Sean M. Law
Sean M. Law
# Summary I have series of tests where the assertion needs to be executed inside of a closure (nested) test function since it needs to utilize a separate test framework...
Recently, I received some feedback: 1. There is too much friction to "get started". With limited time, the tutorials are too verbose for users who are looking for the one...
This [new paper](https://www.sciencedirect.com/science/article/pii/S0743731524000194) titled "Exploring Multiprocessor Approaches to Time Series Analysis" claims to significantly improve the performance of matrix profile calculations. We should consider looking into this. Additionally, we should...
[This paper](https://www.merl.com/publications/docs/TR2022-040.pdf) by MERL discusses the use of double ended queues to speed up computation of matrix profiles but it isn't clear how this may/may not affect top-k nearest neighbors....
Here is [the preprint](https://www.dropbox.com/scl/fi/hd9gt0xs8v8mrsx3upwd3/ICDM23_Madrid_023.pdf?rlkey=s5s95y2eeyk159lx69qn1469e&dl=0) [Website](https://sites.google.com/view/madrid-icdm-23) [Code](https://sites.google.com/view/madrid-icdm-23/documentation?authuser=0#h.by9sfjsorcs6) [Datasets](https://sites.google.com/view/madrid-icdm-23/dataset?authuser=0)
It has [come to our attention](https://github.com/TDAmeritrade/stumpy/issues/929) that the docstring for `ignore_trivial` may be too vague. We should consider improving the docs for this
Sometimes, debugging a Github Actions workflow can be slow, inefficient, and can lead to unwanted test commits. [nektos/act](https://github.com/nektos/act) allows you to run your workflows locally and improve the process. The...
Side-Length-Independent Motif (SLIM): Motif Discovery and Volatility Analysis in Time Series—SAX, MDL and the Matrix Profile [Paper](https://www.mdpi.com/2571-9394/4/1/13) [Code](https://github.com/eoincart/SLIM)
See [this paper](https://epubs.siam.org/doi/epdf/10.1137/1.9781611977653.ch77) on finding multi-dimensional anomalies in a subset of dimensions. The website can be found [here](https://sites.google.com/view/tsadis) The datasets can be found [here](https://drive.google.com/drive/folders/1AkX3wh3RT8w6pKw2UnhLSM_noOKXFHpB?usp=sharing) The code can be found [here](https://drive.google.com/drive/folders/1AkX3wh3RT8w6pKw2UnhLSM_noOKXFHpB?usp=sharing)...
In functions like `_stump`, the sub-functions `_compute_diagonal` and `core._shift_insert_at_index` may be called a lot. Therefore, we may gain some (small) performance improvement by adding `@njit(inline='always')` to those (and other) functions...