var dk = require('datakitjs');

//READ A CSV FILE

//file.csv
// COL1, COL2
// val11, val12
// val21, val22

dk.csv('file.csv', function(data) {
  console.log(data);
});

//Output:
//[{ COL1: val11, COL2: val12 }, { COL1: val21, COL2: val22 }]


//GET A COLUMN FROM AN ARRAY OF ROW OBJECTS
dk.csv('file.csv', function(data) {
  var c2 = dk.col(data, 'COL2');
  console.log(c2);
});

//Output:
//[val12, val22]

// By default, dk.csv will convert all values to strings. You can convert select
// columns to numbers by passing an array of column names to 'dk.numeric'.

//file2.csv
// COL1, COL2
// val11, 1
// val21, 2

dk.csv('file2.csv', function(data) {
  var d = dk.numeric(data, ['COL2'], 0) // The third parameter value will be filled
  // in to blank cells. Its default value is 0.
  var c2 = dk.col(d, 'COL2');
  console.log(c2);
});

//Output:
//[1, 2]


//PLOT ARRAY(S) OF DATA

var chart = new dk.Chart({
  //optional config
  height: 500,
  width: 500,
  xLab: 'x-Axis Label',
  yLab: 'y-Axis Label'
});

chart.addDataSet({
  x: [1, 2, 3],
  y: [4, 5, 6],
  z: [2, 3, 5],
  colors: ['blue', 'green', 'red']
}).addDataSet({
  x: [1, 10],
  y: [2, -1],
  type: 'line'
}).addDataSet({
  x: [10, 5, 1],
  y: [4, 5, 2],
  labels: ["first", "second", "third"]
}).plot();

var dk = require('datakitjs');

//MEAN OF AN ARRAY
dk.mean([1, 2, 3]); //returns 2

//STANDARD DEVIATION AND VARIANCE OF AN ARRAY
dk.sd([1, 2, 3]); //returns 1
dk.vari([1, 2, 3]); //returns 1

//COVARIANCE OF TWO ARRAYS
dk.cov([1, 2, 3], [3, 2, 1]); //returns -1

//SIMPLE LINEAR REGRESSION

var x = [1, 2, 3];
var y = [2, 1, 3];

var model = dk.reg(x, y);

// model.f is a function that returns the estimated y for an input x (estimated via standard OLS regression)
// model.f = function(x) {
//  return (a + b * x);
// };

// model.pts is an array of the estimated y for each element of x
// model.pts = [1.5, 2, 2.5];

// model.endPoints is an object with the coordinates of the boundary points
// model.endPoints = { x1: 1, x2: 3, y1: 1.5, y2: 2.5 };

var dk = require('datakitjs');

//GENERATE AN ARRAY WITH A SEQUENCE OF NUMBERS

dk.seq(1, 5); //returns [1, 2, 3, 4, 5]

dk.seq(0, 1, 0.25); //returns [0, 0.25, 0.5, 0.75, 1]

//GENERATE AN ARRAY WITH REPEATED VALUE

dk.rep(1, 5); //returns [1, 1, 1, 1, 1]

//CHECK IF NUMBERS ARE CLOSE
dk.isclose(0, Math.pow(10, -15)); //returns true

dk.isclose(0, Math.pow(10, -5)); //returns false

//SUM AN ARRAY OF NUMBERS
//uses Kahan summation

dk.sum([1, 2, 3]); //returns 6

//PRODUCT OF AN ARRAY OF NUMBERS
//implementation from 'Accurate Floating Point Product' - Stef Graillat

dk.prod([1, 2, 3]); //returns 6

//MAX AND MIN OF AN ARRAY
var x = [1, 2, 3];
dk.min(x); //returns 1
dk.max(x); //returns 3

var dk = require('datakitjs');

//GET AN ARRAY OF EXPONENTIALLY DISTRIBUTED VALUES

dk.exp(3, 1); //returns [0.3584189321510761, 1.0466439500242446, 0.08887770301056963]


//GET AN ARRAY OF NORMALLY DISTRIBUTED VALUES

dk.norm(3, 0, 1); //returns [-1.709768103193772, 0.23530041388459744, 0.4431320382580479]

//GET AN ARRAY OF UNIFORMLY DISTRIBUTED VALUES

dk.uni(3); //returns [0.30658303829841316, 0.1601463456172496, 0.8538850131444633]