Non-linear-transformation NPM

non-linear-transformation-npm-package

There is a helping method for graphs name transformDataToNonLinearList. This method can transform a random numeric axis data of a graphs into nonlinear axis data set.

Dependencies:

lodash: https://lodash.com/docs/4.17.15
set-clustering: https://www.npmjs.com/package/set-clustering

Lodash is a modern JavaScript utility library delivering modularity, performance & extras. We are using its methods like cloneDeep, uniq, isUndefined, isNull, isNaN

Set Clustering is a tool for grouping objects based on similarity. Give an array of arbitrary elements, and a function to determine how similar two elements are. The elements can then be divided into a number of groups to your liking. The elements in each group will be more similar to each other than to elements of other groups.

Code:

/**
 * @param list: list of numbers
 * @param forceInsertZero: if true the code will add 0 in return axis
 * @param lengthRequireForOutput: optional min number of element you want in response
 */
module.exports.transformDataToNonLinearList = function(
  list = [],
  forceInsertZero = false,
  lengthRequireForOutput = null
) {
  // code is in git 
}

DRY Run: See script.js file to precomputed sample output and a sample run function.

Examples:

Sample 1:

Input [{"x":59836,"y":4475},{"x":358074,"y":100},{"x":95244,"y":2858},{"x":12184,"y":655},{"x":205809,"y":4913},{"x":123533,"y":66}, {"x":251479,"y":378},{"x":368263,"y":813},{"x":402066,"y":864},{"x":415754,"y":2949},{"x":445232,"y":3064},{"x":364614,"y":1011}, {"x":146937,"y":1248},{"x":104115,"y":3587},{"x":77770,"y":4348},{"x":92350,"y":4652},{"x":87065,"y":912},{"x":125944,"y":4127},{"x":123138,"y":688}, {"x":124141,"y":4129},{"x":140733,"y":568},{"x":475890,"y":2094},{"x":215401,"y":3464},{"x":265129,"y":3053},{"x":23731,"y":4542}, {"x":362218,"y":4871},{"x":455136,"y":2233},{"x":393355,"y":3184},{"x":145136,"y":2237},{"x":433029,"y":1873},{"x":70962,"y":4777}, {"x":285408,"y":844},{"x":281586,"y":2457},{"x":252086,"y":635},{"x":476036,"y":2550},{"x":427947,"y":3169},{"x":495084,"y":1647}, {"x":482966,"y":2947},{"x":106180,"y":4173},{"x":100875,"y":4431},{"x":56636,"y":3064},{"x":62198,"y":4648},{"x":327610,"y":4458}, {"x":452805,"y":1110},{"x":427972,"y":3304},{"x":90057,"y":3781},{"x":356033,"y":1226},{"x":229719,"y":3170},{"x":182785,"y":363}, {"x":147862,"y":4632}]

output X: [0, 336930, 408104, 410378, 411543, 414616, 414678, 414820, 415178, 490554]

output Y: [0, 585, 603, 604, 3928, 4739, 4741, 4759, 4786, 4793]

Sample 2:

Input: [{x: -1, y: 10}, {x: -11, y: 15},{x: -5, y: 17}, {x: 7, y: 25},{x: 15, y: 11}, {x: -100, y: 18},{x: 20, y: 50}, {x: 50, y: 50}]

output X-axis: [-150,11,16,21,25,29,100]

output Y-axis: [-40,10,11,12,100]

Sample 3:

When flag forceInsertZero is set to true.

Input: [{x: -1, y: 10}, {x: -11, y: 15},{x: -5, y: 17}, {x: 7, y: 25},{x: 15, y: 11}, {x: -100, y: 18},{x: 20, y: 50}, {x: 50, y: 50}]

output X-axis: [-150,0,16,24,27,50,100]

output Y-axis: [-40,0,13,15,100]

Sample 4: