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Custom Axis labels for Grouped Bar chart

Needed output:
I need to configure a grouped bar chart in which the type of each bar is shown in the axis itself.
I am using chartjs 2.9. How can I add the text "Availability","Co-funded","CPC" in the axis itself. I can't find any configuration which support this implementation in Chart js . Is there any other JS library where this is possible
this.barChart = new .Chart(ctx, {
type: "bar",
data: {
labels: this.barChartData["chart-data"].map((obj) => obj.y),
datasets:
this.barChartData["chart-mapping"].map((obj) => {
return {
label: obj.label,
data: this.barChartData["chart-data"],
backgroundColor: obj.color,
parsing: {
xAxisKey: obj.key,
},
};
}),
},
options: {
datasets: {
barThickness: 20,
},
indexAxis: "y",
plugins: {
legend: { position: "right", align: "start", title: "Type" },
},
},
});
barChartData = {
"chart-mapping": [
{
key: "avi",
label: "Availability..",
color: "rgba(50, 144, 237, 1)",
},
{
key: "cfd",
label: "Co-funded..",
color: "rgba(119, 181, 242, 1)",
},
{
key: "CPC",
label: "CPC",
color: "rgba(157, 83, 242, 1)",
},
{
key: "od",
label: "Order Drop..",
color: "rgba(195, 152, 245, 1)",
},
],
"chart-data": [
{
y: "Name1",
avi: 32,
cfd: 32,
CPC: 57,
od: 12,
},
{
y: "AK",
avi: 15,
cfd: 23,
CPC: 42,
od: 45,
},
{
y: "Name3",
avi: 67,
cfd: 34,
CPC: 21,
od: 43,
},
],
};
Current implementation:

is it possible to duplicate the y axis labels to the right side of a google chart?

is there anyone having some experience with Google Charts, who was facing a similar problem before? I basically need to display the same y axis labels on the both sides of the graph, as shown on the image:
image of the graph
Here is my dataset:
['Date', 'Drilling', 'Stacked', 'Cold stacked', 'Construction', 'Repair']
['2020-09-16', 406, 171, 135, 67, 3]
['2020-09-17', 407, 170, 135, 67, 3]
['2020-09-18', 408, 169, 135, 67, 3]
['2020-09-19', 408, 169, 135, 67, 3]
['2020-09-20', 409, 168, 135, 67, 3]
['2020-09-21', 408, 169, 135, 67, 3]
['2020-09-22', 406, 171, 135, 67, 3]
['2020-09-23', 407, 170, 135, 67, 3]
...and so on...
And graph settings:
{
isStacked: true,
colors: ['#ff4852', '#005BFF', '#FFAB2E', '#af5ddf', '#00A580'],
vAxis: {
format: '######',
},
chartArea: {
top: '30',
height: '75%',
width: '80%',
},
series: {
0: {
textPosition: 'none',
},
},
vAxes: {
1: {
textPosition: 'none',
},
},
hAxes: {
0: {
gridlines: { color: 'transparent' },
},
},
}

Need to test it out but let's try as below. Otherwise you have to duplicate the series data and set it to 'targetAxisIndex: 1'.
series: {
0: {
targetAxisIndex: 0,
targetAxisIndex: 1,
},
},

