I am using canvg to convert a chart svg to an image. We have the issue that by default not all CSS attributes are applied to the image so we ended up using getComputedStyle in a loop.
This is a total mess under performance aspects if we have 10 or even 20 charts to be exported at once.
var labels = ['2018-10-01', '2018-10-02', '2018-10-03', '2018-10-04', '2018-10-05', '2018-10-06', '2018-10-07', '2018-10-08', '2018-10-09', '2018-10-10', '2018-10-11', '2018-10-12', '2018-10-13', '2018-10-14', '2018-10-15', '2018-10-16', '2018-10-17', '2018-10-18', '2018-10-19', '2018-10-20', '2018-10-21', '2018-10-22', '2018-10-23', '2018-10-24', '2018-10-25', '2018-10-26', '2018-10-27', '2018-10-28', '2018-10-29', '2018-10-30', '2018-10-31', '2018-11-01', '2018-11-02', '2018-11-03', '2018-11-04', '2018-11-05', '2018-11-06', '2018-11-07', '2018-11-08', '2018-11-09', '2018-11-10', '2018-11-11', '2018-11-12', '2018-11-13', '2018-11-14', '2018-11-15', '2018-11-16', '2018-11-17', '2018-11-18', '2018-11-19', '2018-11-20', '2018-11-21', '2018-11-22', '2018-11-23', '2018-11-24', '2018-11-25', '2018-11-26', '2018-11-27', '2018-11-28', '2018-11-29', '2018-11-30', '2018-12-01', '2018-12-02', '2018-12-03', '2018-12-04', '2018-12-05', '2018-12-06', '2018-12-07', '2018-12-08', '2018-12-09', '2018-12-10', '2018-12-11', '2018-12-12', '2018-12-13', '2018-12-14', '2018-12-15', '2018-12-16', '2018-12-17', '2018-12-18', '2018-12-19', '2018-12-20', '2018-12-21', '2018-12-22', '2018-12-23', '2018-12-24', '2018-12-25', '2018-12-26', '2018-12-27', '2018-12-28', '2018-12-29', '2018-12-30', '2018-12-31', '2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04', '2019-01-05', '2019-01-06', '2019-01-07', '2019-01-08', '2019-01-09', '2019-01-10', '2019-01-11', '2019-01-12', '2019-01-13', '2019-01-14', '2019-01-15', '2019-01-16', '2019-01-17', '2019-01-18', '2019-01-19', '2019-01-20', '2019-01-21', '2019-01-22', '2019-01-23', '2019-01-24', '2019-01-25', '2019-01-26', '2019-01-27', '2019-01-28', '2019-01-29', '2019-01-30', '2019-01-31', '2019-02-01', '2019-02-02', '2019-02-03', '2019-02-04', '2019-02-05', '2019-02-06', '2019-02-07', '2019-02-08', '2019-02-09', '2019-02-10', '2019-02-11', '2019-02-12', '2019-02-13', '2019-02-14', '2019-02-15', '2019-02-16', '2019-02-17', '2019-02-18', '2019-02-19', '2019-02-20', '2019-02-21', '2019-02-22', '2019-02-23', '2019-02-24', '2019-02-25', '2019-02-26', '2019-02-27', '2019-02-28'];
var columns = ['data101', 'data2', 'data347'];
var data = [
[0, 0, 2, 2, 1, 2, 7, 3, 1, 7, 5, 5, 5, 5, 6, 6, 11, 7, 2, 7, 16, 7, 3, 5, 10, 9, 11, 7, 3, 7, 7, 10, 10, 9, 18, 10, 20, 13, 9, 19, 16, 13, 20, 18, 14, 15, 18, 20, 19, 11, 13, 13, 12, 16, 11, 12, 21, 20, 23, 19, 19, 23, 23, 24, 23, 25, 21, 23, 20, 22, 21, 23, 24, 25, 27, 29, 28, 25, 24, 17, 20, 24, 22, 27, 21, 27, 19, 26, 31, 27, 28, 27, 21, 20, 27, 22, 22, 19, 17, 21, 23, 19, 22, 20, 21, 25, 15, 19, 20, 19, 21, 28, 17, 20, 14, 18, 17, 20, 27, 21, 18, 18, 20, 16, 27, 16, 16, 9, 18, 8, 19, 13, 8, 16, 15, 16, 9, 15, 10, 13, 10, 11, 10, 13, 12, 7, 14, 16, 13, 14, 8],
[0, 0, 338, 1201, 1268, 1371, 1286, 1148, 446, 288, 228, 253, 193, 201, 283, 393, 436, 379, 421, 444, 444, 417, 513, 353, 364, 399, 238, 191, 305, 337, 365, 349, 365, 244, 101, 39, 55, 72, 151, 98, 31, 127, 114, 92, 104, 196, 307, 245, 84, 168, 41, 38, 292, 488, 536, 569, 495, 448, 408, 358, 344, 380, 328, 334, 332, 330, 345, 312, 369, 377, 356, 301, 226, 273, 237, 116, 178, 133, 114, 138, 95, 143, 74, 74, 83, 47, 75, 101, 96, 59, 46, 128, 70, 57, 93, 80, 94, 93, 63, 86, 81, 63, 70, 102, 91, 67, 69, 68, 88, 76, 79, 70, 119, 88, 74, 94, 76, 54, 82, 90, 75, 130, 67, 78, 106, 91, 81, 27, 77, 21, 104, 83, 55, 60, 62, 304, 393, 191, 292, 77, 76, 55, 125, 89, 99, 127, 60, 75, 99, 120, 56],
