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Update date bugs #16

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4 changes: 2 additions & 2 deletions package.json
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
},
"name": "timeseries-analysis",
"description": "timeseries-analysis",
"version": "1.0.12",
"version": "1.0.13",
"homepage": "https://github.com/26medias/timeseries-analysis",
"licenses": [
{
Expand All @@ -31,6 +31,6 @@
"bugs": {
"url": "https://github.com/26medias/timeseries-analysis/issues"
},
"_id": "timeseries-analysis@1.0.12",
"_id": "timeseries-analysis@1.0.13",
"_from": "timeseries-analysis@latest"
}
32 changes: 18 additions & 14 deletions timeseries-analysis.js
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Original file line number Diff line number Diff line change
@@ -1,6 +1,5 @@
var _ = require("underscore");
var gimage = require("google-image-chart").charts;
var moment = require("moment");

var timeseries = function (data, options) {
/*
Expand Down Expand Up @@ -621,6 +620,8 @@ timeseries.prototype.regression_forecast = function (options) {
degree: 5,
// Is the training only use last x sample data points or up to entire data points?
growthSampleMode: false,
// Real data to be used.
data: this.data,
},
options
);
Expand All @@ -634,32 +635,32 @@ timeseries.prototype.regression_forecast = function (options) {
options.n = options.n === null ? l - options.sample : options.n;

// Remove the mean.
var mean = this.mean();
this.offset(-mean);
var mean = this.mean(options.data);
options.data = this.offset(-mean, options.data, true);

// Temporary working datasets.
// var backup = this.clone();
var buffer = this.clone();
var buffer = _.map(options.data, function (item) {
return [item[0], item[1] * 1];
});

// MSE atributtes.
var knownValue = NaN;
var dataCountMSE = 0;
var MSE = 0;

// Get different interval of time attribute from dataset.
var timeDiff = Math.abs(buffer[1][0] - buffer[0][0]);
var timeDiff = Math.abs(
new Date(buffer[1][0]).getTime() - new Date(buffer[0][0]).getTime()
);

for (var i = options.start - 1; i < options.start + options.n - 1; i++) {
// Get sample as training dataset.
var sample = options.growthSampleMode
? buffer.slice(i - options.sample - (i - (options.start - 1)), i)
: buffer.slice(i - options.sample, i);

// The current dataset when training is only a sample.
this.data = sample;

// Get the AR coeffs.
var coeffs = this[options.method]({ degree: options.degree });
// Get the AR coeffs from current sample dataset.
var coeffs = this[options.method]({ degree: options.degree, data: sample });

// console.log({i, buffer: buffer.map(val=>[val[0], val[1]+mean]), coeffs, data: this.data.map(val=>[val[0], val[1]+mean])})

Expand All @@ -668,7 +669,10 @@ timeseries.prototype.regression_forecast = function (options) {
knownValue = buffer[i][1] * 1;
buffer[i][1] = 0;
} else {
buffer.push([new Date(new Date(buffer[i - 1][0]) + timeDiff), 0]);
buffer.push([
new Date(new Date(buffer[i - 1][0]).getTime() + timeDiff),
0,
]);
}

// Get forecasted datapoint.
Expand Down Expand Up @@ -1092,7 +1096,7 @@ timeseries.prototype.regression_analysis = function (options) {
for (i = 0; i < theList.length - 1; i++) {
for (j = i + 1; j < theList.length; j++) {
if (theList[j] < theList[i]) {
temp = theList[i];
var temp = theList[i];
theList[i] = theList[j];
theList[j] = temp;
}
Expand Down Expand Up @@ -1348,4 +1352,4 @@ adapter.tan = function (options) {

exports.main = timeseries;
exports.adapter = adapter;
exports.version = "1.0.12";
exports.version = "1.0.13";