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DigitalPig / GPC_Fit

Python script to process GPC raw data for peak deconvolution
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ZHIL1669.arw data example #1

Open rodrigoSantamaria opened 8 years ago

rodrigoSantamaria commented 8 years ago

Hi there! Looks like a great script for peak deconvolution :) However I'm trying to use it for another field of application and, although I can see the raw data format you are using by inspecting the code (basically 2-columns with x an y), I think it might be useful for quick assessing to include the ZHIL1669.arw as a data example.

DigitalPig commented 8 years ago

Hi! Glad you like the script. The file is proprietary data from our company. Therefore I cannot post it on public domain. However, I can describe the file format for you. The raw file is a tab-separated txt file. It has two columns with the first column is time and the second column is signal.

In the meantime, I am in the middle of turning this into a Heroku App. That will make it independent on raw files. Will post it out after it is done.

Thank you again for your interest.

rodrigoSantamaria commented 8 years ago

Cheers, thanks! Yes I ended up figuring out the format, as it was simple.

Great code, thanks for making it pulbic :)

Rodrigo http://vis.usal.es/rodrigo

2016-06-12 17:53 GMT+02:00 Zhenqing Li notifications@github.com:

Hi! Glad you like the script. The file is proprietary data from our company. Therefore I cannot post it on public domain. However, I can describe the file format for you. The raw file is a tab-separated txt file. It has two columns with the first column is time and the second column is signal.

In the meantime, I am in the middle of turning this into a Heroku App. That will make it independent on raw files. Will post it out after it is done.

Thank you again for your interest.

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/DigitalPig/GPC_Fit/issues/1#issuecomment-225444784, or mute the thread https://github.com/notifications/unsubscribe/ABhss-koUSVg0axEQPEuZpoLGwyXdJoKks5qLCtggaJpZM4IqZuL .