ashenfad · December 15, 2015 18:39
diff --git a/README.md b/README.md
diff --git a/abalone-sex-model.json b/abalone-sex-model.json
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diff --git a/index.html b/index.html
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    .outerRadius(function(d) { return Math.max(0, y(d.y + d.dy)); });

 // Interpolate the scales!
 function arcTween(d) {
  var xd = d3.interpolate(x.domain(), [d.x, d.x + d.dx]),
      yd = d3.interpolate(y.domain(), [d.y, 1]),
      yr = d3.interpolate(y.range(), [d.y ? 20 : 0, radius]);
  return function(d, i) {
    return i
        ? function(t) { return arc(d); }
        : function(t) { x.domain(xd(t)); y.domain(yd(t)).range(yr(t)); return arc(d); };
  };
 }

 function find_minmax(node, attr) {
  if (node.children) {
    minmaxs = node.children.map(function (n) { return find_minmax(n, attr); });
    min = Math.min.apply(null, minmaxs.map(function (mm) {return mm.min}));
    max = Math.max.apply(null, minmaxs.map(function (mm) {return mm.max}));
    return {"min": Math.min(min, node[attr]), "max": Math.max(max, node[attr])};
  } else {
    return {"min": node[attr], "max": node[attr]};
  }
 }

 d3.json("abalone-sex-model.json", function(error, root) {
  var model = root.model;
  var model_type = model.model_fields[root.objective_field].optype == "categorical" ?
               "classification" : "regression";
  var minmaxs = {};
  if (model_type == "classification") {
    minmaxs.confidence = find_minmax(model.root, "confidence");
  } else {
    // Hacky label switch for regression trees
    document.getElementById("cnf").innerHTML = "Expected Error";

    minmaxs.expected_error = find_minmax(model.root, "confidence");
    minmaxs.output = find_minmax(model.root, "output");
  }

  var scale_pred = model_type == "classification" ?
                     d3.scale.category10() :
                     d3.scale.linear().domain([minmaxs.output.min,
                                               minmaxs.output.max])
                                      .range(["#222", "#2ee"]);
  var scale_conf = model_type == "classification" ?
                     d3.scale.linear().domain([minmaxs.confidence.min,
                                               minmaxs.confidence.max])
                                      .range(["#d33", "#3d3"]) :
                     d3.scale.linear().domain([minmaxs.expected_error.max,
                                               minmaxs.expected_error.min])
                                      .range(["#d33", "#3d3"]);
  var scale_split = d3.scale.category20b();

  var color_lookup =
    {"prediction": function(d) { return hover_adjust(d, scale_pred(d.output)); },
     "confidence": function(d) { return hover_adjust(d, scale_conf(d.confidence)); },
     "split": function(d) { return hover_adjust(d, scale_split(d.predicate.field)); } };

  var color_fn = color_lookup["prediction"];

  var path = svg.selectAll("path")
      .data(partition.nodes(root.model.root))
      .enter().append("path")
      .attr("d", arc)
      .style("fill", color_fn)
      .style("stroke", "#fff")
      .on("click", click)
      .on("mouseover", mouseover)
      .on("mouseout", mouseout);

  var click_in_progress = false;

  function click(d) {
    mark_hover(d, false);

    click_in_progress = true;
    path.transition().duration(750).style("fill", color_fn).attrTween("d", arcTween(d));
    setTimeout(function() {click_in_progress = false;}, 750);
  }

  d3.selectAll("input").on("change", change);

  function change() {
    color_fn = color_lookup[this.value];
    path.transition().duration(250).style("fill", color_fn);
  }

  function mouseover(d) {
    var split = d.predicate;
    var split_msg = split.field ? model.model_fields[split.field].name + " " +
                                  split.operator + " " + split.value
                                : "Tree Root";
    var conf_msg = {"classification": "Confidence", "regression": "Expected Error"};

    var hover = d3.select("#hover-info");
    hover.append("div").attr("class", "split-predicate").text(split_msg);
    tbody = hover.append("table").attr("class", "node-info").append("tbody");
    var output = model_type == "classification" ? d.output : parseFloat(d.output.toFixed(3));

