Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/9413#discussion_r44046167
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/CholeskyDecomposition.scala
---
@@ -40,4 +40,20 @@ private[spark] object CholeskyDecomposition {
assert(code == 0, s"lapack.dpotrs returned $code.")
bx
}
+
+ /**
+ * Computes the inverse of a real symmetric positive definite matrix A
+ * using the Cholesky factorization A = U**T*U.
+ * The input arguments are modified in-place to store the inverse matrix.
+ * @param UAi the upper triangular factor U from the Cholesky
factorization A = U**T*U
+ * @param k the dimension of A
+ * @return the upper triangle of the (symmetric) inverse of A
+ */
+ def inverse(UAi: Array[Double], k: Int): Array[Double] = {
+ val info = new intW(0)
+ lapack.dpptri("U", k, UAi, info)
+ val code = info.`val`
+ assert(code == 0, s"lapack.dpptri returned $code.")
--- End diff --
This throws an AssertionError on failure. It'd be better to throw a
RuntimeError (or one based on the return code, though that may be too much
trouble).
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