Allow the user to disable scaling on GASF and GADF images

[TobCar]

The normalization step when generating the compound images is really useful. However, if the time series data being turned into a compound image is an observation of a longer series of data with a larger range of values, the normalization removes valuable information.

I'm part of a research team at Queen's University and we are using your library to predict who will experience delirium in the ICU. While developing our model we realized the normalization step made it impossible for the model to learn. To give a practical example, one of the features we have is a patient's heart rate. One patient may have a peak heart rate of 200 whereas another one may have a peak heart rate of 140. The normalization treats both peak values as 1 because the smaller values belongs to a different patient and a different training case. To resolve this we, normalize the data across all the patients before creating the compound images without the normalization step. This way, the GASF and GADF have values within a limited range as required, but we keep information regarding what observations are greater than others to keep the observation in context.

[pep8speaks]

Hello @TobCar! Thanks for updating the PR.

Cheers ! There are no PEP8 issues in this Pull Request. 🍻

Comment last updated on February 05, 2019 at 15:36 Hours UTC

[codecov]

Codecov Report

Merging #18 into master will decrease coverage by 0.18%.
The diff coverage is 33.33%.

@@            Coverage Diff             @@
##           master      #18      +/-   ##
==========================================
- Coverage   82.14%   81.96%   -0.19%     
==========================================
  Files          27       27              
  Lines        1759     1763       +4     
  Branches      324      326       +2     
==========================================
  Hits         1445     1445              
- Misses        163      165       +2     
- Partials      151      153       +2

Impacted Files	Coverage Δ
pyts/image/image.py	70.23% <33.33%> (-1.72%)	⬇️

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[codecov]

Codecov Report

Merging #18 into master will decrease coverage by 0.18%.
The diff coverage is 33.33%.

@@            Coverage Diff             @@
##           master      #18      +/-   ##
==========================================
- Coverage   82.14%   81.96%   -0.19%     
==========================================
  Files          27       27              
  Lines        1759     1763       +4     
  Branches      324      326       +2     
==========================================
  Hits         1445     1445              
- Misses        163      165       +2     
- Partials      151      153       +2

Impacted Files	Coverage Δ
pyts/image/image.py	70.23% <33.33%> (-1.72%)	⬇️

---

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 72e1e51...8f87267. Read the comment docs.

[johannfaouzi]

Thank you for the PR. I did not think about the practical case when the observations are only subseries of time series.

I added a small gotcha to your PR to ensure that all the values are between -1 and 1 when the scaling is disabled.

[TobCar]

Ah, that's a good catch!

[TobCar]

Hi Johann would it be possible to merge the PR?

[johannfaouzi]

Sure, I totally forgot about it. Sorry for that!

[TobCar]

Thanks again Johann! Is there a chance you could also mark a new release (0.72?), we want to cite the code as it is right now.

[johannfaouzi]

It's done! The version will be 0.7.3 (I wrote a typo when I edited your PR and I did not run the tests before uploading the new version, so I had to upload a new version once more). When you import the package and run pyts.__version__, it will output 0.7.0 because I also forgot to change the version in the __init__.py, but it does not change anything.

By the way I have worked the past few months to improve the package. This work is only local for the moment, but I hope to release the 0.8.0 version by the end of March.

[TobCar]

Sounds good, I'll keep an eye out for it.