[0, 0, 0, 1419, 7454, 12638, 10944, 7652, 4272, 11219, 9071, 7207, 7929, 8373, 9566, 6310, 7406, 9286, 8415, 7659, 6457, 3380, 10902, 10952, 10508, 7219, 4625, 4484, 4396, 5178, 5991, 7927, 14132, 14307, 5094, 10011, 6257, 9184, 18574, 12597, 11415, 7118, 9991, 10225, 14337, 4417, 12701, 17833, 23553, 10037, 4833, 5894, 19421, 14735, 12597, 8730, 5888, 11836, 13143, 17219, 10492, 10528, 8649, 11868, 10502, 6758, 7672, 8479, 11142, 22330, 26595, 4423, 17434, 8709, 9657, 7823, 9135, 19765, 18016, 16010, 8419, 7300, 8877, 9611, 9050, 8680, 8211, 6635, 3069, 10739, 6288, 6761, 7807, 16243, 20415, 23051, 19727, 8721, 6445, 8585, 13688, 14728, 17113, 16255, 3898, 4622, 3869, 3774, 4190, 3461, 4824, 4608, 4613, 3677, 3648, 3575, 3556, 4036, 3732, 2517, 4676, 4129, 3250, 4142, 3987, 4396, 3362, 2964, 1849, 2609, 2851, 3003, 3583, 3473, 3190, 2658, 4363, 3959, 4588, 3771, 4315, 3178, 3354, 3159, 2695, 4114, 4292, 3322, 1218, 3526, 3717]
];
var colors = ['#0065A3', '#767670', '#D73648', '#7FB2CE', '#00345B'];
var padding = 5;
//prepare chart data
var columnData = [];
var chartDataColumns = [];
var chartData = [];
chartData.push([columns[0]].concat(data[0]));
chartDataColumns = [
['x'].concat(labels)
].concat(chartData);
var chart1 = c3.generate({
bindto: d3.select('#chart1'),
data: {
x: 'x',
columns: [['x'].concat(labels)].concat(chartData),
type: 'line',
onmouseover: function(d) {
chart1.focus(d.id);
chart2.focus(d.id);
},
onmouseout: function() {
chart1.revert();
chart2.revert();
}
},
legend: {
position: 'right',
show: true,
item: {
onclick: function(id) {
if (chart1) chart1.toggle(id);
if (chart2) chart2.toogle(id);
},
onmouseover: function(id) {
if (chart1) chart1.focus(id);
if (chart2) chart2.focus(id);
},
onmouseout: function(id) {
if (chart1) chart1.revert();
if (chart2) chart2.revert();
}
}
},
tooltip: {
show: true,
format: {
value: function(value) {
return d3.format(",.0f")(value);
}
}
},
zoom: {
enabled: true
},
axis: {
x: {
type: 'timeseries',
tick: {
rotate: 90,
format: '%Y-%m-%d'
}
},
y: {
label: 'sample-data',
tick: {
format: d3.format(",")
}
}
},
color: {
pattern: colors
}
});
var chart2 = c3.generate({
bindto: d3.select('#chart2'),
data: {
columns: [[columns[0]].concat(data[0])],
type: 'pie',
onmouseover: function(id) {
if (chart1) chart1.focus(id);
if (chart2) chart2.focus(id);
},
onmouseout: function(id) {
if (chart1) chart1.revert();
if (chart2) chart2.revert();
}
},
legend: {
position: 'right',
show: true,
item: {
onclick: function(id) {
if (chart1) chart1.toggle(id);
if (chart2) chart2.toogle(id);
},
onmouseover: function(id) {
if (chart1) chart1.focus(id);
if (chart2) chart2.focus(id);
},
onmouseout: function(id) {
if (chart1) chart1.revert();
if (chart2) chart2.revert();
}
}
},
color: {
pattern: colors
},
});
for (var i = 1; i < columns.length; i++) {
setTimeout(function(column) {
chart1.load({
columns: [
[columns[column]].concat(data[column])
]
});
chart2.load({
columns: [[columns[column]].concat(data[column])]
});
}, (i * 5000 / columns.length), i);
}
document.getElementById("exportButton").onclick = function() {
exportChartToImage();
};
function exportChartToImage() {
var createImagePromise = new Promise(function(resolve, reject) {
var images = [];
d3.selectAll('svg').each(function() {
if (this.parentNode) {
images.push(getSvgImage(this.parentNode, true));
}
});
if (images.length > 0)
resolve(images);
else
reject(images);
});
createImagePromise.then(function(images) {
images.forEach(function(img, n) {
img.toBlob(function(blob) {
saveAs(blob, "image_" + (n + 1) + ".png");
});
});
})
.catch(function(error) {
throw error;
});
};
/**
* Converts a SVG-Chart to a canvas and returns it.
