new Matrices()
- Source:
Methods
(static) dense(numRows, numCols, values) → {module:eclairjs/mllib/linalg.Matrix}
Creates a column-major dense matrix.
Parameters:
Name | Type | Description |
---|---|---|
numRows |
number | number of rows |
numCols |
number | number of columns |
values |
Array.<number> | matrix entries in column major |
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Returns:
(static) diag(vector) → {module:eclairjs/mllib/linalg.Matrix}
Generate a diagonal matrix in `Matrix` format from the supplied values.
Parameters:
Name | Type | Description |
---|---|---|
vector |
module:eclairjs/mllib/linalg.Vector | a `Vector` that will form the values on the diagonal of the matrix on the diagonal |
Returns:
Square `Matrix` with size `values.length` x `values.length` and `values`
(static) eye(n) → {module:eclairjs/mllib/linalg.Matrix}
Generate a dense Identity Matrix in `Matrix` format.
Parameters:
Name | Type | Description |
---|---|---|
n |
number | number of rows and columns of the matrix |
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Returns:
`Matrix` with size `n` x `n` and values of ones on the diagonal
(static) horzcat(matrices) → {module:eclairjs/mllib/linalg.Matrix}
Horizontally concatenate a sequence of matrices. The returned matrix will be in the format
the matrices are supplied in. Supplying a mix of dense and sparse matrices will result in
a sparse matrix. If the Array is empty, an empty `DenseMatrix` will be returned.
Parameters:
Name | Type | Description |
---|---|---|
matrices |
Array.<module:eclairjs/mllib/linalg.Matrix> | array of matrices |
Returns:
a single `Matrix` composed of the matrices that were horizontally concatenated
(static) ones(numRows, numCols) → {module:eclairjs/mllib/linalg.Matrix}
Generate a `DenseMatrix` consisting of ones.
Parameters:
Name | Type | Description |
---|---|---|
numRows |
number | number of rows of the matrix |
numCols |
number | number of columns of the matrix |
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Returns:
`Matrix` with size `numRows` x `numCols` and values of ones
(static) rand(numRows, numCols, rng) → {module:eclairjs/mllib/linalg.Matrix}
Generate a `DenseMatrix` consisting of `i.i.d.` uniform random numbers.
Parameters:
Name | Type | Description |
---|---|---|
numRows |
number | number of rows of the matrix |
numCols |
number | number of columns of the matrix |
rng |
Random | a random number generator |
Returns:
`Matrix` with size `numRows` x `numCols` and values in U(0, 1)
(static) randn(numRows, numCols, rng) → {module:eclairjs/mllib/linalg.Matrix}
Generate a `DenseMatrix` consisting of `i.i.d.` gaussian random numbers.
Parameters:
Name | Type | Description |
---|---|---|
numRows |
number | number of rows of the matrix |
numCols |
number | number of columns of the matrix |
rng |
Random | a random number generator |
Returns:
`Matrix` with size `numRows` x `numCols` and values in N(0, 1)
(static) sparse(numRows, numCols, colPtrs, rowIndices, values) → {module:eclairjs/mllib/linalg.Matrix}
Creates a column-major sparse matrix in Compressed Sparse Column (CSC) format.
Parameters:
Name | Type | Description |
---|---|---|
numRows |
number | number of rows |
numCols |
number | number of columns |
colPtrs |
Array.<number> | the index corresponding to the start of a new column |
rowIndices |
Array.<number> | the row index of the entry |
values |
Array.<number> | non-zero matrix entries in column major |
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Returns:
(static) speye(n) → {module:eclairjs/mllib/linalg.Matrix}
Generate a sparse Identity Matrix in `Matrix` format.
Parameters:
Name | Type | Description |
---|---|---|
n |
number | number of rows and columns of the matrix |
Returns:
`Matrix` with size `n` x `n` and values of ones on the diagonal
(static) sprand(numRows, numCols, density, rng) → {module:eclairjs/mllib/linalg.Matrix}
Generate a `SparseMatrix` consisting of `i.i.d.` gaussian random numbers.
Parameters:
Name | Type | Description |
---|---|---|
numRows |
number | number of rows of the matrix |
numCols |
number | number of columns of the matrix |
density |
number | the desired density for the matrix |
rng |
Random | a random number generator |
Returns:
`Matrix` with size `numRows` x `numCols` and values in U(0, 1)
(static) sprandn(numRows, numCols, density, rng) → {module:eclairjs/mllib/linalg.Matrix}
Generate a `SparseMatrix` consisting of `i.i.d.` gaussian random numbers.
Parameters:
Name | Type | Description |
---|---|---|
numRows |
number | number of rows of the matrix |
numCols |
number | number of columns of the matrix |
density |
number | the desired density for the matrix |
rng |
Random | a random number generator |
Returns:
`Matrix` with size `numRows` x `numCols` and values in N(0, 1)
(static) vertcat(matrices) → {module:eclairjs/mllib/linalg.Matrix}
Vertically concatenate a sequence of matrices. The returned matrix will be in the format
the matrices are supplied in. Supplying a mix of dense and sparse matrices will result in
a sparse matrix. If the Array is empty, an empty `DenseMatrix` will be returned.
Parameters:
Name | Type | Description |
---|---|---|
matrices |
Array.<module:eclairjs/mllib/linalg.Matrix> | array of matrices |
Returns:
a single `Matrix` composed of the matrices that were vertically concatenated
(static) zeros(numRows, numCols) → {module:eclairjs/mllib/linalg.Matrix}
Generate a `Matrix` consisting of zeros.
Parameters:
Name | Type | Description |
---|---|---|
numRows |
number | number of rows of the matrix |
numCols |
number | number of columns of the matrix |
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Returns:
`Matrix` with size `numRows` x `numCols` and values of zeros