Distance Metric APIs - 5.2 English - 68552

Compute the distance matrix for an m by k matrix X and optionally an n by k matrix Y.

Parameters:

• order – [in] a da_order enumerated type, specifying whether X, Y and D are stored in row-major order or column-major order.

• m – [in] the number of rows of matrix X.

• n – [in] the number of rows of matrix Y.

• k – [in] the number of columns of matrices X and Y.

• X – [in] the m \(\times \) k matrix.

• ldx – [in] the leading dimension of the matrix X. Constraint: ldx \(\ge\) m if order = column_major, or ldx \(\ge\) k if order = row_major.

• Y – [in] the n \(\times \) k matrix.

• ldy – [in] the leading dimension of the matrix Y. Constraint: ldy \(\ge\) n if order = column_major, or ldy \(\ge\) k if order = row_major.

• D – [out] if Y is nullptr, the m \(\times \) m distance matrix, and the m \(\times \) n distance matrix, otherwise.

• ldd – [in] the leading dimension of the matrix D. Constraint: ldd \(\ge\) m, if Y is nullptr or order = column_major, and ldd \(\ge\) n, otherwise.

• p – [in] the order of the Minkowski metric used to compute the distance matrix. For p = 1.0, this defaults to Manhattan metric and for p = 2.0 this defaults to Euclidean metric. p is only used for Minkowski distance and will be ignored otherwise.

• metric – [in] enum that specifies the metric to use to compute the distance matrix. The default value is da_euclidean.

Returns:

da_status. The function returns:

• da_status_success - the operation was successfully completed.

• da_status_invalid_leading_dimension - one of the constraints on ldx, ldy or ldd was violated.

• da_status_invalid_pointer - one of the arrays X or D is null.

• da_status_invalid_array_dimension - either m \(< 1\), or k \(< 1\), or n \(< 1\), while Y is not nullptr.

• da_status_not_implemented - an option that is currently not implemented was set.

• da_status_memory_error - a memory allocation error occurred.