How to change sparkline background color within Kendo UI - user-interface
$("#spark-collector").kendoSparkline({
type: "line",
data: [
71, 70, 69, 68, 65, 60, 55, 55, 50, 52,
73, 72, 72, 71, 68, 63, 57, 58, 53, 55,
63, 59, 61, 64, 58, 53, 48, 48, 45, 45,
63, 64, 63, 67, 58, 56, 53, 59, 51, 54
],
valueAxis: {
min: 0,
max: 100
},
seriesColors: ["blue"],
tooltip: {
visible: true
}
});
How to change sparkline background color within Kendo UI?
I believe you can use PlotArea for that. Please refer to the documentation. You can set Background, border, margin, opacity and padding
https://www.telerik.com/kendo-angular-ui/components/charts/api/PlotArea/
You should use the property chartArea.background. Referring to your example:
$("#spark-collector").kendoSparkline({
type: "line",
charArea: {
background: "cyan"
},
data: [
71, 70, 69, 68, 65, 60, 55, 55, 50, 52,
73, 72, 72, 71, 68, 63, 57, 58, 53, 55,
63, 59, 61, 64, 58, 53, 48, 48, 45, 45,
63, 64, 63, 67, 58, 56, 53, 59, 51, 54
],
valueAxis: {
min: 0,
max: 100
},
seriesColors: ["blue"],
tooltip: {
visible: true
}
});
Check the documentation here
Following a code snippet...
$("#spark-collector").kendoSparkline({
type: "line",
chartArea: {
background: "cyan"
},
data: [
71, 70, 69, 68, 65, 60, 55, 55, 50, 52,
73, 72, 72, 71, 68, 63, 57, 58, 53, 55,
63, 59, 61, 64, 58, 53, 48, 48, 45, 45,
63, 64, 63, 67, 58, 56, 53, 59, 51, 54
],
valueAxis: {
min: 0,
max: 100
},
seriesColors: ["blue"],
tooltip: {
visible: true
}
});
<link rel="stylesheet" href="https://kendo.cdn.telerik.com/2018.1.221/styles/kendo.bootstrap-v4.min.css" />
<script src="https://kendo.cdn.telerik.com/2018.1.221/js/jquery.min.js"></script>
<script src="https://kendo.cdn.telerik.com/2018.1.221/js/kendo.all.min.js"></script>
<div id="spark-collector"></div>
Related
how to play streaming mp3 messages (uint8 bytes) generated by ROS audio_capture in html WebAudio Api
I am trying to play streaming mp3 messages (uint8 bytes) generated by ROS audio_capture in html using WebAudio api.
The messages are generated by ROS audio_capture which publishes the mp3 as uint8 bytes. I am grabbing each message and trying to play it in the Web browser using web audio api.
Below is the sample mp3 message:
data: [255, 243, 152, 68, 193, 22, 185, 255, 114, 223, 97, 38, 124, 172, 27, 246, 218, 254, 194, 80, 189, 84, 180, 209, 56, 254, 114, 135, 214, 30, 151, 78, 75, 159, 104, 148, 93, 149, 152, 155, 66, 68, 77, 137, 197, 34, 132, 145, 8, 138, 163, 10, 159, 17, 160, 23, 78, 4, 43, 174, 73, 201, 40, 63, 17, 28, 209, 153, 70, 81, 180, 42, 180, 226, 199, 155, 79, 189, 189, 51, 135, 145, 183, 139, 206, 179, 81, 185, 55, 158, 158, 89, 168, 133, 27, 112, 101, 139, 143, 24, 73, 193, 5, 201, 195, 32, 81, 205, 100, 189, 224, 214, 122, 225, 61, 221, 74, 155, 134, 73, 229, 200, 24, 71, 83, 118, 86, 245, 166, 149, 53, 187, 113, 23, 17, 124, 43, 40, 232, 206, 60, 171, 168, 41, 158, 44, 112, 218, 54, 123, 29, 123, 163, 99, 79, 94, 174, 49, 242, 214, 50, 238, 153, 95, 57, 221, 223, 129, 247, 35, 157, 50, 77, 52, 69, 119, 110, 70, 44, 83, 84, 85, 141, 220, 190, 12, 85, 81, 24, 2, 122, 169, 36, 150, 238, 0, 232, 21, 230, 42, 96, 104, 226, 58, 78, 169, 244, 172, 228, 145, 76, 173, 170, 129, 62, 173, 50, 73, 91, 246, 17, 201, 6, 36, 101, 70, 69, 42, 146, 182, 124, 54, 11, 164, 78, 43, 44, 166, 188, 233, 96, 170, 171, 123, 66, 202, 107, 172, 152, 150, 143, 54, 68, 85, 70, 15, 3, 147, 69, 205, 25, 64, 210, 175, 185, 48, 165, 166, 94, 101, 85, 3, 36, 66, 99, 232, 153, 102, 196, 75, 152, 133, 79, 206, 202, 226, 158, 140, 158, 69, 221, 1, 70, 217, 193, 204, 138, 48, 138, 76, 127, 88, 211, 52, 173, 249, 85, 63, 201, 204, 210, 86, 42, 28, 135, 255, 187, 122, 220, 51, 27, 45, 238, 104, 73, 101, 165, 63, 190, 110, 102, 247, 66, 218, 251, 79, 131, 181, 44, 92, 167, 133, 160, 155, 228, 102, 119, 151, 159, 105, 85, 235, 145, 60, 252, 125, 120, 73, 211, 98]
Raw data received from audio source before base64 decoding mentioned below, let me know if its not a valid mp3 format.
