(columns neanderthal-mx)Returns the number of columns.
Returns the number of columns.
(fmap f a)Maps a function onto a functor.
Maps a function onto a functor.
(lls a b)Linear Linear Squares, solving for 'x', where a × x = b. Returns
solution.
Linear Linear Squares, solving for 'x', where `a` × x = `b`. Returns solution.
(lls! a b)Linear Linear Squares, solving for 'x', where a × x = b. After
destruction, a will contain factorization data, and b will contain
solution. Also returns solution.
Linear Linear Squares, solving for 'x', where `a` × x = `b`. After destruction, `a` will contain factorization data, and `b` will contain solution. Also returns solution.
(lls-with-error a b)Linear Linear Squares, solving for 'x', where a × x = b. Returns map
of solution, projection matrix, annihilation matrix, and the maximum
likelihood estimate for the error.
Linear Linear Squares, solving for 'x', where `a` × x = `b`. Returns map of solution, projection matrix, annihilation matrix, and the maximum likelihood estimate for the error.
(mx* neanderthal-mx1 neanderthal-mx2)(mx* neanderthal-mx1 neanderthal-mx2 & more)Matrix multiplication.
Matrix multiplication.
(neanderthal-columns neanderthal-mx)Returns the columns as neanderthal vectors.
Returns the columns as neanderthal vectors.
(neanderthal-matrix->matrix neanderthal-mx)(neanderthal-matrix->matrix neanderthal-mx take-nrows)(neanderthal-rows neanderthal-mx)Returns the rows as neanderthal vectors.
Returns the rows as neanderthal vectors.
(rows neanderthal-mx)Returns the number of rows.
Returns the number of rows.
(sv-decomposition neanderthal-m)Calculates the compact Singular Value Decomposition of a Neanderthal
matrix. The Singular Value Decomposition of neanderthal-m is a set of three
matrices: svd-left, singular-values, and svd-right such that:
neanderthal-m = svd-left × singular-values × svd-right.
Let neanderthal-m be a m × n matrix, then svd-left is a m × p orthogonal
matrix of the left singular vectors, singular-values is a p × p diagonal
matrix of singular values with positive or nil elements, and are ordered from
largest to smallest. svd-right is a p × n orthogonal matrix of the right
singular vectors where p = min(m,n). Note that:
Identity Matrix = (transpose svd-left) × svd-left =
svd-right × (transpose svd-right).
Returns a map containing:
::svd-left -- Neanderthal matrix of left singular vectors
::singular-values -- diagonal Neanderthal Commons matrix
::svd-right -- transpose of Neanderthal matrix of right singular
vectors
::rank -- rank.
Calculates the compact Singular Value Decomposition of a Neanderthal
matrix. The Singular Value Decomposition of `neanderthal-m` is a set of three
matrices: `svd-left`, `singular-values`, and `svd-right` such that:
`neanderthal-m` = `svd-left` × `singular-values` × `svd-right`.
Let `neanderthal-m` be a m × n matrix, then `svd-left` is a m × p orthogonal
matrix of the left singular vectors, `singular-values` is a p × p diagonal
matrix of singular values with positive or nil elements, and are ordered from
largest to smallest. `svd-right` is a p × n orthogonal matrix of the right
singular vectors where p = min(m,n). Note that:
Identity Matrix = (transpose `svd-left`) × `svd-left` =
`svd-right` × (transpose `svd-right`).
Returns a map containing:
`::svd-left` -- Neanderthal matrix of left singular vectors
`::singular-values` -- diagonal Neanderthal Commons matrix
`::svd-right` -- transpose of Neanderthal matrix of right singular
vectors
`::rank` -- rank.(vector->neanderthal-matrix rows columns v by-column?)v is a vector of data.
`v` is a vector of data.
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