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aficionado/53fcdf440af5e86c5f005265.json

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53fcdf440af5e86c5f005265.json
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0.433, 22, "false"], [2, 175, 88, 0, 0, 22.9, 0.326, 22, "false"], [2, 92, 52, 0, 0, 30.1, 0.141, 22, "false"], [3, 130, 78, 23, 79, 28.4, 0.323, 34, "true"], [8, 120, 86, 0, 0, 28.4, 0.259, 22, "true"], [2, 174, 88, 37, 120, 44.5, 0.646, 24, "true"], [2, 106, 56, 27, 165, 29.0, 0.426, 22, "false"], [2, 105, 75, 0, 0, 23.3, 0.56, 53, "false"], [4, 95, 60, 32, 0, 35.4, 0.284, 28, "false"], [0, 126, 86, 27, 120, 27.4, 0.515, 21, "false"], [8, 65, 72, 23, 0, 32.0, 0.6, 42, "false"], [2, 99, 60, 17, 160, 36.6, 0.453, 21, "false"], [1, 102, 74, 0, 0, 39.5, 0.293, 42, "true"], [11, 120, 80, 37, 150, 42.3, 0.785, 48, "true"], [3, 102, 44, 20, 94, 30.8, 0.4, 26, "false"], [1, 109, 58, 18, 116, 28.5, 0.219, 22, "false"], [9, 140, 94, 0, 0, 32.7, 0.734, 45, "true"], [13, 153, 88, 37, 140, 40.6, 1.174, 39, "false"], [12, 100, 84, 33, 105, 30.0, 0.488, 46, "false"], [1, 147, 94, 41, 0, 49.3, 0.358, 27, "true"], [1, 81, 74, 41, 57, 46.3, 1.096, 32, "false"], [3, 187, 70, 22, 200, 36.4, 0.408, 36, "true"], [6, 162, 62, 0, 0, 24.3, 0.178, 50, "true"], [4, 136, 70, 0, 0, 31.2, 1.182, 22, "true"], [1, 121, 78, 39, 74, 39.0, 0.261, 28, "false"], [3, 108, 62, 24, 0, 26.0, 0.223, 25, "false"], [0, 181, 88, 44, 510, 43.3, 0.222, 26, "true"], [8, 154, 78, 32, 0, 32.4, 0.443, 45, "true"], [1, 128, 88, 39, 110, 36.5, 1.057, 37, "true"], [7, 137, 90, 41, 0, 32.0, 0.391, 39, "false"], [0, 123, 72, 0, 0, 36.3, 0.258, 52, "true"], [1, 106, 76, 0, 0, 37.5, 0.197, 26, "false"], [6, 190, 92, 0, 0, 35.5, 0.278, 66, "true"], [2, 88, 58, 26, 16, 28.4, 0.766, 22, "false"], [9, 170, 74, 31, 0, 44.0, 0.403, 43, "true"], [9, 89, 62, 0, 0, 22.5, 0.142, 33, "false"], [10, 101, 76, 48, 180, 32.9, 0.171, 63, "false"], [2, 122, 70, 27, 0, 36.8, 0.34, 27, "false"], [5, 121, 72, 23, 112, 26.2, 0.245, 30, "false"], [1, 126, 60, 0, 0, 30.1, 0.349, 47, "true"], [1, 93, 70, 31, 0, 30.4, 0.315, 23, "false"]]}
Raw
README.md

Dynamic scatterplot of the a sample from dataset 53fcdf440af5e86c5f005265

Controls:

  • Left click to choose X-axis.
  • Right click to choose Y-axis.
  • Alt + right click to choose color axis.
  • Repeat click (left, right, or alt) for log scale.
  • Hover over a point to see all field values.
  • Click a multi-point (larger circle) to cycle through values.
  • Drag box to zoom in.
  • Click on empty area to zoom out.
  • Choose plot granularity with keys 1-9 (1 is the default).