//OYRM0VceN1L2EjfqzL/sJWwwydElS3xJYcJKpYaLXtfXvddaz6w5T+8w8/p6du6oWOCT6zoDp+zx9GnhKa8j0MGzMgZEs3bs5Z+x0InDcmNueXnI5J+eVwfp9emvuEZ2Oy2mNa7P3YYm+eK90yG6ktKsaInN/SpHvPlpxWo92+lBsUa9GHQagbEyziEbey/u8pi28oYYYW6B5mt0jZk1Ob7IFLsMIKSlOT3W2WXmcPS1Mhc0KIUiDkQ4IelkEbh6+OfQ/2llZ0karuqgLm5UZmFiYKwpE4wJMp0skT+cEmnaGUBIwvvpdXGyMCIEEEJAuQRTlJZtZoV0xGzMpG5tM+6ae6QKo5vTV2cmIBtiktmtOaqyQgxndQE/iCQQLCgpB8HVYUHBB0ldKDBBtGQKKkMKijjKVRoZIC/TYqVBS48IOBsoQsTiGpCygM3vbJNoZglxABBQerkwRDi7ipiISrDbitccaj
I am holding it in javascript array initially, then converting it to ArrayBuffer, then passing ArrayBuffer to decodeAudioData(), where i'm getting below error
Error in promise : Unable to decode Audio Data
Below is code:
function playByteArray(byteArray) {
var arrayBuffer = new ArrayBuffer(byteArray.length);
var bufferView = new Uint8Array(arrayBuffer);
for (i = 0; i < byteArray.length; i++) {
bufferView[i] = byteArray[i];
}
context.decodeAudioData(arrayBuffer, function(buffer) {
buf = buffer;
play();
});
}
// Play the loaded file
function play() {
// Create a source node from the buffer
var source = context.createBufferSource();
source.buffer = buf;
// Connect to the final output node (the speakers)
source.connect(context.destination);
// Play immediately
source.start(0);
}
Thanks in advance for help.
Your chunk of audio data probably isn't complete. In any case, you should consider using MediaSource Extensions for this task. That way, you can stream from the source and let the browser handle the rest.
How to convert a chart with kernel density estimation line from d3.js version 3 to d3.js version 4
I have a chart with kernel density estimation line (created with science.js). Currently, d3 version 3 is used here, I need this to be converted to version 4 of d3.js.
Please Help.
JSBin/Code Link: http://jsbin.com/nuzucibiju/edit?html,output
<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html;charset=utf-8">
<title>LOESS</title>
<script src="http://bl.ocks.org/curran/raw/b595fde4d771c5784421/science.v1.min.js"></script>
<script src="//d3js.org/d3.v3.min.js"></script>
<style>
body {
font: 10px sans-serif;
}
path {
stroke: #000;
stroke-width: 1.5px;
fill: none;
}
</style>
</head>
<body>
<div id="vis">
</div>
<script>
// Based on http://bl.ocks.org/900762 by John Firebaugh
var data = [
79, 54, 74, 62, 85, 55, 88, 85, 51, 85, 54, 84, 78, 47, 83, 52, 62, 84, 52, 79, 51, 47, 78, 69, 74, 83, 55, 76, 78, 79, 73, 77, 66, 80, 74, 52, 48, 80, 59, 90, 80, 58, 84, 58, 73, 83, 64, 53,
82, 59, 75, 90, 54, 80, 54, 83, 71, 64, 77, 81, 59, 84, 48, 82, 60, 92, 78, 78, 65, 73, 82, 56, 79, 71, 62, 76, 60, 78, 76, 83, 75, 82, 70, 65, 73, 88, 76, 80, 48, 86, 60, 90, 50, 78, 63, 72,
84, 75, 51, 82, 62, 88, 49, 83, 81, 47, 84, 52, 86, 81, 75, 59, 89, 79, 59, 81, 50, 85, 59, 87, 53, 69, 77, 56, 88, 81, 45, 82, 55, 90, 45, 83, 56, 89, 46, 82, 51, 86, 53, 79, 81, 60, 82, 77,
76, 59, 80, 49, 96, 53, 77, 77, 65, 81, 71, 70, 81, 93, 53, 89, 45, 86, 58, 78, 66, 76, 63, 88, 52, 93, 49, 57, 77, 68, 81, 81, 73, 50, 85, 74, 55, 77, 83, 83, 51, 78, 84, 46, 83, 55, 81, 57,
76, 84, 77, 81, 87, 77, 51, 78, 60, 82, 91, 53, 78, 46, 77, 84, 49, 83, 71, 80, 49, 75, 64, 76, 53, 94, 55, 76, 50, 82, 54, 75, 78, 79, 78, 78, 70, 79, 70, 54, 86, 50, 90, 54, 54, 77, 79, 64,
75, 47, 86, 63, 85, 82, 57, 82, 67, 74, 54, 83, 73, 73, 88, 80, 71, 83, 56, 79, 78, 84, 58, 83, 43, 60, 75, 81, 46, 90, 46, 74
];
var w = 952,
h = 476,
x = d3.scale.linear().domain([30, 110]).range([0, w]),
bins = d3.layout.histogram().frequency(false).bins(x.ticks(60))(data),
