This trait is commonly used for breeze.linalg.sum and its kin for summing along a particular axis of a Matrix.
TODO @ dwhl: What does enforceLength exactly do?
TODO
Class for classes that are broadcasting their columns.
Class for classes that are broadcasting their rows.
A compressed sparse column matrix, as used in Matlab and CSparse, etc.
A map-like tensor that acts like a collection of key-value pairs where the set of values may grow arbitrarily.
A map-like tensor that acts like a collection of key-value pairs where the set of values may grow arbitrarily.
A DenseMatrix is a matrix with all elements found in an array.
A DenseVector is the "obvious" implementation of a Vector, with one twist.
A HashVector is a sparse vector backed by an OpenAddressHashArray
Marker trait for exceptions thrown from the breeze.linalg package.
Thrown when trying to solve using a singular matrix.
This decorator automatically caches the norm and sums of a vector and invalidates the cache whenever the vector is updated.
Exception thrown if a routine has not converged.
In some sense, this is the real root of the linalg hierarchy.
We occasionally need a Tensor that doesn't extend NumericOps directly.
for adding slicing
A SliceVector is a vector that is a view of another underlying tensor.
A Binary-search backed vector.
A Tensor defines a map from an index set to a set of values.
A Vector represents the mathematical concept of a vector in math.
A VectorBuilder is basically an unsorted Sparse Vector.
Trait that can mixed to companion objects to enable utility methods for creating vectors.
Trait for operators and such used in vectors.
Trait used for methods that can return a view or a copy.
Computes the LU factorization of the given real M-by-N matrix X such that X = P * L * U where P is a permutation matrix (row exchanges).
Import this to provide access to a DenseMatrix[Double] as a MutableInnerProductSpace, so it can be used in optimization.
Returns true if all elements are non-zero
Returns true if any element is non-zero
Computes y += x * a, possibly doing less work than actually doing that operation
Computes the cholesky decomposition A of the given real symmetric positive definite matrix X such that X = A A.
clip(a, lower, upper) returns an array such that all elements are "clipped" at the range (lower, upper)
Copy a T.
Copy a T. Most tensor objects have a CanCopy implicit, which is what this farms out to.
Vector cross product of 3D vectors a and b.
Reads in a DenseMatrix from a CSV File
Computes the determinant of the given real matrix.
returns a vector along the diagonal of v.
Differences between adjacent elements and discrete derivatives.
Eigenvalue decomposition (right eigenvectors)
Computes all eigenvalues (and optionally right eigenvectors) of the given real symmetric matrix X.
mirrors the columns (left<->right).
mirrors the rows (up down)
Computes the inverse of a given real matrix.
Returns the Kronecker product of two matrices a and b, usually denoted a ⊗ b.
Generates a vector of linearly spaced values between a and b (inclusive).
Generates a vector of linearly spaced values between a and b (inclusive). The returned vector will have length elements, defaulting to 100.
The lower triangular portion of the given real quadratic matrix X.
The lower triangular portion of the given real quadratic matrix X. Note that no check will be performed regarding the symmetry of X.
A breeze.generic.UFunc for computing the mean of objects
A breeze.generic.UFunc for computing the mean and variance of objects.
Computes the minimum.
Raises m to the exp'th power via eigenvalue decomposition.
Computes the norm of an object.
Normalizes the argument such that its norm is 1.
Computes the Moore-Penrose pseudo inverse of the given real matrix X.
Computes the product
QR Factorization
QR Factorization with pivoting
Computes the rank of a matrix.
Returns the rank of each element in the given vector, adjusting for ties.
Returns a reversed copy of the DenseVector.
Rotates a matrix by 90 * k degrees counter clockwise.
Computes the softmax (a.
Computes the standard deviation by calling variance and then sqrt'ing
Computes the SVD of a m by n matrix Returns an m*m matrix U, a vector of singular values, and a n*n matrix V'
The upper triangular portion of the given real quadratic matrix X.
The upper triangular portion of the given real quadratic matrix X. Note that no check will be performed regarding the symmetry of X.
A breeze.generic.UFunc for computing the variance of objects.
This package contains everything relating to Vectors, Matrices, Tensors, etc.
If you're doing basic work, you probably want breeze.linalg.DenseVector and breeze.linalg.DenseMatrix, which support most operations. We also have breeze.linalg.SparseVectors and (basic!) support for a sparse matrix (breeze.linalg.CSCMatrix).
This package object contains Matlab-esque functions for interacting with tensors and matrices.