    table_add(tbody, "Prediction", output);
    table_add(tbody, conf_msg[model_type], parseFloat(d.confidence.toFixed(3)));
    table_add(tbody, "Count", d.count);

    mark_hover(d, true);
    if (!click_in_progress) {
      path.style("fill", color_fn);
    }

    var summ_doc = d3.select("#summary-info");
    var summaries = summarize(d);
    for (id in summaries) {
      if (!summaries.hasOwnProperty(id)) { continue; }
      var name = model.model_fields[id].name;
      var msg = name;

      fs = summaries[id];
      if (isNum(fs.min)) {
        msg = parseFloat(fs.min.toFixed(3)) + " < " + msg;
      }
      if (isNum(fs.max)) {
        msg += " <= " + parseFloat(fs.max.toFixed(3));
      }
      if (fs.eq) {
        msg += " = " + fs.eq;
      } else if (fs.not_eq) {
        msg += " !=";
        var first = true;
        for (category in fs.not_eq) {
          if (first) {
            first = false;
          } else {
            msg += "|";
          }
          if (!fs.not_eq.hasOwnProperty(category)) { continue; }
          msg += " " + category;
        }
        msg = msg;
      }

      summ_doc.append("div").text(msg);
    }
  }

  function mouseout(d) {
    d3.select("#hover-info").html("");
    d3.select("#summary-info").html("");
    mark_hover(d, false);
    if (!click_in_progress) {
      path.style("fill", color_fn);
    }
  }

  function mark_hover (d, val) {
    if (d.parent) { mark_hover(d.parent, val); };
    d.hover = val;
  }
 });

 d3.select(self.frameElement).style("height", height + "px");

 function isNum(n) {
  return !isNaN(parseFloat(n)) && isFinite(n);
 }

 function summarize (node) {
  var pred = node.predicate;
  if (node.parent) {
    var summary = summarize(node.parent);
    switch(pred.operator) {
      case "<=":
        if (summary[pred.field]) {
          var old_max = summary[pred.field].max;
          max = isNum(old_max) ? Math.min(pred.value, old_max) : pred.value;
          summary[pred.field].max = max;
        } else {
          summary[pred.field] = {"max": pred.value};
        }
        break;
      case ">":
        if (summary[pred.field]) {
          var old_min = summary[pred.field].min;
          min = isNum(old_min) ? Math.max(pred.value, old_min) : pred.value;
          summary[pred.field].min = min;
        } else {
          summary[pred.field] = {"min": pred.value};
        }
        break;
      case "=":
        summary[pred.field] = {"eq": pred.value};
        break;
      case "!=":
        if (!summary[pred.field]) {
          summary[pred.field] = {};
        }
        if (!summary[pred.field].not_eq) {
          summary[pred.field].not_eq = {};
        }
        summary[pred.field].not_eq[pred.value] = true;
        break;
    }
    return summary;
  } else {
    return {};
  }
 }

 function table_add (table, field, val) {
  var row = table.append("tr");
  row.append("td").text(field);
  row.append("td").text(val);
  return row;
 }

 </script>
diff --git a/thumbnail.png b/thumbnail.png
	<!DOCTYPE html>
	<meta charset="utf-8">
	<style>

	body {
	font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
	margin: auto;
	position: relative;
	width: 960px;
	background: #fff;
	}

	#color-controls {
	font: 14px sans-serif;
	position: absolute;
	right: 10px;
	top: 10px;
	padding: 3px;
	}

	#color-controls div {
	padding: 4px;
	}

	#hover-info {
	font: 14px sans-serif;
	position: absolute;
	left: 10px;
	top: 10px;
	}

	#summary-info {
	font: 14px sans-serif;
	position: absolute;
	left: 10px;
	bottom: 10px;
	font: 12px sans-serif;
	}

	#summary-info div {
	padding: 2px;
	}

	.split-predicate {
	font-weight:bold;
	border-bottom: 1px solid #DFDFDF;
	padding: 7px;
	}

	.node-info {
	margin-top: 10px;
	}

	.node-info td {
	padding: 2px 7px 2px;
	}

	</style>
	<body>
	<div id="color-controls">
	<form>
	<div>
	<input type="radio" name="mode" value="prediction" checked \>
	<label>Prediction</label>
	</div>