max = d3.max(bins, function(d) { return d.y; }),
y = d3.scale.linear().domain([0, .1]).range([0, h]),
kde = science.stats.kde().sample(data);
var vis = d3.select("body")
.append("svg")
.attr("width", w)
.attr("height", h);
var bars = vis.selectAll("g.bar")
.data(bins)
.enter().append("g")
.attr("class", "bar")
.attr("transform", function(d, i) {
return "translate(" + x(d.x) + "," + (h - y(d.y)) + ")";
});
bars.append("rect")
.attr("fill", "steelblue")
.attr("width", function(d) {
return x(d.dx + 30) - 1; })
.attr("height", function(d) {
console.log('height',d);
return y(d.y); });
var line = d3.svg.line()
.x(function(d) { return x(d[0]); })
.y(function(d) { return h - y(d[1]); });
vis.selectAll("path")
.data(d3.values(science.stats.bandwidth))
.enter().append("path")
.attr("d", function(h) {
return line(kde.bandwidth(h)(d3.range(30, 110, .1)));
});
</script>
</body>
</html>
I am trying to convert d3.js v3 to v4 but getting a lot of errors.
It would be great if the chart is converted to the desired version 4.
SourceCode
I recommend you read this article. It is a great explanation how histogram was changed in d3v4 compared to d3v3.
You should rewrite your code this way:
var w = 952,
h = 476,
x = d3.scaleLinear().domain([30, 110]).range([0, w]),
bins = d3.histogram().domain(x.domain()).thresholds(x.ticks(30))(data),
max = d3.max(bins, function(d) { return d.y; }),
y = d3.scaleLinear().domain([0, .1]).range([0, h]),
yForHistogram = d3.scaleLinear()
.domain([0, d3.max(bins, function(d) { return d.length; })])
.range([h, 0]),
kde = science.stats.kde().sample(data);
var vis = d3.select("body")
.append("svg")
.attr("width", w)
.attr("height", h);
var bars = vis.selectAll("g.bar")
.data(bins)
.enter().append("g")
.attr("class", "bar")
.attr("transform", function(d) { return "translate(" + x(d.x0) + "," + yForHistogram(d.length) + ")"; });
bars.append("rect")
.attr("fill", "steelblue")
.attr("width", x(bins[0].x1) - x(bins[0].x0) - 1)
.attr("height", function(d) {
return h - yForHistogram(d.length);
});
...
Check my fork of JSBin that you mentioned. It works with d3v4.
A fast look up value in vectors MATLAB code comparion
I am using MATLAB to look up the value in two vectors OCT_EXP, OCT_LOG, from two input values u,v and output is val as condition
if (( u == 0 )||( v == 0 ))
val = 0;
else
val = OCT_EXP( OCT_LOG(u) + OCT_LOG(v) + 1);
I tried to use three ways: normal way (no_vectorized way), vectorized way, and mex way. I expected that mex way will be the best way, then vectorized way. However, when I measure time consumption, the first way (no vectorized way) is best, the vectorized way is worst way. What is happen in my code? Thank all
I want to consider the speed up of the function because it will be called many time: 300.000 times
The first way:
function val = gfmult_no_vec( u, v )
OCT_EXP = [ 1, 2, 4, 8, 16, 32, 64, 128, 29, 58, 116, 232, 205, 135, 19, 38,...
76, 152, 45, 90, 180, 117, 234, 201, 143, 3, 6, 12, 24, 48, 96, 192, 157,...
39, 78, 156, 37, 74, 148, 53, 106, 212, 181, 119, 238, 193, 159, 35,...
70, 140, 5, 10, 20, 40, 80, 160, 93, 186, 105, 210, 185, 111, 222,...
161, 95, 190, 97, 194, 153, 47, 94, 188, 101, 202, 137, 15, 30, 60,...
120, 240, 253, 231, 211, 187, 107, 214, 177, 127, 254, 225, 223, 163,...
91, 182, 113, 226, 217, 175, 67, 134, 17, 34, 68, 136, 13, 26, 52,...
104, 208, 189, 103, 206, 129, 31, 62, 124, 248, 237, 199, 147, 59,...
118, 236, 197, 151, 51, 102, 204, 133, 23, 46, 92, 184, 109, 218,...
169, 79, 158, 33, 66, 132, 21, 42, 84, 168, 77, 154, 41, 82, 164, 85,...
