所以我結束了各具特色我自己d3.js解決方案:
我用d3.time.scale規模爲時間維度,然後d3.scale.category20規模爲類別的顏色。然後,我將分類數據繪製爲時間軸上開始時間的高度相關值,並使用d3.time.scale比例來計算每個矩形的相應箱寬。
可重用的組件(以下在http://bost.ocks.org/mike/chart/模式)的例子可以看這裏:
function timeSeriesCategorical() {
var w = 860,
h = 70,
margin = {top: 20, right: 80, bottom: 30, left: 50},
width = w - margin.left - margin.right,
height = h - margin.top - margin.bottom;
var xValue = function(d) { return d[0]; },
yValue = function(d) { return d[1]; };
var yDomain = null;
var xScale = d3.time.scale()
.range([0, width]);
var yScale = d3.scale.category20();
var xAxis = d3.svg.axis()
.scale(xScale)
.tickSubdivide(1)
.tickSize(-height)
.orient('bottom');
var yAxis = d3.svg.axis()
.scale(yScale)
.ticks(5)
.orient('left');
var binwidth = 20;
function chart(selection) {
selection.each(function(data) {
// convert data to standard representation
data = data.map(function(d, i) {
return [xValue.call(data, d, i), yValue.call(data, d, i)];
//return d;
});
// scale the x and y domains based on the actual data
xScale.domain(d3.extent(data, function(d) { return d[0]; }));
if (!yDomain) {
yScale.domain(d3.extent(data, function(d) { return d[1]; }));
} else {
yScale.domain(yDomain);
}
// compute binwidths for TODO better comment
// d looks like {timestamp, category}
data.forEach(function(d, i) {
if (data[i+1]) {
w_current = xScale(data[i][0]);
w_next = xScale(data[i+1][0]);
binwidth = w_next - w_current;
}
d.binwidth = binwidth;
});
// create chart space as svg
// note: 'this' el should not contain svg already
var svg = d3.select(this).append('svg').data(data);
// external dimensions
svg.attr('width', w)
.attr('height', h);
// internal dimensions
svg = svg.append('g')
.attr('transform', 'translate(' + margin.left + ',' + margin.top + ')');
// x axis
svg.append('g')
.attr('class', 'x axis')
.attr('transform', 'translate(0,' + height + ')')
.call(xAxis);
// TODO bars legend
// bars
svg.selectAll('rect')
.data(data)
.enter().append('rect')
.attr('x', function(d, i) { return xScale(d[0]); })
.attr('width', function(d, i) { return d.binwidth; })
.attr('height', height)
.attr('fill', function(d, i) { return yScale(d[1]); })
.attr('stroke', function(d, i) { return yScale(d[1]); });
});
}
chart.x = function(_) {
if (!arguments.length) return xValue;
xValue = _;
return chart;
};
chart.y = function(_) {
if (!arguments.length) return yValue;
yValue = _;
return chart;
};
chart.yDomain = function(_) {
if (!arguments.length) return yDomain;
yDomain = _;
return chart;
};
return chart;
}
而且是可調用的東西,如:
d3.csv('./data.csv', function(data) {
var chartActivity = timeSeriesCategorical()
.x(function(d) { return d.when; })
.y(function(d) { return d.activity; })
.yDomain([0,1]);
d3.select('#chart-activity')
.datum(data)
.call(chartActivity);
});
但願這是有幫助的人!這個項目是在https://github.com/interaction-design-lab/stress-sense-portal
非常酷:)做得很好。 – 2015-05-25 20:09:09