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column; otherwise every column is assigned to one row. The assignment minimizes the sum of the assigned elements.\n\n## Instalation\n\n`$ npm i linear-sum-assignment`\n\n## Usage\n\n```js\nimport linearSumAssignment from 'linear-sum-assignment';\nimport { xCostMatrix } from 'ml-spectra-processing';\n\n/**\n * there is one more value in the experimental values, so one of\n * them will be not assigned.\n **/\nconst experimental = [1, 2, 3, 4, 5, 7];\nconst predicted = [3.1, 1.1, 1.9, 3.99, 5.2];\n\n/**\n * We will compute a cost matrix where experimental are\n * rows and predicted in columns.\n * In this case we will look for the closest peak for each experimental peak value.\n **/\n\nconst diff = xCostMatrix(experimental, predicted, {\n  fct: (a, b) => Math.abs(a - b),\n});\nconst result = linearSumAssignment(diff, { maximaze: false });\nconsole.log(result);\n/**\n{\n  rowAssignments: Float64Array(6) [ 1, 2, 0, 3, 4, -1 ],\n  columnAssignments: Float64Array(5) [ 2, 0, 1, 3, 4 ],\n  gain: 0.5100000000000002,\n  dualVariableForColumns: Float64Array(5) [\n    0.0900000000000003,\n    0.0900000000000003,\n    0.0900000000000003,\n    0,\n    0.1900000000000004\n  ],\n  dualVariableForRows: Float64Array(6) [ 0, 0, 0, 0, 0, 0 ]\n}\n*/\n```\n\n`rowAssignments` contains the index of the column assigned to each element in the rows (experimental).\n\n`columnAssignments` contains the index of the row assigned to each element in the columns. So the first element in predicted is assigned to third element in experimental.\n`dualVariableForColumns` and `dualVariableForRows` are the Lagrange multipliers or dual variables.\n`gain` the sum of the elements in the cost matrix.\n\n## License\n\n[MIT](./LICENSE)\n\n[npm-image]: https://img.shields.io/npm/v/linearSumAssignment.svg\n[npm-url]: https://www.npmjs.com/package/linearSumAssignment\n[ci-image]: https://github.com/mljs/linear-sum-assignment/workflows/Node.js%20CI/badge.svg?branch=main\n[ci-url]: https://github.com/mljs/linear-sum-assignment/actions?query=workflow%3A%22Node.js+CI%22\n[codecov-image]: https://img.shields.io/codecov/c/github/mljs/linear-sum-assignment.svg\n[codecov-url]: https://codecov.io/gh/mljs/linear-sum-assignment\n[download-image]: https://img.shields.io/npm/dm/linearSumAssignment.svg\n[download-url]: https://www.npmjs.com/package/linearSumAssignment\n","readmeFilename":"README.md"}