Raw
dataset-gen.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
##############################################################################
# Copyright (c) 2014 BigML, Inc
#
# Permission is hereby granted, free of charge, to any person obtaining
# a copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish,
# distribute, sublicense, and/or sell copies of the Software, and to
# permit persons to whom the Software is furnished to do so, subject to
# the following conditions:
#
# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
# LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
# OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
# WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
##############################################################################
import sys
import argparse
import csv
import json
from bigml.api import BigML
DATATYPE = {
'int8': int,
'int16': int,
'double': float,
'string': str}
def main(args=sys.argv[1:]):
"""Parses command-line parameters and calls the actual main function.
"""
parser = argparse.ArgumentParser(
description="Generates Dynamic Scatterplot",
epilog="BigML, Inc")
# dataset
parser.add_argument('--dataset',
required=True,
action='store',
dest='dataset',
help="dataset/id")
args = parser.parse_args(args)
api = BigML()
dataset = api.get_dataset(args.dataset)
api.ok(dataset)
fields = dataset['object']['fields']
field_list = []
for k,v in fields.iteritems():
v['id'] = k
field_list.append(v)
fields = sorted(field_list, key=lambda field: field['order'])
before, sep, dataset_id = args.dataset.rpartition('dataset/')
csvfilename = dataset_id + '.csv'
jsonfilename = dataset_id + '.json'
csvfilename = api.download_dataset(args.dataset, csvfilename)
csvfile = open(csvfilename, 'r')
reader = csv.reader(csvfile)
headers = reader.next()
rows = []
for row in reader:
for i in range(len(row)):
row[i] = DATATYPE[fields[i]['datatype']](row[i])
rows.append(row)
dataset = {'fields': fields, 'rows': rows}
jsonfile = open(jsonfilename, 'w')
json.dump(dataset, jsonfile)
if __name__ == "__main__":
main()
Raw
index.html
</script>
<!DOCTYPE html>
<meta charset="utf-8">
<style>
.domain {
stroke: #ddd;
stoke-width: 1px;
fill: none;
}
.tick line {
stroke: #ddd;
stroke-dasharray: 3,3;
}
.field {
cursor: pointer;
-moz-user-select: none;
-khtml-user-select: none;
-webkit-user-select: none;
-ms-user-select: none;
user-select: none;
}
.brush .extent {
stroke: #fff;
fill-opacity: .125;
shape-rendering: crispEdges;
}
svg {
-webkit-user-select: none; /* webkit (safari, chrome) browsers */
-moz-user-select: none; /* mozilla browsers */
-khtml-user-select: none; /* webkit (konqueror) browsers */
-ms-user-select: none; /* IE10+ */
}
.field-marker {
}
</style>
<body oncontextmenu="return false;">
<script src="http://d3js.org/d3.v3.min.js"></script>
<script>
function getParam(key) {
if(key=(new RegExp('[?&]'+encodeURIComponent(key)+'=([^&]*)'))
.exec(location.search))
return decodeURIComponent(key[1]);
}
function setParam(key, value) {
key = encodeURI(key); value = encodeURI(value);
var s = document.location.search;
var kvp = key+"="+value;
var r = new RegExp("(&|\\?)"+key+"=[^\&]*");
s = s.replace(r,"$1"+kvp);
if(!RegExp.$1) {s += (s.length>0 ? '&' : '?') + kvp;};
