
            int i = dis(gen), j = dis(gen);
            if (i != j) diffs(count++) = std::abs(X(i,j) - X(j,i));
        }
        if (count == 0) return true;
        return diffs.head(count).maxCoeff() <= 1e-12 * std::max(1.0, X.cwiseAbs().maxCoeff());
    }

7 Usage Example

#include "BigDataStatMeth.hpp"

// Example usage
auto result = isMatrixSymmetric(...);

---
title: "isMatrixSymmetric"
subtitle: "C++ Function Reference"
---

## Signature

```cpp
bool BigDataStatMeth::isMatrixSymmetric(const Eigen::MatrixXd &X, int sample_size=100)
```

## Description

Matrix symmetry detection.

## Parameters

- `X` (`const Eigen::MatrixXd &`)
- `sample_size` (`int`)

## Returns

Type: `bool`

## Caller Graph

::: {.diagram-section}
<object type="image/svg+xml" data="images/namespace_big_data_stat_meth_a45e2b926781664ca98be48c1bce0379c_icgraph.svg" class="class-diagram">
  <img src="images/namespace_big_data_stat_meth_a45e2b926781664ca98be48c1bce0379c_icgraph.svg" alt="Function dependencies"/>
</object>
:::

## Source Code

::: {.callout-note collapse="true"}
### Implementation

**File:** `inst/include/hdf5Algebra/matrixEigenDecomposition.hpp` • **Lines 84-104**

```cpp
inline bool isMatrixSymmetric(const Eigen::MatrixXd& X, int sample_size = 100) {
        if (X.rows() != X.cols()) return false;
        int n = X.rows();
        if (n <= 3) return true;
        if (n <= 50) {
            double max_diff = (X - X.transpose()).cwiseAbs().maxCoeff();
            return max_diff <= 1e-12 * std::max(1.0, X.cwiseAbs().maxCoeff());
        }
        sample_size = std::min(sample_size, n * n / 4);
        Eigen::VectorXd diffs(sample_size);
        int count = 0;
        std::random_device rd;
        std::mt19937 gen(rd());
        std::uniform_int_distribution<> dis(0, n - 1);
        for (int s = 0; s < sample_size && count < sample_size; ++s) {
            int i = dis(gen), j = dis(gen);
            if (i != j) diffs(count++) = std::abs(X(i,j) - X(j,i));
        }
        if (count == 0) return true;
        return diffs.head(count).maxCoeff() <= 1e-12 * std::max(1.0, X.cwiseAbs().maxCoeff());
    }
```
:::

## Usage Example

```cpp
#include "BigDataStatMeth.hpp"

// Example usage
auto result = isMatrixSymmetric(...);
```