170, 73, 146, 57, 114, 228, 213, 183, 115, 230, 209, 191, 99, 198,...
145, 63, 126, 252, 229, 215, 179, 123, 246, 241, 255, 227, 219, 171,...
75, 150, 49, 98, 196, 149, 55, 110, 220, 165, 87, 174, 65, 130, 25,...
50, 100, 200, 141, 7, 14, 28, 56, 112, 224, 221, 167, 83, 166, 81,...
162, 89, 178, 121, 242, 249, 239, 195, 155, 43, 86, 172, 69, 138, 9,...
18, 36, 72, 144, 61, 122, 244, 245, 247, 243, 251, 235, 203, 139, 11,...
22, 44, 88, 176, 125, 250, 233, 207, 131, 27, 54, 108, 216, 173, 71,...
142, 1, 2, 4, 8, 16, 32, 64, 128, 29, 58, 116, 232, 205, 135, 19, 38,...
76, 152, 45, 90, 180, 117, 234, 201, 143, 3, 6, 12, 24, 48, 96, 192,...
157, 39, 78, 156, 37, 74, 148, 53, 106, 212, 181, 119, 238, 193, 159,...
35, 70, 140, 5, 10, 20, 40, 80, 160, 93, 186, 105, 210, 185, 111,...
222, 161, 95, 190, 97, 194, 153, 47, 94, 188, 101, 202, 137, 15, 30,...
60, 120, 240, 253, 231, 211, 187, 107, 214, 177, 127, 254, 225, 223,...
163, 91, 182, 113, 226, 217, 175, 67, 134, 17, 34, 68, 136, 13, 26,...
52, 104, 208, 189, 103, 206, 129, 31, 62, 124, 248, 237, 199, 147,...
59, 118, 236, 197, 151, 51, 102, 204, 133, 23, 46, 92, 184, 109, 218,...
169, 79, 158, 33, 66, 132, 21, 42, 84, 168, 77, 154, 41, 82, 164, 85,...
170, 73, 146, 57, 114, 228, 213, 183, 115, 230, 209, 191, 99, 198,...
145, 63, 126, 252, 229, 215, 179, 123, 246, 241, 255, 227, 219, 171,...
75, 150, 49, 98, 196, 149, 55, 110, 220, 165, 87, 174, 65, 130, 25,...
50, 100, 200, 141, 7, 14, 28, 56, 112, 224, 221, 167, 83, 166, 81,...
162, 89, 178, 121, 242, 249, 239, 195, 155, 43, 86, 172, 69, 138, 9,...
18, 36, 72, 144, 61, 122, 244, 245, 247, 243, 251, 235, 203, 139, 11,...
22, 44, 88, 176, 125, 250, 233, 207, 131, 27, 54, 108, 216, 173, 71,...
142 ];
OCT_LOG = [ 0, 1, 25, 2, 50, 26, 198, 3, 223, 51, 238, 27, 104, 199, 75, 4,...
100, 224, 14, 52, 141, 239, 129, 28, 193, 105, 248, 200, 8, 76, 113, 5,...
138, 101, 47, 225, 36, 15, 33, 53, 147, 142, 218, 240, 18, 130, 69,...
29, 181, 194, 125, 106, 39, 249, 185, 201, 154, 9, 120, 77, 228, 114,... end
166, 6, 191, 139, 98, 102, 221, 48, 253, 226, 152, 37, 179, 16, 145,...
34, 136, 54, 208, 148, 206, 143, 150, 219, 189, 241, 210, 19, 92,...
131, 56, 70, 64, 30, 66, 182, 163, 195, 72, 126, 110, 107, 58, 40,...
84, 250, 133, 186, 61, 202, 94, 155, 159, 10, 21, 121, 43, 78, 212,...
229, 172, 115, 243, 167, 87, 7, 112, 192, 247, 140, 128, 99, 13, 103,...
74, 222, 237, 49, 197, 254, 24, 227, 165, 153, 119, 38, 184, 180,...
124, 17, 68, 146, 217, 35, 32, 137, 46, 55, 63, 209, 91, 149, 188,...
207, 205, 144, 135, 151, 178, 220, 252, 190, 97, 242, 86, 211, 171,...
20, 42, 93, 158, 132, 60, 57, 83, 71, 109, 65, 162, 31, 45, 67, 216,...
183, 123, 164, 118, 196, 23, 73, 236, 127, 12, 111, 246, 108, 161,...
59, 82, 41, 157, 85, 170, 251, 96, 134, 177, 187, 204, 62, 90, 203,...
89, 95, 176, 156, 169, 160, 81, 11, 245, 22, 235, 122, 117, 44, 215,...
79, 174, 213, 233, 230, 231, 173, 232, 116, 214, 244, 234, 168, 80,...
88, 175 ];
if (( u == 0 )||( v == 0 ))
val = 0;
else
val = OCT_EXP( OCT_LOG(u) + OCT_LOG(v) + 1);
The second way: Vectorized way
function val = gfmult_vec( u, v )
OCT_EXP = [ 1, 2, 4, 8, 16, 32, 64, 128, 29, 58, 116, 232, 205, 135, 19, 38,...