JSON.parse() throws error when JSON gets too long

I have spawned a python child_process in node.js that returns JSON data. In my python file I used json.dumps() before passing it back to node.
Whenever the list "results" in the JSON contains more than 62 entries, my node.js server dies when trying to parse it. Otherwise it works all fine?
Even when the node app dies, the data gets still sent back correctly to the client.
The error message is only thrown when calling JSON.parse(), but I cannot leave it out here, because the received data from python is in a buffered format:
<Buffer 7b 0d 0a 20 20 22 70 61 72 61 6d 65 74 65 72 73 22 3a 20 5b 0d 0a 20 20 20 20 7b 0d 0a 20 20 20 20 20 20 22 70 72 6f 70 65 72 74 79 22 3a 20 22 42 65 ... 9136 more bytes>
<Buffer 0d 0a>
Has anyone an idea what the problem could be?
The thrown error message is:
undefined:2
SyntaxError: Unexpected end of JSON input
at JSON.parse (<anonymous>)
at Socket.<anonymous> (D:\Projects\data-farming-framework-api\app.js:52:23)
at Socket.emit (events.js:310:20)
at addChunk (_stream_readable.js:286:12)
at readableAddChunk (_stream_readable.js:268:9)
at Socket.Readable.push (_stream_readable.js:209:10)
at Pipe.onStreamRead (internal/stream_base_commons.js:186:23)
My node.js code:
app.post('/api/ps/executeExperiments', async (req, res, next) => {
let path = req.body.path;
let experiments = JSON.stringify(req.body.data);
let python = await spawn('python', ['./plantsim.py', 'execute_experiments()', path, experiments]);
python.stdout.on('data', data => {
if (data.toString() == 'ERROR') {
callback(new Error('ERROR'))
}
let result = JSON.parse(data);
res.send(result);
});
});
The returned JSON has following format:
{
parameters: [
{ property: 'Bearbeitungszeit', object: 'Einzelstation' },
{ property: 'Bearbeitungszeit', object: 'Einzelstation2' }
],
results: [
{ id: 1, input: 252, output: 249, values: [Array] },
{ id: 2, input: 198, output: 195, values: [Array] },
{ id: 3, input: 165, output: 162, values: [Array] },
{ id: 4, input: 204, output: 201, values: [Array] },
{ id: 5, input: 169, output: 166, values: [Array] },
{ id: 6, input: 239, output: 236, values: [Array] },
{ id: 7, input: 225, output: 222, values: [Array] },
{ id: 8, input: 312, output: 309, values: [Array] },
{ id: 9, input: 324, output: 321, values: [Array] },
{ id: 10, input: 248, output: 245, values: [Array] },
{ id: 11, input: 199, output: 196, values: [Array] },
{ id: 12, input: 186, output: 183, values: [Array] },
{ id: 13, input: 161, output: 158, values: [Array] },
{ id: 14, input: 149, output: 146, values: [Array] },
{ id: 15, input: 175, output: 172, values: [Array] },
{ id: 16, input: 201, output: 198, values: [Array] },
{ id: 17, input: 242, output: 239, values: [Array] },
{ id: 18, input: 162, output: 159, values: [Array] },
{ id: 19, input: 184, output: 181, values: [Array] },
{ id: 20, input: 157, output: 154, values: [Array] },
{ id: 21, input: 160, output: 157, values: [Array] },
{ id: 22, input: 290, output: 287, values: [Array] },
{ id: 23, input: 358, output: 355, values: [Array] },
{ id: 24, input: 153, output: 150, values: [Array] },
{ id: 25, input: 155, output: 152, values: [Array] },
{ id: 26, input: 195, output: 192, values: [Array] },
{ id: 27, input: 174, output: 171, values: [Array] },
{ id: 28, input: 269, output: 266, values: [Array] },
{ id: 29, input: 341, output: 338, values: [Array] },
{ id: 30, input: 263, output: 260, values: [Array] },
{ id: 31, input: 156, output: 153, values: [Array] },
{ id: 32, input: 167, output: 164, values: [Array] },
{ id: 33, input: 295, output: 292, values: [Array] },
{ id: 34, input: 230, output: 227, values: [Array] },
{ id: 35, input: 189, output: 186, values: [Array] },
{ id: 36, input: 172, output: 169, values: [Array] },
{ id: 37, input: 254, output: 251, values: [Array] },
{ id: 38, input: 182, output: 179, values: [Array] },
{ id: 39, input: 206, output: 203, values: [Array] },
{ id: 40, input: 232, output: 229, values: [Array] },
{ id: 41, input: 259, output: 256, values: [Array] },
{ id: 42, input: 159, output: 156, values: [Array] },
{ id: 43, input: 305, output: 302, values: [Array] },
{ id: 44, input: 151, output: 148, values: [Array] },
{ id: 45, input: 181, output: 178, values: [Array] },
{ id: 46, input: 302, output: 299, values: [Array] },
{ id: 47, input: 187, output: 184, values: [Array] },
{ id: 48, input: 245, output: 242, values: [Array] },
{ id: 49, input: 149, output: 146, values: [Array] },
{ id: 50, input: 279, output: 276, values: [Array] },
{ id: 51, input: 215, output: 212, values: [Array] },
{ id: 52, input: 170, output: 167, values: [Array] },
{ id: 53, input: 288, output: 285, values: [Array] },
{ id: 54, input: 329, output: 326, values: [Array] },
{ id: 55, input: 283, output: 280, values: [Array] },
{ id: 56, input: 193, output: 190, values: [Array] },
{ id: 57, input: 177, output: 174, values: [Array] },
{ id: 58, input: 348, output: 345, values: [Array] },
{ id: 59, input: 265, output: 262, values: [Array] },
{ id: 60, input: 219, output: 216, values: [Array] },
{ id: 61, input: 352, output: 349, values: [Array] },
{ id: 62, input: 151, output: 148, values: [Array] }
]
}
Values is also a list, however i don't know why it is not displayed in the terminal correctly. The data is still there as it gets passed to the client correctly.

