Highly comparative time-series analysis with hctsa
  • Information about hctsa
    • Introduction
    • Getting started
    • Publications using hctsa
    • UMAP Projections
    • Related Time-Series Resources
    • List of included code files
    • FAQ
  • Installing and using hctsa
    • General advice and common pitfalls
    • Installing and setting up
      • Structure of the hctsa framework
      • Overview of an hctsa analysis
      • Compiling binaries
    • Running hctsa computations
      • Input files
      • Performing calculations
      • Inspecting errors
      • Working with hctsa files
    • Analyzing and visualizing results
      • Assigning group labels to data
      • Filtering and normalizing
      • Clustering rows and columns
      • Visualizing the data matrix
      • Plotting the time series
      • Low dimensional representation
      • Finding nearest neighbors
      • Investigating specific operations
      • Exploring classification accuracy
      • Finding informative features
      • Interpreting features
      • Comparing to existing features
      • Working with short time series
    • Working with a mySQL database
      • Setting up the mySQL database
      • The database structure
      • Populating the database with time series and operations
      • Adding time series
      • Retrieving from the database
      • Computing operations and writing back to the database
      • Cycling through computations using runscripts
      • Clearing or removing data
      • Retrieving data from the database
      • Error handling and maintenance
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  • 🖥️ Talks and live demos
  • 💾 hctsa datasets, and example workflows

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  1. Information about hctsa

Getting started

Some advice for getting started with an hctsa analysis

PreviousIntroductionNextPublications using hctsa

Last updated 12 months ago

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🖥️ Talks and live demos

💾 hctsa datasets, and example workflows

Sometimes it's easiest to quickly get going when you can follow on to some example code. Here are some repositories that allow you to do just this. There are a range of open datasets with pre-computed hctsa features, as well as some examples of hctsa workflows. You may also check the for example publications that have used hctsa—some of these contain associated open code.

If you have data to share and host, let me know and I'll add it to this list.

page of publications using hctsa
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of a tutorial session on feature-based time-series analysis tools at Computational Neuroscience Academy 2023, Krakow, Poland.

https://www.youtube.com/watch?v=c1adfGjof8s
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t, check out this slides for the full talk about analyzing neural dynamics using hctsa at CNS 2020 are . July 2020.

https://github.com/benfulcher/hctsaTutorial_BonnEEG
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Talk about the importance of comparison for time-series analysis to QMNET. , . (August 2020).

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Seizure EEG. An overview tutorial on applying hctsa to a 5-class EEG dataset is in (including the use of reduced feature set, catch22, within the hctsa framework). There is also a recording of the tutorial (final ~hour is a hands-on demo using this dataset) on .

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Worms in a dish. and associated . You can try your hand at classifying different strains of the nematode worm C. elegans based on their time series of their movement speed. The repository, with links to pre-computed HCTSA.mat files, is .

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Flies in a tube. and associated . This repository allows you to skip the process of running an hctsa calculation (you can download pre-computed results), and get straight to following key analyses, including classifying day/night, or male/female.

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. A collection of 1000 diverse empirical time series to test algorithms on.

Youtube live stream
YouTube video walking through the
utorial on classifying EEG data
here
Slides
YouTube
this GitHub repo
YouTube
C. elegans movement speed data
analysis code
here
Drosophila movement speed
analysis code
1000 empirical time series