MNoichl/.block

## .block
license: mit

## README.md

      
    Raw
  

              README.md
            
          
    Method
The 500 most cited or all accessible papers from the following journals where downloaded, and there citation records accessed:
analytical journals:

Mind
Analysis
Philosophical Quarterly
Ethics

continental journals:

Continental Philosophy Review
Journal of Speculative Philosophy
Constellations
Journal of the British Society for Phenomenology

The citation data was stripped to the cited authors. The resulting documents where tokenized - divided into single words. Then it was determined for every paper if it contained any of the found names.


Paper Nr.
Heidegger
Ryle
...


1
1
0
...


2
1
0
...


3
0
1
...


These resulting examples where clustered with a K-means-Algorithm. The Davies-Bouldin-Indexes for this Clustering are shown above. A low index indicates good clustering, which means that the clusters have high internal consistency and are very different to each other So we can say that the hypothesis of two clusters (eg. analytic and continental philosophy) seems not particulary merited (DB = 8.6), expecially when compared to 7 clusters, which yields a DB of 6.92.
forked from MNoichl's block: DB-Indexes for  selected paper-clusters

  
## cereal.csv

          
            k
            DB
            W

            
              2.0
              8.615821506268905
              9.689455603922553

            
              3.0
              8.372683745091003
              9.613802707240781

            
              4.0
              8.060323505815674
              9.560900214038929

            
              5.0
              7.554504049059224
              9.493703031235166

            
              6.0
              7.2756812254733925
              9.447811112043595

            
              7.0
              6.923465652878521
              9.405677164477725

            
              8.0
              7.334561607266986
              9.373500004392408

            
              9.0
              6.940523517981654
              9.351522900176995

            
              10.0
              7.010046258819619
              9.290545797722556

## index.html
<html>
  <head>
    <meta charset="utf-8">
    <title>Visualization</title>
    <link rel="stylesheet" href="scatter.css" charset="utf-8">
        <link href="https://fonts.googleapis.com/css?family=Alegreya|Alegreya+SC|Alegreya+Sans|Alegreya+Sans+SC|Cormorant+Garamond|Cormorant+SC:300,400,500,600,700|EB+Garamond|Fanwood+Text:400,400i|Goudy+Bookletter+1911|IM+Fell+Double+Pica+SC|IM+Fell+French+Canon+SC|IM+Fell+French+Canon:400,400i|IM+Fell+Great+Primer+SC|IM+Fell+Great+Primer:400,400i|Spectral+SC:200,200i,300,300i,400,400i,500,500i,600,600i,700,700i,800,800i|Vollkorn+SC:400,600,700,900&amp;subset=latin-ext" rel="stylesheet">

  </head>
  <body>
    <div id="scatter"></div>

    <input type="button" name="xAxis" value="xAxis">

    <script src="http://d3js.org/d3.v3.min.js" charset="utf-8"></script>
    <script src="http://labratrevenge.com/d3-tip/javascripts/d3.tip.v0.6.3.js"></script>
    <script src="scatter.js" charset="utf-8"></script>
  </body>
</html>

## scatter.css
rect {
  fill: transparent;
  shape-rendering: crispEdges;
}

.axis path,
.axis line {
  fill: none;
  stroke: rgba(0, 0, 0, 0.1);
  shape-rendering: crispEdges;
}


h1 {
  font-family: Alegreya SC, serif;
}

text {
  margin-top: 40pt;
  margin-bottom:5pt;
  text-align: left;
  font-family: 'Alegreya SC', serif;
  font-size: 12pt;
  font-weight: 300;


}
.axisLine {
  fill: none;
  shape-rendering: crispEdges;
  stroke: rgba(0, 0, 0, 0.5);
  stroke-width: 2px;
}

.dot {
  fill-opacity: .8;
}


.d3-tip {
   /* width: 100px;*/
    background-color: #ffffff;
    padding: 3px 12px;
    font-family: serif;
    border: 1px solid #bbbbbb;
    box-shadow: 1px 1px 4px #bbbbbb;
    font-family: EB Garamond, serif;
    text-transform: capitalize;
  background: rgba(255,255,255, 0.6);

}

/*
.d3-tip {
  line-height: 1;
  font-weight: bold;
  padding: 12px;
  background: rgba(0, 0, 0, 0.8);
  color: #fff;
  border-radius: 2px;
}