data events deliver chunks of data on arbitrary boundaries. As long as you are getting the entire JSON in one chunk (something you do not control), your code probably just happens to work. But, as soon as the data gets large enough of takes long enough to generate that it gets sent in more than one chunk, then your code dies trying to parse an individual chunk of data. This is why it is size dependent. At some size of data, it will start arriving in more than one chunk. And, you can't parse each chunk as JSON separately (thus your JSON.parse() error.
Instead, if you're going to parse it into JSON, you need to accumulate all the chunks and then when it's done, parse the entire thing. JSON is not a format that can easily be incrementally parsed (there is JSON stream code that can do it, but it's a lot of work).
app.post('/api/ps/executeExperiments', async (req, res, next) => {
let path = req.body.path;
let experiments = JSON.stringify(req.body.data);
let python = spawn('python', ['./plantsim.py', 'execute_experiments()', path, experiments]);
let allData = [];
// collect from all the data events here
python.stdout.on('data', data => {
allData.push(data.toString());
}).on('error', e => {
console.log(e);
res.sendStatus(500);
}).on('close', () => {
// we have all data now
let result = allData.join(allData, "");
if (result.startsWith('ERROR')) {
console.log(result);
res.sendStatus(500);
} else {
res.send(allData);
}
});
});
In your existing code what is callback()? You don't show that and it has me confused so I removed it.
You also need to send an error response to the incoming POST request if you get an error.
And, there's no point to using await on the return value from spawn(). It doesn't return a promise so await doesn't do anything useful.
Also, it appears there is no need to even parse the JSON. If you're going to just parse it and then send it right off with res.send(), all res.send() is going to do is turn it back into JSON again. So, perhaps all you really need to do it to just stream python.stdout as your response?

The issue is not with the long file, the issue is with the way you tried to collect data. python.stdout.on is the stream of data. Data comes in the chunk. So you need to collect all data then return to response. You can simplify, using basic util method as given below.
const spawn = require("child_process").spawn;
function run(path, experiments) {
let command = spawn("python", [
"./plantsim.py",
"execute_experiments()",
path,
experiments,
]);
return new Promise((resolve) => {
var result = "";
command.stdout.on("data", function (data) {
result += data.toString();
});
command.on("close", function (code) {
resolve(result);
});
});
}
app.post("/api/ps/executeExperiments", async (req, res, next) => {
let path = req.body.path;
let experiments = JSON.stringify(req.body.data);
const data = await run(path, experiments);
res.send(result);
});
If you are just returning file[no parse or transform] you can just pipe the data to the response.
Sample:
const { spawn } = require("child_process");
const express = require("express");
const app = express();
app.get("/json", (req, res) => {
let command = spawn("cat", [
__dirname + "/test.json",
]);
command.stdout.pipe(res)
command.on("close", function (data) {
console.log("done writing");
});
});
app.listen(3000)

SVG to Image export performance issues (using canvg / XMLSerializer / getComputedStyle)

