EfratVil/README.md

## README.md

      
    Raw
  

              README.md
            
          
    Compering 2 normal distributions.

  
## index.html
<!DOCTYPE html>
<meta charset="utf-8">
    <style>

        body {
          font: 10px sans-serif;
        }

        .line {
          stroke: #000;
          stroke-width: 1.5px;
        }

        .axis path,
        .axis line {
          fill: none;
          stroke: #000;
          shape-rendering: crispEdges;
        }

    </style>
<body>
    <script src="https://d3js.org/d3.v4.min.js"></script>
    <script src="https://cdn.jsdelivr.net/jstat/latest/jstat.min.js"></script>
<script>

var margin = {top: 20, right: 30, bottom: 30, left: 40},
    width = 960 - margin.left - margin.right,
    height = 500 - margin.top - margin.bottom;

var array1 = Random_normal_Dist(30, 15);
var array2 = Random_normal_Dist(30, 10);

var x = d3.scaleLinear()
            .rangeRound([0, width]);

    //Min q
    var d1 = d3.min(array1, function (d) { return d.q; });
    var d2 = d3.min(array2, function (d) { return d.q; });
    var min_d = d3.min([d1, d2]);

    //Max q
    d1 = d3.max(array1, function (d) { return d.q; });
    d2 = d3.max(array2, function (d) { return d.q; });
    var max_d = d3.max([d1, d2]);

    //Max p
    d1 = d3.max(array1, function (d) { return d.p; });
    d2 = d3.max(array2, function (d) { return d.p; });
    var max_p = d3.max([d1, d2]);

  x.domain([min_d, max_d]).nice;

  var y = d3.scaleLinear()
      .domain([0, max_p])
      .range([height, 0]);

  var svg = d3.select("body").append("svg")
      .attr("width", width + margin.left + margin.right)
      .attr("height", height + margin.top + margin.bottom)
    .append("g")
      .attr("transform", "translate(" + margin.left + "," + margin.top + ")");

  var gX = svg.append("g")
              .attr("class", "x axis")
              .attr("transform", "translate(0," + height + ")")
              .call(d3.axisBottom(x));

  //var gY = svg.append("g")
  //            .attr("class", "y axis")
  //            .call(d3.axisLeft(y));


  var line = d3.line()
      .x(function (d) { return x(d.q); })
      .y(function (d) { return y(d.p); });


  svg.append("path")
      .datum(array1)
      .attr("class", "line")
      .attr("d", line)
      .style("fill", "#fdae61")
      .style("opacity", "0.5");

  svg.append("path")
      .datum(array2)
      .attr("class", "line")
      .attr("d", line)
      .style("fill", "#4393c3")
      .style("opacity", "0.5");


  function Random_normal_Dist(mean, sd) {
      data = [];
      for (var i = mean - 4 * sd; i < mean + 4 * sd; i += 1) {
          q = i
          p = jStat.normal.pdf(i, mean, sd);
          arr = {
              "q": q,
              "p": p
          }
          data.push(arr);
      };
      return data;
  }


</script>

## thumbnail.png

      
    Raw
  

              thumbnail.png
	<!DOCTYPE html>
	<meta charset="utf-8">
	<style>

	body {
	font: 10px sans-serif;
	}

	.line {
	stroke: #000;
	stroke-width: 1.5px;
	}

	.axis path,
	.axis line {
	fill: none;
	stroke: #000;
	shape-rendering: crispEdges;
	}

	</style>
	<body>
	<script src="https://d3js.org/d3.v4.min.js"></script>
	<script src="https://cdn.jsdelivr.net/jstat/latest/jstat.min.js"></script>
	<script>

	var margin = {top: 20, right: 30, bottom: 30, left: 40},
	width = 960 - margin.left - margin.right,
	height = 500 - margin.top - margin.bottom;

	var array1 = Random_normal_Dist(30, 15);
	var array2 = Random_normal_Dist(30, 10);

	var x = d3.scaleLinear()
	.rangeRound([0, width]);

	//Min q
	var d1 = d3.min(array1, function (d) { return d.q; });
	var d2 = d3.min(array2, function (d) { return d.q; });
	var min_d = d3.min([d1, d2]);

	//Max q
	d1 = d3.max(array1, function (d) { return d.q; });
	d2 = d3.max(array2, function (d) { return d.q; });
	var max_d = d3.max([d1, d2]);

	//Max p
	d1 = d3.max(array1, function (d) { return d.p; });
	d2 = d3.max(array2, function (d) { return d.p; });
	var max_p = d3.max([d1, d2]);

	x.domain([min_d, max_d]).nice;

	var y = d3.scaleLinear()
	.domain([0, max_p])
	.range([height, 0]);

	var svg = d3.select("body").append("svg")
	.attr("width", width + margin.left + margin.right)
	.attr("height", height + margin.top + margin.bottom)
	.append("g")
	.attr("transform", "translate(" + margin.left + "," + margin.top + ")");

	var gX = svg.append("g")
	.attr("class", "x axis")
	.attr("transform", "translate(0," + height + ")")
	.call(d3.axisBottom(x));

	//var gY = svg.append("g")
	// .attr("class", "y axis")
	// .call(d3.axisLeft(y));


	var line = d3.line()
	.x(function (d) { return x(d.q); })
	.y(function (d) { return y(d.p); });


	svg.append("path")
	.datum(array1)
	.attr("class", "line")
	.attr("d", line)
	.style("fill", "#fdae61")
	.style("opacity", "0.5");

	svg.append("path")
	.datum(array2)
	.attr("class", "line")
	.attr("d", line)
	.style("fill", "#4393c3")
	.style("opacity", "0.5");


	function Random_normal_Dist(mean, sd) {
	data = [];
	for (var i = mean - 4 * sd; i < mean + 4 * sd; i += 1) {
	q = i
	p = jStat.normal.pdf(i, mean, sd);
	arr = {
	"q": q,
	"p": p
	}
	data.push(arr);
	};
	return data;
	}


	</script>