## scatter.js
var margin = { top: 50, right: 300, bottom: 50, left: 50 },
    outerWidth = 1050,
    outerHeight = 500,
    width = outerWidth - margin.left - margin.right,
    height = outerHeight - margin.top - margin.bottom;

var x = d3.scale.linear()
    .range([0, width]).nice();

var y = d3.scale.linear()
    .range([height, 0]).nice();

var xCat = "k",
    yCat = "DB",
    rCat = "c1",
    colorCat = "cluster";

d3.csv("cereal.csv", function(data) {
  data.forEach(function(d) {
    d.DB = +d.DB;
    d.k = +d.k;
    d["Protein (g)"] = +d["Protein (g)"];
    d["Serving Size Weight"] = +d["Serving Size Weight"];
    d.Sodium = +d.Sodium;
    d.Sugars = +d.Sugars;
    d["Vitamins and Minerals"] = +d["Vitamins and Minerals"];
  });

  var xMax = d3.max(data, function(d) { return d[xCat]; }) * 1.05,
      xMin = d3.min(data, function(d) { return d[xCat]; }),
      xMin = xMin > 0 ? 0 : xMin,
      yMax = d3.max(data, function(d) { return d[yCat]; }) * 1.05,
      yMin = d3.min(data, function(d) { return d[yCat]; }) / 1.05;

  x.domain([xMin, xMax]);
  y.domain([yMin, yMax]);

  var xAxis = d3.svg.axis()
      .scale(x)
      .orient("bottom")
      .tickSize(-height);

  var yAxis = d3.svg.axis()
      .scale(y)
      .orient("left")
      .tickSize(-width);

  var color = d3.scale.category20();

  var tip = d3.tip()
      .attr("class", "d3-tip")
      .offset([-10, 0])
      .html(function(d) {
        return xCat + ": " + d[xCat] + "<br>" + yCat + ": " + d[yCat];
      });

  var zoomBeh = d3.behavior.zoom()
      .x(x)
      .y(y)
      .scaleExtent([0, 500])
      .on("zoom", zoom);

  var svg = d3.select("#scatter")
    .append("svg")
      .attr("width", outerWidth)
      .attr("height", outerHeight)
    .append("g")
      .attr("transform", "translate(" + margin.left + "," + margin.top + ")")
      .call(zoomBeh);

  svg.call(tip);

  svg.append("rect")
      .attr("width", width)
      .attr("height", height);

  svg.append("g")
      .classed("x axis", true)
      .attr("transform", "translate(0," + height + ")")
      .call(xAxis)
    .append("text")
      .classed("label", true)
      .attr("x", width)
      .attr("y", margin.bottom - 10)
      .style("text-anchor", "end")
      .text(xCat);

  svg.append("g")
      .classed("y axis", true)
      .call(yAxis)
    .append("text")
      .classed("label", true)
      .attr("transform", "rotate(-90)")
      .attr("y", -margin.left)
      .attr("dy", ".71em")
      .style("text-anchor", "end")
      .text(yCat);

  var objects = svg.append("svg")
      .classed("objects", true)
      .attr("width", width)
      .attr("height", height);

  objects.append("svg:line")
      .classed("axisLine hAxisLine", true)
      .attr("x1", 0)
      .attr("y1", 0)
      .attr("x2", width)
      .attr("y2", 0)
      .attr("transform", "translate(0," + height + ")");

  objects.append("svg:line")
      .classed("axisLine vAxisLine", true)
      .attr("x1", 0)
      .attr("y1", 0)
      .attr("x2", 0)
      .attr("y2", height);

  objects.selectAll(".dot")
      .data(data)
    .enter().append("circle")
      .classed("dot", true)
      .attr("r", 3)//function (d) { return 6 * Math.sqrt(d[rCat] / Math.PI); }
      .attr("transform", transform)
      .style("fill", function(d) { return color(d[colorCat]); })
      .on("mouseover", tip.show)
      .on("mouseout", tip.hide);

  var legend = svg.selectAll(".legend")
      .data(color.domain())
    .enter().append("g")
      .classed("legend", true)
      .attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });
/*
  legend.append("circle")
      .attr("r", 3.5)
      .attr("cx", width + 20)
      .attr("fill", color);

  legend.append("text")
      .attr("x", width + 26)
      .attr("dy", ".35em")
      .text(function(d) { return d; });
*/
  d3.select("input").on("click", change);

  function change() {
    xCat = "Carbs";
    xMax = d3.max(data, function(d) { return d[xCat]; });
    xMin = d3.min(data, function(d) { return d[xCat]; });

