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jpvantassel / swprocess

Python package for surface wave processing.
https://pypi.org/project/swprocess/
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About Signal preprocessing #31

Open Qmbnowhere opened 2 weeks ago

Qmbnowhere commented 2 weeks ago

hello,@jpvantassel I'm very sorry to bother you，about Signal preprocessing,Can you provide some sample active source data as well as pre-processed jupyter-notebook examples, as I don't really understand how the process works so that I can learn from you about these treatments to minimize subsequent dispersive data uncertainty, thank you very much!

jpvantassel commented 2 weeks ago

Hi @Qmbnowhere,

The swprocess project includes example data here a worked example using that same data here. I am not sure what you mean by "Signal preprocessing". I would recommend that you read the paper by Vantassel and Cox (https://doi.org/10.1007/s10950-021-10035-y) to better understand the effects of preprocessing on the MASW dispersion image.

Qmbnowhere commented 2 weeks ago

hello,@jpvantassel, about Signal preprocessing,I was reading the paper you mentioned has a section on signal preprocessing, so I wanted to ask if you could provide some sample code and data about this section, sorry for not being clear enough!Specifically, I want to understand about treatments such as stackless, frequency domain stacking, time domain stacking, and time domain muting, as well as different approaches to wavefield transformations, so I'm looking for some relevant data and code

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jpvantassel commented 2 weeks ago

Hi @Qmbnowhere, These options are all included as settings in the example MASW notebook. You can change them and see the effect on your data.