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.
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 = [];
var C3Styles = null;
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 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(canvasComputed);
/* taken from https://gist.github.com/aendrew/1ad2eed6afa29e30d52e#file-exportchart-js
and changed from, angular to D3 functions
*/
/* Take styles from CSS and put as inline SVG attributes so that Canvg
can properly parse them. */
var chartStyle;
if (!C3Styles) {
// Get rules from c3.css
var styleSheets = document.styleSheets;
for (var i = 0; i <= styleSheets.length - 1; i++) {
if (styleSheets[i].href && (styleSheets[i].href.indexOf('c3.min.css') !== -1 || styleSheets[i].href.indexOf('c3.css') !== -1)) {
try {
if (styleSheets[i].rules !== undefined) {
chartStyle = styleSheets[i].rules;
} else {
chartStyle = styleSheets[i].cssRules;
}
break;
}
//Note that SecurityError exception is specific to Firefox.
catch (e) {
if (e.name == 'SecurityError') {
console.log("SecurityError. Cant read: " + styleSheets[i].href);
continue;
}
}
}
if (chartStyle !== null && chartStyle !== undefined) {
C3Styles = {};
var selector;
// Inline apply all the CSS rules as inline
for (i = 0; i < chartStyle.length; i++) {
if (chartStyle[i].type === 1) {
selector = chartStyle[i].selectorText;
var styleDec = chartStyle[i].style;
for (var s = 0; s < styleDec.length; s++) {
C3Styles[styleDec[s]] = styleDec[styleDec[s]];
}
}
}
}
}
}
if (C3Styles)
d3.select(svgCopyEl).selectAll('.c3:not(.c3-chart):not(path)').style(C3Styles);
// SVG doesn't use CSS visibility and opacity is an attribute, not a style property. Change hidden stuff to "display: none"
d3.select(svgCopyEl).selectAll('*')
.filter(function(d) {
return d && d.style && (d.style('visibility') === 'hidden' || d.style('opacity') === '0');
})
.style('display', 'none');
//fix weird back fill
d3.select(svgCopyEl).selectAll("path").attr("fill", "none");
//fix no axes
d3.select(svgCopyEl).selectAll("path.domain").attr("stroke", "black");
//fix no tick
d3.select(svgCopyEl).selectAll(".tick line").attr("stroke", "black");
// transform SVG to canvas using external canvg
canvg(canvasComputed, new XMLSerializer().serializeToString(svgCopyEl));
//remove temp document objects
canvasComputed.remove();
svgCopyEl.remove();
container.remove();
return canvasComputed;
}
<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>
<div id="chart1" class "c3">
</div>
<div id="chart2" class="c3">
</div>
<button type="button" id="exportButton">
export to SVG
</button>
Unfortunately
document.styleSheets[i].rules
can't be accessed in the script here. It worked in my environment though.
Any idea why this does not work here?

Draw 5 way diagram using d3.js

I am using venn.js to try to visualize 5-way data. The data I am using is from R's VennDiagram Package. But it somehow can't show up. Most of the examples are using the even number of sets, is there anything special about the odd number?
My code is as below:
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>mds venn.js example</title>
<style>
body {
font-family: "Helvetica Neue",Helvetica,Arial,sans-serif;
font-size: 14px;
}
</style>
</head>
<body>
<div id="venn"></div>
</body>
<script src="http://www.numericjs.com/lib/numeric-1.2.6.min.js"></script>
<script src="http://d3js.org/d3.v3.min.js"></script>
<script src="venn.js"></script>
<script src="http://www.benfrederickson.com/images/mds.js"></script>
<script>
var sets = [{sets: ['A'], size: 301},
{sets: ['B'], size: 321},
{sets: ['C'], size: 311},
{sets: ['D'], size: 321},
{sets: ['E'], size: 301}
{sets: ['A','B'], size: 188},
{sets: ['A','C'], size: 191},
{sets: ['A','D'], size: 184},
{sets: ['A','E'], size: 177},
{sets: ['B','C'], size: 194},
{sets: ['B','D'], size: 197},
{sets: ['B','E'], size: 190},
{sets: ['C','D'], size: 190},
{sets: ['C','E'], size: 173},
{sets: ['D','E'], size: 186}];
var chart = venn.VennDiagram()
.width(600)
.height(400)
.layoutFunction(
function(d) { return venn.venn(d, { initialLayout: venn.classicMDSLayout });}
);
d3.select("#venn").datum(sets).call(chart);
</script>
</html>
The original data come from
venn.plot <- draw.quintuple.venn(
area1 = 301,
area2 = 321,
area3 = 311,
area4 = 321,
area5 = 301,
n12 = 188,
n13 = 191,
n14 = 184,
n15 = 177,
n23 = 194,
n24 = 197,
n25 = 190,
n34 = 190,
n35 = 173,
n45 = 186,
n123 = 112,
n124 = 108,
n125 = 108,
n134 = 111,
n135 = 104,
n145 = 104,
n234 = 111,
n235 = 107,
n245 = 110,
n345 = 100,
n1234 = 61,
n1235 = 60,
n1245 = 59,
n1345 = 58,
n2345 = 57,
n12345 = 31,
category = c("A", "B", "C", "D", "E"),
fill = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
cat.col = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
cat.cex = 2,
margin = 0.05,
cex = c(1.5, 1.5, 1.5, 1.5, 1.5, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8,
1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 1, 1, 1, 1, 1.5),
ind = TRUE
);

You have a syntax error in your javascript, this line "{sets: ['E'], size: 301}" should have a comma after it - adding the comma and it produces output like: