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STUMPY is a powerful and scalable Python library for modern time series analysis
I think there is a ~minor~ bug in `stumpy/snippet.py`. one can see the bug by setting param `s` to a value less than or equal to `m / 2`. To...
Added my first attempts at optimizing `stump` using unsigned integer indexing. I added a temporarity `stumpy.stump_uint` module, which (if successfully optimized) may replace `stump`. But I haven't had too much...
This is in reference to the discussion around the differences in using `np.int64` and `np.uint64` to index numpy errors in [this PR](https://github.com/TDAmeritrade/stumpy/pull/463) and [this numba discussion thread](https://numba.discourse.group/t/uint64-vs-int64-indexing-performance-difference/1500?u=seanlaw). Based on the...
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...
The MIN Python version mentioned In `README.rst` is outdated (see the following line) ``` STUMPY supports [Python 3.7+](https://python3statement.org/) and, due to ... ``` Is it okay to just change it...
[Update] Here, I am providing some important links to external resources or the comments mentioned here: * So far: [6-8step-FFT-based MASS, with Numba (SingleThreaded)](https://gist.github.com/NimaSarajpoor/077c91a07858039b66cdfa0c98d2f4b4) * [A comment regarding: OFFT uses...
Currently, STUMPY supports the parameter [normalize](https://github.com/TDAmeritrade/stumpy/blob/3559b38c9a45bf450359dab40eb081d0b87687a4/stumpy/stump.py#L547-L550) which allows users to compute matrix profile for the following cases: (1) `normalize == False`: Compute the distance between subsequences with no transformation (2)...
[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....
This PR is a replacement for PR #872. This PR is to address #606. --- I will start with implementing the original algorithm, as proposed in the paper, as close...
This PR addresses the issue raised in #938. We want to create a new function for `sliding_dot_product` that: (1) has a performance that is close to the performance of `core.sliding_dot_product`...