window.history.replaceState({}, "", s);
}
function removeParam(key) {
var sourceURL = document.location.search;
var rtn = sourceURL.split("?")[0],
param,
params_arr = [],
queryString = (sourceURL.indexOf("?") !== -1) ? sourceURL.split("?")[1] : "";
if (queryString !== "") {
params_arr = queryString.split("&");
for (var i = params_arr.length - 1; i >= 0; i -= 1) {
param = params_arr[i].split("=")[0];
if (param === key) {
params_arr.splice(i, 1);
}
}
rtn = rtn + "?" + params_arr.join("&");
}
window.history.replaceState({}, "", rtn);
}
var margin = {top: 20, right: 20, bottom: 20, left: 20},
width = 1000 - margin.left - margin.right,
height = 640 - margin.bottom - margin.top;
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 defs = d3.select("svg").append("defs");
d3.json("53fcdf440af5e86c5f005265.json", function(error, data) {
var fields = data.fields;
var rows = data.rows;
var shows;
var buffer = width / 20;
var field_size = width / 4;
var right_fields = 250;
var plotWidth = width - 2 * buffer - right_fields;
var plotHeight = 0.75 * height;
resetConstraints();
function resetConstraints() {
for (var i = 0; i < fields.length; i++) {
fields[i].constraint = false;
}
shows = [];
for (var i = 0; i < rows.length; i++) {
shows.push(true);
}
evalConstraints();
}
function evalConstraints() {
var visiblePoints = 0;
for (var i = 0; i < rows.length; i++) {
var show = true;
for (var j = 0; j < fields.length && show; j++) {
var field = fields[j];
if (field.constraint) {
var val = rows[i][j];
if ((field.optype == "numeric" &&
(val < field.minConstraint || val > field.maxConstraint)) ||
(field.optype == "categorical" && !(val in field.catConstraint))) {
show = false;
}
}
}
if (show) visiblePoints += 1;
shows[i] = show;
}
if (visiblePoints == 0) {
resetConstraints();
} else {
r = Math.pow((6 * Math.min(plotWidth, plotHeight)) / Math.min(visiblePoints, 1024), 0.5);
}
}
var brushX = d3.scale.identity().domain([buffer, plotWidth]),
brushY = d3.scale.identity().domain([0, plotHeight]);
var brushExtent;
var brush = d3.svg.brush()
.x(brushX)
.y(brushY)
.on("brush", brushed)
.on("brushend", brushended);
svg.append("g")
.attr("class", "brush")
.call(brush)
.call(brush.event);
function brushed() {
brushExtent = brush.extent();
}
function brushended() {
var validConstraint = true;
if (!d3.event.sourceEvent) return; // only transition after input
if (fields[x].optype == "numeric") {
fields[x].minConstraint = xScale.invert(brushExtent[0][0]);
fields[x].maxConstraint = xScale.invert(brushExtent[1][0]);
} else {
var cats = fields[x].cats;
var selected = {};
for (var i = 0; i < cats.length; i++) {
var val = xScale(cats[i]);
if (val >= brushExtent[0][0] && val <= brushExtent[1][0]) {
selected[cats[i]] = true;
}
}
fields[x].catConstraint = selected;
}
if (fields[y].optype == "numeric") {
fields[y].minConstraint = yScale.invert(brushExtent[1][1]);
fields[y].maxConstraint = yScale.invert(brushExtent[0][1]);
} else {
var cats = fields[y].cats;
var selected = {};
for (var i = 0; i < cats.length; i++) {
var val = yScale(cats[i]);
if (val >= brushExtent[0][1] && val <= brushExtent[1][1]) {
selected[cats[i]] = true;
}
}
if (selected.length == 0) {
validConstraint = false;
}
fields[y].catConstraint = selected;
}
d3.select(this).call(brush.extent([[0, 0], [0, 0]]));
if (validConstraint) {
fields[x].constraint = true;
fields[y].constraint = true;
evalConstraints();
updateForClick();
} else {
fields[x].constraint = false;
fields[y].constraint = false;
}
}
var maxNameChars = 0;
for (var i = 0; i < fields.length; i++) {
maxNameChars = Math.max(maxNameChars, fields[i].name.length);
}
var valueOffset = 9 * maxNameChars;
for (var i = 0; i < fields.length; i++) {
fields[i].constraint = false;
makeField(fields[i], i);
calcRange(i);
}
var hintY = i * 28;
var hintX = width - right_fields - buffer;
hint = svg.append("g").attr("class", "hint").style("font-size","12px");
hint.append("text")
.attr("transform", "translate(" + hintX + "," + (hintY + 20) + ")")
.text("Left click --> Set X Axis");
hint.append("text")
.attr("transform", "translate(" + hintX + "," + (hintY + 35) + ")")
.text("Right click --> Set Y Axis");
hint.append("text")
.attr("transform", "translate(" + hintX + "," + (hintY + 50) + ")")
.text("Alt + left click --> Set Color");
var fcX = width - right_fields - buffer + valueOffset;
var fcY = -5;
svg.append("g").attr("class", "field-counter").append("text")
.attr("transform", "translate(" + fcX + "," + fcY + ")");
var gx, gy;
var xAxis, yAxis;
var xScale;
var yScale;
var uniqueMap;
var xMap;
var yMap;
var colorMap;
var colorFn;
var currentRow = null;
var currentIds;
var x = getParam("x");
var y = getParam("y");
var c = getParam("c");
if (x == null) x = 4;
if (y == null) y = 1;
if (c == null) c = fields.length - 1;
setParam("x", x);
setParam("y", y);
setParam("c", c);
var xLogMode = getParam("xLog");
var yLogMode = getParam("yLog");
var cLogMode = getParam("cLog");
if (xLogMode == null) xLogMode = false;
if (yLogMode == null) yLogMode = false;
if (cLogMode == null) cLogMode = false;
var granularity = getParam("g");
if (granularity == null) granularity = 1;
var pointIndex = 0;
var r;
makeAxis();
makePoints();
updateForClick();
function genKey(row) {
var xVal, yVal;
var g = 1 + ((granularity - 1) * 5);
if (fields[x].optype == "numeric") {
xVal = Math.round(xScale(row[x]) / g) * g;
} else {
xVal = row[x];
}
if (fields[y].optype == "numeric") {
yVal = Math.round(yScale(row[y]) / g) * g;
} else {
yVal = row[y];
}
return xVal.toString() + "," + yVal.toString();
}
d3.select("body").on("keydown", keydown);
function keydown() {
var needUpdate = true;
var lastKeyDown = d3.event.keyCode;
if (lastKeyDown >= 49 && lastKeyDown <= 57) {
granularity = lastKeyDown - 48;
if (granularity == 1) {
removeParam("g");
} else {
setParam("g", granularity);
}
updateForClick();
}
}
function updateForClick() {
updateScales();
updateUniqueMap();
updateColorFn();
updatePoints();
updateFieldMarkers();
updateAxis();
}
function makeField(field, index) {
var x_loc = width - right_fields - buffer;
var y_loc = 20 + index * 28;
var field_text = svg.append("g")
.attr("class", "field");
field_text.append("text")
.attr("class", "field")
.attr("transform", "translate(" + x_loc + "," + y_loc + ")")
.on("click", function() {
if (d3.event.altKey) {
if (c == index && fields[c].optype == "numeric") {
cLogMode = !cLogMode;
} else {
cLogMode = false;
}
if (cLogMode == true) {
setParam("cLog", true);
} else {
removeParam("cLog");
}
c = index;
setParam("c", index);
} else {
if (x == index && fields[x].optype == "numeric") {
xLogMode = !xLogMode;
} else {
xLogMode = false;
}
if (xLogMode == true) {
setParam("xLog", true);
} else {
removeParam("xLog");
}
x = index;
setParam("x", index);
}
updateForClick();
})
.on("contextmenu", function() {
if (y == index && fields[y].optype == "numeric") {
yLogMode = !yLogMode;
} else {
yLogMode = false;
}
if (yLogMode == true) {
setParam("yLog", true);
} else {
removeParam("yLog");
}
y = index;
setParam("y", index);
updateForClick();
})
.text(field.name);
svg.append("g")
.append("text")
.attr("class", "field-value")
.attr("transform", "translate(" + (valueOffset + x_loc) + "," + y_loc + ")");
svg.append("g")
.append("text")
.attr("class", "field-marker")
.attr("transform", "translate(" + (-6 + x_loc) + "," + y_loc + ")")
.style("text-anchor", "end")
.text("");
}
function makeAxis() {
gy = svg.append("g")
.attr("class", "y-axis")
.attr("transform", "translate(" + buffer + "," + 0 + ")");
gx = svg.append("g")
.attr("class", "x-axis")
.attr("transform", "translate(" + 0 + "," + plotHeight + ")");
}
function updateAxis() {
var currentY = gy.transition()
.duration(700)
.call(yAxis);
if (fields[y].optype == "categorical") {
currentY.selectAll("text")
.attr("y", 10)
.attr("x", 2)
.style("fill", "#999")
.style("font-size", "13")
.style("text-anchor", "start");
}
var currentX = gx.transition()
.duration(700)
.call(xAxis);
if (fields[x].optype == "categorical") { // && fields[x].cats.length > 4) {
currentX.selectAll("text")
.attr("y", 5)
.attr("x", 2)
.attr("transform", "rotate(-90)")
.style("fill", "#999")
.style("font-size", "13")
.style("text-anchor", "start");
}
}
function updateFieldMarkers() {
var ids = Array.apply(null, Array(fields.length)).map(function (_, i) {return i;});
svg.selectAll(".field-marker")
.data(ids)
.text(function(d) {
var marker = "";
if (d == x) {
if (xLogMode) {
marker += "x";
} else {
marker += "X";
}
}
if (d == y) {
if (yLogMode) {
marker += "y";
} else {
marker += "Y";
}
}
if (d == c) {
if (cLogMode) {
marker += "c";
} else {
marker += "C";
}
}
if (marker != "") { marker += ":"};
return marker;
})
}
function updateFieldValues() {
var ids = Array.apply(null, Array(fields.length)).map(function (_, i) {return i;});
var currentRow;
if (currentIds != null) {
currentRow = rows[currentIds[pointIndex % currentIds.length]];
}
svg.selectAll(".field-value")
.data(ids)
.text(function(d) {
var val = "";
if (currentRow != null) {
val += currentRow[d].toString();
}
return val;
});
svg.select(".field-counter").select("text")
.text(function(d) {
var str = "";
if (currentIds != null && currentIds.length > 1) {
str += (1 + pointIndex % currentIds.length) + " of " + currentIds.length;
}
return str;
});
}
function updateUniqueMap() {
uniqueMap = {};
for (var i = 0; i < rows.length; i++) {
if (shows[i]) {
var key = genKey(rows[i]);
if (key in uniqueMap) {
uniqueMap[key].push(i);
} else {
uniqueMap[key] = [i];
}
}
}
colorMap = {};
xMap = {};
yMap = {};
for (var key in uniqueMap) {
var ids = uniqueMap[key];
if (ids.length > 1) {
if (fields[x].optype == "numeric") {
var sum = 0;
for (var j = 0; j < ids.length; j++) {
sum += rows[ids[j]][x];
}
xMap[key] = sum / ids.length;
} else {
xMap[key] = rows[ids[0]][x];
}
if (fields[y].optype == "numeric") {
var sum = 0;
for (var j = 0; j < ids.length; j++) {
