You might want to compare two **Eigen** matrices for equality while writing unit tests for your mathematical operations. You could always do an element-wise comparison manually. However, there are Eigen methods that can ease the comparison.

# isApprox

This method performs element-wise subtraction of the two matrices and computes the **Frobenius norm** of the resulting matrix. It checks if this value is **less than or equal** to a precision parameter that you can pass in. If you do not pass in any precision value, then the norm is compared to **zero**. More details on this are here

Usage:

typedef typename Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> EigenMatrix; EigenMatrix a, b; // True if equal bool r = a.isApprox(b);

# norm

You could do the above computation yourself. For example:

typedef typename Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> EigenMatrix; EigenMatrix a, b; // Compare bool r = ((a - b).norm() == 0); // Approx compare bool r = ((a - b).norm() < small_positive_value);

Above “norm” comparison is invalid.

isApprox essientiall uses:

|a-b|./ min(|a|,|b|) < small_positive_value

while your norm in the 1D case equates to:

sqrt( (a-b)^2 ) = |a-b| < small_positive_value.

My conclusion is that you dont know how to compare floating point values so stop misinforming others…dd

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