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| author | Sam Scholten | 2025-10-23 15:28:37 +1000 |
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| committer | Sam Scholten | 2025-10-23 15:28:37 +1000 |
| commit | d7ac57d46e56620ebeb71f27e4d5c1382f66f6c3 (patch) | |
| tree | 75ffa5d8fc0be5f27c99064ac249a88118c0f072 /README.md | |
| parent | 307bf648d8e3fe852d7daf2fa1567d1896e50f7e (diff) | |
| download | transivent-d7ac57d46e56620ebeb71f27e4d5c1382f66f6c3.tar.gz transivent-d7ac57d46e56620ebeb71f27e4d5c1382f66f6c3.zip | |
Add project logo to README
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| -rw-r--r-- | README.md | 2 |
1 files changed, 2 insertions, 0 deletions
@@ -1,5 +1,7 @@ # transivent +<img src="logo.svg" width="120" markdown="1"> + `transivent` is a Python library for detecting and analysing transient events (~spikes) in time-series data. It provides a flexible and configurable pipeline for processing waveform data, identifying events based on signal-to-noise ratio, and visualizing the results. The library is designed to handle large files efficiently through chunked processing. Additionally, `transivent` includes tools for diffusion analysis of detected events, including Mean Square Displacement (MSD) calculation, autocorrelation analysis, and statistical visualization. |