76, 152, 45, 90, 180, 117, 234, 201, 143, 3, 6, 12, 24, 48, 96, 192, 157,...
39, 78, 156, 37, 74, 148, 53, 106, 212, 181, 119, 238, 193, 159, 35,...
70, 140, 5, 10, 20, 40, 80, 160, 93, 186, 105, 210, 185, 111, 222,...
161, 95, 190, 97, 194, 153, 47, 94, 188, 101, 202, 137, 15, 30, 60,...
120, 240, 253, 231, 211, 187, 107, 214, 177, 127, 254, 225, 223, 163,...
91, 182, 113, 226, 217, 175, 67, 134, 17, 34, 68, 136, 13, 26, 52,...
104, 208, 189, 103, 206, 129, 31, 62, 124, 248, 237, 199, 147, 59,...
118, 236, 197, 151, 51, 102, 204, 133, 23, 46, 92, 184, 109, 218,...
169, 79, 158, 33, 66, 132, 21, 42, 84, 168, 77, 154, 41, 82, 164, 85,...
170, 73, 146, 57, 114, 228, 213, 183, 115, 230, 209, 191, 99, 198,...
145, 63, 126, 252, 229, 215, 179, 123, 246, 241, 255, 227, 219, 171,...
75, 150, 49, 98, 196, 149, 55, 110, 220, 165, 87, 174, 65, 130, 25,...
50, 100, 200, 141, 7, 14, 28, 56, 112, 224, 221, 167, 83, 166, 81,...
162, 89, 178, 121, 242, 249, 239, 195, 155, 43, 86, 172, 69, 138, 9,...
18, 36, 72, 144, 61, 122, 244, 245, 247, 243, 251, 235, 203, 139, 11,...
22, 44, 88, 176, 125, 250, 233, 207, 131, 27, 54, 108, 216, 173, 71,...
142, 1, 2, 4, 8, 16, 32, 64, 128, 29, 58, 116, 232, 205, 135, 19, 38,...
76, 152, 45, 90, 180, 117, 234, 201, 143, 3, 6, 12, 24, 48, 96, 192,...
157, 39, 78, 156, 37, 74, 148, 53, 106, 212, 181, 119, 238, 193, 159,...
35, 70, 140, 5, 10, 20, 40, 80, 160, 93, 186, 105, 210, 185, 111,...
222, 161, 95, 190, 97, 194, 153, 47, 94, 188, 101, 202, 137, 15, 30,...
60, 120, 240, 253, 231, 211, 187, 107, 214, 177, 127, 254, 225, 223,...
163, 91, 182, 113, 226, 217, 175, 67, 134, 17, 34, 68, 136, 13, 26,...
52, 104, 208, 189, 103, 206, 129, 31, 62, 124, 248, 237, 199, 147,...
59, 118, 236, 197, 151, 51, 102, 204, 133, 23, 46, 92, 184, 109, 218,...
169, 79, 158, 33, 66, 132, 21, 42, 84, 168, 77, 154, 41, 82, 164, 85,...
170, 73, 146, 57, 114, 228, 213, 183, 115, 230, 209, 191, 99, 198,...
145, 63, 126, 252, 229, 215, 179, 123, 246, 241, 255, 227, 219, 171,...
75, 150, 49, 98, 196, 149, 55, 110, 220, 165, 87, 174, 65, 130, 25,...
50, 100, 200, 141, 7, 14, 28, 56, 112, 224, 221, 167, 83, 166, 81,...
162, 89, 178, 121, 242, 249, 239, 195, 155, 43, 86, 172, 69, 138, 9,...
18, 36, 72, 144, 61, 122, 244, 245, 247, 243, 251, 235, 203, 139, 11,...
22, 44, 88, 176, 125, 250, 233, 207, 131, 27, 54, 108, 216, 173, 71,...
142 ];
OCT_LOG = [ 0, 1, 25, 2, 50, 26, 198, 3, 223, 51, 238, 27, 104, 199, 75, 4,...
100, 224, 14, 52, 141, 239, 129, 28, 193, 105, 248, 200, 8, 76, 113, 5,...
138, 101, 47, 225, 36, 15, 33, 53, 147, 142, 218, 240, 18, 130, 69,...
29, 181, 194, 125, 106, 39, 249, 185, 201, 154, 9, 120, 77, 228, 114,...
166, 6, 191, 139, 98, 102, 221, 48, 253, 226, 152, 37, 179, 16, 145,...
34, 136, 54, 208, 148, 206, 143, 150, 219, 189, 241, 210, 19, 92,...
131, 56, 70, 64, 30, 66, 182, 163, 195, 72, 126, 110, 107, 58, 40,...
84, 250, 133, 186, 61, 202, 94, 155, 159, 10, 21, 121, 43, 78, 212,...
229, 172, 115, 243, 167, 87, 7, 112, 192, 247, 140, 128, 99, 13, 103,...
74, 222, 237, 49, 197, 254, 24, 227, 165, 153, 119, 38, 184, 180,...