	<div>
	<input type="radio" name="mode" value="confidence"\>
	<label id="cnf">Confidence</label>
	</div>

	<div>
	<input type="radio" name="mode" value="split"\>
	<label>Split Field</label>
	</div>
	</form>
	</div>
	<div id="hover-info"></div>
	<div id="summary-info"></div>
	</body>

	<script src="http://d3js.org/d3.v3.min.js"></script>
	<script>

	var width = 960,
	height = 600,
	radius = Math.min(width, height) / 2;

	function hover_adjust(d, color) {
	return d.hover ? d3.rgb(color).brighter(0.66) : color;
	}

	var svg = d3.select("body").append("svg")
	.attr("width", width)
	.attr("height", height)
	.append("g")
	.attr("transform", "translate(" + width / 2 + "," + (height / 2 + 0) + ")");

	var partition = d3.layout.partition().value(function(d) { return d.count; });

	var x = d3.scale.linear().range([0, 2 * Math.PI]);
	var y = d3.scale.sqrt().range([0, radius]);

	var arc = d3.svg.arc()
	.startAngle(function(d) { return Math.max(0, Math.min(2 * Math.PI, x(d.x))); })
	.endAngle(function(d) { return Math.max(0, Math.min(2 * Math.PI, x(d.x + d.dx))); })
	.innerRadius(function(d) { return Math.max(0, y(d.y)); })
	.outerRadius(function(d) { return Math.max(0, y(d.y + d.dy)); });

	// Interpolate the scales!
	function arcTween(d) {
	var xd = d3.interpolate(x.domain(), [d.x, d.x + d.dx]),
	yd = d3.interpolate(y.domain(), [d.y, 1]),
	yr = d3.interpolate(y.range(), [d.y ? 20 : 0, radius]);
	return function(d, i) {
	return i
	? function(t) { return arc(d); }
	: function(t) { x.domain(xd(t)); y.domain(yd(t)).range(yr(t)); return arc(d); };
	};
	}

	function find_minmax(node, attr) {
	if (node.children) {
	minmaxs = node.children.map(function (n) { return find_minmax(n, attr); });
	min = Math.min.apply(null, minmaxs.map(function (mm) {return mm.min}));
	max = Math.max.apply(null, minmaxs.map(function (mm) {return mm.max}));
	return {"min": Math.min(min, node[attr]), "max": Math.max(max, node[attr])};
	} else {
	return {"min": node[attr], "max": node[attr]};
	}
	}

	d3.json("abalone-sex-model.json", function(error, root) {
	var model = root.model;
	var model_type = model.model_fields[root.objective_field].optype == "categorical" ?
	"classification" : "regression";
	var minmaxs = {};
	if (model_type == "classification") {
	minmaxs.confidence = find_minmax(model.root, "confidence");
	} else {
	// Hacky label switch for regression trees
	document.getElementById("cnf").innerHTML = "Expected Error";

	minmaxs.expected_error = find_minmax(model.root, "confidence");
	minmaxs.output = find_minmax(model.root, "output");
	}

	var scale_pred = model_type == "classification" ?
	d3.scale.category10() :
	d3.scale.linear().domain([minmaxs.output.min,
	minmaxs.output.max])
	.range(["#222", "#2ee"]);
	var scale_conf = model_type == "classification" ?
	d3.scale.linear().domain([minmaxs.confidence.min,
	minmaxs.confidence.max])
	.range(["#d33", "#3d3"]) :
	d3.scale.linear().domain([minmaxs.expected_error.max,
	minmaxs.expected_error.min])
	.range(["#d33", "#3d3"]);
	var scale_split = d3.scale.category20b();

	var color_lookup =
	{"prediction": function(d) { return hover_adjust(d, scale_pred(d.output)); },
	"confidence": function(d) { return hover_adjust(d, scale_conf(d.confidence)); },
	"split": function(d) { return hover_adjust(d, scale_split(d.predicate.field)); } };

	var color_fn = color_lookup["prediction"];

	var path = svg.selectAll("path")
	.data(partition.nodes(root.model.root))
	.enter().append("path")
	.attr("d", arc)
	.style("fill", color_fn)
	.style("stroke", "#fff")
	.on("click", click)
	.on("mouseover", mouseover)
	.on("mouseout", mouseout);

	var click_in_progress = false;

	function click(d) {
	mark_hover(d, false);

	click_in_progress = true;
	path.transition().duration(750).style("fill", color_fn).attrTween("d", arcTween(d));
	setTimeout(function() {click_in_progress = false;}, 750);
	}

	d3.selectAll("input").on("change", change);

	function change() {
	color_fn = color_lookup[this.value];
	path.transition().duration(250).style("fill", color_fn);
	}

	function mouseover(d) {
	var split = d.predicate;
	var split_msg = split.field ? model.model_fields[split.field].name + " " +
	split.operator + " " + split.value
	: "Tree Root";
	var conf_msg = {"classification": "Confidence", "regression": "Expected Error"};

	var hover = d3.select("#hover-info");
	hover.append("div").attr("class", "split-predicate").text(split_msg);
	tbody = hover.append("table").attr("class", "node-info").append("tbody");
	var output = model_type == "classification" ? d.output : parseFloat(d.output.toFixed(3));

	table_add(tbody, "Prediction", output);
	table_add(tbody, conf_msg[model_type], parseFloat(d.confidence.toFixed(3)));
	table_add(tbody, "Count", d.count);

	mark_hover(d, true);
	if (!click_in_progress) {
	path.style("fill", color_fn);
	}

	var summ_doc = d3.select("#summary-info");
	var summaries = summarize(d);
	for (id in summaries) {
	if (!summaries.hasOwnProperty(id)) { continue; }
	var name = model.model_fields[id].name;
	var msg = name;

	fs = summaries[id];
	if (isNum(fs.min)) {
	msg = parseFloat(fs.min.toFixed(3)) + " < " + msg;
	}
	if (isNum(fs.max)) {
	msg += " <= " + parseFloat(fs.max.toFixed(3));
	}
	if (fs.eq) {
	msg += " = " + fs.eq;
	} else if (fs.not_eq) {
	msg += " !=";
	var first = true;
	for (category in fs.not_eq) {
	if (first) {
	first = false;
	} else {
	msg += "\|";
	}
	if (!fs.not_eq.hasOwnProperty(category)) { continue; }
	msg += " " + category;
	}
	msg = msg;
	}

	summ_doc.append("div").text(msg);
	}
	}

	function mouseout(d) {
	d3.select("#hover-info").html("");
	d3.select("#summary-info").html("");
	mark_hover(d, false);
	if (!click_in_progress) {
	path.style("fill", color_fn);
	}
	}

	function mark_hover (d, val) {
	if (d.parent) { mark_hover(d.parent, val); };
	d.hover = val;
	}
	});

	d3.select(self.frameElement).style("height", height + "px");

	function isNum(n) {
	return !isNaN(parseFloat(n)) && isFinite(n);
	}

	function summarize (node) {
	var pred = node.predicate;
	if (node.parent) {
	var summary = summarize(node.parent);
	switch(pred.operator) {
	case "<=":
	if (summary[pred.field]) {
	var old_max = summary[pred.field].max;
	max = isNum(old_max) ? Math.min(pred.value, old_max) : pred.value;
	summary[pred.field].max = max;
	} else {
	summary[pred.field] = {"max": pred.value};
	}
	break;
	case ">":
	if (summary[pred.field]) {
	var old_min = summary[pred.field].min;
	min = isNum(old_min) ? Math.max(pred.value, old_min) : pred.value;
	summary[pred.field].min = min;
	} else {
	summary[pred.field] = {"min": pred.value};
	}
	break;
	case "=":
	summary[pred.field] = {"eq": pred.value};
	break;
	case "!=":
	if (!summary[pred.field]) {
	summary[pred.field] = {};
	}
	if (!summary[pred.field].not_eq) {
	summary[pred.field].not_eq = {};
	}
	summary[pred.field].not_eq[pred.value] = true;
	break;
	}
	return summary;
	} else {
	return {};
	}
	}

	function table_add (table, field, val) {
	var row = table.append("tr");
	row.append("td").text(field);
	row.append("td").text(val);
	return row;
	}

	</script>