sum += rows[ids[j]][y];
}
yMap[key] = sum / ids.length;
} else {
yMap[key] = rows[ids[0]][y];
}
if (fields[c].optype == "numeric") {
var sum = 0;
for (var j = 0; j < ids.length; j++) {
sum += rows[ids[j]][c];
}
colorMap[key] = sum / ids.length;
} else {
var cat_counts = {};
for (var j = 0; j < ids.length; j++) {
var cat = rows[ids[j]][c];
if (cat in cat_counts) {
cat_counts[cat] = cat_counts[cat] + 1;
} else {
cat_counts[cat] = 1;
}
}
var max_count = 0;
var max_cat;
for (cat in cat_counts) {
if (cat_counts[cat] > max_count) {
max_count = cat_counts[cat];
max_cat = cat;
}
}
colorMap[key] = max_cat;
if (rows[ids[0]][c] != max_cat) {
for (var j = 0; j < ids.length; j++) {
if (rows[ids[j]][c] == max_cat) {
var temp = ids[0];
ids[0] = ids[j];
ids[j] = temp;
break;
}
}
}
}
} else {
colorMap[key] = rows[ids[0]][c];
xMap[key] = rows[ids[0]][x];
yMap[key] = rows[ids[0]][y];
}
}
}
function updateColorFn() {
if (fields[c].optype == "numeric") {
if (cLogMode && fields[c].min > 0) {
colorFn = d3.scale.log()
.domain([fields[c].min, fields[c].max])
.range(["#3f3", "#f55"])
} else {
if (cLogMode) removeParam("cLog");
colorFn = d3.scale.linear()
.domain([fields[c].min, fields[c].max])
.range(["#3f3", "#f55"])
}
} else {
if (fields[c].cats.length <= 10) {
colorFn = d3.scale.category10().domain(fields[c].cats);
} else {
colorFn = d3.scale.category20().domain(fields[c].cats);
}
}
}
function calcRange(col) {
if (fields[col].optype == "numeric") {
var min = rows[0][col];
var max = rows[0][col];
for (var i = 0; i < rows.length; i++) {
min = Math.min(min, rows[i][col]);
max = Math.max(max, rows[i][col]);
}
fields[col].min = min;
fields[col].max = max;
} else {
var categories = {};
for (var i = 0; i < rows.length; i++) {
var val = rows[i][col];
if (val == null || val == "") {
val = "?";
rows[i][col] = val;
}
categories[val] = true;
}
var finalCats = [];
for (var cat in categories) {
finalCats.push(cat);
}
fields[col].cats = finalCats.sort();
}
}
function updateScale(col, rangeMin, rangeMax, isX) {
if (fields[col].optype == "numeric") {
var firstIndex;
for (firstIndex = 0; firstIndex < shows.length; firstIndex++) {
if (shows[firstIndex]) {
break;
}
}
var min = rows[firstIndex][col];
var max = rows[firstIndex][col];
var uniques = {};
var uniqueCount = 0;
for (var i = 0; i < rows.length; i++) {
if (shows[i]) {
var key = rows[i][col].toString();
if (!(key in uniques)) {
uniques[key] = true;
uniqueCount += 1;
}
min = Math.min(min, rows[i][col]);
max = Math.max(max, rows[i][col]);
}
}
if (min == max) {
var buf = (fields[col].max - fields[col].min) / 100;
if (buf == 0) {
buf = 0.1;
}
min -= buf;
max += buf;
}
if (min > 0 && ((col == x && xLogMode && isX) || (col == y && yLogMode && !isX))) {
return d3.scale.log()
.range([rangeMin, rangeMax])
.domain([min, max]);
} else {
if (min <= 0 && ((col == x && xLogMode && isX) || (col == y && yLogMode && !isX))) {
if (isX) {
xLogMode = false;
removeParam("xLog");
} else {
yLogMode = false;
removeParam("yLog");
}
}
var diff = max - min;
if (uniqueCount > 4) {
max += diff / 30;
min -= diff / 30;
} else {
max += diff / 5;
min -= diff / 5;
}
return d3.scale.linear()
.range([rangeMin, rangeMax])
.domain([min, max]);
}
} else {
if (isX) {
xLogMode = false;
} else {
yLogMode = false;
}