124, 17, 68, 146, 217, 35, 32, 137, 46, 55, 63, 209, 91, 149, 188,...
207, 205, 144, 135, 151, 178, 220, 252, 190, 97, 242, 86, 211, 171,...
20, 42, 93, 158, 132, 60, 57, 83, 71, 109, 65, 162, 31, 45, 67, 216,...
183, 123, 164, 118, 196, 23, 73, 236, 127, 12, 111, 246, 108, 161,...
59, 82, 41, 157, 85, 170, 251, 96, 134, 177, 187, 204, 62, 90, 203,...
89, 95, 176, 156, 169, 160, 81, 11, 245, 22, 235, 122, 117, 44, 215,...
79, 174, 213, 233, 230, 231, 173, 232, 116, 214, 244, 234, 168, 80,...
88, 175 ];
uv0 = (~(( u == 0 )|( v == 0 )));
val = zeros(size(u));
val(uv0) = OCT_EXP( OCT_LOG(u(uv0)) + OCT_LOG(v(uv0)) + 1);
end
The last way: mex code
#include "mex.h"
double look_up(double u, double v)
{
double OCT_EXP [510] = { 1, 2, 4, 8, 16, 32, 64, 128, 29, 58, 116, 232, 205, 135, 19, 38,
76, 152, 45, 90, 180, 117, 234, 201, 143, 3, 6, 12, 24, 48, 96, 192, 157,
39, 78, 156, 37, 74, 148, 53, 106, 212, 181, 119, 238, 193, 159, 35,
70, 140, 5, 10, 20, 40, 80, 160, 93, 186, 105, 210, 185, 111, 222,
161, 95, 190, 97, 194, 153, 47, 94, 188, 101, 202, 137, 15, 30, 60,
120, 240, 253, 231, 211, 187, 107, 214, 177, 127, 254, 225, 223, 163,
91, 182, 113, 226, 217, 175, 67, 134, 17, 34, 68, 136, 13, 26, 52,
104, 208, 189, 103, 206, 129, 31, 62, 124, 248, 237, 199, 147, 59,
118, 236, 197, 151, 51, 102, 204, 133, 23, 46, 92, 184, 109, 218,
169, 79, 158, 33, 66, 132, 21, 42, 84, 168, 77, 154, 41, 82, 164, 85,
170, 73, 146, 57, 114, 228, 213, 183, 115, 230, 209, 191, 99, 198,
145, 63, 126, 252, 229, 215, 179, 123, 246, 241, 255, 227, 219, 171,
75, 150, 49, 98, 196, 149, 55, 110, 220, 165, 87, 174, 65, 130, 25,
50, 100, 200, 141, 7, 14, 28, 56, 112, 224, 221, 167, 83, 166, 81,
162, 89, 178, 121, 242, 249, 239, 195, 155, 43, 86, 172, 69, 138, 9,
18, 36, 72, 144, 61, 122, 244, 245, 247, 243, 251, 235, 203, 139, 11,
22, 44, 88, 176, 125, 250, 233, 207, 131, 27, 54, 108, 216, 173, 71,
142, 1, 2, 4, 8, 16, 32, 64, 128, 29, 58, 116, 232, 205, 135, 19, 38,
76, 152, 45, 90, 180, 117, 234, 201, 143, 3, 6, 12, 24, 48, 96, 192,
157, 39, 78, 156, 37, 74, 148, 53, 106, 212, 181, 119, 238, 193, 159,
35, 70, 140, 5, 10, 20, 40, 80, 160, 93, 186, 105, 210, 185, 111,
222, 161, 95, 190, 97, 194, 153, 47, 94, 188, 101, 202, 137, 15, 30,
60, 120, 240, 253, 231, 211, 187, 107, 214, 177, 127, 254, 225, 223,
163, 91, 182, 113, 226, 217, 175, 67, 134, 17, 34, 68, 136, 13, 26,
52, 104, 208, 189, 103, 206, 129, 31, 62, 124, 248, 237, 199, 147,
59, 118, 236, 197, 151, 51, 102, 204, 133, 23, 46, 92, 184, 109, 218,
169, 79, 158, 33, 66, 132, 21, 42, 84, 168, 77, 154, 41, 82, 164, 85,
170, 73, 146, 57, 114, 228, 213, 183, 115, 230, 209, 191, 99, 198,
145, 63, 126, 252, 229, 215, 179, 123, 246, 241, 255, 227, 219, 171,
75, 150, 49, 98, 196, 149, 55, 110, 220, 165, 87, 174, 65, 130, 25,
50, 100, 200, 141, 7, 14, 28, 56, 112, 224, 221, 167, 83, 166, 81,
162, 89, 178, 121, 242, 249, 239, 195, 155, 43, 86, 172, 69, 138, 9,
18, 36, 72, 144, 61, 122, 244, 245, 247, 243, 251, 235, 203, 139, 11,
22, 44, 88, 176, 125, 250, 233, 207, 131, 27, 54, 108, 216, 173, 71,
142 };
double OCT_LOG[255] = { 0, 1, 25, 2, 50, 26, 198, 3, 223, 51, 238, 27, 104, 199, 75, 4,
100, 224, 14, 52, 141, 239, 129, 28, 193, 105, 248, 200, 8, 76, 113, 5,
138, 101, 47, 225, 36, 15, 33, 53, 147, 142, 218, 240, 18, 130, 69,
29, 181, 194, 125, 106, 39, 249, 185, 201, 154, 9, 120, 77, 228, 114,
166, 6, 191, 139, 98, 102, 221, 48, 253, 226, 152, 37, 179, 16, 145,
34, 136, 54, 208, 148, 206, 143, 150, 219, 189, 241, 210, 19, 92,