    zoomBeh.x(x.domain([xMin, xMax])).y(y.domain([yMin, yMax]));

    var svg = d3.select("#scatter").transition();

    svg.select(".x.axis").duration(750).call(xAxis).select(".label").text(xCat);

    objects.selectAll(".dot").transition().duration(1000).attr("transform", transform);
  }

  function zoom() {
    svg.select(".x.axis").call(xAxis);
    svg.select(".y.axis").call(yAxis);

    svg.selectAll(".dot")
        .attr("transform", transform);
  }

  function transform(d) {
    return "translate(" + x(d[xCat]) + "," + y(d[yCat]) + ")";
  }
});
k	DB	W
2.0	8.615821506268905	9.689455603922553
3.0	8.372683745091003	9.613802707240781
4.0	8.060323505815674	9.560900214038929
5.0	7.554504049059224	9.493703031235166
6.0	7.2756812254733925	9.447811112043595
7.0	6.923465652878521	9.405677164477725
8.0	7.334561607266986	9.373500004392408
9.0	6.940523517981654	9.351522900176995
10.0	7.010046258819619	9.290545797722556
	<html>
	<head>
	<meta charset="utf-8">
	<title>Visualization</title>
	<link rel="stylesheet" href="scatter.css" charset="utf-8">
	<link href="https://fonts.googleapis.com/css?family=Alegreya\|Alegreya+SC\|Alegreya+Sans\|Alegreya+Sans+SC\|Cormorant+Garamond\|Cormorant+SC:300,400,500,600,700\|EB+Garamond\|Fanwood+Text:400,400i\|Goudy+Bookletter+1911\|IM+Fell+Double+Pica+SC\|IM+Fell+French+Canon+SC\|IM+Fell+French+Canon:400,400i\|IM+Fell+Great+Primer+SC\|IM+Fell+Great+Primer:400,400i\|Spectral+SC:200,200i,300,300i,400,400i,500,500i,600,600i,700,700i,800,800i\|Vollkorn+SC:400,600,700,900&subset=latin-ext" rel="stylesheet">

	</head>
	<body>
	<div id="scatter"></div>

	<input type="button" name="xAxis" value="xAxis">

	<script src="http://d3js.org/d3.v3.min.js" charset="utf-8"></script>
	<script src="http://labratrevenge.com/d3-tip/javascripts/d3.tip.v0.6.3.js"></script>
	<script src="scatter.js" charset="utf-8"></script>
	</body>
	</html>
	rect {
	fill: transparent;
	shape-rendering: crispEdges;
	}

	.axis path,
	.axis line {
	fill: none;
	stroke: rgba(0, 0, 0, 0.1);
	shape-rendering: crispEdges;
	}


	h1 {
	font-family: Alegreya SC, serif;
	}

	text {
	margin-top: 40pt;
	margin-bottom:5pt;
	text-align: left;
	font-family: 'Alegreya SC', serif;
	font-size: 12pt;
	font-weight: 300;


	}
	.axisLine {
	fill: none;
	shape-rendering: crispEdges;
	stroke: rgba(0, 0, 0, 0.5);
	stroke-width: 2px;
	}

	.dot {
	fill-opacity: .8;
	}




	.d3-tip {
	/* width: 100px;*/
	background-color: #ffffff;
	padding: 3px 12px;
	font-family: serif;
	border: 1px solid #bbbbbb;
	box-shadow: 1px 1px 4px #bbbbbb;
	font-family: EB Garamond, serif;
	text-transform: capitalize;
	background: rgba(255,255,255, 0.6);

	}

	/*
	.d3-tip {
	line-height: 1;
	font-weight: bold;
	padding: 12px;
	background: rgba(0, 0, 0, 0.8);
	color: #fff;
	border-radius: 2px;
	}
	var margin = { top: 50, right: 300, bottom: 50, left: 50 },
	outerWidth = 1050,
	outerHeight = 500,
	width = outerWidth - margin.left - margin.right,
	height = outerHeight - margin.top - margin.bottom;

	var x = d3.scale.linear()
	.range([0, width]).nice();

	var y = d3.scale.linear()
	.range([height, 0]).nice();

	var xCat = "k",
	yCat = "DB",
	rCat = "c1",
	colorCat = "cluster";

	d3.csv("cereal.csv", function(data) {
	data.forEach(function(d) {
	d.DB = +d.DB;
	d.k = +d.k;
	d["Protein (g)"] = +d["Protein (g)"];
	d["Serving Size Weight"] = +d["Serving Size Weight"];
	d.Sodium = +d.Sodium;
	d.Sugars = +d.Sugars;
	d["Vitamins and Minerals"] = +d["Vitamins and Minerals"];
	});