*/
function getSvgImage(svgContainer, png) {
var svgEl = d3.select(svgContainer).select('svg').node();
var svgCopyEl = svgEl.cloneNode(true);
if (!svgCopyEl)
return;
//remove elements not for printing
lensObject = d3.selectAll(".hidden-print").remove().exit();
//add temp document objects
var emptySvgEl = d3.select(document.createElementNS("http://www.w3.org/2000/svg", "svg")).attr("id", "emptysvg")
.attr("version", 1.1)
.attr("height", 2)
.node();
var canvasComputed = d3.select(document.createElement("canvas")).attr("id", "canvasComputed").node();
var container = d3.select(document.createElement("div")).attr("style", "display: none;")
.attr("class", "c3").node();
svgContainer.append(container);
container.append(svgCopyEl);
container.append(emptySvgEl);
container.append(canvasComputed);
//apply all CSS styles to SVG
exportStyles(svgCopyEl, emptySvgEl);
// transform SVG to canvas using external canvg
canvg(canvasComputed, new XMLSerializer().serializeToString(svgCopyEl));
//remove temp document objects
canvasComputed.remove();
emptySvgEl.remove();
svgCopyEl.remove();
container.remove();
return canvasComputed;
}
function exportStyles(svg, emptySvg) {
var tree = [];
var emptySvgDeclarationComputed = getComputedStyle(emptySvg);
//d3.select(svg).selectAll().each(function() {
$(svg).find("*").each(function() {
explicitlySetStyle(this, emptySvgDeclarationComputed);
});
}
function traverse(obj, tree) {
tree.push(obj);
if (obj.hasChildNodes()) {
var child = obj.firstChild;
while (child) {
if (child.nodeType === 1 && child.nodeName != 'SCRIPT') {
traverse(child, tree);
}
child = child.nextSibling;
}
}
return tree;
}
function explicitlySetStyle(element, emptySvgDeclarationComputed) {
var cSSStyleDeclarationComputed = getComputedStyle(element);
var i, len, key, value;
var computedStyleStr = "";
for (i = 0, len = cSSStyleDeclarationComputed.length; i < len; i++) {
key = cSSStyleDeclarationComputed[i];
value = cSSStyleDeclarationComputed.getPropertyValue(key);
if (value !== emptySvgDeclarationComputed.getPropertyValue(key)) {
if (key == 'visibility' && value == 'hidden') {
computedStyleStr += 'display: none;';
} else {
computedStyleStr += key + ":" + value + ";";
}
}
}
element.setAttribute('style', computedStyleStr);
}
<link href="https://cdnjs.cloudflare.com/ajax/libs/c3/0.6.12/c3.min.css" rel="stylesheet" />
<script src="https://d3js.org/d3.v5.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/c3/0.6.12/c3.min.js"></script>
<!-- Required to convert named colors to RGB -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/canvg/1.4/rgbcolor.min.js"></script>
<!-- Optional if you want blur -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/stackblur-canvas/1.4.1/stackblur.min.js"></script>
<!-- Main canvg code -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/canvg/1.5/canvg.js"></script>
<script src="https://fastcdn.org/FileSaver.js/1.1.20151003/FileSaver.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.3.1/jquery.min.js"></script>
<div id="chart1" class "c3">
</div>
<div id="chart2" class="c3">
</div>
<button type="button" id="exportButton">
export to SVG
</button>
=> http://jsfiddle.net/gothmogg/jLt3yq75/
This sample shows exemplary how we apply the CSS styles to the SVG. If we use normal canvg without getComputedStyle the x and y axes of the c3 chart look like a total mess...
Do you know faster way to get valid images? Is there a way to filter the CSS-styles? Maybe use "c3" styles only?
I have managed to solve the performance problems of exporting C3 SVG charts to PNG by avoiding to use getComputedStyle.
Browsing the issues in C3 I found issue #313
https://github.com/c3js/c3/issues/313
For others http://www.nihilogic.dk/labs/canvas2image/ might also be a good place to look at but I found a solution at https://gist.github.com/aendrew/1ad2eed6afa29e30d52e#file-exportchart-js-L29.
I have changed the code from using angular to d3 and now it works (for me).
Hopefully this might help others having the same issue.
Here the working code. Please note: the css styles are only examined and inlined once.
Unfortunately
can't be accessed in the script here. It worked in my environment though. Any idea why this does not work here?