131, 56, 70, 64, 30, 66, 182, 163, 195, 72, 126, 110, 107, 58, 40,
84, 250, 133, 186, 61, 202, 94, 155, 159, 10, 21, 121, 43, 78, 212,
229, 172, 115, 243, 167, 87, 7, 112, 192, 247, 140, 128, 99, 13, 103,
74, 222, 237, 49, 197, 254, 24, 227, 165, 153, 119, 38, 184, 180,
124, 17, 68, 146, 217, 35, 32, 137, 46, 55, 63, 209, 91, 149, 188,
207, 205, 144, 135, 151, 178, 220, 252, 190, 97, 242, 86, 211, 171,
20, 42, 93, 158, 132, 60, 57, 83, 71, 109, 65, 162, 31, 45, 67, 216,
183, 123, 164, 118, 196, 23, 73, 236, 127, 12, 111, 246, 108, 161,
59, 82, 41, 157, 85, 170, 251, 96, 134, 177, 187, 204, 62, 90, 203,
89, 95, 176, 156, 169, 160, 81, 11, 245, 22, 235, 122, 117, 44, 215,
79, 174, 213, 233, 230, 231, 173, 232, 116, 214, 244, 234, 168, 80,
88, 175 };
if (( u == 0 )||( v == 0 ))
return 0;
else
{
int index=OCT_LOG[int(u-1)] + OCT_LOG[int(v-1)] + 1;
return OCT_EXP [index-1];
}
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
double *u, *v, *uv;
int mrows, ncols;
plhs[0] = mxCreateDoubleMatrix(1,1, mxREAL);
/* Assign pointers to each input and output. */
u = mxGetPr(prhs[0]);
v = mxGetPr(prhs[1]);
uv = mxGetPr(plhs[0]);
*uv = look_up(*u, *v);
}
The measurement code
function main
function test1()
for i=1:200
for j=1:200
gfmult_no_vec(i,j);
end
end
end
function test2()
for i=1:200
for j=1:200
gfmult_vec(i,j);
end
end
end
function test3()
for i=1:200
for j=1:200
gfmult_mex(i,j);
end
end
end
f1=#()test1();
t1=timeit(f1)
f2=#()test2();
t2=timeit(f2)
f3=#()test3();
t3=timeit(f3)
end
Report time:
t1 = 0.1934,
t2 = 1.1739,
t3 = 0.3584
This solution takes 0.0006 second in my computer (and it is vectorized): u = randi(5,200,1)-1; % some arbitrary data including zeros v = randi(5,200,1)-1; % some arbitrary data including zeros [U,V] = ndgrid(u(u~=0),v(v~=0)); % make all possible combinations of u and v val = zeros(length(u),length(v)); % initialize the output size, in case the last value in u or v is zero. f = #(u,v) OCT_EXP(OCT_LOG(u)+OCT_LOG(v)+1); val((u~=0),(v~=0)) = f(U,V); Now val(u,v) = OCT_EXP(OCT_LOG(u)+OCT_LOG(v)+1) if u and v are both not zeros, otherwise val(u,v) = 0. If you want gfmult to have a scalar input, then your first method seems to be the fastest way. However, I would define OCT_EXP and OCT_LOG outside the function and pass them to it, instead of assigning this values over and over: function val = gfmult(OCT_EXP,OCT_LOG,u,v) if (u==0)||(v==0) val = 0; else val = OCT_EXP(OCT_LOG(u)+OCT_LOG(v)+1); end end in my computer it reduces running time from 0.21444 (with your version) to 0.158 second for 100K iteration, which is not such a big improvement (0.05644 second), but if you have millions of those, it may be significant.
c++11 Aggregate Initialize two dimensional int vector from std::string dynamically?
I'm sorry if this has been asked before but i searched and couldn't find anything like the case i have, however i'm coming from C# so i'm still learning C++, i have a std::string that represents the int data for vector<vector<int>> like this:
{
{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 },
{ 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220 }};
as you can see, the data is formatted same way when you aggregate initialize the vector<vector<int>>, how and what is the best way to load this data into vector<vector<int>> at runtime?
Please note, reformatting the data is not a problem since its coming from another application and i have the source code for that application and can change it to any format if it cannot be done with the supplied format.
