PyCBC-Tutorials
Graph_Signal_Processing
| PyCBC-Tutorials | Graph_Signal_Processing | |
|---|---|---|
| 2 | 2 | |
| 107 | 14 | |
| 0.9% | - | |
| 3.4 | 2.6 | |
| 11 months ago | almost 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
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PyCBC-Tutorials
- How can we use PSD for inverse spectrum truncation?
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[GWpy] How do you know what time an event is occurring from a frequency plot?
If you want to get a sense for a signal is actually detected and at what time it occurs, I'd suggest taking a look at PyCBC and the tutorials there. https://github.com/gwastro/PyCBC-Tutorials In particular the following you may find useful, but you may find the others helpful as well. https://colab.research.google.com/github/gwastro/pycbc-tutorials/blob/master/tutorial/3\_WaveformMatchedFilter.ipynb
Graph_Signal_Processing
What are some alternatives?
pycbc - Core package to analyze gravitational-wave data, find signals, and study their parameters. This package was used in the first direct detection of gravitational waves (GW150914), and is used in the ongoing analysis of LIGO/Virgo data.
semi-supervised-segmentation-on-graphs - Semi supervised segmentation on graphs (images and pointclouds). Using Eikonal equation.
pythoncode-tutorials - The Python Code Tutorials
D3Feat - [TensorFlow] Official implementation of CVPR'20 oral paper - D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features https://arxiv.org/abs/2003.03164
bigpython - Source code for Big Python tutorials on YouTube
fCWT - The fast Continuous Wavelet Transform (fCWT) is a library for fast calculation of CWT.
stingray - Anything can happen in the next half hour (including spectral timing made easy)!
3-ogc - Third Open Gravitational-wave Catalog of Compact Binary Mergers. Using the data from LIGO and Virgo from 2015-2019, a comprehensive catalog including 57 detected mergers (55 BBH, 2 BNS) and sub-threshold candidates throughout O1, O2, and O3a.
uawardata - The data behind uawardata.com
indaba-pracs-2022 - Notebooks for the Practicals at the Deep Learning Indaba 2022.
interactive_tutorials - Repository for all ArangoDB interactive tutorial notebooks.