Sliding window statistics for Nodejs and browser.
Time and Size sliding windows, capable of calculating incremental statistics, such as count, sum, avg, stdev, freq, etc...
npm install swstats
Nodejs:
const SWindow = require("swstats");
// Create a time window of 10 seconds. Each value pushed to
// the window will be stored in a unique slot (step:1)
// Window will slide on each second
var sw = new SWindow.TimeStats(10000,{step:1});
var i=0;
setInterval(()=>{
sw.push(Math.random());
},1);
setInterval(()=>{
console.log(sw.stats);
},100);
or browser:
<!doctype html>
<html>
<head>
<script src="swstats.min.js"></script>
</head>
<body>
<textarea id="values" readonly="readonly" cols="40" rows="15">
</textarea>
<script>
// Create a time window of 10 secons.
// Window will slide on each second
var sw = new SWindow.TimeStats(10000,{step:1});
var i=0;
var ta = document.getElementById("values");
setInterval(()=>{
sw.push(Math.random());
},10);
setInterval(()=>{
ta.value = JSON.stringify(sw.stats,null,2);
},100);
</script>
</body>
</html>
The results will be something like:
{ count: 9,
sum: 4.383476926850223,
avg: 0.48705299187224704,
max: 0.9865126881294235,
min: 0.0023880687887007923,
stdev:
{ avg: 0.48705299187224704,
sqsum: 2.6772528231211963,
sum: 4.383476926850223,
stdev: 0.24546266317028345 } }
....
{ count: 994,
sum: 495.03542685194975,
avg: 0.4980235682615189,
max: 0.9865126881294235,
min: 0.0023880687887007923,
stdev:
{ avg: 0.4980235682615189,
sqsum: 332.1783737578395,
sum: 495.03542685194975,
stdev: 0.29352342336095866 } }
Creates a new time window of time duration. The window will slide on each second. options is optional, and can take the following parameters:
Example:
const SWindow = require("swstats");
// Time window of 10 seconds
var tw1 = new SWindow.TimeStats(10000,{
step:1000, // Values will be accumulated in slots of 1 second
type:"numeric", // Numeric values
ops:["sum"], // We only want to sum values
stats : {
sum : 233 // Initial value where sum will start
}
});
// Time window of 10 seconds with relative timestamp
var tw2 = new SWindow.TimeStats(10000,{
timestamp:TimeStats.TS.RELATIVE,
step:1000, // Values will be accumulated in slots of 1 second
type:"numeric" // Numeric values
});
Adds a new value to the window. It will consume a new slot or be added to the current one, depending on the step value. If timestamp mode is absolute, simply push the value, but if relative is activated, you must push an object with value and timestamp:
tw1.push(10);
tw2.push({ts:Date.now(),v:10});
Adds multiple values at once, in the same manner as push(val).
Resets window and stats.
Pauses the window, so no slide occurs, but no new values will be added.
Resumes a paused window. If shift is true, the timestamps of each slots will be shifted relative to the time the window is resumed, otherwise they keep their original timestamps. This will affect how the window is slided on the next second.
Kill the window, so no new values will be added, and no slide will occur. You can still access to its stats.
Gets the current size of the window (number of slots)
Gets the current calculated stats
{ count: 9,
sum: 4.638591015963949,
max: 0.8745422003577794,
min: 0.04623850021742104,
avg: 0.5153990017737722,
stdev:
{ avg: 0.5153990017737722,
sqsum: 3.044764166996456,
sum: 4.638591015963949,
stdev: 0.26957558983867996 } }
Gets the current calculated stats per slot
[ { t: 1517499437649,
sum: { David: 571, John: 404 },
freq: { David: 0.5856410256410256, John: 0.41435897435897434 },
mode: 'David',
threshold: { David: false, John: false } },
{ t: 1517499438649,
sum: { John: 398, David: 580 },
freq: { John: 0.4069529652351738, David: 0.5930470347648262 },
mode: 'David',
threshold: { John: false, David: false } },
{ t: 1517499439649,
sum: { David: 449, John: 274 },
freq: { David: 0.6210235131396957, John: 0.3789764868603043 },
mode: 'David',
threshold: { David: true, John: false } } ]
Creates a new size window with size slots. The window will slide when the maximum slots have been reached. options is optional, and can take the following parameters:
Example:
const SWindow = require("swstats");
// Size window of 100 values
vat sw = new SWindow.SizeStats(100,{
type:"category", // Category values
ops:["freq"], // We only want the value frequency
stats : {
freq : { // Initial value where freq will start
"john" : 0.3,
"david" : 0.7
}
}
});
Adds a new value to the window. It will consume a new slot.
Adds multiple values at once. In case of category values, unlike the temporary window, all the values pushed in one call will be added together in the same slot:
sizeWindow.push(["value1","value2"]);
will consume only one slot, whereas:
sizeWindow.push("value1");
sizeWindow.push("value2");
will consume two slots.
Resets window and stats.
Gets the current size of the window (number of slots)
Gets the current calculated stats
Gets the current calculated stats per slot
It is possible to implement and plug a custom function to calculate any stats you need. To register a new stats function, you must call the register function with the following parameters:
fn(currval,newitems,olditems,allitems,newstats,oldstats)
The stats function passed to the register method takes the following arguments:
The items in the newitems, olditems and allitems arrays, have the following format:
{
t : 1496843741554, // Timestamp in unix format (ms)
v : 12.34, // Total value for this slot
min : 2.4 // Minimum of the accumulated values
max : 4.5 // Maximum of the accumulated values
l : 4 // Values accumulated in this slot
}
{
t : 1496843741554, // Timestamp in unix format (ms)
v : { // Total values for this slot
"john" : 4,
"david" : 6
}
}
Note: Timestamp only appears in time windows.
Examples:
const SWindow = require("swstats");
// Calculates the variance
SWindow.register("numeric","variance",["stdev"],
(currval,newitems,olditems,allitems,newstats,oldstats)=>{
return Math.pow(newstats.stdev.stdev,2);
}
);
// A Weighted sum, where value decreases as more items are pushed
// to the window
SWindow.register("numeric","decsum",[],
(currval,newitems,olditems,allitems,newstats,oldstats)=>{
currval = currval || {};
if(!currval.ratio) currval.ratio = 0.99;
if(!currval.weight) currval.weight = 1.0;
if(!currval.sum) currval.sum = 0;
var oldWeight = currval.weight;
var newWeight = oldWeight * currval.ratio;
var olen = olditems.length;
var nlen = newitems.length;
// Adds the new items, and append the weight values, so
// we can fetch them in the substract phase
for(let i=0;i<nlen;i++) {
newitems[i].weight = newWeight;
currval.sum += newitems[i].v * newWeight;
}
// Substract the removed items
for(let i=0;i<olen;i++) {
currval.sum -= olditems[i].v * olditems[i].weight;
}
currval.weight = newWeight;
return currval;
}
);
var sw = new SWindow.SizeStats(10,{
ops : ["variance","decsum"],
stats : {decsum : {ratio : 0.99}}
});
for(let i=0;i<100;i++) {
sw.push(10);
sw.push(5);
}
console.log(sw.stats);
Results:
{ decsum:
{ ratio: 0.99,
weight: 0.13397967485796175,
sum: 10.53536530978331 },
avg: 7.5,
stdev: { avg: 7.5, sqsum: 625, sum: 75, stdev: 2.5 },
variance: 6.25 }
FAQs
Sliding window statistics
The npm package swstats receives a total of 137 weekly downloads. As such, swstats popularity was classified as not popular.
We found that swstats demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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