var categories = {};
for (var i = 0; i < rows.length; i++) {
categories[rows[i][col]] = true;
}
var finalCats = [];
for (var cat in categories) {
if (!fields[col].constraint || cat in fields[col].catConstraint) {
finalCats.push(cat);
}
}
return d3.scale.ordinal()
.domain(finalCats.sort())
.rangePoints([rangeMin, rangeMax], 1);
}
}
function updateScales () {
xScale = updateScale(x, buffer, plotWidth, true);
yScale = updateScale(y, plotHeight, 0, false);
xAxis = d3.svg.axis()
.scale(xScale)
.orient("bottom")
.tickPadding(10)
.tickSize(-plotHeight);
yAxis = d3.svg.axis()
.scale(yScale)
.orient("left")
.tickPadding(10)
.tickSize(-plotWidth + buffer);
}
function point_size(index) {
if (shows[index]) {
return r * Math.pow(uniqueMap[genKey(rows[index])].length, 0.5);
} else {
return r;
}
}
function makePoints() {
svg.selectAll(".data")
.data(Array.apply(null, Array(rows.length)).map(function (_, i) {return i;}))
.enter()
.append("g")
.attr("class", "data")
.style("opacity", "0")
.style("fill", "#fff")
.style("stroke", "#fff")
.style("stroke-width", "1.5")
.append("circle")
.attr("class", "point")
.on("click", function(d) {
pointIndex += 1;
updateFieldValues();
})
.on("mouseover", function(d) {
d3.select(this)
.attr("r", point_size(d) + Math.pow(point_size(d), 0.15) + 1);
currentIds = uniqueMap[genKey(rows[d])];
updateFieldValues();
})
.on("mouseout", function(d) {
d3.select(this)
.attr("r", (point_size(d)));
currentIds = null;
pointIndex = 0;
updateFieldValues();
});
}
function updatePoints() {
var transitions = 0;
svg.selectAll(".data")
.style("cursor", function (d) {
if (shows[d] && uniqueMap[genKey(rows[d])].length > 1) {
return "pointer";
} else {
return "auto";
}
})
.sort(function (a, b) {
var pa = point_size(a);
var pb = point_size(b);
if (pa == pb) {
if (a > b) {
return -1;
} else {
return 1;
}
}
if (pa > pb) {
return -1;
} else {
return 1;
}
})
.transition()
.duration(700)
.style("opacity", function (d) {
if (shows[d] && uniqueMap[genKey(rows[d])][0] == d) {
return "0.9";
} else {
return "0";
}
})
.style("fill", function(d) {
if (shows[d]) {
return colorFn(colorMap[genKey(rows[d])]);
} else {
return "#999";
}
})
.style("stroke", function(d) {
if (shows[d]) {
return d3.rgb(colorFn(colorMap[genKey(rows[d])])).darker(0.3);
} else {
return "#999";
}
})
.select(".point")
.attr("display", function (d) {
if (shows[d]) {
return "inherit";
} else {
return "none";
}
})
.attr("r", function(d) {
return point_size(d);
})
.attr("cx", function(d) {
var key = genKey(rows[d]);
if (key in xMap) {
return xScale(xMap[key]);
} else {
if (fields[x].optype == "numeric") {
return Math.round(xScale(rows[d][x]));
} else {
return xScale(rows[d][x]);
}
}
})
.attr("cy", function(d) {
var key = genKey(rows[d]);
if (key in yMap) {
return yScale(yMap[key]);
} else {
if (fields[y].optype == "numeric") {
return Math.round(yScale(rows[d][y]));
} else {
return yScale(rows[d][y]);
}
}
})
.transition()
.attr("display", function (d) {
if (shows[d] && uniqueMap[genKey(rows[d])][0] == d) {
return "inherit";
} else {
return "none";
}
});
}
function revealPoints() {
svg.selectAll(".data")
.data(Array.apply(null, Array(rows.length)).map(function (_, i) {return i;}))
.select(".point")
}
});
</script>
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