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A matrix strategy lets you use variables in a single job definition to automatically create multiple job runs that are based on the combinations of the variables. For example, you can use a matrix strategy to test your code in multiple versions of a language or on multiple operating systems.
Use jobs..strategy.matrix to define a matrix of different job configurations. Within your matrix, define one or more variables followed by an array of values. For example, the following matrix has a variable called version with the value [10, 12, 14] and a variable called os with the value [ubuntu-latest, windows-latest]:
By default, GitHub will maximize the number of jobs run in parallel depending on runner availability. The order of the variables in the matrix determines the order in which the jobs are created. The first variable you define will be the first job that is created in your workflow run. For example, the above matrix will create the jobs in the following order:
The variables that you define become properties in the matrix context, and you can reference the property in other areas of your workflow file. In this example, you can use matrix.version and matrix.os to access the current value of version and os that the job is using. For more information, see "Contexts."
For example, the following workflow defines the variable version with the values [10, 12, 14]. The workflow will run three jobs, one for each value in the variable. Each job will access the version value through the matrix.version context and pass the value as node-version to the actions/setup-node action.
For example, the following workflow triggers on the repository_dispatch event and uses information from the event payload to build the matrix. When a repository dispatch event is created with a payload like the one below, the matrix version variable will have a value of [12, 14, 16]. For more information about the repository_dispatch trigger, see "Events that trigger workflows."
For each object in the include list, the key:value pairs in the object will be added to each of the matrix combinations if none of the key:value pairs overwrite any of the original matrix values. If the object cannot be added to any of the matrix combinations, a new matrix combination will be created instead. Note that the original matrix values will not be overwritten, but added matrix values can be overwritten.
If you don't specify any matrix variables, all configurations under include will run. For example, the following workflow would run two jobs, one for each include entry. This lets you take advantage of the matrix strategy without having a fully populated matrix.
To remove specific configurations defined in the matrix, use jobs..strategy.matrix.exclude. An excluded configuration only has to be a partial match for it to be excluded. For example, the following workflow will run nine jobs: one job for each of the 12 configurations, minus the one excluded job that matches os: macos-latest, version: 12, environment: production, and the two excluded jobs that match os: windows-latest, version: 16.
jobs..strategy.fail-fast applies to the entire matrix. If jobs..strategy.fail-fast is set to true or its expression evaluates to true, GitHub will cancel all in-progress and queued jobs in the matrix if any job in the matrix fails. This property defaults to true.
You can use jobs..strategy.fail-fast and jobs..continue-on-error together. For example, the following workflow will start four jobs. For each job, continue-on-error is determined by the value of matrix.experimental. If any of the jobs with continue-on-error: false fail, all jobs that are in progress or queued will be cancelled. If the job with continue-on-error: true fails, the other jobs will not be affected.
By default, GitHub will maximize the number of jobs run in parallel depending on runner availability. To set the maximum number of jobs that can run simultaneously when using a matrix job strategy, use jobs..strategy.max-parallel.
A rich hierarchy of sparse and dense matrix classes,including general, symmetric, triangular, and diagonal matriceswith numeric, logical, or pattern entries. Efficient methods foroperating on such matrices, often wrapping the 'BLAS', 'LAPACK',and 'SuiteSparse' libraries.
The RDoC Matrix is a component of the larger RDoC Framework. It is a tool to help implement the principles of RDoC. Before you utilize the RDoC matrix in your study, please read more about the Framework on the About RDoC page. Also, read these notes first if you are new to the RDoC Matrix.
Returns a matrix from an array-like object, or from a string of data.A matrix is a specialized 2-D array that retains its 2-D naturethrough operations. It has certain special operators, such as *(matrix multiplication) and ** (matrix power).
A dimnames attribute for the matrix:NULL or a list of length 2 giving the row and columnnames respectively. An empty list is treated as NULL, and alist of length one as row names. The list can be named, and thelist names will be used as names for the dimensions.
If there are too few elements in data to fill the matrix,then the elements in data are recycled. If data haslength zero, NA of an appropriate type is used for atomicvectors (0 for raw vectors) and NULL for lists.
is.matrix returns TRUE if x is a vector and has a"dim" attribute of length 2 and FALSE otherwise.Note that a data.frame is not a matrix by thistest. The function is generic: you can write methods to handlespecific classes of objects, see InternalMethods.
as.matrix is a generic function. The method for data frameswill return a character matrix if there is only atomic columns and anynon-(numeric/logical/complex) column, applying as.vectorto factors and format to other non-character columns.Otherwise, the usual coercion hierarchy (logical < integer < double
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A matrix is a concise and useful way of uniquely representing and working with linear transformations. In particular, every linear transformation can be represented by a matrix, and every matrix corresponds to a unique linear transformation. The matrix, and its close relative the determinant, are extremely important concepts in linear algebra, and were first formulated by Sylvester (1851) and Cayley.
In his 1851 paper, Sylvester wrote, "For this purpose we must commence, not with a square, but with an oblong arrangement of terms consisting, suppose, of lines and columns. This will not in itself represent a determinant, but is, as it were, a Matrix out of which we may form various systems of determinants by fixing upon a number , and selecting at will lines and columns, the squares corresponding of th order." Because Sylvester was interested in the determinant formed from the rectangular array of number and not the array itself (Kline 1990, p. 804), Sylvester used the term "matrix" in its conventional usage to mean "the place from which something else originates" (Katz 1993). Sylvester (1851) subsequently used the term matrix informally, stating "Form the rectangular matrix consisting of rows and columns.... Then all the determinants that can be formed by rejecting any one column at pleasure out of this matrix are identically zero." However, it remained up to Sylvester's collaborator Cayley to use the terminology in its modern form in papers of 1855 and 1858 (Katz 1993).
In his 1867 treatise on determinants, C. L. Dodgson (Lewis Carroll) objected to the use of the term "matrix," stating, "I am aware that the word 'Matrix' is already in use to express the very meaning for which I use the word 'Block'; but surely the former word means rather the mould, or form, into which algebraical quantities may be introduced, than an actual assemblage of such quantities...." However, Dodgson's objections have passed unheeded and the term "matrix" has stuck.
An matrix consists of rows and columns, and the set of matrices with real coefficients is sometimes denoted . To remember which index refers to which direction, identify the indices of the last (i.e., lower right) term, so the indices of the last element in the above matrix identify it as an matrix. Note that while this convention matches the one used for expressing measurements of a painting on canvas (where height comes first then width), it is opposite that used to measure paper, room dimensions, and windows, (in which the width is listed first followed by the height; e.g., 8 1/2 inch by 11 inch paper is 8 1/2 inches wide and 11 inches high).
A matrix is said to be square if , and rectangular if . An matrix is called a column vector, and a matrix is called a row vector. Special types of square matrices include the identity matrix , with (where is the Kronecker delta) and the diagonal matrix (where are a set of constants).
It is sometimes convenient to represent an entire matrix in terms of its matrix elements. Therefore, the th element of the matrix could be written , and the matrix composed of entries could be written as , or simply for short.
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