RapidLib issueshttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues2017-09-01T09:10:30Zhttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues/98"Shape identification using Dynamic Time Warping" is broken2017-09-01T09:10:30ZFrancisco Bernardo"Shape identification using Dynamic Time Warping" is brokenI haven't updated myself on the last changes on RapidLib.DTW but there is this bug about an offset in the example.
https://live.codecircle.com/d/87dKNLQorohuER84X
I suspect this is about the change in the library.I haven't updated myself on the last changes on RapidLib.DTW but there is this bug about an offset in the example.
https://live.codecircle.com/d/87dKNLQorohuER84X
I suspect this is about the change in the library.Michael ZbyszyńskiMichael Zbyszyńskihttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues/25Check why ofx example needed input normalization2017-09-20T10:05:07ZMichael ZbyszyńskiCheck why ofx example needed input normalizationAPI v0.1Michael ZbyszyńskiMichael Zbyszyńskihttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues/16fix conflict with maxiLIb2017-09-20T10:05:07ZMichael Zbyszyńskifix conflict with maxiLIbIt seems like both modules are fighting for the namespace "Module"?It seems like both modules are fighting for the namespace "Module"?API v0.1Michael ZbyszyńskiMichael Zbyszyńskihttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues/109JS seriesClassification fails with large series2017-09-21T13:33:58ZMichael ZbyszyńskiJS seriesClassification fails with large seriesTesting on this page:
https://live.codecircle.com/d/87dKNLQorohuER84X
seriesClassification seems to fail when either the learned series or the input series is long. This is inconsistent, though.Testing on this page:
https://live.codecircle.com/d/87dKNLQorohuER84X
seriesClassification seems to fail when either the learned series or the input series is long. This is inconsistent, though.API demonstratorsMichael ZbyszyńskiMichael Zbyszyńskihttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues/29JSON API inRanges, inBases, outRange, outBase2017-05-02T14:07:05ZMichael ZbyszyńskiJSON API inRanges, inBases, outRange, outBaseI had originally had the API giving inMaxes, etc. This should be changed so the regression object takes Ranges and Bases, which are calculated elsewhere.I had originally had the API giving inMaxes, etc. This should be changed so the regression object takes Ranges and Bases, which are calculated elsewhere.API v0.1Michael ZbyszyńskiMichael Zbyszyńskihttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues/70kNN should remember requested k.2017-09-25T12:59:40ZMichael ZbyszyńskikNN should remember requested k.If setK() asks for a k that is greater than the current number of neighbours, then k is set to the number of neighbours.
kNN should remember the number that the user requested so that k can be increased if new neighbours are added.If setK() asks for a k that is greater than the current number of neighbours, then k is set to the number of neighbours.
kNN should remember the number that the user requested so that k can be increased if new neighbours are added.API v0.2Michael ZbyszyńskiMichael Zbyszyńskihttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues/23Re-implement arguments for Regression() and Classification()2017-09-20T10:05:07ZMichael ZbyszyńskiRe-implement arguments for Regression() and Classification()I broke these while moving this code to C++.I broke these while moving this code to C++.API v0.2Michael ZbyszyńskiMichael Zbyszyńskihttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues/112seriesClassifcation crash in Node2017-11-15T16:32:39ZMichael ZbyszyńskiseriesClassifcation crash in NodeThis code crashes in NodeJS:
```javascript
var rapidMix = require('rapidlib');
var testDTW = new rapidMix.SeriesClassification();
testSet2 = [];
for (let i = 0; i < 5; ++i) {
testSet2.push([0.1, 0.1, 0.1]);
}
let series2 = {input: ...This code crashes in NodeJS:
```javascript
var rapidMix = require('rapidlib');
var testDTW = new rapidMix.SeriesClassification();
testSet2 = [];
for (let i = 0; i < 5; ++i) {
testSet2.push([0.1, 0.1, 0.1]);
}
let series2 = {input: testSet2, label: "yyy"};
let series1 = {input: testSet2, label: "zzz"};
let sset = [series1, series2];
console.log(testDTW.train(sset));
console.log(testDTW.run(testSet2));
```
It doesn't crash in the browser here:
https://live.codecircle.com/d/oma4nGEEk8SXvZ6hg
It doesn't crash in C++.
It doesn't crash if the feature vector has 2 or 4 members. It also doesn't crash for many power of two, or similar, set lengths.
It calls ```_abort``` from the emscripten ``_free()`` method.Future APIMichael ZbyszyńskiMichael Zbyszyńskihttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues/84train() not clearing properly for classification2017-08-14T13:39:15ZMichael Zbyszyńskitrain() not clearing properly for classificationSee here:
https://live.codecircle.com/d/3NpkuThvqgiGoH4ufSee here:
https://live.codecircle.com/d/3NpkuThvqgiGoH4ufMichael ZbyszyńskiMichael Zbyszyńskihttps://gitlab.doc.gold.ac.uk/rapid-mix/RapidLib/-/issues/47Virtual train in modelSet2017-05-02T14:07:05ZMichael ZbyszyńskiVirtual train in modelSetMarco reported:
"I just noticed that the method train of modelSet isn't virtual. Looks like it is supposed to be."
Marco reported:
"I just noticed that the method train of modelSet isn't virtual. Looks like it is supposed to be."
API v0.2Michael ZbyszyńskiMichael Zbyszyński