Elasticsearch + Oracle JDBC River
Maybe this is a simple question but im new at ElasticSearch.. Installed es 1.4, Oracle 10g is up and running, jdbc plugin loaded in ES without issue. Marvel also working.. Tried to create a river with this statement in Marvel/Sense:
PUT _river/mydata/_meta
{
"type": "jdbc",
"jdbc": {
"driver": "oracle.jdbc.OracleDriver",
"url": “jdbc:oracle:thin:#host:1521:SID",
"user": “oracleusr",
"password": “ oraclepass",
"index": “myindex",
"type": “mytype",
"sql": "select * from aTable"
}
}
And i get this error all the time:
{
"error": "MapperParsingException[failed to parse]; nested: ElasticsearchParseException[Failed to derive xcontent from (offset=0, length=323): [80, 85, 84, 32, 95, 114, 105, 118, 101, 114, 47, 109, 52, 99, 47, 95, 109, 101, 116, 97, 32, 10, 123, 10, 32, 32, 34, 116, 121, 112, 101, 34, 58, 32, 34, 106, 100, 98, 99, 34, 44, 10, 32, 32, 34, 106, 100, 98, 99, 34, 58, 32, 123, 10, 32, 32, 32, 32, 32, 32, 32, 32, 34, 100, 114, 105, 118, 101, 114, 34, 58, 32, 34, 111, 114, 97, 99, 108, 101, 46, 106, 100, 98, 99, 46, 79, 114, 97, 99, 108, 101, 68, 114, 105, 118, 101, 114, 34, 44, 10, 32, 32, 32, 32, 32, 32, 32, 32, 34, 117, 114, 108, 34, 58, 32, -30, -128, -100, 106, 100, 98, 99, 58, 111, 114, 97, 99, 108, 101, 58, 116, 104, 105, 110, 58, 64, 49, 48, 46, 49, 57, 52, 46, 49, 55, 46, 49, 55, 51, 58, 49, 53, 50, 49, 58, 109, 52, 99, 34, 44, 10, 32, 32, 32, 32, 32, 32, 32, 32, 34, 117, 115, 101, 114, 34, 58, 32, -30, -128, -100, 109, 52, 99, 34, 44, 10, 32, 32, 32, 32, 32, 32, 32, 32, 34, 112, 97, 115, 115, 119, 111, 114, 100, 34, 58, 32, -30, -128, -100, 32, 109, 52, 99, 49, 50, 48, 57, 48, 53, 34, 44, 10, 32, 32, 32, 32, 32, 32, 32, 32, 34, 105, 110, 100, 101, 120, 34, 58, 32, -30, -128, -100, 109, 52, 99, 34, 44, 10, 32, 32, 32, 32, 32, 32, 32, 32, 34, 116, 121, 112, 101, 34, 58, 32, -30, -128, -100, 112, 97, 105, 115, 34, 44, 10, 32, 32, 32, 32, 32, 32, 32, 32, 34, 115, 113, 108, 34, 58, 32, 34, 115, 101, 108, 101, 99, 116, 32, 42, 32, 102, 114, 111, 109, 32, 77, 52, 67, 80, 65, 73, 83, 34, 10, 32, 32, 32, 32, 32, 32, 125, 10, 125, 10]]; ",
"status": 400
}
on the CLI i get:
org.elasticsearch.index.mapper.MapperParsingException: failed to parse
at org.elasticsearch.index.mapper.DocumentMapper.parse(DocumentMapper.java:562)
at org.elasticsearch.index.mapper.DocumentMapper.parse(DocumentMapper.java:490)
at org.elasticsearch.index.shard.service.InternalIndexShard.prepareIndex(InternalIndexShard.java:413)
at org.elasticsearch.action.index.TransportIndexAction.shardOperationOnPrimary(TransportIndexAction.java:189)
at org.elasticsearch.action.support.replication.TransportShardReplicationOperationAction$AsyncShardOperationAction.performOnPrimary(TransportShardReplicationOperationAction.java:511)
at org.elasticsearch.action.support.replication.TransportShardReplicationOperationAction$AsyncShardOperationAction$1.run(TransportShardReplicationOperationAction.java:419)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.elasticsearch.ElasticsearchParseException: Failed to derive xcontent from (offset=0, length=323)
I first though was a connection problem but checking around it seems its a problem with the mapping in ES & Oracle. Does someone have done ES+Oracle River integration? Any help would be really appreciated.
I found a solution that worked out really straigth forward. Instead of putting the command on the what i did is have a json config file like this:
{
"type" : "jdbc" ,
"jdbc" :{
"strategy" : "oneshot",
"driver" : "oracle.jdbc.OracleDriver",
"url" : "jdbc:oracle:thin:#host:1521:DNS",
"user" : "user",
"password" : "password",
"sql" : "select * from aTable",
"poll" : "1h",
"scale" : 0,
"autocommit" : false,
"fetchsize" : 100,
"max_rows" : 0,
"max_retries" : 3,
"max_retries_wait" : "10s"
},
"index" : {
"index" : "aIndex",
"type" : "aType",
"bulk_size" : 100
}
}
and then call it with curl like this:
'http://127.0.0.1:9200/_river/jdbcriver/_meta' -d #config.json
I don't know it's a parser issue or what but this way worked like a charm.
Thanks