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PowerBroker2 / MAMMAL

MAMMAL - Magnetic Anomaly Map Matching Airborne and Land: A Python package for simulating and processing aeromagnetic anomaly survey data. It can be used to create magnetic anomaly maps for Magnetic Navigation solutions (MagNav).
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Test data request #1

Open LX724 opened 1 month ago

LX724 commented 1 month ago

Although there are still some grammatical problems in the code, your work is very meaningful and I am very interested in your things. Can you share some data, such as' intermagnet_log.sec',' intermagnet_log.csv',' map.tiff',' flight_log.csv', and' __ground_cal__.csv' from the calibration example, etc. I want to further test and experience. I hope to share some case data as much as possible to facilitate the test experience.

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PowerBroker2 commented 1 month ago

Hello, thanks for your interest!

there are still some grammatical problems in the code

What would those problems be?

Can you share some data, such as' intermagnet_log.sec',' intermagnet_log.csv',' map.tiff',' flight_log.csv', and' ground_cal.csv' from the calibration example, etc.

Sorry, I'm not allowed to share any raw data, just the processed data in graph form (as seen in the iPython notebooks). If I could share, I would.

If you have your own magnetometers, Pixhawk, and UAV, you should be able to calibrate and process your own maps using the provided code. Explanations of how I did it is included here. If you're using different magnetometers than what I used, you might need to create your own data parser and calibration libraries, but other than that, you should be good to go.

LX724 commented 1 month ago

Thank you for your answer. It may be a problem with the data I used, which caused some mistakes. I sincerely hope that you can add some test data to "example", at least to ensure the normal operation of the sample code and facilitate further understanding and testing by others. If possible, it is recommended to use python 3.10 and numpy 2.0.0 or above to set the environment. numpy 1.20.3 is old, and it is easy to cause dependency conflicts.

PowerBroker2 commented 1 month ago

There is a simulation portion of the code that you can use to generate fake data and process it into a map. The functionality is limited to a single 2D gaussian magnetic anomaly, but it's better than nothing.

I'll think about how to make better simulated datasets that can actually be shared or user-generated...