	var xMax = d3.max(data, function(d) { return d[xCat]; }) * 1.05,
	xMin = d3.min(data, function(d) { return d[xCat]; }),
	xMin = xMin > 0 ? 0 : xMin,
	yMax = d3.max(data, function(d) { return d[yCat]; }) * 1.05,
	yMin = d3.min(data, function(d) { return d[yCat]; }) / 1.05;

	x.domain([xMin, xMax]);
	y.domain([yMin, yMax]);

	var xAxis = d3.svg.axis()
	.scale(x)
	.orient("bottom")
	.tickSize(-height);

	var yAxis = d3.svg.axis()
	.scale(y)
	.orient("left")
	.tickSize(-width);

	var color = d3.scale.category20();

	var tip = d3.tip()
	.attr("class", "d3-tip")
	.offset([-10, 0])
	.html(function(d) {
	return xCat + ": " + d[xCat] + "<br>" + yCat + ": " + d[yCat];
	});

	var zoomBeh = d3.behavior.zoom()
	.x(x)
	.y(y)
	.scaleExtent([0, 500])
	.on("zoom", zoom);

	var svg = d3.select("#scatter")
	.append("svg")
	.attr("width", outerWidth)
	.attr("height", outerHeight)
	.append("g")
	.attr("transform", "translate(" + margin.left + "," + margin.top + ")")
	.call(zoomBeh);

	svg.call(tip);

	svg.append("rect")
	.attr("width", width)
	.attr("height", height);

	svg.append("g")
	.classed("x axis", true)
	.attr("transform", "translate(0," + height + ")")
	.call(xAxis)
	.append("text")
	.classed("label", true)
	.attr("x", width)
	.attr("y", margin.bottom - 10)
	.style("text-anchor", "end")
	.text(xCat);

	svg.append("g")
	.classed("y axis", true)
	.call(yAxis)
	.append("text")
	.classed("label", true)
	.attr("transform", "rotate(-90)")
	.attr("y", -margin.left)
	.attr("dy", ".71em")
	.style("text-anchor", "end")
	.text(yCat);

	var objects = svg.append("svg")
	.classed("objects", true)
	.attr("width", width)
	.attr("height", height);

	objects.append("svg:line")
	.classed("axisLine hAxisLine", true)
	.attr("x1", 0)
	.attr("y1", 0)
	.attr("x2", width)
	.attr("y2", 0)
	.attr("transform", "translate(0," + height + ")");

	objects.append("svg:line")
	.classed("axisLine vAxisLine", true)
	.attr("x1", 0)
	.attr("y1", 0)
	.attr("x2", 0)
	.attr("y2", height);

	objects.selectAll(".dot")
	.data(data)
	.enter().append("circle")
	.classed("dot", true)
	.attr("r", 3)//function (d) { return 6 * Math.sqrt(d[rCat] / Math.PI); }
	.attr("transform", transform)
	.style("fill", function(d) { return color(d[colorCat]); })
	.on("mouseover", tip.show)
	.on("mouseout", tip.hide);

	var legend = svg.selectAll(".legend")
	.data(color.domain())
	.enter().append("g")
	.classed("legend", true)
	.attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });
	/*
	legend.append("circle")
	.attr("r", 3.5)
	.attr("cx", width + 20)
	.attr("fill", color);

	legend.append("text")
	.attr("x", width + 26)
	.attr("dy", ".35em")
	.text(function(d) { return d; });
	*/
	d3.select("input").on("click", change);

	function change() {
	xCat = "Carbs";
	xMax = d3.max(data, function(d) { return d[xCat]; });
	xMin = d3.min(data, function(d) { return d[xCat]; });

	zoomBeh.x(x.domain([xMin, xMax])).y(y.domain([yMin, yMax]));

	var svg = d3.select("#scatter").transition();

	svg.select(".x.axis").duration(750).call(xAxis).select(".label").text(xCat);

	objects.selectAll(".dot").transition().duration(1000).attr("transform", transform);
	}

	function zoom() {
	svg.select(".x.axis").call(xAxis);
	svg.select(".y.axis").call(yAxis);

	svg.selectAll(".dot")
	.attr("transform", transform);
	}

	function transform(d) {
	return "translate(" + x(d[xCat]) + "," + y(d[yCat]) + ")";
	}
	});