-
Currently array indexing is 1-based, and list indexing is 0-based. this makes, in particular, the array indexing in the DTW example needlessly complex, as things don't line up. We should move to repre…
-
Hi,
Perhaps I'm not understanding your code properly, but I was hoping you could clear some things up. When performing DTW on the dataset you read in `data/UCI-HAR-Dataset/train/X_train.txt` - Thi…
-
Hi, Paul
Very excellent implementation of dtw.
I am trying to integrate the DTW sub-module into well-known tensorflow as an gpu operator. For being compatible to the tf APIs, it is better to h…
-
Thank you for your great work!
I want to know about the time of the two works( without soft-dtw 1.5k step and the training with soft-dtw 15k step).
Have you ever try delete some parameters and the …
-
Jake Armitage reported the following:
```
root@bela:~/RapidLib# ./rapidLibTest
----- Bayes test passed.
----- DTW empty test passed.
----- DTW test passed.
----- Multilayer tests skipped.
b…
-
It would be nice to make kNN searches faster when Sakoe-Chiba constrained DTW is concerned using LB_Keogh based pre-filtering.
This should be implemented in the `kneighbors` method of class `KNeigh…
-
When I run "python setup.py build " , it return the following statesment and I cannot import sdtw normally :
"Using deprecated NumPy API, disable it by " "#defining NPY_NO_DEPRECATED_API NPY_1_7_API_…
-
import librosa.display
import matplotlib.pyplot as plt
from scipy.spatial.distance import euclidean,mahalanobis
from dtw import dtw
dist, _, cost, path = dtw(mfcc1.T, mfcc2.T, dist=euclidean)
-
Thank you very much for your share! Could you help me figure out how to implement the soft dtw as a custom loss in the deep learning training framework (in tf)? What I hope is to replace the RMSE/MAE.…
-
**Describe the issue**
It is a miss in your benchmarking. I think you should look at the "time-series-bakeoff" for others like it.
DTW is a pain, and very well known and well used method.
The …